Browse Topic: Adaptive control

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Advanced Signal Domain Techniques for Real-Time Control and Prognostics in VTOL SystemsSM-2026-VLADA-52051/27/2026
Vertical Take-Off and Landing (VTOL) aircraft introduce complex monitoring challenges due to distributed propulsion, lightweight structures, and variable operating conditions. This paper presents advanced Frequency and Orders domain techniques that repurpose existing flight control, propulsion, and structural sensor data to enhance observability without additional instrumentation. By transforming vibration, acoustic, and electrical signals into frequency and order domains, the approach enables detection of harmonics, resonance, and fault signatures tied to rotor dynamics, supporting adaptive control and predictive maintenance. Beyond rotor systems, these techniques are equally effective for monitoring electric motor health, gearbox wear, bearing degradation, and structural coupling effects in composite airframes. They also provide insight into power electronics and thermal management systems by identifying spectral anomalies linked to electrical imbalance or cooling inefficiencies. Aggregated fleet data strengthens prognostic capabilities, enabling early detection of systemic issues and trend analysis. Applications include mitigating ground resonance and modal instabilities, as well as improving reliability of propulsion and structural subsystems. Integration into avionics emphasizes computational efficiency, scalability, and compliance with standards such as DO-160 [1], DO-178 [2], ARP4761 [3] and ARP4764 [4]. Simulation and bench testing confirm feasibility, demonstrating potential to enhance safety, reliability, and lifecycle cost for next-generation urban air mobility platforms.
LaRue, David
Use of Generalized Predictive Control for Flutter Suppression of the Tiltrotor Aeroelastic System Testbed (TRAST)F-0081-2025-03505/20/2025
Generalized Predictive Control (GPC) is an advanced form of an adaptive control algorithm that uses experimentally acquired data to determine the input-output relationship of complex systems through a process called system identification. GPC has historically been employed for stability augmentation and vibration reduction of dynamically-scaled tiltrotor aircraft wind-tunnel models since the complex nature of these dynamic systems does not lend itself well to traditional control approaches. The present research expands upon previous analytical and experimental work with wind-tunnel experiments that utilize improved GPC techniques. These techniques improved controller robustness such that a working controller was stable across a multitude of model configurations and wind-tunnel conditions and successfully suppressed vibration and vehicle flutter. Advanced GPC (AGPC) enables self-adaptation of a traditional GPC control law. AGPC was also investigated during the present research but was not needed as anticipated because of the robustness resulting from improvements made to traditional GPC.
Ivanco, Thomas, Sekula, Martin, Thornburgh, Robert, Kreshock, Andrew
Model-Reference Adaptive Pilot Model of Rotorcraft Tracking Tasks with Time-Varying Vehicle DynamicsF-0081-2025-01525/20/2025
The development of an adaptive pilot model for rotorcraft tracking tasks is useful to understand and replicate human pilot behavior under varying vehicle dynamics and environmental conditions. This paper presents a Model-Reference Adaptive Control (MRAC)-based pilot model designed to emulate the adaptability of human pilots during attitude and position tracking tasks. The model leverages wavelet analysis to characterize pilot behavior and employs a closed-loop system identification approach to derive baseline pilot parameters. MRAC methodology using state-feedback is implemented and validated through simulations involving time-varying vehicle dynamics, such as changes in control sensitivity and added phase delays. Results demonstrate the model's ability to maintain consistent tracking performance despite dynamic modifications, though discrepancies with human pilot data highlight the complexity of fully capturing adaptive human control strategies. The proposed model offers a framework for integrating human adaptability into flight system design and simulation tools.
Chen, Zhouzhou, Horn, Joseph
Optimal Design for Maximum Fundamental Frequency and Minimum Intermediate Support Stiffness for Uniform and Stepped Beams Composed of Different Materials2020-01-50142/6/2020
The minimum support stiffness that achieves the maximum modal frequencies or critical speed is very important in the design of mechanical systems. The optimal values of the intermediate support stiffness and geometrical parameters of uniform and stepped Timoshenko beams composed of single or two materials are studied in order to maximize the modal frequency and minimize the intermediate support stiffness. Dynamic stiffness matrix (DSM) method and multi-objective particle swarm optimization (MOPSO) algorithm are used together to evaluate new optimal parameters. For single material, the results show that for uniform thick beams, the optimal maximum fundamental frequency and minimum intermediate support stiffness are lower than those of Bernoulli-Euler beams. In addition, the optimal design for stepped beams made of two metallic materials is investigated. For three different metallic combinations, gain factors of 1.561 to 2.745 are obtained for a beam without intermediate support. Comparison with experimental results is carried out. The current study and its results can be applied to improve the dynamic performance of many of industrial applications, such as guyed masts derricks, vertical tube furnaces, and long rotary machines with intermediate support.
Ahmed, Elsawaf, Tamer, Elsayed, Said, Farghaly
Vibration Control of an Active Seat Suspension System Integrated Pregnant Woman Body Model2019-01-01724/2/2019
Proportional-integral-derivative (PID) controller is effective, popular and cost effective for a lot of scientific and engineering applications. In this paper, PID and fuzzy-self-tuning PID (FSTPID) controllers are applied to improve the performance of an active seat suspension system to enhance the pregnant woman comfort. The equations of motion of thirteen-degrees-of-freedom (13-DOF) active seat suspension system incorporating pregnant woman body model are derived and simulated. PID gains are tuned and estimated using genetic algorithm (GA) to formulate GA PID controller. In FSTPID, fuzzy logic technique is used to tune PID controller gains by selecting appropriate fuzzy rules using Matlab/Simulink software. Both controlled active seat suspension systems are compared with a passive seat suspension. Suspension performance is evaluated under bump and random road excitations in order to verify the success of the proposed controllers. Theoretical results reveal that the proposed controllers using GA PID and FSTPID grant a significant enhancement of the pregnant woman comfort and her fetus.
Ali, Shaimaa A., Metered, H., Bassiuny, A. M, Abdel-Ghany, AM
Circuit Models for Robust, Adaptive Neural Control19AERP02_082/1/2019
Understanding a nematode's simple circuit could provide a foundation for understanding much more complex behaviors. Air Force Research Laboratory, Arlington, Virginia This project seeks to reproduce the neural circuits used by the nematode Caenorhabditis elegans for locomotion. Caenorhabditis elegans is a small (∼1.2 millimeter) nematode found in rotting fruit in many parts of the world. It feeds on bacteria and is neither parasitic nor pathogenic. Although capable of sexual reproduction, most laboratory strains reproduce primarily as self-fertilizing hermaphrodites, with each adult hermaphrodite producing approximately 300 progeny (Figure 1). C. elegans is a very simple organism, with only 959 somatic cells in the adult hermaphrodite. Although the total number of cells is small, they are differentiated into the standard array of tissues: 302 neurons, 95 body muscle cells, 32 gut cells, etc. In addition, the position, morphology, and lineage of each cell are reproducible from animal to animal. Because of the small size of the animal, the relatively small number of neurons, and the reproducible nature of the nervous system, it has been possible to provide an almost-complete synaptic connectivity map of the adult hermaphrodite nervous system (Figure 2).
