Fault-Tolerant Vibration Control in a Networked and Embedded Rocket Fairing System

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.

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.

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.

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.

Considering the problems of model uncertainties, higher harmonics, uncertain boundary conditions, external excitations, and system time delay in practical vibration control system, a novel active vibration control method is proposed to suppress the vibration of a thin plate structure with acceleration sensor and piezoelectric bimorph actuator in this paper. First, a nonlinear extended state observer (NESO)-based controller is designed to ensure the anti-disturbance performance of the structural vibration control system. Then, an enhanced differentiator-based time delay compensation method is introduced to improve the vibration suppression performance of the NESO-based controller. A real time hardware-in-the-loop benchmark for an all-clamped piezoelectric thin plate is designed to verify and compare the performance of the developed controller against conventional ESO-based methods (linear ESO with/without time delay compensation, NESO without time compensation). The best vibration suppression and disturbance rejection performance of the proposed NESO-based controller with an enhanced time delay compensator is verified in the comparative experimental results. This work is able to provide practitioners with vital guidance in designing active vibration control system in the presence of disturbances and time delay.

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.

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.

This study is concerned with the reliable controller design for networked control systems (NCS) against both probabilistic sensors faults and actuators faults. The faults of each sensor or actuator occur randomly and their failure rates are governed by two sets of unrelated random variables satisfying certain probabilistic distribution. In terms of the probabilistic failures of every sensor or actuator, new type of distribution-based NCS fault model is proposed. Based on the new built model, reliable controller is designed and sufficient conditions for the exponentially mean square stability (EMSS) of NCS are obtained by using Lyapunov functional method. The main contribution of the proposed fault model and methods lies with its practicality and generalisation, which contains many realistic problems in the NCS, such as probabilistic sensors or actuators failures, partial degradation, data distortion, packet dropout, network-induced delay and so on. Moreover, some existing models in the open literatures are deemed as special cases of the proposed fault model. To illustrate the implementation procedure, a vertical take-off and landing (VTOL) aircraft system is given to show the effectiveness and application of the proposed method.

Connecting a complex control system with various sensors, actuators, and controllers as a networked control system by a shared data network can effectively reduce complicated wiring connections. This system is also easy to install and maintain. The trend is to use networked control systems for time-sensitive applications, such as remote DC motor actuation control. The performance of a networked control system can be improved if the network can guarantee quality-of-service (QoS). Due to time-varying network traffic demands and disturbances, QoS requirements provided by a network may change. In this case, a network has to reallocate its resources and may not be able to provide QoS requirements to a networked control application as needed. Therefore, the application may have to gracefully degrade its performance and perform the task as best as possible with the provided network QoS. This paper proposes a novel approach for networked DC motor control systems using controller gain adaptation to compensate for the changes in QoS requirements. Numerical and experimental simulations, and prototyping, are presented to demonstrate the feasibility of the proposed adaptation scheme to handle network QoS variation in a control loop. The effective results show the promising future of the use of gain adaptation in networked control applications.

In this paper, the robust H∞ control problem is developed for a class of linear time-varying networked control system (NCS) with uncertainties and external disturbance. In network, the network-induced delay and packet dropouts are simultaneously considered. Firstly, a discrete-time switched system model is established based on the signals transmission delay in network. Then, a time-varying H∞ controller is designed. Such the controller can vary according to delay in network. Furthermore, by constructing delay-dependent Lyapunov-Krasovskii functional, a sufficient condition is given to guarantee that the closed-loop system is stochastically stable with an H∞ disturbance attenuation level in terms of nonlinear matrix inequalities. In order to solve the controller gain, the cone complementarity linearization (CCL) algorithm is employed. Finally, a networked DC motor control system is analyzed to illustrate the effectiveness of the proposed method.

Networked Control System (NCS) is a class of feedback control system forming a closed loop through the communication network. Due to the nodes conflicts, poor network stability, limited data bandwidth and other uncontrollable factors in the transmission, network-induced delay is the main factor reducing system performance and stability. Studying the state feedback rules of Long Delay Network Control system, the author proposes Stability and stabilization method for Random Long Delay Network Control. The method models random long delay closed-loop network control system, compensate the delay and complete the network stability and stabilization. Finally, a numerical example is given to verify the validity of the conclusion.

In this paper, the time-delay compensation control of a class of networked control system (NCS) with randomly varying long time-delays is addressed. Firstly, we give a novel modeling method which is easy to implement time delay compensation. By prediction of a model-based estimator in the controller node and building buffers in the actuator node, the NCS with delayed state feedback is compensated. A linear matrix inequality based (LMI-based) sufficient condition for stability of the NCS with time-delay compensation is derived. The simulation results of an Internet-based continuous stirred tank reactor (CSTR) demonstrate the efficiency and correctness of our compensation method.