An adaptive actuator failure compensation scheme for controlling a morphing aircraft model

This paper develops a new adaptive compensation control scheme for two linked mobile robots with actuator failurs. A configuration with two linked two-wheel drive (2WD) mobile robots is proposed, and the modelling of its kinematics and dynamics are given. An adaptive failure compensation scheme is developed to compensate actuator failures, consisting of a kinematic controller and a multi-design integration based dynamic controller. The kinematic controller is a virtual one, and based on which, multiple adaptive dynamic control signals are designed which covers all possible failure cases. By combing these dynamic control signals, the dynamic controller is designed, which ensures system stability and asymptotic tracking properties. Simulation results verify the effectiveness of the proposed adaptive failure compensation scheme.

Adaptive actuator failure compensation schemes are developed for a class of multi-input and single-output plants with actuator failures characterized by certain inputs stuck at some unknown fixed value at unknown time instants. Conditions and controller structures for achieving state tracking and output tracking in the presence of actuator failures are derived. Adaptive laws are designed for updating some of the controller parameters when the actuator failure parameters are unknown. Simulation results for a linearized transport aircraft model with actuator failure show the desired system performance with adaptive failure compensation.

SUMMARYThis paper presents an adaptive actuator failure compensation method, which compensates for uncertainties due to unknown actuator failures for redundant manipulator systems. The method is first developed for manipulators whose joints are concurrently actuated. While physical realization of concurrently actuated manipulators and the advantages of their use have been understood before, in this paper failure modeling, controller structure, and adaptive update rules for handling uncertainties from the actuator failures are studied. The adaptive actuator failure compensation method is then expanded for a cooperating multiple manipulator system with uncertain actuator failures. Dynamic equations of such a multiple manipulator system in the task space are derived and the adaptive actuator failure compensation problem is formulated in the task space, for which a compensation controller structure is proposed with stable adaptive parameter update laws. The adaptive control scheme is able to compensate for the uncertainties of system parameters and actuator failures in a more general sense. For both cases, closed-loop system stability and asymptotic tracking are proved, despite uncertain system failures.

A new adaptive actuator failure compensation scheme using output feedback is presented in this paper for an enlarged class of nonlinear systems with state-dependent nonlinearities, which are bounded by both linear parameterized static functions and dynamic signals. By introducing the dynamic bounding technique to construct a backstepping control law, the control scheme ensures asymptotic output regulation and closed-loop stability via a Lyapunov based design in the presence of unknown actuator failures as well as system parameter and dynamic uncertainties. Simulation results are included to illustrate the control effectiveness.

Actuator failure compensation for nonlinear systems which can be transformed into parametric strict-feedback form with zero dynamics is investigated. Direct adaptive compensation control schemes are developed to ensure asymptotic output tracking and stabilize the system despite the uncertainties in actuator failures as well as in system parameters. Two main cases are studied for adaptive actuator failure compensation: systems with stable zero dynamics, and systems with extra controls for stabilization. Design conditions on systems suitable for actuator failure compensation are clarified.

In this chapter, we further the study of adaptive actuator failure compensation control to nonlinear systems with parameter uncertainties. We fisrt develop adaptive control solutions to parametric-strict-feedback systems without zero dynamics in the presence of actuator failures in Section 10.1. The actuator failure compensation problem is characterized in terms of two actuation models, and output matching conditions for the two actuation models are derived. Adaptive compensation control schemes are developed for parametric-strict-feedback systems without zero dynamics based on matching designs for two different actuation models. Closed-loop signal boundedness and asymptotic output tracking are ensured by the developed adaptive control schemes. Simulation results for the control of an aircraft wing-rock model with augmented actuators verifies the desired performance of our adaptive designs.

In this paper, a novel multiple-model second-level adaptive failure compensation scheme is proposed for high-speed trains with unknown failures to achieve the desired system performance. High-speed train dynamics with unknown system parameters actuator failures are first derived in detail. Multiple identification models are used to handle the parametric uncertainties and realize the desired speed and position tracking of a high-speed train with actuator failures in a first-level adaptation; identification errors of multiple identification models are used to obtain a virtual model for improving the convergence rate of parameters in a second-level adaptation. A second-level adaptive controller set is designed by using the parameters of the corresponding virtual model and the convex combination of the parameter estimates from the identification models. Finally, a switching mechanism associated with individual controllers is introduced to select the correct controller from the controller set. The stability of the closed-loop system and the performance of asymptotic state tracking are proved via the Lyapunov stability theory. Further, a simulation study was carried out by using the real line data of the CRH380A-type high-speed train from the Jinan section to the Xuzhou section. The simulation results show that in the presence of unknown actuator failures, the control scheme can control the speed tracking error within 0.4 km/h, and the switching strategy can quickly switch to the correct controller within 1 s, which verifies the effectiveness and feasibility of the proposed failure compensation scheme.