Circuit Models for Robust, Adaptive Neural ControlTBMG-337662/1/2019
This project seeks to reproduce the neural circuits used by the nematode Caenorhabditis elegans for locomotion. Caenorhabditis elegans is a small (~1.2 millimeter) nematode found in rotting fruit in many parts of the world. It feeds on bacteria and is neither parasitic nor pathogenic. Although capable of sexual reproduction, most laboratory strains reproduce primarily as self-fertilizing hermaphrodites, with each adult hermaphrodite producing approximately 300 progeny (Figure 1).
Electronic Bi-Directional Shift Control Design and Calibration for Farm Vehicle2017-01-220510/8/2017
Agricultural tractors are often subjected to various applications like front end loading work, cultivation work, where frequent forward and reverse gears are needed. Most of Indian agricultural tractors are equipped with mechanical transmission system which demands repeated clutching and de-clutching operation for such applications resulting in increased operator fatigue and lesser productivity. Also need of electronics in Indian agricultural industry for better farm mechanization is growing high. This research work depicts development of electronic bi-directional shifting (power shuttle) control design and calibration for farm vehicle fitted with wet clutch transmission. This research also reduces operator fatigue via frequent directional shift through electronic transmission. The control system is designed without any electronic interfacing with engine and also provides clutch-less gear shifting and auto-launch which offers ease to drive even for novice driver. The power shuttle transmission control system offers more functionality and features in adjunct to in-built safety features without any additional sensors or components. Use of minimal sensor for system control and calibration delivers cost effect solutions. Adaptive control strategy is adopted for achieving efficient and optimal clutch fill modulation which is calibrateable for various climatic zone, vehicle loads, gears etc. Control software is designed by considering the vehicle variants pertinent to clutch load and engine characteristics. Modular control system design is employed in this research which can be extended across all tractor variants.
M A, Velmurugan, Rajagopal, MahendraMohan
Hydraulic Control of Integrated Electronic Hydraulic Brake System Based on LuGre Friction Model2017-01-25139/17/2017
In this paper, an integrated electronic hydraulic brake(I-EHB) system is introduced, which is mainly composed of a motor, a worm gear, a worm, a gear, a rack etc. The friction leads the system to the creeping phenomenon and the dead zone. These phenomenon seriously affect the response speed and the hydraulic pressure control .In order to realize the accurate hydraulic pressure control of I-EHB system, a new friction compensation control method is proposed based on LuGre dynamic friction model. And the theoretical design of adaptive control method is designed based on the feedback of the master cylinder pressure and the operating state of the system. Then the stability of the control method is proved by Lyapunov theorem. A co-simulation model is built with Matlab/Simulink and AMESim, so as to prove the validity of the control method. Related experiments are carried out to track the different target signals, which is step signal, (different amplitude and frequency) sine wave signal and Artemis signal. Compared with the test result with PID control method or compensation control method based on static friction model, this method based on LuGre dynamic friction model has a definite improvement, which has advantages in dynamic control error. The maximum dynamic control error at low frequency with this method is less than 1 bar and the RMS of error is about 0.2 bar. Therefore this method is an effective way to control the I-EHB system.
Li, Haocheng, Yu, Zhuoping, Xiong, Lu, Han, Wei
Adaptive Cascade Optimum Braking Control Based on a Novel Mechatronic Booster2017-01-25149/17/2017
BBW (Brake-by-wire) can increase the electric and hybrid vehicles performance and safety. This paper proposes a novel mechatronic booster system, which includes APS (active power source), PFE (pedal feel emulator), ECU (electronic control unit). The system is easily disturbed when the system parameters and the outside conditions change. The system performance is weakened. The cascade control technique can be used to solve the problem. This paper develops an adaptive cascade optimum control (ACOC) algorithm based on the novel mechatronic booster system. The system is divided into main loop and servo loop, both of them are closed-loop system. The servo-loop system can eliminate the disturbance which exists in the servo loop. So the robustness of the cascade control system is improved than which of the general closed-loop control system. Different control object is respectively chosen. The control-oriented mathematical model is designed. Based on the control-oriented model, optimum control algorithm(LQR) is used to design the servo-loop controller for optimum error and rapid response. To eliminate the system uncertainty and control the hydraulic pressure accurately, adaptive control algorithm, which includes the feedforward controller and the adaptive module based on the recursive least-square algorithm with a fixed forgetting factor(λ)(abbr. RFF), is used to design the main-loop controller. The performance of the novel mechatronic booster system is evaluated by co-simulation and bench test. Experimental results prove that the system fulfills the requirements of the brake system for automotive. Compared with using PI single-loop system and cascade PI system, the adaptive cascade optimum control algorithm can improve the rapidity and robustness of system. The system performance is also enhanced.
Han, Wei, Xiong, Lu, Yu, Zhuoping, Li, Haocheng
An Improved PID Controller Based on Particle Swarm Optimization for Active Control Engine Mount2017-01-10563/28/2017
Manufacturers have been encouraged to accommodate advanced downsizing technologies such as the Variable Displacement Engine (VDE) to satisfy commercial demands of comfort and stringent fuel economy. Particularly, Active control engine mounts (ACMs) notably contribute to ensuring superior effectiveness in vibration attenuation. This paper incorporates a PID controller into the active control engine mount system to attenuate the transmitted force to the body. Furthermore, integrated time absolute error (ITAE) of the transmitted force is introduced to serve as the control goal for searching better PID parameters. Then the particle swarm optimization (PSO) algorithm is adopted for the first time to optimize the PID parameters in the ACM system. Simulation results are presented for searching optimal PID parameters. In the end, experimental validation is conducted to verify the optimized PID controller. The study demonstrates that the improved PID controller reveals effective vibration isolation performance.
