Time-varying Actuator Faults Research Articles

Adaptive NFTSM-Based Fault Tolerant Control for a Class of Nonlinear System With Actuator Fault and Saturation

In this paper, an adaptive fault-tolerant control (FTC) strategy is proposed for a class of nonlinear systems in the presence of actuator fault, actuator saturation, and unknown external disturbance. The mathematical model of a second-order nonlinear system with actuator fault is first given, and a fault estimation observer is designed to estimate the occurred time-varying actuator fault. On this basis, the adaptive FTC strategy is proposed using both nonsingular fast terminal sliding mode (NFTSM) and radial basis function neural networks (RBFNNs) techniques to compensate for the negative effects caused by time-varying actuator fault and external disturbance. Another adaptive FTC scheme is further presented under actuator saturation case, and the Lyapunov stability analysis demonstrates that the designed FTC approach could guarantee that the trajectory of sliding mode dynamics could converge to a small neighborhood of the origin within a finite time. Compared with some existing results, the FTC approach proposed in this paper has better fault acceptability. Finally, the proposed adaptive FTC approach is applied to the attitude control of rigid spacecraft, and the simulation results illustrate the advantages of the designed control scheme.

Finite-time leaderless consensus of uncertain multi-agent systems against time-varying actuator faults

Abstract This paper addresses the finite-time leaderless consensus problem for a class of continuous-time multi-agent systems subject to linear fractional transformation uncertain parameters using an observer-based fault-tolerant controller. Here, it is considered that the network of the system is described by an undirected graph subject to fixed topology and the aforementioned controller is impacted by time-varying actuator faults. Then, the desired consensus protocols are proposed in such a way that the effects of possible uncertainties and actuator faults are compensated efficiently within a prescribed finite-time period. More precisely, the leaderless consensus analysis is carried out in the framework of Lyapunov-Krasovskii functional and the required conditions for the existence of proposed fault-tolerant controller are derived in terms of linear matrix inequalities. Moreover, the proposed consensus design parameters can be computed by solving a set of linear matrix inequality constraints. Finally, two examples including a formation flying satellites model are provided to show the efficiency and usefulness of the proposed control scheme.

Decentralized reliable guaranteed cost control for large-scale nonlinear systems using actor-critic network

Abstract In this paper, the decentralized reliable guaranteed cost control problem of large-scale nonlinear systems with mismatched interconnection and time-varying actuator fault is investigated. The unknown actuator fault is assumed to be with known upper bounds. Under the case that the interconnection term is unknown and mismatched, the guaranteed cost control problem for a class of large-scale nonlinear systems can be transformed into design an optimal control strategy of the isolated system, which is necessary to solve the HJB (Hamilton–Jacobi–Bellman) equations by using adaptive dynamic programming (ADP) of actor-critic networks. The convergence property of the neural network weights and the stability of the closed-loop system have been strictly proved even if time-varying actuator faults and unknown interconnection coexist. Finally, simulation examples are given to show the effectiveness of the proposed approach.

Finite-time consensus of Markov jumping multi-agent systems with time-varying actuator faults and input saturation

This paper gives attention to the issue of finite-time leader-following consensus of nonlinear discrete-time multi-agent systems with Markov jump parameters. A robust fault-tolerant control protocol that takes the effect of time-varying actuator faults and actuator saturation into account is considered for the addressed system. The main purpose of the paper is to design a fault-tolerant controller such that the leader-following consensus of the addressed system is achieved over a prescribed finite-time interval. By using the Lyapunov functional approach, Abel’s lemma and some properties of Kronecker product, a sufficient condition for the existence of fault-tolerant state feedback controller for the addressed system is presented and an explicit parameterization of such a controller is obtained. Eventually, a numerical example along with its simulation results is exploited to reflect the applicability of the proposed design method, wherein the robust performance of controller is exhibited despite the presence of actuator saturation and time-varying actuator faults.

Adaptive Fault-Tolerant Consensus Protocols for Multiagent Systems With Directed Graphs.

This paper investigates the problem of adaptive fault-tolerant tracking control for the multiagent systems (MASs) under the time-varying actuator faults and bounded unknown control input of the leader. On the basis of the local state information of neighboring agents, an adaptive fault-tolerant control protocol, which consists of the adaptive estimation of faults, is constructed to compensate for the loss of actuator effectiveness in the leader-follower consensus of MASs. Moreover, the modification term in the adaptive estimation can avoid high-frequency oscillations. It is shown that the tracking errors converge to a neighborhood around the origin in the presence of actuator faults, and the performance of the tracking problem is improved. Furthermore, the protocol is distributed in the sense that the coupling gains are independent. Finally, two examples are given to show the effectiveness of the proposed control protocol.

