Browse Topic: Steering systems
Complex vertical takeoff and landing configurations that transition between vertical and forward flight modes necessitate advanced flight control systems to substantially reduce pilot workload. Prior work demonstrated the Trajectory Control System, a flight control architecture that enables such Simplified Vehicle Operations. However, there may also be scenarios or applications that require more aggressive maneuvering with rates and attitudes that exceed the nominal envelope. This paper demonstrates a flight control architecture with a middle-loop that harmonizes the Trajectory Control System with a Tactical Maneuvering System that enables more aggressive maneuvering, with seamless in-flight transitions between the two. In both cases, the middle-loop is linked with an explicit model-following inner-loop control system. Flight test results for the Trajectory Control System and maneuver simulation results for the Tactical Maneuvering System are shown for a subscale tilt-wing
This paper presents a distributed algorithm to track a desired target while fostering the emergence of a swarm formation and providing obstacle avoidance capability to deal with unknown scenarios. The proposed approach is based on the merge between a Flight Management System for global path planning and the definition of virtual forces through a custom Artificial Potential Field to prevent drones collisions between each other, with external objects and to provide cohesion of the swarm configuration. Each drone independently computes its global route and adjusts its path based on an optimal control action to minimize a potential energy function induced by its neighbors and obstacles. This approach results in a high cost-effective strategy to enhance UAVs autonomy level by managing a large group of drones, guaranteeing a low cost per unit thanks to the low computational effort and low-budget sensor suit while providing all the capabilities to accomplish the desired mission.
Helicopters' Vertical Take-Off and Landing (VTOL) capabilities are essential for maritime operations, especially for small-deck naval vessels. Unmanned Aerial Vehicles (UAVs) offer a cheaper, expendable, and efficient alternative for certain tasks, such as reducing pilot risk and lowering fuel consumption. While the procedures to approach and land on (moving) ships are standardized and bound to established operational limits in the case of crewed helicopters, UAVs lack such guidelines. This study investigates optimal rotary-wing UAV approach trajectories to a moving ship, for varying wind conditions and relative initial positions, and for different objectives. The goal is to provide preliminary guidelines for maritime UAV recovery operations, and a preliminary estimation of performance-based operational limits. The optimal trajectories are obtained using a global path-performance optimization framework based on Optimal Control Theory. The trajectories are compared to each other and to
In this paper, an offline path planning module, which is capable of generating dynamically feasible 3D trajectories for a class of Vertical Takeoff and Landing (VTOL) vehicles is presented. Input to the module is a flight plan defined by a set of way-points and its output is twofold: first, it produces an improved flight plan introducing additional waypoints and speed changes based on the heuristics and dynamical constraints of the vehicle. This new plan facilitates the pilot by providing information on specific locations and changes of the original flight path. Second, it generates a set of reference points, which can be used as the initial set of inputs for an online reactive trajectory optimization algorithm. The proposed development is capable of processing both climbs and descents as well as both fly-by and flyover waypoints, and speed changes in between those way-points. The module was also designed to capture the pilot's perspective of an abstract way-point mission. NRC has
The complex vertical takeoff and landing configurations currently under development necessitate flight control system design that enables substantial reductions of pilot workload through Simplified Vehicle Operations. This paper shows optimization and simulation of such a flight control system architecture for a subscale vectored thrust aircraft configuration. A full-envelope Trajectory Control System for longitudinal dynamics was coupled with explicit model-following inner-loop controllers, and a scheduled control allocation logic. Control system parameters were determined using a genetic algorithm optimization scheme subject to dynamic stability, robustness, and control responsiveness constraints. Flight simulation results for a series of representative maneuvers including departure and arrival transitions and forward flight maneuvers are presented to demonstrate the effectiveness of the proposed flight control system architecture.
ABSTRACT Rotorcraft shipboard landing continues to be challenging due to increased pilot workload in dealing with effects of ship air wake turbulence on vehicle motion and random ship motion. Some of the recent work has proposed a pilot assist function for reduced pilot workload using model predictive control methods. This paper explores the use of a recently developed Model Predictive Path Integral (MPPI) method based on a stochastic optimal control framework for trajectory guidance solution to the shipboard landing problem. First, a proof-of-concept study is presented by applying the MPPI method to a simple point mass approximation of helicopter dynamics represented in the form of a first-order command acceleration model, representative of helicopter trajectory motion in the vertical plane. Next, the MPPI method is used in conjunction with a six degrees-of-freedom linear model of a helicopter in order to gain further insight into the applicability of the MPPI framework to the
The ongoing development of numerous novel vertical takeoff and landing configurations necessitates flight control system design that enables the Simplified Vehicle Operations paradigm. This paper shows flight test results for one subscale lift-plus-cruise and one tilt-wing configuration employing such a flight control system architecture. Pilot inceptor inputs are used to synthesize trajectory commands that are processed by a full-envelope trajectory control system that generates propulsor thrust commands, a wing angle command, and attitude and rate commands for linear quadratic integral and explicit model-following inner-loop control systems. Commonalities and differences in the flight control implementation for the two configurations are highlighted. Results are shown for both configurations subject in manually piloted flights. The flight test results demonstrate that the flight control system designs allow a minimally trained operator to operate the two flight test vehicles safely
This paper presents a path planning concept based on the Manned-Unmanned Teaming (MUM-T) between the helicopter and a drone. The drone flies ahead of the helicopter to detect possible unexpected obstacles in the mission area and sends the data to the helicopter. The path of the helicopter is automatically replanned to avoid the meteorological and physical obstacles detected by the drone. The path planning is based on the Rapidly-exploring Random Tree* (RRT*) and the Bidirectional Rapidly-exploring Random Tree (BiRRT) algorithms. The reference trajectory is planned by means of the RRT* algorithm and the replanning is performed with the BiRRT. The node connection is realized with the Dubins curves, that force the path to comply with the prescribed limitations on the helicopter's roll angle and flight path angle. The Savitzky-Golay filter is used to smooth the trajectory achieving curvature continuity. A closed-loop simulation model containing the dynamics of the pilot is used to evaluate
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