Browse Topic: Fuzzy logic

Items (130)

Articulated Vehicle Lateral Stability Management via Active Rear-Wheel Steering of Tractor Using Fuzzy Logic and Model Predictive Control

02-13-02-0008

7/1/2020

In-phase rear-wheel steering, where rear wheels are steered in the same direction of front wheels, has been widely investigated in the literature for vehicle stability improvements along with stability control systems. Much faster response can be achieved by steering the rear wheels automatically during an obstacle avoidance maneuver without applying the brakes where safe stopping distance is not available. Sudden lane change movements still remain challenging for heavy articulated vehicles, such as tractor and semitrailer combinations, particularly on roads with low coefficient of adhesion. Different lateral accelerations acting on tractor and semi-trailer may cause loss of stability resulting in jackknifing, trailer-swing, rollover, or slip-off. Several attempts have been made in the literature to use active steering of semi-trailer’s rear wheels to prevent jackknifing and rollover. However, loss of stability in an articulated vehicle is usually caused by an oversteered tractor, and the semitrailer’s rear wheels have little effect on the tractor’s directional control. In this study, viability of active rear-wheel steering of tractor to maintain the stability of an articulated vehicle during a high-speed obstacle avoidance maneuver is investigated. Two different controllers, fuzzy logic and linear model-based predictive controllers, are proposed to minimize the off-tracking behavior of an articulated vehicle. The controllers were tested in IPG/TruckMaker environment with MATLAB/Simulink interface on roads with various coefficient of adhesions, performing single lane change maneuvers. The simulated results showed that jackknifing occurring right after sudden lane changes can be successfully prevented using the tractor’s active rear-wheel steering based on model predictive control algorithm when the feedback gains are tuned correctly.

Sahin, Hasan, Akalin, Ozgen

Observer for Faulty Perception Correction in Autonomous Vehicles

2020-01-06944/14/2020

Operation of an autonomous vehicle (AV) carries risk if it acts on inaccurate information about itself or the environment. The perception system is responsible for interpreting the world and providing the results to the path planning and other decision systems. The perception system performance is a result of the operating state of the sensors, e.g. is a sensor in fault or being adversely affected by the weather or environmental conditions, and approach to sensor measurement interpretation. We propose a trailing horizon switched system observer that minimizes the difference between reference tracking values developed from sensor fusion performed at an upper level and the values from a potentially faulty sensor based upon the convex combination of different sensor observation model outputs; the sensor observations models are associated with different sensor operating errors. The preferred observer target is a stationary landmark so as to remove additional uncertainty resulting from tracking of moving targets. Results for five scenarios show the observer identifies the appropriate sensor model in no more than a few sample intervals.

Omwansa, Mark, Meyer, Rick, Asher, Zachary, Goberville, Nick

A Fuzzy Logic Based Energy Management of Grid Connected Hybrid Energy System

2019-28-007610/11/2019

On account of boundless presence and eco-friendly nature of Sustainable Energy Sources (SES) like Wind system, PV etc. power generation using SES became more captivating. This work concentrates on Energy Management (EM) of grid synchronized Hybrid Renewable Energy System (HRES) along with fuzzy logic control. Where the HRES system is a combination of solar panel and wind turbine as sources. Along with an electrical battery for energy storage via an interface using a DC-DC fused CUK-SEPIC converter with multiple input is adopted. This convertor is employed to incorporate the HRES to the main grid. In addition to grid integration a Fuzzy Logic Based (FLB) controller is employed to increase the efficiency of the system. The converter topology used is a crossbreed of wind and solar power system, which is used to eliminate the inclusion of MPPT. A two level framework is imposed, which includes a logic controller to ensure efficient EM when HRESs are interconnected with the grid. Simulation of the FLB energy management system is performed along with the implementation of hardware setup.

Dayalan, Suchitra, Rathinam, Rajarajeswari, Pandey, Pranav, Adap, Mrutyunjay

Detection Method for Cavity Defects in Ballastless Track Structures of High-Speed Railways Based on Air-Coupled Ultrasonic Lamb Waves

10-03-02-00107/2/2019

This study proposes a method for the rapid detection and location of cavity defects in ballastless track structures of high-speed railways in service. First, the propagation of air-coupled ultrasonic Lamb waves in the ballastless track structure is studied. Theoretical calculation results show that the ultrasonic Lamb wave group velocity of the A2 mode in the track plate is 4000 m/s. Then, the excitation and reception methods of the air-coupled ultrasound are studied. Theoretical and experimental results show that the A2 mode Lamb wave can be generated by the 3.8° oblique incidence of the ballastless track structure. Finally, an experimental system for air-coupled ultrasonic testing is constructed. A pair of air-coupled ultrasonic probes is used to provide excitation and reception Lamb wave signals at an inclined angle of 3.8°, 20 mm away from the surface of the track plate, and 40 mm/step along the scanning direction. Experimental data indicate that interaction between the Lamb wave and cavity conforms to the energy leakage principle, and the amplitude of the Lamb wave increases with the increase in cavity of the scanning path. The “position-amplitude” curve is drawn from the collected experimental data. Based on the quantitative relationship between the convex interval of the curve and the size of the cavity that can be calculated to obtain the cavity size, the detection error value is ±5 mm. Theoretical and experimental results show that noncontact rapid detection of cavities can be realized by using the air-coupled ultrasonic Lamb waves.