Guo, Rong, Wei, Xiao-Kang, Gao, Jun
Implementation of an Extended Model for Multi-Axle Articulated Vehicle with Nonlinear Tire Model2017-01-04363/28/2017
A new extended planar model for multi-axle articulated vehicle with nonlinear tire model is presented. This nonlinear multi-axle articulated vehicle model is specifically intended for improving the model performance in operating regimes where tire lateral force is near the point of saturation, and it has the potential to extend the specific axles model to any representative configuration of articulated vehicle model. At the same time, the extended nonlinear vehicle model can reduce the model's sensitivity to the tire cornering coefficients. Firstly, a nonlinear tire model is used in conjunction with the 6-axle planar articulated vehicle model to extend the ranges of the original linear model into the nonlinear regimes of operation. Secondly, the performance analysis of proposed nonlinear vehicle model is verified through the double lane change maneuver on different road adhesion coefficients using TruckSim software. Simulation results demonstrate that the proposed vehicle model shows high accuracy, which provides accurate simulation of the vehicle states on different road adhesion coefficient.
Zhu, Tianjun, Li, Bin
Electric Water Cooling Pump Sensitivity Based Adaptive Control2017-01-06023/28/2017
With the trending electrification of vehicle accessory drives brings new control concepts useful in many cases to optimize energy management within the powertrain system. Considering that direct engine drives do not have as much flexibility as independent electric drives, it is apparent that several advantages are to be expected from electric drives. New developed high efficient electric drives can be implemented when considering many vehicle sub-systems. Combinations of continuous varying and discrete flow control devices offer thermal management opportunities across several vehicle attributes including fuel economy, drivability, performance, and cabin comfort. Often new technologies are integrated with legacy systems to deliver maximum value. Leveraging both electrical and mechanical actuators in some cases presents control challenges in optimizing energy management while delivering robust system operation. In this paper Electrification of Water Cooling Pump has been considered where Sensitivity Based Adaptive Control has been investigated because of the simplicity of this methodology resulting in lower computational burdens and its applicability to many engineering projects. Sensitivity Based Adaptive Control has lead us to opinion that Renaissance of this method may soon come.
Kokotovic, Vladimir Vasilije, Buckman, Colby
On the Tradeoffs between Static and Dynamic Adaptive Optimization for an Automotive Application2017-01-06053/28/2017
Government regulations for fuel economy and emission standards have driven the development of technologies that improve engine performance and efficiency. These technologies are enabled by an increased number of actuators and increasingly sophisticated control algorithms. As a consequence, engine control calibration time, which entails sweeping all actuators at each speed-load point to determine the actuator combination that meets constraints and delivers ideal performance, has increased significantly. In this work we present two adaptive optimization methods, both based on an indirect adaptive control framework, which improve calibration efficiency by searching for the optimal process inputs without visiting all input combinations explicitly. The difference between the methods is implementation of the algorithm in steady-state vs dynamic operating conditions. The goal of this work is to study the optimization performance tradeoffs between robustness to sensor noise and required optimization time. We demonstrate both methods on an engine installed in a dynamometer where multiple actuators were calibrated to minimize Break Specific Fuel Consumption (BSFC), while satisfying input and output constraints.
D'Amato, Anthony, Wang, Yan, Filev, Dimitar, Remes, Enrique
Resistance Spot weld in Vehicle Structures Using Dynamic Resistance Adaptive Control2016-36-030310/25/2016
To highlight the importance of resistance spot weld in the automotive industry, it's important know that a vehicle has on average 4,000 welding spots [BROWN; SCHWABER 2000] and based on worldwide vehicle production in 2015 with 90.78 million vehicles produced [OICA, 2015], were performed more than 363 billion welding spots. The number of machines in manual and automatic workstations (robots), based on 20 points by equipment and production of 45 vehicles / hour add up more than 20 million of welding machines in all over world. According new production lines are being introduced using the adaptive dynamic resistance control the welding constant current control are being replaced, so understand this technology and know implement it with efficiency needs a deep knowledge in how dynamic resistance works and correlate his behavior with the problems that causes failures in welding, so is necessary give for the welding engineers this knowledge.
Reis, Frederico Fernandes, Furlanetto, Valdir, Batalha, Gilmar Ferreira
High Performance Motion Control Without a Foundation For Fuselage Fastening Automation2016-01-21039/27/2016
This technical paper details an optimized Drivmatic machine design delivered to a Tier 1 aero structure supplier to automate drilling and installation of rivets, hi-loks, lockbolts & swage collars for individual fuselage panel assemblies with high throughput & strict quality requirements. While certain robot solutions continue to be explored for specific applications at many Tier 1 aero structure suppliers, robot payload capacity has limitations beyond certain criteria, which often times point towards an alternative machine design as in this case study. A typical approach for adding more automation is to allocate shop floor space based on the solution’s foot print, however contrary to most approaches this solution had to be designed to fit within a pre-determined factory footprint over a geographic location with a high water table that would not permit a foundation. GEMCOR was therefore challenged to deliver a CNC automatic fastening solution with high-speed motion control technology that would accurately and reliably perform under higher speed conditions without a foundation.
Barton, Eric
Residual Mode FiltersTBMG-253189/1/2016
NASA has developed a unique control algorithm and synthesis method that uses a system’s output to modify control inputs to cause the system to track a reference model or a fixed value in the presence of unmodeled system dynamics, varying operating environments, and unpredictable disturbances. The unique feature of this algorithm is the ability to instantaneously adapt the system according to its output, rejecting persistent disturbances, and ultimately improving the system’s performance. This makes the controller ideally suited for applications where there are unknown modeling parameters or uncertain operating environments. Many aerospace systems must function in unknown or highly variable environments. This technology allows the system to achieve its objectives in these types of unpredictable environments. In comparison to current adaptive controller technologies, the addition of residual mode filters allows operation when flexible modes are present that could inhibit the controller. This is especially useful for systems where initial modeling is costly, or the fidelity of existing system models is low.
L1-based Model Following Control of an Identified Helicopter Model in HoverF-0072-2016-114665/17/2016
The aim of this study is to augment the uncertain dynamics of the helicopter in order to resemble the dynamics of a new kind of vehicle, the so called Personal Aerial Vehicle. To achieve this goal a two step procedure is proposed. First, the helicopter model dynamics is augmented with a PID-based dynamic controller. Such controller implements a model following on the nominal helicopter model without uncertainties. Then, anL1 adaptive controller is designed to restore the nominal responses of the augmented helicopter when variations in the identified parameters are considered. The performance of the adaptive controller is evaluated via Montecarlo simulations. The results show that the application of the adaptive controller to the augmented helicopter dynamics can significantly reduce the effects of uncertainty due to the identification of the helicopter model. For implementation reasons the adaptive controller was applied to a subset of the outputs of the system. However, the under actuation typical of helicopters makes the tracking of the nominal responses good also on the not directly adapted outputs.