Robust stability analysis of formation control in local frames under time-varying delays and actuator faults

This paper investigates the robust stability of a multiagent system moving to a desired rigid formation in presence of unknown time-varying communication delays and actuator faults. Each agent uses relative position measurements to implement the proposed control method, which does not require common coordinate references. However, the presence of time delays in the measurements, which is inherent to the communication links between agents, has a negative impact in the control system performance leading, in some cases, to instability. Furthermore, the robust stability analysis becomes more complex if failures on actuators are taken into account. In addition, delays may be subject to time variations, depending on network load, availability of communication resources, dynamic routing protocols, or other environmental conditions. To cope with these problems, a sufficient condition based on Linear Matrix Inequalities (LMI) is provided to ensure the robust asymptotic convergence of the agents to the desired formation. This condition is valid for any arbitrarily fast time-varying delays and actuator faults, given a worst-case point-to-point delay. Finally, simulation results show the performance of the proposed approach.

Reliable $$\mathcal {H}_{\infty }$$ H ∞ controller for uncertain networked control systems with additive time-varying delays and nonlinear actuator faults

In this paper, the problem of exponential stability for a class of networked control system is investigated. Proposed system consisting additive time-varying delays, parameter uncertainties, external disturbance, nonlinearities and actuator faults which makes more generalized system model. The inclusion of actuator fault matrix and nonlinear perturbation in the formulation of reliable controller gives more practical applications in networked control system. The main goal of this paper is to formulate a reliable $$\mathcal {H}_{\infty }$$ controller which assures the exponential stability of considered system. Based on the integral inequality technique, a new linear matrix inequality criteria has been obtained by formulating a suitable Lyapunov–Krasovskii functional for the exponential stability of the proposed networked control system. Finally, numerical example is provided to validate the effectiveness of the proposed method.

Adaptive Fuzzy Sliding Mode Control for Network-Based Nonlinear Systems With Actuator Failures

This paper investigates the robust control problem of nonlinear systems with unknown time-varying actuator faults over digital communication networks. In the study, a new adaptive sliding mode control (SMC) scheme is developed for the investigated nonlinear systems, where the unknown nonlinearity is approximated via the adaptive fuzzy mechanism in the presence of signal quantization. The proposed control law can compensate the time-varying faults and the quantization errors completely by injecting the quantizer parameter into the controller gain. Moreover, in this design, the adaptive fuzzy law is constructed via the quantized state information instead of using the exact original information. Under the proposed quantized SMC scheme, the closed-loop control systems are guaranteed to be asymptotically stable, and the reachability of the sliding surface can be ensured strictly. Finally, two examples are presented to show the effectiveness of the method.

Leader-following exponential consensus of input saturated stochastic multi-agent systems with Markov jump parameters

Abstract This paper is concerned with the solvability of leader-following exponential consensus of a stochastic nonlinear multi-agent system in the presence of Markov jump parameters and input saturation by using a fault-tolerant control scheme. Firstly, the interconnection topology that represents the communication between the leader and follower agents is chosen to be undirected and fixed. Secondly, to exhibit real scenario, a time-varying actuator fault model is incorporated in the fault-tolerant control design. Thirdly, by introducing a simple linear transformation, an error system is then formulated. Based on these setups and by employing the tools from algebraic graph theory and Lyapunov–Krasovskii stability theory, a distributed robust fault-tolerant controller is designed for each follower node in terms of linear matrix inequalities such that the closed-loop error system is exponentially stable in the sense of mean-square even in the presence of possible actuator faults. Lastly, a simulation study is presented to illustrate the efficacy of the proposed control design technique.

Fault-tolerant control of linear systems using adaptive virtual actuator

ABSTRACTIn this paper, design and development of fault-tolerant control (FTC) is investigated for linear systems subject to loss of effectiveness and time-varying additive actuator faults as well as an external disturbance using the fault-hiding approach. The main aim of this approach is to keep the nominal controller and to design a virtual actuator that is inserted between the faulty plant and the nominal controller in order to hide actuator faults and disturbances from the nominal controller, and consequently the performance of the system before and after the occurrence of actuator faults is kept to be the same. The proposed adaptive virtual actuator does not require a separated fault detection, isolation and identification (FDII) unit and both state and output feedback cases are considered. An illustrative example is given to demonstrate the effectiveness of the proposed adaptive virtual actuator in both cases.