Wenfa, Zhu, Wei, Shao, Xingjie, Chen, Xiangzhen, Meng, Haiyan, Zhang

How Dual Polarization Technique May Improve Weather Radar on Commercial Aircraft

2019-01-19826/10/2019

The airborne weather radar on a commercial aircraft is essential to ensure flight safety. It is able to detect severe weather, probable areas where presence of hail may be suspected, and thanks to its Doppler capability, the wind shears that may be dangerous when taking-off or landing. However, because it operates at X-band, the picture that it offers to the pilot may be seriously biased in situation of severe weather, in reason of the attenuation of the radar wave. The adoption of the dual pol technique in this weather radar would be most beneficial for the quality of the information delivered to the pilot for the following reasons: 1 Dual pol technique allows to operate a classification of the precipitation: distinguishing rain, melting layer, snow, hail, small ice particles. 2 Dual pol technique allows correcting the return signal for attenuation in rain. The paper aims reporting recent advances in the exploitation of dual pol radar data, based on the concept of normalisation of the particle size distribution (PSD) and on ZPHI® algorithm for precipitation retrieval. Their combination helps retrieving parameter N0* able to represent alone the variability of the PSD, for rain or ice particles whatever. The main interest of the combination between dual pol radar and ZPHI® software for inflight application is: To be able to measure ice concentration in altitude by implementing a new version of ZPHI® describing the along beam N0* evolution, in order to interpret the radar reflectivity in terms of ice particle concentration; To be able to calibrate the radar using self-consistency of polarimetric variables.

Testud, Jacques Victor, Moreau, Emmanuel, Le Bouar, Erwan

Cognitive Model of the Internal Combustion Engine

2018-01-17389/10/2018

This paper describes research focused upon improved the quality of automobile engine quality. Methods and models were developed for estimating and predicting the technical condition of internal combustion engine (ICE), which provides usage of the decision support making in the search for minimum fuel consumption regimes. We developed models of multi-criterion, multiparametric optimization of energy and material-material characteristics of ICE according to the system approach. The developed methods and models for estimating and predicting the technical state of the functionally interconnected and interacting ICE components are performed taking into account their hierarchy and topologies, energy resource used and the fuel. The cognitive methodology has been used to make engine models researches and analysis. The paper focuses on the fuzzy logic approach applying, considering the indeterminacy, incompleteness and unclear information in the engines operation processes. Cognitive, imitation and fuzzy models for estimating and predicting the technical state of ICE have been developed by the authors of this paper, which allowed to identify ICE’s most vulnerable components, set weight values, influence on fuel consumption according to the quantitative and qualitative energy interchange between ICE components. The received results provide quality enlargement of the ICE operation and their functional components, based on the developed estimation and prediction methods of their technical condition. The paper describes results the cross-platform software application which was implemented using the high-level Java programming language and XML markup language. Developed software allows us to provide user’s flexible interaction process with the module of the decision support system, which is based on implementation of the developed methods and models for the ICE technical condition estimating and predicting. Usage of the developed software helped to obtain optimization results of the energy and material characteristics of the explored ICE, which allows us to find several Pareto-optimal solutions for quality criteria that affect fuel consumption for each single model. This has led to a reduction of components wear, which leads to reducing fuel consumption during ICE operation.

Vychuzhanin, Vladimir, Rudnichenko, Nickolay, Shybaiev, Denys, Gritsuk, Igor, Boyko, Victor, Shybaieva, Natalia, Golovan, Andrii, Zaharchuk, Victor, Rabinovich, Ernest, Savchuk, Volodymyr, Zenkin E.Y., Evgeny

Driver Risk Perception Model under Critical Cut-In Scenarios

2018-01-16268/7/2018

In China Cut-in scenarios are quite common on both highway and urban road with heavy traffic. They have a potential risk of rear-end collision. When facing a cutting in vehicle, driver tends to brake in most case to reduce collision risk. The timing and dynamic characteristics of brake maneuver are indicators of driver subjective risk perception. Time to collision (TTC) and Time Headway (THW) demonstrate objective risk. This paper aims at building a model quantitatively revealing the relationship between drivers’ subjective risk perception and objective risk. A total of 66 valid critical Cut-in cases was extracted from China-FOT, which has a travel distance of about 130 thousand miles. It is found that under Cut-in scenarios, driver tended to brake when the cutting in vehicle right crossing line. This time point was defined as initial brake time. Brake strength and brake speed were taken to describe brake maneuver. Average brake pressure (ABP) and acceleration at initial brake time indicated brake strength. Brake pressure change rate (BPCR) and longitudinal jerk (derivative of acceleration) at initial brake time indicated brake speed. Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation Method were adopted to obtain an integrated subjective risk perception indicator D. Critical cases were divided into 3 groups by distance of within 5 m, from 5 to 15 m and over 15 m. Within the distance of 5 m, D was linear with 1/THW. Within the distance of from 5 to 15 m, D was linear with 1/TTC. Within the distance of over 15 m, both 1/THW and 1/TTC have linear relationship with D.

