Stochastic Actuator Faults Research Articles

Fuzzy sampled-data control for single-master multi-slave teleoperation systems with stochastic actuator faults

This article investigates the sampled-data control design for single-master multi-slave teleoperation systems with stochastic actuator faults and time-varying delays. At first, the nonlinear bilateral teleoperation systems are modeled as Takagi–Sugeno (T–S) fuzzy systems through membership functions. The decentralized sampled-data control technique is proposed with actuator faults occurring in both master and slave robots. Here, the stochastic faults satisfy certain probability conditions and the forward and backward delays between the master and slaves are time-variant and asymmetric. Next, the delay-dependent Lyapunov–Krasovskii functionals (LKFs) are constructed for the proposed fuzzy model to obtain sufficient stability conditions in terms of linear matrix inequality (LMI). Finally, the reliability and superiority of the proposed method are illustrated by numerical results.

Iterative learning fault-tolerant control for discrete-time nonlinear systems subject to stochastic actuator faults

This paper is concerned with an iterative learning fault-tolerant control strategy for discrete-time nonlinear systems where actuator faults arbitrarily occur. First, the stochastic faults occurring in multiplicative and additive manner are considered. Then, statistical behaviors of both faults-corrupted control signals from the actuator to the plant and faults-free ones from the iterative learning controller to the actuator are analyzed. Meanwhile, sufficient conditions of convergence for the proposed strategy are established by resorting to the time-weighted norm technique. Finally, two numerical examples are provided to illustrate the effectiveness and reliability of the proposed results. Both theoretical analysis and simulations indicate that the developed strategy is satisfactory in preserving decent tracking accuracy of the addressed systems subject to actuator faults.

Stabilization of Fuzzy Hydraulic Turbine Governing System With Parametric Uncertainty and Membership Function Dependent H∞ Performance

This paper examines the stabilization problem and membership function dependent <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty $ </tex-math></inline-formula> performance analysis for uncertain hydraulic turbine governing systems with stochastic actuator faults and time-varying delays via sampled-data control. At first, the nonlinear hydraulic turbine systems are modeled as Takagi-Sugeno (T-S) fuzzy systems with time-varying delay and bounded external disturbance through membership functions. Then, a novel delay-dependent looped Lyapunov-Krasovskii functional (LKF) is formulated with complete information throughout the sampling interval. In the meantime, a membership function dependent <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty $ </tex-math></inline-formula> performance index is suggested to diminish the impact of disturbances on the uncertain fuzzy system. Based on the robust control and novel LKF, new delay-dependent stability conditions for the closed-loop system are attained in the framework of linear matrix inequalities (LMIs). At last, the numerical example validates the proposed theoretical contributions in terms of achieving robust stability and minimizing disturbance attenuation levels.

Fuzzy Sampled-Data Control for DFIG-Based Wind Turbine With Stochastic Actuator Failures

The stabilization of fault-tolerant control problem for the doubly fed induction generator (DFIG)-based wind turbine (WT) model has been investigated with stochastic actuator faults by incorporating a Takagi-Sugeno (T-S) fuzzy technique. To depict such stochastic actuator faults, the proposed model is incorporated with Markovian switching parameters for denoting various faulty modes. Besides, a novel fault-tolerant fuzzy switching control with sampled-data (SD) inputs has also been employed for eliminating the stochastic faults so that the stabilization of the system and an optimal H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> level could be ensured simultaneously. Furthermore, the stability conditions are derived by employing fuzzy Lyapunov-Krasovskii functionals (LKFs), whose matrices are membership dependent functions. Finally, the proposed control method for the stabilization problem is validated through a numerical simulation performed on the DFIG-based WT model.

Memory-event-triggering H ∞ reliable control for networked jacket platforms against earthquakes and stochastic actuator faults

This paper deals with the problems of networked modelling and memory-event-triggering reliable control for steel jacket-type platforms in network environments. First, a networked model of the jacket platform against earthquakes and probabilistic actuator faults is established. Based on this model, a memory-based event-triggering communication scheme is introduced to account for the constrained communication resources. A distinct feature of the proposed triggering scheme is that it has great potential to identify and trigger the significantly changed data than the existing ones without ‘memory’. Then, by formulating the network-based closed-loop platform system as a stochastic delay system, some sufficient conditions are derived for co-designing the desired controller and the triggering scheme. Finally, comparative simulation results are provided to demonstrate the effectiveness and merits of the proposed triggering and control co-design method. It is shown that compared with some existing event-triggering control methods, the proposed memory-event-triggering reliable controller is effective to mitigate vibrations of the jacket platform and is potentially advantageous to save more network bandwidth and control cost.

