Fault-tolerant control of Markovian jump stochastic systems via the augmented sliding mode observer approach

Li, Hongyi; Gao, Huijun; Shi, Peng; Zhao, Xudong

doi:10.1016/j.automatica.2014.04.006

Cited by 515 publications

(258 citation statements)

References 34 publications

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“…It has proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are bounded in probability, and the tracking error converges to an adjustable neighborhood of the origin and remains within the prescribed performance bounds. Future research will concentrate on the adaptive FTC methods for uncertain MIMO stochastic nonlinear systems and uncertain stochastic nonlinear large-scale systems based on the results of this paper and the references of [26][27][28][29][30][31][32][33][34][35][36].…”

Section: Resultsmentioning

confidence: 99%

Adaptive Fuzzy Fault-Tolerant Output Feedback Tracking Control of Uncertain Stochastic Nonlinear Systems with Unknown Time-Delay and Tracking Error Constrained

Sui

Tong

2014

Journal of Applied Mathematics

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The problem of tracking error constrained adaptive fuzzy output feedback control is investigated for a class of single-input and single-output (SISO) stochastic nonlinear systems with actuator faults, unknown time-delay, and unmeasured states. The considered faults are modeled as both loss of effectiveness and lock-in-place. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy adaptive observer is designed for estimating the unmeasured states. By transforming the tracking errors into new virtual error variables and based on backstepping recursive design technique, a new fuzzy adaptive output feedback control method is developed. It is shown that all the signals of the resulting closed-loop system are bounded in probability and the tracking error remains an adjustable neighborhood of the origin within the prescribed bounds. The simulation results are provided to show the effectiveness of the proposed approach.

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Section: Resultsmentioning

confidence: 99%

Adaptive Fuzzy Fault-Tolerant Output Feedback Tracking Control of Uncertain Stochastic Nonlinear Systems with Unknown Time-Delay and Tracking Error Constrained

Sui

Tong

2014

Journal of Applied Mathematics

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“…Finally, simulation results are provided to illustrate the effectiveness of the method proposed in this paper and the advantages over those of the fuzzy-model-based approach. In our future work, we will consider the sliding mode control problem [19,22,28,29] for nonlinear systems based on polynomial-approximation-based approach.…”

Section: Discussionmentioning

confidence: 99%

“…By applying the sector nonlinearity method, considering x 1 ∈ [−2, 2], the dynamic of system (19) can be converted into the following polynomial fuzzy model:…”

Section: Casementioning

confidence: 99%

Polynomial-Approximation-Based Control for Nonlinear Systems

Zhou

Chen

Lam

2016

Circuits Syst Signal Process

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This paper is concerned with the stabilization problem for nonlinear systems. A new polynomial-approximation-based approach for modeling nonlinear systems is first proposed. The nonlinearity is approximated by polynomials and the approximation errors are treated as modeling uncertainties. The original nonlinear systems are converted into polynomial systems with modeling uncertainties. In order to highlight the approximation accuracy, the piecewise polynomial approximation functions are utilized. A novel polynomial state-feedback controller is designed to solve the stabilization problem. Furthermore, switched polynomial state-feedback controllers are designed to improve the performance. The stabilization conditions are presented in terms of sum of squares, which can be numerically solved via SOSTOOLS. Finally, simulation examples are provided to demonstrate the feasibility of the proposed method and show its advantage over the polynomial-fuzzy-model-based approach.

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“…Although the effect of sensor noise and actuator fault on the system performance is eliminated, the complexity of calculation and the dimension of system are increased for the sake of two observers proposed in [9][10][11][12]. To further simplify the design procedure, the work of [15][16][17][18][19][20] developed a novel descriptor sliding mode approach to exactly estimate system state, actuator fault and sensor noise simultaneously, which is inspired by the descriptor observer approach in [13,14]. Based on the estimated state, an observer-based fault-tolerant controller was constructed to stabilize the resulting fault system.…”

Section: Introductionmentioning

confidence: 99%

Output feedback control for a class of nonlinear systems with actuator degradation and sensor noise

et al. 2016

ISA Transactions

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a b s t r a c tThis paper investigates the output feedback control problem of a class of nonlinear systems with sensor noise and actuator degradation. Firstly, by using the descriptor observer approach, the origin system is transformed into a descriptor system. On the basis of the descriptor system, a novel Proportional Derivative (PD) observer is developed to asymptotically estimate sensor noise and system state simultaneously. Then, by designing an adaptive law to estimate the effectiveness of actuator, an adaptive observer-based controller is constructed to ensure that system state can be regulated to the origin asymptotically. Finally, the design scheme is applied to address a flexible joint robot link problem.

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Fault-tolerant control of Markovian jump stochastic systems via the augmented sliding mode observer approach

Cited by 515 publications

References 34 publications

Adaptive Fuzzy Fault-Tolerant Output Feedback Tracking Control of Uncertain Stochastic Nonlinear Systems with Unknown Time-Delay and Tracking Error Constrained

Adaptive Fuzzy Fault-Tolerant Output Feedback Tracking Control of Uncertain Stochastic Nonlinear Systems with Unknown Time-Delay and Tracking Error Constrained

Polynomial-Approximation-Based Control for Nonlinear Systems

Output feedback control for a class of nonlinear systems with actuator degradation and sensor noise

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