Ma, Xuehan, Feng, Zhiwei, Zhu, Xichan, Ma, Zhixiong

Intelligent Robotics Safeguarding

TBMG-268605/1/2017

Traditional robot applications limit operator access to hazards through hard-guarding and protective devices that either detect and stop the hazard, or prevent access into the safeguarding space until the hazard no longer exists. The introduction of power- and force-limited robots used in collaborative applications changes this environment. Reduced or nonexistent hard-guarding, along with continuous motion and interaction between the robot and the operator, makes the environment inherently dynamic and uncertain. Methods to reduce risks to a tolerable level include limiting forces and speed, but these measures can yield unacceptable production rates.

Transient Power Optimization of an Organic Rankine Cycle Waste Heat Recovery System for Heavy-Duty Diesel Engine Applications

2017-01-01333/28/2017

This paper presents the transient power optimization of an organic Rankine cycle waste heat recovery (ORC-WHR) system operating on a heavy-duty diesel (HDD). The optimization process is carried on an experimentally validated, physics-based, high fidelity ORC-WHR model, which consists of parallel tail pipe and EGR evaporators, a high pressure working fluid pump, a turbine expander, etc. Three different ORC-WHR mixed vapor temperature (MVT) operational strategies are evaluated to optimize the ORC system net power: (i) constant MVT; (ii) constant superheat temperature; (iii) fuzzy logic superheat temperature based on waste power level. Transient engine conditions are considered in the optimization. Optimization results reveal that adaptation of the vapor temperature setpoint based on evaporation pressure strategy (ii) provides 1.1% mean net power (MNP) improvement relative to a fixed setpoint strategy (i). The highest net power is produced by setpoint strategy (iii), which exhibited a 2.1% improvement compared strategy (i), revealing importance of utilizing engine conditions during reference trajectory generation. These results serve as the benchmark for the ORC system net power optimal control.

Xu, Bin, Yebi, Adamu, Onori, Simona, Filipi, Zoran, Liu, Xiaobing, Shutty, John, Anschel, Paul, Hoffman, Mark

A Trajectory Planning and Fuzzy Control for Autonomous Intelligent Parking System

2017-01-00323/28/2017

This paper proposed a two-section trajectory planning algorithm. In this trajectory planning, sigmoid function is adopted to fit two tangent arcs to meet limited parking spaces by reducing the radius of turning. Then the transverse preview model is established and the path tracking errors including distance error and angle error are estimated. The weight coefficient is considered to distribute the impact factor of traverse distance error or traverse angle error in the total error. The fuzzy controller is designed to track the two-section trajectory in autonomous intelligent parking system. The fuzzy controller is developed due to its real-time and robustness in the parking process. Traverse errors and its first-order derivative are selected as input variables and the outer wheel steering angle is selected as the output variable in fuzzy controller. They are also divided into seven fuzzy sets. Finally, forty rules are decided to achieve effective trajectory tracking. The detailed description of the proposed trajectory planning is demonstrated. The design aspects of Fuzzy Logic Controller and kinematic/dynamic theories in intelligent parking system are investigated in details. A combination of PreScan and Matlab Simulink is used to develop a numerical simulation model in order to verify the effectiveness of the proposed trajectory planning algorithm and Fuzzy Logic Controller in parking system. A superior performance is demonstrated and concluded for the proposed autonomous intelligent parking system.

Yang, Wei, Zheng, Ling, Li, Yinong, Ren, Yue, Li, Yusheng

A Novel Approach to Create Dimensional Tolerance Requirements from Expert Knowledge

2017-01-02413/28/2017

Geometric Dimensioning and Tolerancing is used to describe the allowed feature variations regarding the product design. Tolerance specification is important in many stages of all phases on product development. The product development engineering need to define the symbols to use on the Feature Control Frame of every component. Since the component function has an increment on its complexity year over year, it is not trivial to define those symbols anymore. The determination of dimensional tolerance shall be preceded by careful specification of the types of tolerance and symbols that will be applied in controlled features. Poor tolerance specifications can increase the production cost, require late product changes or lead to legal issues. In this scenario, this paper presents a method to evaluate this engineering information for a few number of GD&T technical experts in a specific system, like chassis or powertrain, and translate it into dimensional tolerance requirements to support the tolerance specification process using fuzzy logic. Also, the method suggests the best set of symbols based on the feature geometry, assembly and function analysis and classify these features to generate significant information on the automotive industry.

Murari, Thiago B., Ungaretti, Paulo, Moret, Marcelo A.

