Adaptive actuator failure compensation for a transport aircraft model

An adaptive compensation control scheme is developed for a morphing aircraft model with actuator failures. Morphing actuators are special in the sense that they operate only at two states: on or off, and that they are used in large numbers to fulfill certain actuation function. We derive a failure model for morphing actuators and develop an adaptive scheme to estimate the actuation effectiveness and to update the number of actuators to be activated. A feedback control scheme is redesigned for adaptive actuator failure compensation, which ensures desired closed-loop stability and tracking properties. A simulation study with a linearized lateral dynamics model of the ICE aircraft is presented to demonstrate the system performance in the presence of uncertain actuator failures.

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.

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.

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.

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.

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.

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.

A state feedback output tracking adaptive control scheme is developed for plants with actuator failures characterized by the failure pattern that some inputs are stuck at some unknown fixed values at unknown time instants. This scheme relaxes the conditions on the controlled plant for desired plant-model output matching in the presence of actuator failures. New controller parametrization and adaptive law are developed under less restrictive conditions. All closed-loop signals are bounded and the plant output tracks a given reference output asymptotically, despite the uncertainties in actuator failures and plant parameters. Simulation results verify the desired adaptive control system performance.

An output feedback model reference adaptive controller is developed for a class of linear systems with multiple unknown time-varying state delays and in the presence of actuator failures. The adaptive controller is designed based on SPR-Lyapunov approach and is robust with respect to multiple unknown time-varying plant delays and to an external disturbance with unknown bounds. Closed-loop system stability and asymptotic output tracking are proved using suitable Lyapunov-Krasovskii functional and Simulation results are provided to demonstrate the effectiveness of the proposed controller.

This paper presents an output-feedback adaptive controller for a class of linear systems with unknown time-varying state delay and in the presence of actuator failures. We consider a common type of actuator failure in which some unknown system inputs may be stuck at some unknown fixed values and at unknown time instants. The adaptive controller is designed based on SPR–Lyapunov approach for relative degree one and two cases. Closed-loop system stability and asymptotic output tracking are proved using suitable Lyapunov–Krasovskii functional for each case. Simulation results are provided to demonstrate the effectiveness of the proposed results.

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.

In this technical note, an adaptive failure compensation problem has been studied for a class of nonlinear uncertain systems subject to stochastic actuator failures and unknown parameters. The stochastic functions related to Markovian variables have been introduced to denote the failure scaling factors for each actuators which is much more practical and challenging. Firstly, by taking into account of the Markovian variables existing in the system, some preliminary knowledges have been established. Then, by employing backstepping strategy, an adaptive failure compensation control scheme has been proposed, which ensures the boundedness in probability of all the closed-loop signals in the presence of stochastic actuator failures. A simulation example is presented to show the effectiveness of the proposed scheme.

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.

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.