Finite-time synchronization of nonlinear fractional chaotic systems with stochastic actuator faults

Abstract This paper states with the objective of investigating the synchronization problem of nonlinear delayed fractional-order chaotic systems in conjunction with quantization, actuator faults, randomly occurring parametric uncertainties and exogenous disturbances. Moreover, the actuator faults are randomly occurring at any instant of time. The resultant random variables obeying Bernoulli distribution are introduced to account stochastic behavior. In spite of ensuring the robust performance, the finite-time synchronization of the addressed system is achieved and satisfies passive disturbance attenuation level by developing robust quantized stochastic reliable control protocol. As a consequence, the fast synchronization of the considered system is ensured in a finite time period. Owing to this perspective, the desired controller gain matrices can be obtained by solving developed linear matrix inequality. Further, the effectiveness of the theoretical result developed in this paper is validated via numerical simulation.

Reliable Fuzzy H∞ Control for Permanent Magnet Synchronous Motor Against Stochastic Actuator Faults

This article examines the issue of reliable fuzzy H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control with permanent magnet synchronous motor (PMSM) and stochastic actuator faults. The principle target of modeling the reliable control for PMSM is to improve the performance of PMSM in terms of speed of response, tracking accuracy, and robustness. In contrast to work found in the literature, the proposed dynamic model of a PMSM the load torque variation acts as disturbances, speed control strategy is developed based on the Takagi-Sugeno (T-S) fuzzy model and stochastic actuator faults are considered which is more practical and challenging. In such a manner, first, the nonlinear PMSM model is altered into corresponding linear submodels through the sufficient T-S fuzzy membership rules. Then, based on the obtained dynamic model, reliable H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> control is designed for the considered PMSM. By executing an appropriate Lyapunov-Krasovskii (L-K) functional together with linear matrix inequality (LMI) optimization procedure, Wirtinger-based integral inequality approach, and arrangement of the delay-dependent adequate condition is determined which ensures that the closed-loop PMSM is robust asymptotic stable. Based on the acquired condition, the controller gains are derived by solving a set of LMIs. At last, the simulation results are depicted to validate the efficiency of our presented control method.

Asynchronous adaptive event-triggered tracking control for multi-agent systems with stochastic actuator faults

This paper investigates the problem of consensus tracking control for multi-agent systems with stochastic actuator faults, where the asynchronous adaptive event-triggered scheme (AETS) is proposed to reduce communication burden. The failure phenomenon for each actuator is described by an independent and identically distributed (i.i.d) random process. The communication information is divided two groups according to the scenario whether the followers can receive the information from the leader or not. Two adaptive event-triggered communication schemes are introduced based on the above classified information. Considering the stochastic actuator faults and the designed AETS, a new closed-loop fault-tolerant tracking control system model is established. Then, by employing the Lyapunov stability theory and stochastic analysis technique, a new fault-dependent stability criterion is derived, which ensures that the leader-following tracking error system is stochastically mean-square stable. Based on this criterion, the fault-tolerant consensus controller gains and the triggering parameters are obtained simultaneously by solving a linear matrix inequality (LMI). Moreover, the Zeno behavior of the AETS is excluded. Finally, a simulation example is included to illustrate the effectiveness of theoretical results.

Robust finite–time stochastic stabilization and fault–tolerant control for uncertain networked control systems considering random delays and probabilistic actuator faults

This paper focuses on the problem of reliable finite–time stochastic stability (FTSS) for uncertain networked control systems (NCSs). A Markovian jump system (MJS) model with partly unknown transition probabilities (TPs) for the NCSs with random delays, data packet dropouts (disorders as well) and stochastic actuator faults is established to describe the closed–loop system. A mode-dependent static output feedback controller is designed taking only the measured outputs into account. A new criterion is also derived in terms of linear matrix inequalities (LMIs) to ensure reliable FTSS of the closed–loop system, based on the stochastic stability theory. Simulation studies on a benchmark numerical example, as well as an unstable numerical example can verify the effectiveness of the proposed method.