Design of an Integrated Yaw-Roll Moment and Active Front Steering Controller using Fuzzy Logic Control

2017-01-15693/28/2017

This paper presents an advanced control system, which integrates three fuzzy logic controllers namely; Direct Yaw-moment Control (DYC), Active Roll-moment Control (ARC) and Active Front Steering (AFS) to enhance vehicle cornering and overturning stability. Based on a well-developed and validated fourteen degree of freedom (DOF) full vehicle model with non-linear tire characteristics, a reference 3-DOF yaw-roll plane vehicle model is introduced to control yaw rate, sideslip angle, and roll angle of the vehicle body. The control actions of both direct yaw and active roll moments are performed by generating differential braking moments across the front wheels, while the control action of the active steering is performed by modifying the steering wheel angle. Different standard cornering tests are conducted in MATLAB / Simulink environment such as J-turn, fishhook and lane change maneuvers. The simulation results show a substantial improvement in vehicle stability by employing the proposed integrated controller compared to that of the individual controllers and the conventional vehicle without control.

Elhefnawy, Amro, sharaf, Alhossein, Ragheb, Hossam, Hegazy, Shawky

The Effect Factors and Location Planning Method Study of a Novel Car-Sharing Network

2017-01-02493/28/2017

With the development of the Internet for vehicles, the Car-sharing has been developed rapidly in recent years. This paper focuses on the network programming and distribution for Car-sharing, which helps to clarify the characteristics and basic law of Car-sharing network development, as well as the main approaches to construct it. Firstly, by analyzing the effect factors and expanding ways of Car-sharing network, characteristics of the development of Car-sharing industry and its network, as well as main Car-sharing users and services, the influence factors of Car-sharing demand and the main demand points in a city are summarized. Secondly, in order to better evaluate the network programming and distribution for Car-sharing, this paper proposes an optimization decision method of the car-sharing network planning by evaluating the possible alternatives in a same scale. The assessment index of Car-sharing network planning is constructed. Then the Analytic Hierarchy Process (AHP) and grey correlation analysis system are utilized to select the best scheme. Finally, by using the two-dimensional space analytical method, the paper constructs a Car-sharing network location sitting model which can make a balance between supply and demand. Then, the model is applied in the city of Wuhan and the results show that the model is practicable. So, the theory and method of Car-sharing network and location planning can be applied to any city by using the same ways introduced in this paper, which are useful for the network programming and distribution for Car-sharing.

Mi, Jia, Jie, Hu, Zhu, Hao, Liu, Hao, Zhang, Yuzhou

Control Strategy Development for Parallel Plug-In Hybrid Electric Vehicle Using Fuzzy Control Logic

2016-01-222210/17/2016

The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is currently developing a control strategy for a parallel plug-in hybrid electric vehicle (PHEV). The hybrid powertrain is being implemented in a 2016 Chevrolet Camaro for the EcoCAR 3 competition. Fuzzy rule sets determine the torque split between the motor and the engine using the accelerator pedal position, vehicle speed and state of charge (SOC) as the input variables. The torque producing components are a 280 kW V8 L83 engine with active fuel management (AFM) and a post-transmission (P3) 100 kW custom motor. The vehicle operates in charge depleting (CD) and charge sustaining (CS) modes. In CD mode, the model drives as an electric vehicle (EV) and depletes the battery pack till a lower state of charge threshold is reached. Then CS operation begins, and driver demand is supplied by the engine operating in V8 or AFM modes with supplemental or loading torque from the P3 motor. The 0 - 60 mph acceleration time with the Fuzzy control strategy is 4.8 seconds, which is close to the 4.9 seconds result yielded by a deterministic rule-based control strategy. The total energy consumption result for the Fuzzy control strategy is 555 Wh/km, which slightly beats the 560 Wh/km yielded by the deterministic rule-based strategy. Although the Fuzzy control strategy does not vastly improve the energy consumption or performance results, it proves to be a functional starting strategy that meets HEVT goals for EcoCAR 3.

Marquez, Eduardo D., Nelson, Douglas

A Model-Free Stability Control Design Scheme with Active Steering Actuator Sets

2016-01-16554/5/2016

This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.

Hirche, Benjamin, Ayalew, Beshah

Implementation of Fuzzy Logic Control in Semiactive Suspension for a Vehicle Using MATLAB SIMULINK

2016-28-00352/1/2016

The design of the conventional passive suspension has always been a compromise between vehicle handling and comfort, which led to the development of the modern active and semi active suspension systems. Amongst these, semi-active suspension has been focus of research in recent years owing to its lesser complexity and less power consumption as compared to active suspension. Semi active suspension uses real time variation in damping coefficient which can be achieved by using various control strategies. It is observed from available literature that Skyhook (for better ride comfort), Groundhook (for better vehicle handling) and Hybrid are most widely used strategies. These strategies use ‘On-Off’ control strategy (i.e. two preset values of damping co-efficient) but a better control over damping coefficients can be achieved using Continuous Control strategy. This paper aims to implement Continuous control strategy using Fuzzy logic for the semi active suspension. For the analysis, Two degree of freedom Quarter car model is used which is excited by three road profiles namely Bump, Sine Wave and Swept Sine wave. Comparison is done on the basis of vehicle parameters: Body displacement, Wheel displacement, Suspension working space and Dynamic tire deflection. Also frequency response of system is analysed using Fast Fourier Transform. Simulation is done using MATLAB SIMULINK and results of ‘Continuous control strategy’ are compared with the results of ‘On-Off control strategy’ and ‘Passive suspension’. Continuous control strategy using Fuzzy Logic control was found to provide better overall performance with 22.1% reduction in body displacement, 11.66% reduction in dynamic tire deflection and 31.77% reduction in suspension working space. Also Fuzzy logic control retained its stability over whole frequency range.