Picardi, Giacomo, Pollini, Lorenzo, Geluardi, Stefano, Olivari, Mario, Buelthoff, Heinrich, Innocenti, Mario
Testing an Artificial PancreasTBMG-241463/1/2016
A team of scientists from the University of Virginia (UVA) School of Medicine and the Harvard John A. Paulson School of Engineering and Applied Sciences developed a project to turn an ordinary smartphone into an artificial pancreas that has since received a $3.4 million grant from the National Institutes of Health. Now, researchers are beginning one of the largest-ever long-term clinical trials of a system designed to help regulate blood sugar levels of individuals with type 1 diabetes mellitus. The “artificial pancreas” system will be tested in 240 patients at nine sites in the US and Europe. Two six-month trials are beginning in early 2016, in collaboration with a half dozen other institutional partners.
Electrical Interface Between Numerical Control and Machine ToolsEIARS431 (Current)7/1/2015
This standard covers both active and passive aspects of the electrical interface between the Numerical Control (NC) and the machine power and logic control, motor drive equipment, and other electrical apparatus on or associated with the machine tool. It covers:
Systems Management Council
Controlling Execution Sequence Using Tactile-Classification During Manipulation by a Humanoid RobotTBMG-224087/1/2015
It is necessary to track system state during robotic manipulation. System state is defined to be manipulator and environment configuration. Without tracking, the robot is ignorant of the outcomes of its actions. State tracking enables the robot to respond to sub-task failures. Tracking system state is difficult for complex robots that incorporate hundreds of individual sensor signals. It is difficult to determine which signals are relevant and which are not, and to find low dimensional representations of system state.
Active Control of Structure-Borne Road Noise Based on the Separation of Front and Rear Structural Road Noise Related Dynamics2015-01-22226/15/2015
Axle forces from tire-road interaction can excite different structural resonances of the vehicle hence a high number of sensors is required for observing and separating all the vibrations dynamics that are coherent with the cabin noise. Feed-forward road noise control strategies adopted so far rely mainly on capturing these dynamics and thus the number of sensors constitutes one major limitation of this approach. Therefore there is a necessity for reducing the number of sensors without degrading the performance of an ANC system. In the past coherence function analysis has been found to be a useful tool for optimizing the sensor location. In this case coherence function mapping was performed between an array of vibration sensors and the headrest microphones in order to identify the locations on the structure that are highly correlated with road noise bands in the compartment. A vehicle with an advanced suspension system was used for applying the method and defining some locations as reference signals for feed-forward active road noise control. Three different real-time control experiments were performed with structure-borne road noise simulated by applying broad band random forces to tires through shaker transducers. A single reference feed-forward adaptive controller evaluated the signals from each sensor location with simulated road noise excitation applied to: front wheels only, rear wheels only and whole vehicle. This way it is demonstrated that the control can be focused at specific road noise bands with a low number of sensors.
Zafeiropoulos, Nikos, Ballatore, Marco, Moorhouse, Andy, Mackay, Andy
Method for Improving Control Systems with Normalized Adaptation by Optimal Control ModificationTBMG-220085/1/2015
A new technology has been developed for improving performance and stability of control systems. This method represents a significant advancement in the state-of-the-art of adaptive control technology. The present invention is a new type of adaptive control law, called optimal control modification, which blends two control technologies together: optimal control and adaptive control.
Optimal Control Inputs for Fuel Economy and Emissions of a Series Hybrid Electric Vehicle2015-01-12214/14/2015
Hybrid electric vehicles offer significant fuel economy benefits, because battery and fuel can be used as complementing energy sources. This paper presents the use of dynamic programming to find the optimal blend of power sources, leading to the lowest fuel consumption and the lowest level of harmful emissions. It is found that the optimal engine behavior differs substantially to an on-line adaptive control system previously designed for the Lotus Evora 414E. When analyzing the trade-off between emission and fuel consumption, CO and HC emissions show a traditional Pareto curve, whereas NOx emissions show a near linear relationship with a high penalty. These global optimization results are not directly applicable for online control, but they can guide the design of a more efficient hybrid control system.
Knapp, Jamie, Chapman, Adam, Mody, Sagar, Steffen, Thomas
Model Reference Adaptive Control for Active Trailer Steering of Articulated Heavy Vehicles2015-01-14954/14/2015
This paper proposes a model reference adaptive control (MRAC) strategy for active trailer steering (ATS) in order to improve the lateral stability of articulated heavy vehicles (AHVs). Optimal controllers based on the Linear Quadratic Regulator (LQR) technique have been explored to enhance the lateral stability of AHVs; these controllers are designed under the assumption that the vehicle model parameters and operating conditions are given and they remain as constants. However, in reality, the vehicle system parameters and operating conditions may vary. To address the variable payloads of trailer(s), the controller based on MRAC technique is adopted. A three degrees of freedom (DOF) linear yaw-plane tractor-semitrailer model is generated to design the control law. The reference model is also developed using the linear yaw-plane model with the LQR technique. The effectiveness of the MRAC controller is demonstrated using numerical simulations under an emulated single lane-change maneuver.
Wang, Qiushi, Zhu, Shenjin, He, Yuping
Fault-Tolerant Control for 4WID/4WIS Electric Vehicles2014-01-258910/13/2014
The passive fault-tolerant approach for four-wheel independently driven and steered (4WID/4WIS) electric vehicles has been investigated in this study. An adaptive control based passive fault-tolerant controller is designed to improve vehicle safety, performance and maneuverability when an actuator fault happens. The proposed fault tolerant control method consists of the following three parts: 1) a fault detection and diagnosis (FDD) module that monitors vehicle driving condition, detects and diagnoses actuator failures with the inequality constraints; 2) a motion controller that computes the generalized forces/moments to track the desired vehicle motion using Model Predictive Control (MPC); 3) a reconfigurable control allocator that redistributes the generalized forces/moments to four wheels with equality constrained optimization. The FTC approach is based on the reconfigurable control allocation which reallocates the generalized forces/moments among healthy actuators once the actuator failures is detected. If one or more in-wheel motors lose efficacy, the FDD module diagnoses the actuator failures first. Then the reconfigurable control allocator accommodates faulty in-wheel motors and reconfigures the control allocation law of the healthy motors to achieve the desired vehicle motion to the greatest extent. Numerical simulations have been conducted to verify the proposed algorithm. It has been shown that the FTC controller prevents the fault further expands, and displays the effectiveness of the proposed fault tolerant control approaches in various driving scenarios.