Robust Finite–Time Fault–Tolerant Control of Uncertain Networked Control Systems via Markovian Jump Linear Systems Approach

This paper concerns the problem of static output feedback (SOF) fault–tolerant controller (FTC) design for uncertain networked control systems (NCSs) considering stochastic actuator faults. The NCSs in the presence of random delays and data packet dropouts are firstly modeled as Markovian jump linear systems (MJLSs) with partly unknown transition probabilities (TPs). Afterward, sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to ensure finite–time stochastic stability (FTSS) of the closed–loop system. The Simulation results demonstrate the effectiveness and reliability of the controller.

Robust finite-time non-fragile sampled-data control for T-S fuzzy flexible spacecraft model with stochastic actuator faults

In this paper, the problem of robust finite-time non-fragile sampled-data control is investigated for uncertain flexible spacecraft model with stochastic actuator faults based on Takagi-Sugeno (T-S) fuzzy model approach. Specifically, the existence of stochastic actuator faults are described by using the Bernoulli distribution. On the basis of the input-delay approach, the sampled-data system is reformulated to a continuous time-varying delay system. Further, based on Lyapunov functional approach and linear matrix inequality technique, sufficient conditions are derived for the existence of the desired state feedback controller ensuring the stochastic finite-time bounded with prescribed H∞ performance index. Finally, numerical simulations are provided for the practical flexible spacecraft control system to verify the effectiveness and applicability of the proposed control design.

Adaptive attitude takeover control for space non-cooperative targets with stochastic actuator faults

This paper focuses on the attitude takeover control for the space non-cooperative targets with stochastic actuator faults. In this paper, the stochastic deviation faults and gain faults of the actuators, as well as the inertia tensor calculated errors are all under consideration. By introducing an adaptive deviation fault compensation term and an input uncertainty compensation law in a nonlinear feedback controller, an adaptive fault tolerant attitude takeover control scheme is synthesized in this paper. The considered stochastic thruster faults, the calculated inertia tensor error and the external disturbance can be compensated, the stochastic attitude stabilization and tracking are maintained as a result. Based on a quadratic Lyapunov function, the proof of the stochastic convergence is completed. Simulation results demonstrate the effectiveness and advantages of the proposed method.

Reliable observer-based H∞ control for discrete-time fuzzy systems with time-varying delays and stochastic actuator faults via scaled small gain theorem

Abstract This paper is concerned with the reliable observer-based H ∞ control problem for discrete-time Takagi–Sugeno (T–S) fuzzy systems with time-varying delay and stochastic actuator faults based on input–output approach. A discrete-time homogeneous Markov chain is used to represent the stochastic behavior of actuator faults. First, the discrete-time T–S fuzzy system is transformed into the form of interconnection of two subsystems by employing a new model transformation for the delayed state variables. Furthermore, a sufficient condition on discrete-time T–S fuzzy systems with time-varying delay and actuator faults, which guarantees the corresponding closed-loop system to be stochastically stable and preserves a guaranteed H ∞ performance, is derived by employing the scaled small gain theorem. Meanwhile, the solvability condition for the reliable observer-based H ∞ control is also established, by which the reliable H ∞ fuzzy controller can be solved as linear matrix inequalities (LMIs). Finally, a numerical example is provided to demonstrate the effectiveness of the proposed approach.

Reliable H ∞ non-uniform sampling tracking control for continuous-time non-linear systems with stochastic actuator faults

This study is concerned with the fuzzy H ∞ non-uniform sampling tracking control problem of non-linear systems described by Takagi-Sugeno fuzzy systems. Considering the stochastic actuator failures, together with the input delay approach, a unified tracking control model of the non-linear systems with stochastic parameter matrix is first established. The unified model has three features: (I) the different premise variables and timescales are employed in the T-S fuzzy models and the controller rules; (II) non-uniform sampling controller is designed and (III) the fault statistics of each actuator is individually quantified. Based on Lyapunov functional approach and stochastic analysis technique, a control design scheme that guarantees the prescribed H ∞ tracking performance of the non-linear systems is proposed in terms of linear-matrix-inequalities. Finally, two application examples are given to show the effectiveness of the proposed method.