Rasal, Shraddhesh, Jaganmohan, Jayanth, Agashe, Sohan, Wani, Kiran P

Development of a Safety Assessment Tool for Air Traffic Control System

2015-01-24419/15/2015

This paper outlines an analytical framework to perform a data-driven, risk-based assessment of Air Traffic Control (ATC) facilities. Safety associated with an ATC facility is modeled as an influence network using a set of risk factors. A novel hybrid approach employing Adaptive-Network based Fuzzy Inference Systems is introduced to propagate the model. Statistical analysis of system-wide data for each risk factor is performed to identify outliers and understand underlying distributions. They are then used to define Fuzzy Membership Functions for model variables. Analytical Hierarch Process (AHP) is used to determine rules required by the model's inference engine. Finally, the methodology is applied to a set of ATC facilities using real data.

Oztekin, Ahmet

Aircraft In Situ Validation of Hydrometeors and Icing Conditions Inferred by Ground-based NEXRAD Polarimetric Radar

2015-01-21526/15/2015

MIT Lincoln Laboratory is tasked by the U.S. Federal Aviation Administration to investigate the use of the NEXRAD polarimetric radars* for the remote sensing of icing conditions hazardous to aircraft. A critical aspect of the investigation concerns validation that has relied upon commercial airline icing pilot reports and a dedicated campaign of in situ flights in winter storms. During the month of February in 2012 and 2013, the Convair-580 aircraft operated by the National Research Council of Canada was used for in situ validation of snowstorm characteristics under simultaneous observation by NEXRAD radars in Cleveland, Ohio and Buffalo, New York. The most anisotropic and easily distinguished winter targets to dual pol radar are ice crystals. Accordingly, laboratory diffusion chamber measurements in a tightly-controlled parameter space of temperature and humidity provide the linkage between shape and the expectation for the presence/absence of water saturation conditions necessary for icing hazard in situ. In agreement with the laboratory measurements pertaining to dendritic and hexagonal flat plate crystals, the aircraft measurements have verified the presence of supercooled water in mainly low concentrations coincident with regions showing layered anomalies of positive differential reflectivity (ZDR) by ground-based radar, otherwise known as +ZDR ‘bright bands’. Extreme values of ZDR (up to +8 dB) have also been found to be coincident with hexagonal flat plate crystals and intermittent supercooled water, also consistent with laboratory measurements. The icing conditions found with the anisotropic description are considered non-classical (condensation/collision-coalescence) and require the ascent of air and availability of ice nuclei. A modest ascent rate (<1 m/s) is needed for preservation of the anisotropic ice crystal shapes, making them identifiable to dual-pol radar. In the other limit of strong ascent (several m/s and greater), a vigorous riming process is present leading to graupel and hail, and with attendant radar reflectivity of 30 dBZ and greater. These rimed hydrometeors are also readily verified by dual pol hydrometeor classification and in situ aircraft measurements. For the intermediate level of ascent speed, snow can become rimed, diluting its anisotropy, and presents a challenge to unambiguous detection of an icing condition by dual pol radar. This challenge is under current study.

Williams, Earle, Donovan, Michael F., Smalley, David J., Hallowell, Robert G., Griffin, Elaine P., Hood, Kenta T., Bennett, Betty J., Wolde, Mengistu, Korolev, Alexei V.

Prediction of Automotive Ride Performance Using Adaptive Neuro-Fuzzy Inference System and Fuzzy Clustering

2015-01-22606/15/2015

Artificial intelligence systems are highly accepted as a technology to offer an alternative way to tackle complex and non-linear problems. They can learn from data, and they are able to handle noisy and incomplete data. Once trained, they can perform prediction and generalization at high speed. The aim of the present study is to propose a novel approach utilizing the adaptive neuro-fuzzy inference system (ANFIS) and the fuzzy clustering method for automotive ride performance estimation. This study investigated the relationship between the automotive ride performance and relative parameters including speed, spring stiffness, damper coefficients, ratios of sprung and unsprung mass. A Takagi-Sugeno fuzzy inference system associated with artificial neuro network was employed. The C-mean fuzzy clustering method was used for grouping the data and identifying membership functions. The prediction results were compared with simulation testing data and experimental data of a typical A-Class automobile.