Adaptive sliding mode controller design of Markov jump systems with time-varying actuator faults and partly unknown transition probabilities

This paper addresses the stabilization problem of a class of Markov jump systems with time-varying actuator faults and partially known transition probabilities via the sliding mode control method. In this study, the exact information of the time-varying actuators faults, nonlinearities and external disturbances considered in this paper is unknown for the controller design. By Lyapunov stability theory, some sufficient conditions of stochastic stability for Markov jump systems in the existence of actuators faults, unknown nonlinearities and unknown perturbation are derived. Finally, the effectiveness of the proposed control method is illustrated by a simulation example.

A Piecewise-Markovian Lyapunov Approach to Reliable Output Feedback Control for Fuzzy-Affine Systems With Time-Delays and Actuator Faults

This paper addresses the problem of delay-dependent robust and reliable $\mathscr {H}_{\infty }$ static output feedback (SOF) control for a class of uncertain discrete-time Takagi-Sugeno fuzzy-affine (FA) systems with time-varying delay and actuator faults in a singular system framework. The Markov chain is employed to describe the actuator faults behaviors. In particular, by utilizing a system augmentation approach, the conventional closed-loop system is converted into a singular FA system. By constructing a piecewise-Markovian Lyapunov-Krasovskii functional, a new $\mathscr {H}_{\infty }$ performance analysis criterion is then presented, where a novel summation inequality and S-procedure are succeedingly employed. Subsequently, thanks to the special structure of the singular system formulation, the piecewise-affine SOF controller design is proposed via a convex program. Lastly, illustrative examples are given to show the efficacy and less conservatism of the presented approach.

Fault tolerant shape control for particulate process systems under simultaneous actuator and sensor faults

The problem of fault tolerant shape control for particle size distribution (PSD) process subject to simultaneous time-varying actuator and sensor faults is studied. In this work, sensor and actuator faults are taken into consideration in a unified framework, and estimated by using adaptive observer technique. For the PSD process, the output distribution, rather than the system output signal itself, is adopted for shape control. Square root rational B-spline approximation is used to fit the distribution shape. An innovative on-line fault estimation scheme is proposed for simultaneous actuator and sensor faults estimation. Then an augmented controller based on the virtual actuator and virtual sensor techniques is designed to compensate for the faults and realise PSD shape tracking. A simulation example of emulsion polymerisation is used to validate the proposed scheme and satisfactory performance is obtained.

Robust output feedback fault‐tolerant control of non‐linear multi‐agent systems based on wavelet neural networks

A robust output feedback active fault-tolerant leader-following controller for a class of non-linear multi-agent systems is presented. It is assumed that the states of the followers are not available; therefore, a local observer is constructed to estimate the states of each agent. In addition, the non-linear dynamics of agents may include uncertainties and the control input of the leader dynamics is unknown to all followers. Moreover, taking advantage of wavelet neural networks (WNNs), an online fault estimation scheme is developed which can effectively approximate the unknown actuator faults. The proposed decentralised observer-based robust cooperative controller is capable of compensating for the effects of unknown time-varying additive actuator faults, the model uncertainties, and the unknown input of the leader simultaneously. The stability analysis and convergence results that guarantee boundedness of all closed-loop signals are investigated via Lyapunov's direct method. To demonstrate the effectiveness of the proposed approach, a network of single-link manipulators is studied. As the results verify, the proposed WNN-based fault estimation scheme can properly approximate the unknown actuator faults, which results in efficient compensation in the fault-tolerant control design to achieve cooperative tracking objectives.

Adaptive Reliable $H_{\infty }$ Optimization Control for Linear Systems With Time-Varying Actuator Fault and Delays

This paper deals with the adaptive reliable $\boldsymbol {H_{\infty }}$ optimization control problem for linear time-delayed systems (LTDSs) against time-varying actuator faults. A novel delay-dependent adaptive $\boldsymbol {H_{\infty }}$ performance index is described for LTDSs. An exponential function term has been successfully introduced to establish a novel actuator fault parameters estimation scheme. Moreover, the designed indirect adaptive controller includes both offline and online gains, which can be obtained by robust optimization technique and adaptive fault parameters estimation, respectively. By employing an improved Lyapunov–Krasovskii functional and applying some new-developed integral inequalities technique, some delay-dependent sufficient conditions with less conservatism are established to make the closed-loop systems exponentially stable and have the optimized adaptive delay-dependent $\boldsymbol {H_{\infty }}$ performance index. Finally, the effectiveness and superiority of the presented scheme are demonstrated by two examples.