ABSTRACTThis paper investigates the static output feedback control problem for linear systems. The sensor and actuator may simultaneously suffer the total/partial loss of effectiveness. An adaptive fault-tolerant control scheme is developed by combination of linear matrix inequality method and adaptive mechanism. By estimating the inverses of failure factors online, the adverse effects of sensor and actuator failure can be compensated for. Finally, simulation results on the ‘Raptor-90’ helicopter verify the effectiveness of the proposed approaches.

Actuator failure compensation problem for nonlinear systems is formulated and adaptive actuator failure compensation control with state feedback is investigated for feedback linearizable systems. Under different structure conditions which characterize different classes of systems, adaptive state feedback control schemes are developed for systems with uncertain actuator failures. It is proved that the proposed control schemes ensure asymptotic output tracking and closed-loop signal boundedness.

An adaptive approach is developed for the compensation of uncertain failures in aircraft morphing actuators, which operate at only one of two states: "on" and "off." By modeling such actuator failures as a piecewise-linear characteristic, a compensation scheme with an adaptive inverse is thus constructed to ensure the closed-loop stability and tracking property. An application to the control of an aircraft lateral dynamic model using morphing actuators is presented with simulation results.

An optimal adaptive actuator failure compensation control scheme is proposed for a class of multi-input multi-output (MIMO) uncertain nonlinear continuous-time systems with redundant actuators subject to uncertain failures. Only single neural network is used in the proposed adaptive dynamic programming (ADP) scheme to simultaneously learn the infinite horizon cost function and the approximate optimal control input that minimizes the Hamilton-Jacobi-Bellman (HJB) equation. Besides, an uncertainty estimator is designed to estimate the uncertain dynamics and an adaptive parameter adjustment law is designed to estimate the actuator failure coefficients. Stability analysis and simulation results can demonstrate the effectiveness of the proposed method.

Adaptive actuator failure compensation control of uncertain nonlinear systems with guaranteed transient performance

An adaptive failure compensation control scheme is developed based on linear quadratic (LQ) control for discrete-time possibly nonminimum phase systems with unknown actuator failures with characterizations that some unknown system inputs are stuck at some unknown fixed or varying values at unknown time instants. The failure compensation control problem is formulated as a new LQ control problem. Based on some results on new controller structures and design conditions developed in [9], a stable adaptive law is proposed for the estimation of uncertain parameters from both the plant and actuator-failures. The adaptive failure compensation controller is implemented with adaptive parameter estimates, for achieving closed-loop stability and output regulation. Simulation results are presented to verify the desired adaptive control performance in the presence of uncertain actuator failures.

We present a probabilistic robust control design for a morphing aircraft model subject to uncertain actuator failure. The morphing aircraft model has multiple distributed arrays of shape-change devices that are used to generate moments for stabilization and low-rate maneuvering, augmenting conventional control surfaces. Each actuator operates at either on or off state; failure of each actuator could cause uncertainty in the applied control input. We characterize the morphing aircraft's actuation failure in a probabilistic way. In particular, each shape-change device within an actuator array is assumed to have certain probability to fail while devices from different arrays may have different failure probabilities. Consequently, we model the uncertain actuator failure as a random parametric uncertainty in the input matrix of the morphing aircraft model. A probabilistic robust explicit-model-following controller is then designed to stabilize the closed-loop system and to satisfy tracking performance subject to uncertain actuator failure. Simulation results are presented and evaluated for the application of this probabilistic robust failure compensation design to lateral dynamics of an innovative control effector (ICE) morphing aircraft model

SummaryThis article develops a new framework of adaptive actuator failure compensation control for cooperative manipulator systems with parameter uncertainties in addition to actuator failures, and designs and analyzes effective actuator failure compensation schemes for such robotic systems. The new adaptive control design uses an integration of multiple individual failure compensators and direct adaptation to handle various types of uncertainties in such robotic systems. The design can also be used for concurrent actuator failure cases, to expand the capability of adaptive actuator failure compensation. With a complete proof and performance analysis, it is shown that the proposed control scheme guarantees the desired closed‐loop stability and asymptotic output tracking, despite actuator failures whose patterns, time instants and values are all unknown. Simulation results of a benchmark cooperative manipulator system are presented to verify the desired control performance of the system with both typical constant and square‐wave actuator failure signals.