1,721,783 research outputs found
Ship Collision Avoidance Using Scenario-Based Model Predictive Control
No full textA set of alternative collision avoidance control behaviors are parameterized by two parameters: Offsets to the guidance course angle commanded to the autopilot, and changes to the propulsion command ranging from nominal speed to full reverse. Using predictions of the trajectories of the obstacles and ship, the compliance with the COLREGS rules and collision hazards associated with the alternative control behaviors are evaluated on a finite prediction horizon. The optimal control behavior is computed in a model predictive control implementation strategy. Uncertainty can be accounted for by increasing safety margins or evaluating multiple scenarios for each control behavior. Simulations illustrate the effectiveness in test cases involving multiple dynamic obstacles and uncertainty associated with sensors and predictions
Fault-tolerant control allocation using unknown input observers
No full textThis paper focuses on the use of unknown input observers for detection and isolation of actuator and effector faults with control reconfiguration in overactuated systems. The proposed approach consists in tuning the observer parameters in order to make the filters decoupled from faults affecting selected groups of actuators or effectors. The control allocation actively uses input redundancy in order to make relevant faults observable. The case study of an overactuated marine vessel supports theoretical developments
Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment
Get PDFA relatively small number of alternative col- lision avoidance control behaviors are formulated by con- sidering nominal and evasive maneuvers.The control behaviors are generated by varying two parameters: Offsets to the guidance course angle commanded to the autopilot, and offset the propulsions command ranging from keep speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, the compliances with the COLREGS rules and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon into the future, and the optimal control behavior is selected. The method is conceptually and computationally simple and yet quite versatile and powerful as it can account for the dynamics of the ship, its steering and propulsion system, forces due to wind and ocean current, and any number of obstacles. Simulations show that the method is effective and can manage complex scenarios with multiple dynamic obstacles and uncertainty in sensors and predictions
An unknown input observer based control allocation scheme for icing diagnosis and accommodation in overactuated UAVs
No full textThe accretion of ice layers on wings and control surfaces modifies their lift and drag and, consequently, alters performance and controllability of the aircraft. In this paper we propose a combined unknown input observers and control allocation framework to design icing diagnosis filters and accommodate icing for an overactuated automated aircraft
An unknown input observer approach to icing detection for unmanned aerial vehicles with linearized longitudinal motion
No full textThe accretion of ice layers on wings and control surfaces modifies the shape of the aircraft and, consequently, alters performance and controllability of the vehicle. In this paper we propose an Unknown Input Observers framework to design icing diagnosis filters. A case-study is provided as support and validation of theoretical results
Fault-tolerant control allocation: An Unknown Input Observer based approach with constrained output fault directions
Get PDFThis paper focuses on the use of unknown input observers for detection and isolation of actuator and effector faults with control reconfiguration in overactuated systems. The control allocation actively uses input redundancy in order to make relevant faults observable. The case study of an overactuated marine vessel supports theoretical developments
Fault-tolerant control allocation with actuator dynamics: Finite-time control reconfiguration
No full textThis paper focuses on fault tolerant control allocation for overactuated systems with actuator dynamics. The proposed scheme for fault detection and isolation is based on unknown input observers and the main contribution of the paper consists in the presentation of a finite-time control reconfiguration technique which provides a successful recovering of system performances in spite of actuator faults. Simulation results support theoretical developments
Fault tolerant control of uncertain dynamical systems using interval virtual actuators
Get PDFIn this paper, a model reference fault tolerant control strategy based on a reconfiguration of the reference model, with the addition of a virtual actuator block, is presented for uncertain systems affected by disturbances and sensor noise. In particular, this paper (1) extends the reference model approach to the use of interval state observers, by considering an error feedback controller, which uses the estimated bounds for the error between the real state and the reference state, and (2) extends the virtual actuator approach to the use of interval observers, which means that the virtual actuator is added to the control loop to preserve the nonnegativity of the interval estimation errors and the boundedness of the involved signals, in spite of the fault occurrence. In both cases, the conditions to assure the desired operation of the control loop are provided in terms of linear matrix inequalities. An illustrative example is used to show the main characteristics of the proposed approach
Combining model-free and model-based angle of attack estimation for small fixed-wing UAVs using a standard sensor suite
Get PDFWe propose to estimate steady and turbulent wind velocities and aerodynamic coefficients of a fixed-wing Unmanned Aerial Vehicle (UAV) by using frequency separation as well as kinematic, aerodynamic and wind models combined in an Extended Kalman Filter (EKF). With these estimates it is possible to calculate the angle of attack and the magnitude of the airspeed. Avoiding the need for prior knowledge of UAV parameters, the proposed method utilizes only sensor information that is part of a standard sensor suite, which consists of a Global Navigation Satellite System (GNSS), an Inertial Measurement Unit (IMU) and a pitot-static tube, and attitude information obtained from these sensors. An observability analysis shows that attitude changes are necessary during the initialization phase and from time to time during the flight. Simulation results indicate that, with typical sensor accuracy, the estimates are close to the reference values of the aerodynamic coefficients and wind velocities and is capable of estimating the Angle of Attack with an Root Mean Square Error (RMSE) of 0.33°, the Sideslip Angle with an RMSE of 3.21° and the airspeed with an RMSE of 0.23 m/s
Icing detection and identification for unmanned aerial vehicles: Multiple model adaptive estimation
No full textThe accretion of ice layers on wings and control surfaces modifies the shape of the aircraft and, consequently, alters performance and controllability of the vehicle. In this paper we propose a multiple model adaptive estimation framework to detect icing affecting unmanned aerial vehicles using the following sensors: pitot tube (airspeed sensor), GPS and IMU. A case-study is provided as support and validation of theoretical results
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