Li, Chunshan, Chen, Guoying, Zong, Changfu
Radio Frequency Diesel Particulate Filter Soot and Ash Level Sensors: Enabling Adaptive Controls for Heavy-Duty Diesel Applications2014-01-23499/30/2014
Diesel Particulate Filters (DPF) are a key component in many on- and off-road aftertreatment systems to meet increasingly stringent particle emissions limits. Efficient thermal management and regeneration control is critical for reliable and cost-effective operation of the combined engine and aftertreatment system. Conventional DPF control systems predominantly rely on a combination of filter pressure drop measurements and predictive models to indirectly estimate the soot loading state of the filter. Over time, the build-up of incombustible ash, primarily derived from metal-containing lubricant additives, accumulates in the filter to levels far exceeding the DPF's soot storage limit. The combined effects of soot and ash build-up dynamically impact the filter's pressure drop response, service life, and fuel consumption, and must be accurately accounted for in order to optimize engine and aftertreatment system performance. This work applied a radio frequency (RF) sensor to directly monitor diesel particulate filter soot and ash levels, thereby enabling direct feedback control of the filter based on its actual loading state. Results from fleet tests with Volvo/Mack trucks, over predominantly urban drive cycles, indicated the potential to decrease regeneration duration and associated fuel consumption by 50% to 75%, depending on operating conditions, and also to extend the time between active filter regenerations. Additional testing evaluated the performance of the sensor to distinguish soot from ash and define the DPF ash cleaning based on the actual measured ash load, as opposed to a prescribed filter maintenance interval. The results are useful to develop advanced control strategies to minimize the DPF-related fuel penalty, extend the service life of the filter, and identify anomalies indicative of filter failures or engine malfunctions.
Sappok, Alexander, Bromberg, Leslie
Robot Accuracy: Offline Compensation (EU COMET Project)2014-01-22569/16/2014
The 30 month COMET project aims to overcome the challenges facing European manufacturing industries by developing innovative machining systems that are flexible, reliable and predictable with an average of 30% cost efficiency savings in comparison to machine tools. From a conceptual point of view, industrial robot technology could provide an excellent base for machining being both flexible and cost efficient. However, industrial robots lack absolute positioning accuracy, are unable to reject disturbances in terms of process forces and lack reliable programming and simulation tools to ensure right first time machining, once production commences. These three critical limitations currently prevent the use of robots in typical machining applications. The COMET project is co-funded by the European Commission as part of the European Economic Recovery Plan (EERP) adopted in 2008. The EERP proposes the launch of Public-Private Partnerships (PPP) in three sectors, one of them being Factories of the Future (FoF). Factories of the Future is a EUR 1.2 billion program in which the European Commission and industry are collaborating in research to support the development and innovation of new enabling technologies for the EU manufacturing sector. The 14 project partners combine their experience and expertise in manufacturing from 8 countries across Europe to use plug-and-produce COmponents and METhods for adaptive control of industrial robots enabling high-end machining for cost effective, flexible and reliable manufacturing solutions.
Holden, Roger, Lightowler, Paul, Andreou, Simon
Robot Accuracy: Online Compensation (EU COMET Project)2014-01-22579/16/2014
The 30 month COMET project aims to overcome the challenges facing European manufacturing industries by developing innovative machining systems that are flexible, reliable and predictable with an average of 30% cost efficiency savings in comparison to machine tools. From a conceptual point of view, industrial robot technology could provide an excellent base for machining being both flexible and cost efficient. However, industrial robots lack absolute positioning accuracy, are unable to reject disturbances in terms of process forces and lack reliable programming and simulation tools to ensure right first time machining, once production commences. These three critical limitations currently prevent the use of robots in typical machining applications. The COMET project is co-funded by the European Commission as part of the European Economic Recovery Plan (EERP) adopted in 2008. The EERP proposes the launch of Public-Private Partnerships (PPP) in three sectors, one of them being Factories of the Future (FoF). Factories of the Future is a EUR 1.2 billion program in which the European Commission and industry are collaborating in research to support the development and innovation of new enabling technologies for the EU manufacturing sector. The 14 project partners combine their experience and expertise in manufacturing from 8 countries across Europe to use plug-and-produce COmponents and METhods for adaptive control of industrial robots enabling high-end machining for cost effective, flexible and reliable manufacturing solutions.
Holden, Roger, Lightowler, Paul, Andreou, Simon
A New Adaptive Controller for Performance Improvement of Automotive Suspension Systems with MR Dampers2014-01-00524/1/2014
A control algorithm is developed for active/semi-active suspensions which can provide more comfort and better handling simultaneously. A weighting parameter is tuned online which is derived from two components - slow and fast adaptation to assign weights to comfort and handling. After establishing through simulations that the proposed adaptive control algorithm can demonstrate a performance better than some controllers in prior-art, it is implemented on an actual vehicle (Cadillac STS) which is equipped with MR dampers and several sensors. The vehicle is tested on smooth and rough roads and over speed bumps.
Khajepour, Amir, Agrawal, Ankur
Design of an Actuator Fault Tolerant Flight Control System Using Fault Detection and Diagnosis2013-01-21389/17/2013
This paper presents a fault tolerant flight control design for the longitudinal linear model of the Boeing 737-100. The EMMAE (Extended Multiple Model Adaptive estimation) method is used to design the FDD process (Fault Detection and Diagnosis). Based essentially on a set of EKFs (Extended Kalman Filters), this method makes it possible to simulate several types of faults including stuck and oscillation. To develop the RFC (Reconfigurable Flight Control) law, SMC (Sliding Mode Control) method [11] is used. To rigorously investigate the performance of the overall system with respect of interactions between the two subsystems, The MRAC (Model Reference Adaptive Control) method [3] is used for comparison. Several simulation results using Matlab and Simulink show the desired system performance with fault compensation.
Ghodbane, Azeddine, Saad, Maarouf, Boland, Jean-François, Thibeault, Claude
Integrated Reconfigurable Aero-Propulsion (IRAP) Control for Improved Fault Tolerance2013-01-22559/17/2013
In this paper we present results of a study of an integrated aero-propulsion flight control system. The resulting problem is that of controlling the system in which actuators operate on different time scales. This is a difficult problem since the control strategy needs to balance between not using the slow actuator at all, and slowing down the overall system to the time scale of the slow actuator. In the case of aero-propulsion control design for F/A-18 aircraft, the part of the control derivative matrix associated with engines is not full rank so not all states of interest can be simultaneously forced to track the commands. A control strategy that takes this constraint into account has been developed. The proposed IRAP approach is illustrated through simulation of F/A-18 aircraft dynamics under flight-critical control effector failures.