Fault‐tolerant control of non‐linear systems based on adaptive virtual actuator

A new adaptive fault-tolerant control architecture for Lipschitz non-linear systems is developed. Specifically, the proposed approach involves a novel adaptive virtual actuator which is inserted between the faulty plant and the nominal controller to hide faults and disturbances from the nominal controller. The envisaged adaptive virtual actuator does not require any information about the nominal controller nor does it require a separate fault detection, isolation and identification unit. Moreover, it can tackle loss of effectiveness and time-varying additive actuator faults as well as an external disturbance, and in addition to the stability of the closed-loop system, it also guarantees that the difference between the states of the nominal and the faulty systems tend to zero. Simulation results corresponding to the lateral directional dynamics of an aircraft demonstrate and illustrate the effectiveness of the proposed adaptive virtual actuator.

Sliding mode control of continuous-time Markovian jump systems with digital data transmission

This paper investigates the design problem of sliding mode control for a class of continuous-time Markovian jump systems with digital communication constraints. Two types of classical quantization schemes, that is, dynamical uniform quantizer and static logarithmic quantizer, are employed to perform the design work, respectively. In this study, a novel quantized sliding mode control design method is developed to stabilize the closed-loop systems in the presence of both state and input quantization and unknown time-varying actuator faults. Under the proposed quantized control strategies, the quantization effects can be completely compensated via injecting quantizer parameters into the controller gains. Moreover, in both quantization cases, the proposed robust quantized sliding mode controllers can guarantee the state trajectories of the closed-loop systems to be mean-square stable, and ensure the reachability of the specified sliding surface with probability 1 at the same time. Finally, a numerical example with an F-404 aircraft engine system is provided to show the effectiveness of the proposed digital control design approach.

An advanced robust fault-tolerant tracking control for a doubly fed induction generator with actuator faults

Fault-tolerant controller (FTC) designs for doubly fed induction generators (DFIGs) with actuator faults have recently gained considerable attention due to their important role in maintaining the safety and reliability of DFIG-based wind turbines via configured redundancy. The objective of this paper is to propose a novel active fault-tolerant tracking control strategy for a DFIG subject to actuator faults. The proposed strategy consists of first designing a proportional integral observer (PIO) for simultaneous system states and fault estimation and then secondly the FTC, which depends on the estimated states and faults. The objective of such a controller is to drive the state of the system to track a reference state generated by a reference fault-free model (nominal system). In addition, the main results for stability are demonstrated through a quadratic Lyapunov function, formulated in terms of linear matrix inequalities (LMIs) in order to guarantee the stability of the whole closed-loop system and to reduce the actuator fault effects with noise attenuation. Furthermore, the gain matrices of the FTC and the PIO are computed by solving a set of LMIs using the YALMIP toolbox with the SeDuMi solver. Finally, the simulation results under constant and time-varying actuator faults are provided to show the effectiveness of the developed FTC scheme.

Actuator and sensor faults estimation based on proportional integral observer for TS fuzzy model

This paper presents a novel method to address a Proportional Integral observer design for the actuator and sensor faults estimation based on Takagi–Sugeno fuzzy model with unmeasurable premise variables. The faults are assumed as time-varying signals whose kth time derivatives are bounded. Using Lyapunov stability theory and L2 performance analysis, sufficient design conditions are developed for simultaneous estimation of states and time-varying actuator and sensor faults. The Proportional Integral observer gains are computed by solving the proposed conditions under Linear Matrix Inequalities constraints. A simulation example is provided to illustrate the effectiveness of the proposed approach.

Iterative learning control for non‐repetitive trajectory tracking of robot manipulators with joint position constraints and actuator faults

SummaryIn this work, we present a novel iterative learning control (ILC) scheme for a class of joint position constrained robot manipulator systems with both multiplicative and additive actuator faults. Unlike most ILC literature that requires identical reference trajectory from trail to trail, in this work the reference trajectory can be non‐repetitive over the iteration domain without assuming the identical initial condition. A tan‐type Barrier Lyapunov Function is proposed to deal with the constraint requirements which can be both time and iteration varying, with ILC update laws adopted to learn the iteration‐invariant system uncertainties, and robust methods used to compensate the iteration and time varying actuator faults and disturbances. We show that under the proposed ILC scheme, uniform convergence of the full state tracking error beyond a small time interval in each iteration can be guaranteed over the iteration domain, while the constraint requirements on the joint position vector will not be violated during operation. An illustrative example on a two degree‐of‐freedom robotic manipulator is presented to demonstrate the effectiveness of the proposed control scheme. Copyright © 2016 John Wiley & Sons, Ltd.