Shi, Tianze, Chen, Shuming, Wang, Dengfeng

Triple-Control-Mode for Semi-Active Suspension System

2015-01-06214/14/2015

There is an increasing customer demand for adjustable chassis control features which enable adaption of the vehicle comfort and driving characteristics to the customer requirements. One of the most promising vehicle control systems which can be used to change the vehicle characteristics during the drive is the semi-active suspension system. This paper presents a Rule-Optimized Fuzzy Logic controller for semi-active suspension systems which can continuously adjust itself not only according to the road conditions but also to the driver requirements. The proposed controller offers three different control modes (Comfort, Normal and Sport) which can be switched by the driver during driving. The Comfort Mode minimizes the accelerations imposed on the driver and passengers by using a softer damping. On the other hand, the increased damping in Sport Mode provides better road holding capability, which is critical for sporty handling. The Normal Mode is adjusted to provide an overall balance between the vehicle ride comfort and road holding. The controller synthesis is performed by using an eleven degree of freedom full vehicle ride dynamics simulation model which is validated through laboratory tests performed on a hydraulic four-poster shaker. A unique optimization process is employed for obtaining the optimum Fuzzy Logic membership functions and the optimum rule-base of the proposed semi-active suspension controller. Discrete optimization is performed with Genetic Algorithm (GA) to find the global optima of the cost function which considers the ride comfort and road holding performance of the full vehicle. A comparison between the three control modes in terms of ride comfort and road holding is performed. The results show that, the proposed control modes provide three different vehicle characteristics to the driver. In addition to this, all three control modes are superior to the optimal passive suspension in terms of both ride comfort and road holding.

Kaldas, Mina M.S., Çalışkan, Kemal, Henze, Roman, Küçükay, Ferit

Uncertainty Analysis of Static Plane Problems by Intervals

2015-01-04824/14/2015

We present a new interval-based formulation for the static analysis of plane stress/strain problems with uncertain parameters in load, material and geometry. We exploit the Interval Finite Element Method (IFEM) to model uncertainties in the system. Overestimation due to dependency among interval variables is reduced using a new decomposition strategy for the structural stiffness matrix and the nodal equivalent load vector. Primary and derived quantities follow from minimization of the total energy and they are solved simultaneously and with the same accuracy by means of Lagrangian multipliers. Two different element assembly strategies are introduced in the formulation: one is Element-by-Element, and the other resembles conventional assembly. In addition, we implement a new variant of the interval iterative enclosure method to obtain outer and inner solutions. Numerical examples show that the proposed interval approach guarantees to enclose the exact system response.

Xiao, Naijia, Muhanna, Rafi L., Fedele, Francesco, Mullen, Robert L.

Intelligent Traffic Lights Control System using Fuzzy Logic

2014-36-03599/30/2014

This paper describes the development of an Intelligent Traffic Lights Control System using Fuzzy Logic concepts. Fuzzy Logic offers the possibility to ‘compute with words’, by using a mechanism for representing linguistic constructs common on real world problems. This is very important when the complexity of a task (problem) exceeds a certain threshold. Real world complex problems such human controlled systems involve a certain degree of uncertainty, which cannot be handled by traditional binary set theory. The algorithm implementation will be done inside Mathworks MATLAB software, and the results will be measured on Simulink Tool to create traffic scenarios and comparisons between simple time-based algorithms and the proposed system. During Project phase, a Robustness Parameter-Diagram will be used to design the system and cover its variables, error states, possible noises and control factors. The Project also comprehends some research regarding the currently used algorithms (including Artificial Intelligence) and technologies for Intelligent Traffic Light Control Systems. The benefits of using intelligent traffic lights are well known on society, and this paper can inspire academics and professionals to use different approaches to develop such systems.

Pinto, Alessandro Cezar, Mattioli, Geovanni Vezzaro

Flight Path Reconstruction and Wind Estimation Using Flight Test Data from Crash Data Recorder (CDR)

2014-01-21689/16/2014

This paper presents the implementation of flight path reconstruction (FPR) and wind estimation techniques applied to a high performance fighter aircraft. The analysis is carried out for the flight test data gathered and stored in a Crash Data Recorder (CDR). The data signals obtained from CDR are generally highly noisy, with frequent data drop outs and also with low sampling rate. The estimation technique applied for data reconstruction is the extended Kalman filtering (EKF). The reconstructed trajectories can be compared with the actual flight trajectories such that, in case of unavailability of data from other sources (e.g., digital flight control computer), the algorithm should be able to reconstruct the trajectories with the minimum set of data available from the CDR. Wind estimation along with the trajectory reconstruction can give better accuracy in airspeed as well as flow angles. The algorithm also aims at determining the bias/systematic instrument errors and generating accurate aircraft state trajectories. A standalone application is developed to reconstruct the flight trajectories for the full flight data. The algorithm is implemented using MATLAB®.