Boskovic, Jovan D., Jackson, Joseph, Mehra, Raman
Integrated Health Monitoring and Fault Adaptive Control for an Unmanned Hexrotor Helicopter2013-01-23319/17/2013
This paper presents a novel health monitoring and fault adaptive control architecture for an unmanned hexrotor helicopter. The technologies developed to achieve the described level of robust fault contingency management include; 1.) A Particle Swarm Optimization (PSO) routine for maximizing the “built-in” fault tolerance that the closed loop flight control system affords, 2.) A two-stage Kalman filter scheme for real-time identification of faults that are masked by control system compensation, and 3.) A reconfigurable control allocation method which compensates for large degradations of the six main motor/rotor assemblies. The fault adaptive control system presented herein has strong robustness against small faults without the need for controller reconfiguration, and strong tolerance of large faults through adaptive accommodation of the fault source and severity. By taking advantage of the inherent fault-tolerant nature of typical closed loop control systems, the technology described in this paper avoids the difficulties associated with typical fault detection and isolation (FDI) techniques that have poor performance when targeting incipient faults. Simulation results show the effectiveness of the proposed approach when various levels of fault severity are seeded in one of the six main motors.
Ge, Jianhua, Lefevre, Brian, Roemer, Michael, Martin, Rodney
ℒ 1 Adaptive Flutter Suppression Control Strategy for Highly Flexible Structure2013-01-22639/17/2013
The aim of this work is to apply an innovative adaptive ℒ1 techniques to control flutter phenomena affecting highly flexible wings and to evaluate the efficiency of this control algorithm and architecture by performing the following tasks: i) adaptation and analysis of an existing simplified nonlinear plunging/pitching 2D aeroelastic model accounting for structural nonlinearities and a quasi-steady aerodynamics capable of describing flutter and post-flutter limit cycle oscillations, ii) implement the ℒ1 adaptive control on the developed aeroelastic system to perform initial control testing and evaluate the sensitivity to system parameters, and iii) perform model validation and calibration by comparing the performance of the proposed control strategy with an adaptive back-stepping algorithm. The effectiveness and robustness of the ℒ1 adaptive control in flutter and post-flutter suppression is demonstrated. Results and discussion will follow with pertinent conclusions and future outlooks.
Cassaro, Mario, Battipede, Manuela, Marzocca, Piergiovanni, Cestino, Enrico, Behal, Aman
Flight Control Fault Models Based on SEU Emulation2013-01-22469/17/2013
The increased use of FPGAs over the past decade has induced an increased concern about radiation effects, in particular the effects of single event upsets (SEU) in SRAM-based FPGAs. Technology scaling and density increase have caused FPGAs to be more vulnerable to SEU. Therefore, external radiations present an issue not only for space based systems; but also for critical terrestrial applications operating in harsh environment, such as commercial avionics. In order to build robust fault tolerant systems, SEU effects have to be analyzed and modeled so that the designer understands and considers the system's possible faulty behaviors. In this paper, we present a complete automated methodology, based on the use of SEU controller provided by Xilinx, to efficiently emulate SEUs on an FPGA design and extract possible fault models based on radiation effects. The proposed method is applied on a reconfigurable flight control system based on a reference adaptive control model. With the automatic aspect of the proposed methodology, it was possible to emulate a large number of SEUs with reduced time and effort. Experimental results present the design sensitivity, its failure rate as well as its faulty output behavior. Moreover, results analysis disclose the existence of new actuator control fault models that are not considered in fault tolerant systems, these systems being mainly based on the existing well-known models in the literature. The new fault models can be used by the designer at an earlier stage in the design to build robust flight control systems.
Hobeika, Christelle, Pichette, Simon, Ghodbane, Azeddine, Thibeault, Claude, Audet, Yves, Boland, Jean-François, Saad, Maarouf
Self-Tuning Speed Tracking Controller for a Portable Brake and Throttle Robot2013-01-14344/8/2013
Vehicle testing often requires accurate speed control, whether maintaining a constant speed or following a dynamic speed profile. A portable brake and throttle robot designed for this task must quickly and automatically adapt its control to each test vehicle's mass and powertrain characteristics in order for the controller to perform well on a wide variety of platforms. This application presents two major challenges. First, each new vehicle installation requires rapid retuning of the controller. Manual tuning can be very time-consuming. Second, the “plant” is very nonlinear and asymmetric. Different actuators are employed for acceleration (engine) and braking (road loads and friction brakes). After a broad survey of control strategies and their suitability for this particular application, neurofuzzy techniques were among the most promising. Neurofuzzy networks can not only approximate nonlinear functions accurately, but the fuzzy rule-consequent weights can be readily updated in real time. A neurofuzzy controller was designed for the automotive speed tracking problem. Experimental testing was conducted and results were presented and analyzed.
Mikesell, David R., Sidhu, Anmol
Intelligent Energy Distribution for Series HEVs Using Determined Optimal Driving Patterns via a Genetic Algorithm2013-01-05724/8/2013
This paper introduces an intelligent energy distribution scheme for series plug-in hybrid electric vehicles (PHEVs) which incorporates the complexity of human driving behavior. Driving styles can have a significant impact on fuel consumption, but it is often unclear how one should drive to get the optimal fuel efficiency. Hybrid electric vehicles have been shown to improve fuel economy, reduce vehicle emissions and maintain drivability by incorporating electric motors into the drivetrain. Due to the highly complex system design and vehicle architecture, sophisticated energy management strategies (EMS) are required to optimize the vehicle performance. Currently, the power management system is based on static thresholds optimized on a fixed drive cycle for a given vehicle. This paper introduces an adaptive control method for EMS utilizing the complexity of human driving patterns for energy distribution in a series PHEV. By utilizing the Genetic Algorithm (GA) optimization method to determine the optimal driving patterns offline, an optimal EMS can be derived to maintain an effective control algorithm in real-time.
Ho, Phu, Klang, Eric
Development of a Hybrid Powertrain Active Damping Control System via Sliding Mode Control Scheme2013-01-04864/8/2013
This paper presents the design of a hybrid powertrain damping control algorithm using the sliding mode control (SMC) scheme. Motor control-based active damping control strategy is used to ensure smooth drive line operation and provide the driver with seamless driving experience. In the case of active damping control, motor and engine speeds are measured to monitor the driveline state, and corrective motor torques are generated to dampen out drive line vibrations. Drive lines are prone to internal vibration (engine, clutches and motors) as well as external disturbances caused by road inputs. As such, fast-response actuator-based damping control systems are desirable in a hybrid powertrain application, where a torque converter is generally not used. The most significant aspect of an active damping control algorithm is the error calculation, based on proper states information, and torque determination based on the adaptive control gain applied to the nonlinear system. For the proposed control approach, reference states are computed for different transmission modes and the tracking errors are calculated using actual measured states. The damping control torque is determined using the proposed SMC, which is developed after an analysis of the drive line model, and uses the motors as actuators to minimize the effects of internal and external disturbances. This control algorithm is developed for a power-split hybrid powertrain system and the response of the powertrain under the damping control is evaluated using vehicle-level testing, and results are discussed.
