Adaptive actuator failure compensation for feedback linearizable systems

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.

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.

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.

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

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 for parametric strict feedback systems and an aircraft application

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.

Both dynamic state feedback as well as output feedback tracking control designs are presented in this paper for constrained robot systems under parametric uncertainties and external disturbances. The previous studies on tracking control design, not considering the velocity measurements, address only the unconstrained robot design. In contrast, a dynamic output feedback controller based on a linear and reduced-order observer that uses only position measurements is proposed here for the first time to treat the trajectory tracking control problem of constrained robot systems. Both adaptive state feedback control schemes and adaptive output feedback control schemes with a guaranteed H∞ performance are constructed. It is shown that all the variables of the closed-loop system are bounded and a pre-assigned H∞ tracking performance is achieved, in the sense that the influence of external disturbance on the tracking motion error can be attenuated to any specified level. Moreover, it is also shown that the motion and force trajectories asymptotically converge to the desired ones as the dynamic model of robot systems is well-known and the external disturbance is neglected. Finally, simulation examples are presented to illustrate the tracking performance of a two-link robotic manipulator with a circular path constraint by the proposed control algorithms. © 1998 John Wiley & Sons, Ltd.

This article is concerned with passivity and synchronization for fuzzy coupled reaction-diffusion neural networks (FCRDNNs) with multistate couplings or multiple spatial-diffusion couplings. First, by utilizing an adaptive state feedback controller, several passivity criteria for the FCRDNNs with multistate couplings are obtained. Moreover, a sufficient condition to guarantee the synchronization for the multistate coupled FCRDNNs is also given on the basis of the devised adaptive state feedback control scheme. Additionally, the problems of passivity and synchronization are also addressed for the FCRDNNs with multiple spatial-diffusion couplings by employing the adaptive control technique and Lyapunov functional method. Finally, two numerical examples are presented to validate the effectiveness of the devised adaptive control schemes.

This study presents an adaptive decentralised dynamic surface control (DSC) approach for a class of large‐scale non‐linear systems with unknown non‐linear functions, unknown control gains, time‐varying delays and in the presence of unknown actuator failures. The considered actuator failures are modelled to cover both loss of effectiveness and stuck at some time‐varying values where the values, patterns and time occurrences of the failures are unknown. With the help of neural networks to approximate the unknown non‐linear functions, a novel adaptive actuator failure compensation controller is developed based on the backstepping method and the DSC approach. The appropriate Lyapunov–Krasovskii functionals are introduced to design new adaptive laws to compensate the unknown actuator failures as well as uncertainties from unknown non‐linearities and time delays. The proposed design method does not require a priori knowledge of the bounds of the unknown time delays and actuator failures. The boundedness of all the closed‐loop signals is guaranteed and the tracking errors are proved to converge to a small neighbourhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark and a chemical reactor system. The simulation results show the effectiveness of the proposed method.

ABSTRACTThis article proposes an adaptive tracking control scheme for a class of switched stochastic non‐linear systems subject to full state constraints (FSCs). A unified framework is established by integrating the adaptive backstepping technique with barrier Lyapunov functions (BLFs) to address the time‐varying full state constraints (TFSCs). Accordingly, utilizing the theorem of stochastic non‐linear systems, a new adaptive state feedback control scheme is developed for a class of switching signals with the mode‐dependent average dwell time (MDADT) property. The proposed adaptive controller is mode‐dependent while the adaptive laws are mode‐independent so as to facilitate an easy deployment of the controller. It is rigorously proven that all signals in the closed‐loop system are bounded in probability, the tracking error converges to a bounded compact set, and the TFSCs are not violated. Finally, simulation examples are conducted to validate the effectiveness of the controller.

SummaryA new discrete‐time actuator failure compensation control scheme is developed, using a multiple‐model adaptive control approach which has the capacity to achieve faster and more accurate compensation of failure uncertainties. An individual adaptive system, for each possible failure pattern in a failure pattern set of interest for compensation, is designed using an indirect model reference adaptive control scheme for actuator failure compensation. A multiple‐model control switching mechanism for discrete‐time systems is set up by finding the minimal performance index to select the most appropriate control law. The performance indices are based on the adaptive estimation errors of individual parameterized systems with actuator failures. Simulation results from an aircraft flight control system example are presented to show the desired closed‐loop system stability and tracking performance despite the presence of uncertain actuator failures. Copyright © 2014 John Wiley & Sons, Ltd.

Compensation of nonlinear MIMO systems for actuator failures is investigated with systematic sufficient conditions which guarantee the existence of stable adaptive compensation control schemes for asymptotic output tracking. As an application, we examine the actuator failure compensation of a twin otter aircraft longitudinal model, verify such sufficient conditions, and develop an adaptive control scheme for the nonlinear aircraft model in the presence of uncertain actuator failures, whose effectiveness is demonstrated by simulation results.

Active vibration control using piezoelectric actuators in a networked and embedded environment has been widely applied to solve the rocket fairing vibration problem. However, actuator failures may lead to performance deterioration or system dysfunction. To guarantee the desired system performance, the remaining actuators should be able to coordinate with each other to compensate for the damaging effects caused by the failed actuator in a timely manner. Further, in the networked control environment, timing issues such as sampling jitter and network-induced delay should be considered in the controller design. In this study, a timing compensation approach is implemented in an adaptive actuator failure compensation controller to maintain the fairing system performance by also considering the detrimental effects from real-time constraints. In addition, time-delay compensation in the networked control system is discussed, which is able to reduce damaging effects of network-induced delays.