Nusrath, Khadeeja, Sarmah, Ankur, Singh, Jatinder

Airship Positioning Fuzzy Multi-Ballonet Control Study

2014-01-21469/16/2014

Airship designers research application versions of systems with several ballonets for adjustment of airship roll and/or pitch as a whole. This requires effective automatic status management of each separate ballonet. But multi-ballonet system control issue encounters the absence of industrially measurable variables of each separate ballonet status. Thus status control issue of the system becomes uncertain. The fact requires the issue studying and shaping new scientific and technical solutions. This publication represents research results implying that fairly simple implementation and effective result can be achieved by application of fuzzy control concept. Its application is built on generating the representative quantity of fuzzy production rules. They are based on present set evaluation of known parameters and measured variables. This results in fuzzy but meaningful image of ballonet system status and airship as a whole. Thus achieving fairly good control over multi-ballonet system. This article represents development results of fuzzy automatic control system version of two-ballonet system containing determined positional control systems of pressure difference between body gas environment and atmosphere. The resulted hybrid control system maintains necessary pressure in airship body and provides airship trim control efficiency at low traveling speed. Modes like that appear during take-off and landing. The development is based upon airship model with ballonet control system which adequacy has been checked by previous researches. This model was used to research and experimentally correct conditions and influence results of developed production rules on ballonet system status and airship as a whole. Control law fuzzy derivation procedure is demonstrated and explained. Described is simulation modeling diagram of fuzzy control hybrid system of two-ballonet system in Simulink environment and its computer testing results. Illustrated is airship positioning fuzzy control maintaining boost pressure in body to provide its specified rigidity.

Neydorf, Rudolf, Novikov, Sergey, Kudinov, Nikita

New Methodology for the Prediction of the Aerodynamic Coefficients of an ATR-42 Scaled Wing Model

2014-01-21519/16/2014

A new approach for the prediction of lift, drag and moment coefficients is presented. This approach is based on the Support Vector Machines methodology, and on a optimization algorithm, the Extended Great Deluge. The novelty of this approach is the combination between the SVM and the EGD algorithm. The EGD is used to optimize the SVM parameters to allow it to predict the aerodynamic coefficients of ATR 42 model. The training and validation of this new combination method is realized using the aerodynamic coefficients of an ATR-42 wing model with Xfoil software and experimental tests using the Price-Païdoussis wind tunnel. The results obtained with our approach are compared with the XFoil results, experimental results and XFLR5 software results for different flight cases, expressed as various combinations of angles of attack and Mach numbers. The main purpose of this methodology is to rapidly predict aircraft aerodynamic coefficients.

Ben Mosbah, Abdallah, Botez, Ruxandra, Dao, Thien-my

Learning of Intelligent Controllers for Autonomous Unmanned Combat Aerial Vehicles by Genetic Cascading Fuzzy Methods

2014-01-21749/16/2014

Looking forward to an autonomous Unmanned Combat Aerial Vehicle (UCAV) for future applications, it becomes apparent that on-board intelligent controllers will be necessary for these advanced systems. LETHA (Learning Enhanced Tactical Handling Algorithm) was created to develop intelligent managers for these advanced unmanned craft through the novel means of a genetic cascading fuzzy system. In this approach, a genetic algorithm creates rule bases and optimizes membership functions for multiple fuzzy logic systems, whose inputs and outputs feed into one another alongside crisp data. A simulation space referred to as HADES (Hoplological Autonomous Defend and Engage Simulation) was created in which LETHA can train the UCAVs intelligent controllers. Equipped with advanced sensors, a limited supply of Self-Defense Missiles (SDM), and a recharging Laser Weapon System (LWS), these UCAVs can navigate a pre-defined route through the mission space, counter enemy threats, and destroy mission-critical targets. Multiple missions were developed in HADES and a squadron of four UCAVs was trained by LETHA. Monte Carlo simulations of the resulting controllers were tested in mission scenarios that are distinct from the training scenarios to determine the training effectiveness in new environments and the presence of deep learning. Despite an incredibly large sample space, LETHA has demonstrated remarkable effectiveness in training intelligent controllers for the UCAV squadron and shown robustness to drastically changing states, uncertainty, and limited information while maintaining extreme levels of computational efficiency. Her specific architecture is applicable to a wide array of topics and specializes in problems with limited distributed resources in a spatiotemporal environment containing uncertainties and unknowns.

Ernest, Nicholas, Cohen, Kelly, Schumacher, Corey, Casbeer, David

Robots are (Almost) People, Too

TBMG-204989/1/2014

Biologically inspired robots are being realized by engineers and scientists all over the world. While much emphasis is placed on developing physical characteristics for robots such as human-like faces or artificial muscles, engineers in the Telerobotics Research and Applications Group at NASA’s Jet Propulsion Laboratory in Pasadena, CA, are among those working to program robots with forms of artificial intelligence similar to human thinking processes.

Tethered Vehicle Control and Tracking System

TBMG-199156/1/2014

This innovation can control the flight of a tethered vehicle, in an airborne wind energy (AWE) generation system, through the use of a pan-tilt platform and a visible spectrum digital camera, combined with tracking and control software running on a standard PC.

A Redundant Aircraft Attitude System Based on Fuzzy Logic Data Fusion of the Miniaturized Inertial Sensors

F-0070-2014-9471

5/20/2014

A redundant strap-down attitude system using three miniaturized gyro sensors linear clusters in the detection unit are here presented. For each of the three clusters the inertial sensors' data are fused by using a fuzzy logic method, in order to improve the angular speed signal measured by the detection unit and delivered to the attitude algorithm. After a short introduction the data fusion algorithm and the theoretical background of the attitude system are shown in the sections two and three. In the fourth section, the software implementation and experimental validation of the redundant inertial attitude system are exposed. To perform the experimental validation of the developed redundant attitude system some data were simultaneously acquired from a three-dimensional redundant gyro sensors unit and from an integrated INS/GPS navigator; the INS/GPS system was used as reference system to perform an evaluation of the attitude angles errors. The three-dimensional redundant gyro sensors unit was built with twelve gyros disposed in three clusters of four sensors each, along the x, y and z axes of the body frame.