Kou, You Seok, Weslati, Faz
Design of a Model Reference Cruise Control Algorithm2012-01-04924/16/2012
A methodology to design a model free cruise control algorithm(MFCC) is presented in this paper. General cruise control algorithms require lots of vehicle parameters to control the power train and the brake system, that makes control system complicate. Moreover, when the target vehicle is changed, the vehicle parameters should be reinvestigated in order to apply the cruise control algorithm to the subject vehicle. To overcome these disadvantages of the conventional cruise control algorithm, MFCC algorithm has been developed. The algorithm directly determines the throttle, brake inputs based on the reference model parameters such as clearance, relative velocity, and subject vehicle acceleration. This simple structure facilitates human centered design of cruise controller and makes it easy to apply control algorithm to various vehicles without reinvestigation of vehicle parameters. To achieve vehicle safety and driver comfort, control parameters of the model free cruise control algorithm has been designed using the real-world driving test data. Few parameters have been adapted using a learning algorithm to minimize the effects of unawareness of the vehicle parameters. From the simulation study, the performance of the proposed controller has been compared with that of the conventional adaptive cruise controller(ACC). It is shown that the proposed control strategy its behavior is not only similar to that of the conventional ACC in normal driving condition but also more robust than the ACC for model uncertainty and external disturbance.
Kim, Hakgu, Yi, Kyongsu
A Review Study of Methods for Lithium-ion Battery Health Monitoring and Remaining Life Estimation in Hybrid Electric Vehicles2012-01-01254/16/2012
Due to the high power and energy density and also relative safety, lithium ion batteries are receiving increasing acceptability in industrial applications especially in transportation systems with electric traction such as electric vehicles and hybrid electric vehicles. In this regard, to ensure performance reliability, accurate modeling of calendar life of such batteries is a necessity. In fact, potential failure of Li-ion battery packs remains a barrier to commercialization. Battery pack life is a critical feature to warranty and maintenance planning for hybrid vehicles, and will require adaptive control systems to account for the loss in vehicle range, and loss in battery charge and discharge efficiency. Failure not only results in large replacement costs, but also potential safety concerns such as overheating or short circuiting which may lead to fires. That's why health monitoring, fault detection and end of life prediction capability in battery-equipped systems are of great importance. This paper reviews recent research and achievements in the field of Li-ion battery health monitoring and prognostics. The different models, algorithms and techniques being applied to estimate state of charge (SoC) and capacity, and prediction of the remaining useful life (RUL), are presented along with an analysis of the pros and cons of each model or method. It is hoped that these review and discussions prepare a wider perspective on progresses and challenges of Li-ion battery health monitoring and prognostics.
Samadani, Seyed Ehsan, Fraser, Roydon A., Fowler, Michael
Automatic Tuning of Two-Degree-of-Freedom PID Control for Engine Electronic Throttle System2010-01-01564/12/2010
Engine Electronic Throttle Control (ETC) systems are gaining success in high volume applications. This system helps to improve overall engine and vehicle performance, as well as facilitate the function integration of related control features. The requirement for an ETC system is that it fulfills the commanded throttle plate opening as quickly and accurately as possible. Because of nonlinearity of the electronic throttle system, gain-scheduled control is often used. A method to automatically tune the control for each operating region is needed. In this paper the engine electronic throttle is considered as having dominant linear dynamics for each operating region. A Two-Degree-of-Freedom (2-DOF) PID controller and a method of using Model Reference Adaptive Control (MRAC) algorithm to automatically tune the PID control gains are designed. With this approach, control performance enhancement from initial control settings can be realized with closed loop testing, without the need of a plant model. Control gains that give good performance can be obtained quickly for each operating region of the system. The designed control and automatic tuning algorithm is implemented on a rapid prototyping setup and the application results show the effectiveness of the method.
Jiang, Shugang, Smith, Michael, Kitchen, James
Measurement System to Optimize Automation Processes2009-01-308711/10/2009
Modern manufacturing processes are constantly under observation to improve efficiency and reduce costs. In many cases new materials like CFK need a different approach to check part tolerances which in general increase the effort. Based on these facts a 6DoF Laser Tracker System could become one solution to reduce costs and improve measurement quality especially in the direction of automation. The following paper describes a Laser Tracker with a machine control probe (T-Mac) for online measurements of machines or robots. Measurements to analyse static and dynamic robot performance and different methods to calibrate or improve absolute accuracy of robots are shown. Meanwhile online corrections for a robot or a machine can be realized with an update-rate of 10 Hz, but activities to establish a 1000 Hz real-time interface are planned. With the 6DoF capability this Laser Tracker system provides significant enhancements for measurement assisted assembly or for automated part inspection directly. Recently started developments for further sensor enhancements with respect to automated part inspection will open additional fields of robot and machine applications.
Loser, R., Kleinkes, M.
Crew Life Support System for Interplanetary Vechicles2009-01-24647/12/2009
Interplanetary manned missions will change significantly the requirements imposed upon Life Support Systems (LSS) and specifically the requirements on LSS Automated Control Systems (ACS). During interplanetary manned missions the possibilities to control the operation of a specific system from the Ground Mission Control Center (GMCC) are diminished considerably. Therefore, this demands survivability and intelligent level enhancement LSS ACS. The possible ways to solve this problem are as follows: ◦ use of control units and devices built with serial production technology application leading to the minimum of human factor impact; ◦ application of algorithms based on maximal use of adaptive control principles, methods of artificial intelligence theory, engineering system condition diagnosis and prediction; ◦ making up of an aboard information system on the basis of advanced RS 485 interfaces; ◦ maximal development of LSS&ACS section/module structures ensuring module-board communication via two cables: a power cable and an aboard information network communication cable; ◦ development of intelligent systems for identification and issue instructions to the crew as to isolation of off-normal situations (faults) to enhance survivability and reduce substantially the crew's working time spent on LSS operation. It is demonstrated that the solution of this problem enables building the advanced LSS ACS suitable for implementation of various space programs.
Zaretskiy, B. F., Gavrilov, L. I., Kurmazenko, E. A.
Optimization of PID Control for Engine Electronic Throttle System Using Iterative Feedback Tuning2009-01-03704/20/2009
The Electronic Throttle Control (ETC) system is more and more used and increasingly becoming a standard part of the engine. It controls the amount of air intake into the cylinders by precisely positioning the throttle plate at the desired opening. An ETC system provides the possibility of improving the overall engine and vehicle performance because with such a mechanism, the engine controller can decide and set the throttle position not only based on driver intention, but also taking into consideration the specific engine operation mode information, such as safety factors, emission constraints, etc. After the throttle position target is determined, the requirement for the ETC system is that the throttle plate should achieve the commanded position as accurately and as quickly as possible. In many cases the controller is designed by first establishing a model of the electronic throttle system using experimental identification. However, due to such nonlinear effects as static friction, dynamic friction, and nonlinear return springs etc., identification of a model for the electronic throttle system sometimes does not give good results. This makes a controller design based on the model far from optimal. Iterative Feedback Tuning (IFT) is a method for directly tuning the controller parameters based on the data of closed loop experiments without the need for an explicit model of the system. This property makes IFT an attractive method for ETC design. In this paper a Two-Degree-of-Freedom (2-DOF) Proportional-Integral-Derivative (PID) controller for an engine electronic throttle system is designed and the PID control gains are optimized using IFT. The application shows that the IFT method gives very good performance for controller tuning.
Jiang, Shugang, Smith, Michael H., Kitchen, James
Developments in Adaptive Filtering and System IdentificationTBMG-48878/1/2008
Progress has been made on several fronts in a continuing program of research oriented toward the development of real-time algorithms, and computer and control systems that utilize the algorithms, for adaptive filtering, prediction, and system identification with improved efficiency and numerical stability in applications that involve large numbers of channels and high filter orders. Potential applications include adaptive optics, optical communications, target tracking, image processing, blind identification and deconvolution in wireless communications, and active control of noise and vibration.
Hybrid Adaptive Flight Control with Self-Improving Plant Model for Stability and Control of Damaged Aircraft2007-01-38989/17/2007
This paper presents a hybrid adaptive control method for maintaining stability and control of damaged aircraft. The hybrid method utilizes an adaptive parameter estimation scheme to improve a plant model in a flight control system. Two adaptive parameter estimation schemes are developed: 1) an indirect adaptive control law with normalization based on the Lyapunov direct method that uses tracking error for adaptation, and 2) a recursive least-squares law based on the optimal estimation method that uses plant model error for adaptation. Simulations show that the hybrid adaptive control can provide a significant improvement in the tracking performance of a flight control system.
Nguyen, Nhan
Closed Loop Controlled High Speed Induction Generators Using Adaptive Control Technique2006-01-305111/7/2006
High speed generators offer very high power density solution for electric power requirements in airborne applications. Induction generators are suitable for the high speed environment because of the ability to provide controlled voltage and power output with a reliable rotor construction. An important issue of power control for the high speed induction generator is maintenance of the steady state output voltage within the specified limits over the entire range of speed and load variations. This paper discusses the development of a closed loop control system for a 200 kW induction generator under different load conditions. Field Oriented Control (FOC) schemes are implemented to both operate the generator in the maximum torque conditions available and to decouple the maximum torque from the field under transient and steady state operation. FOC uses Classical Proportional and Integral (PI) controllers for regulation because of their simple implementation. However, PI controllers do not perform well when controlling high order non-linear dynamic plants - such as the high speed induction generators - due to the overshoot response and the output saturation when generator is loaded. To resolve this issue, the proportional gains need adjustments with respect to the load variation as well as the overshoot response in realtime. A gain scheduling control algorithm has been developed to select the appropriate controller gains with respect to the generator load. Further, a relationship between the generator loads and the controller gains have been established. This relationship was modeled using adaptive control technique to vary the gains automatically under any load condition. The adaptive control technique has been successfully generalized for real time DSP implementation to regulate the DC voltage for high speed induction generators rated from 5 kW to 200 kW.
Elkhomri, Ottman, Vaidya, Jay G, Gregory, Earl
Non-Linear Adaptive Attitude Control of Rigid Body in Space2006-01-24168/30/2006
This paper looks at the attitude control of space vehicles. In this research, a new self-tuning adaptive attitude control law has been developed for spatial tracking control of a general rigid satellite. The goal of this research is to demonstrate an adaptive control system that can accurately compensate for modeling and parameters uncertainties. This method can be adapted to unknown parameter variation, for typical flight regimes. Our approach is based on obtaining general rigid body kinematics and dynamics equations. Among different approaches used for defining attitude of a rigid body quaternions or Euler parameters are used in this study. The control law is based on the theory of non-linear feedback linearization. It is shown that the control law is stable according to Lyapunov stability criteria. The design variables of system are inertia properties of rigid body. It is assumed that inertia tensor of the body is unknown. The inertia tensor is estimated using standard least square with bounded gain forgetting method. The total controller and plant model is simulated using MATLAB. Simulation results are provided to illustrate the salient features of the approach. This results show the stability of system, i.e. the adaptive controller is stable and all tracking errors and state variables errors converge to zero. Also according to simulation results, it was confirmed that by using bounded gain forgetting method with standard least square, the estimator would be faster and the estimation errors would be smaller in comparison with using standard least square estimator alone.
Dolatabadi, Afshin Mohammadi, Kabganian, Mansour
Controlling Attitude of a Solar-Sail Spacecraft Using VanesTBMG-957/1/2006
A paper discusses a concept for controlling the attitude and thrust vector of a three-axis stabilized Solar Sail spacecraft using only four single degree of freedom articulated spar-tip vanes. The vanes, at the corners of the sail, would be turned to commanded angles about the diagonals of the square sail. Commands would be generated by an adaptive controller that would track a given trajectory while rejecting effects of such disturbance torques as those attributable to offsets between the center of pressure on the sail and the center of mass. The controller would include a standard proportional + derivative part, a feed forward part, and a dynamic component that would act like a generalized integrator. The controller would globally track reference signals, and in the presence of such control actuator constraints as saturation and delay, the controller would utilize strategies to cancel or reduce their effects. The control scheme would be embodied in a robust, nonlinear algorithm that would allocate torques among the vanes, always finding a stable solution arbitrarily close to the global optimum solution of the control effort allocation problem. The solution would include an acceptably small angle, slow limit-cycle oscillation of the vanes, while providing overall thrust vector pointing stability and performance.
Adaptive Autopilot System for Small Fixed Wing UAVs2005-01-335510/3/2005
Small low cost UAV autopilot systems (research and fielded platforms) in use today are severely restricted in their operational capability and quite costly with respect to their operational capability. The size of the UAV introduces unique problems in the development of Guidance, Navigation, and Control (GNC) algorithms since aerodynamic models of the vehicle are difficult to define and are specific to each airframe. These low Reynolds number vehicles are subjected to varying environmental flight conditions during flight that must be addressed. Constructing a small footprint flight computing system is difficult due to the limited availability of low cost small footprint computing systems with the computational power, memory, and interfaces to support a variety of applications and research. This paper presents a low cost adaptive GNC system and an adaptive control law. The system is named Reconfigurable Autopilot for Vehicles with Enhanced Navigation (RAVEN), which addresses these issues.
Rogers, Steve, Yokum, Steve, Hammaker, Kristian
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