Sandu, Dragos, Grigorie, Teodor, Botez, Ruxandra

Identification of Abnormal Noise Temperature Patterns in Deep Space Network Antennas Using Fuzzy Logic

TBMG-195865/1/2014

The communication between NASA space mission operations teams and their respective spacecraft in outer space is accomplished via the Deep Space Network (DSN). To ensure proper operations in returning telemetry data to mission operations, sending commands to spacecraft and providing radiometric data for navigation purposes, the DSN equipment generates a large set of self-monitor data. System noise temperature (SNT) and link margin are two of the key metrics of system performance for telemetry data return. The ability to detect the signal is affected by the SNT; the lower the noise, the better chance the system can detect the signal. Thus, there is a strong interest in monitoring and classifying the SNT. However, there are many causes of SNT behavior patterns that are still not known and difficult to classify by simple logic. There is a benefit to use a more sophisticated pattern-recognition method to detect and classify abnormal SNT behaviors.

Preview Enhanced Rule-Optimized Fuzzy Logic Damper Controller

2014-01-08684/1/2014

New developments in road profile measurement systems and in semi-active damper technology promote the application of preview control strategies to vehicle suspension systems. This paper details a new semi-active suspension control approach in which a rule-optimized Fuzzy Logic controller is enhanced through preview capability. The proposed approach utilizes an optimization process for obtaining the optimum membership functions and the optimum rule-base of the preview enhanced Fuzzy Logic controller. The preview enhanced Fuzzy Logic controller uses the feedforward road input information and the feedback vehicle state information as the controller inputs. An eleven degree of freedom full vehicle model, which is validated through laboratory tests performed on a hydraulic four-poster shaker, is used for the controller synthesis. The cost function including both ride comfort and road holding performance of the full vehicle is minimized through a discrete optimization process utilizing Genetic Algorithm (GA). The preview distance is also considered as a design parameter during the optimization process. The performance of the preview enhanced rule-optimized Fuzzy Logic controller is evaluated by using a measured stochastic road profile as vehicle model input. The results demonstrate the potential of the preview enhanced controller in improving all aspects of system performance compared to the rule-optimized Fuzzy Logic controller without preview.

Kaldas, Mina, Caliskan, Kemal, Henze, Roman, Küçükay, Ferit

Intelligent Energy Management Strategy for a Parallel Hybrid Vehicle

2014-01-19094/1/2014

Hybrid electric vehicles (HEV's) are facing increasing challenges in optimizing the energy flow through a vehicle system, in order to improve both fuel economy and vehicle emissions. Energy management of HEV's is a difficult task due to the complexity of the total system in terms of electrical, mechanical and thermal behavior. In this paper, an advanced control strategy for a parallel hybrid vehicle is developed. Four main steps are presented, particularly to achieve a reduction in fuel consumption. The first step is the development of a highly complex HEV model, including dynamic and thermal behavior. Second, a heuristical control strategy is developed to determine the HEV modes and third, a State of Charge (SoC) leveling is developed with the interaction of a fuzzy logic controller. It is proposed to calculate the load point shifting of the Internal Combustion Engine (ICE) and the desired battery SoC. Fourth, novel multi-objective optimization techniques, such as a genetic algorithm, are used for the optimization of the fuzzy logic controller and the heuristical control strategy. The simulation results show a potential fuel reduction relative to the baseline control strategy.

Mustafa, Rashad, Schulze, Mirko, Eilts, Peter, Küçükay, Ferit

A New Control Strategy for Electric Power Steering on Low Friction Roads

2014-01-00834/1/2014

In vehicles equipped with conventional Electric Power Steering (EPS) systems, the steering effort felt by the driver can be unreasonably low when driving on slippery roads. This may lead inexperienced drivers to steer more than what is required in a turn and risk losing control of the vehicle. Thus, it is sensible for tire-road friction to be accounted for in the design of future EPS systems. This paper describes the design of an auxiliary EPS controller that manipulates torque delivery of current EPS systems by supplying its motor with a compensation current controlled by a fuzzy logic algorithm that considers tire-road friction among other factors. Moreover, a steering system model, a nonlinear vehicle dynamics model and a Dugoff tire model are developed in MATLAB/Simulink. Physical testing is conducted to validate the virtual model and confirm that steering torque decreases considerably on low friction roads. Finally, simulation results show that the new EPS assist control strategy successfully increases steering effort under slippery conditions without compromising ease of steering, while ensuring that road feel also increases with decreasing in road friction and/or increasing vehicle speed as an additional safety measure.

Fan, Lu, Zhou, Bing, Zheng, Harry

Fuzzy Neuron: Method and Hardware Realization

TBMG-18908

1/1/2014

Simple and effective learning functions and adaptive elements can be placed into small hardware systems to include instruments for space, bioimplantable devices, and stochastic observers.