Robust sliding-mode observer-based sensor fault estimation, actuator fault detection and isolation for uncertain nonlinear systems

Yang, Junqi; Zhu, Fanglai; Wang, Xin; Bu, Xuhui

doi:10.1007/s12555-014-0159-4

Cited by 86 publications

(69 citation statements)

References 27 publications

(74 reference statements)

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“…Then, FE algorithm (10) using iterative learning scheme can realize e k .t / and r k .t / uniformly bounded. Namely, the monotonic convergence of tracking error (16) and the H 1 performance (18) of error argued system are achieved. It should be pointed out that the condition in Theorem 1 cannot be directly employed for observer design of nonlinear time-delay system (1).…”

Section: Theoremmentioning

confidence: 93%

Observer‐based fault estimators using iterative learning scheme for nonlinear time‐delay systems with intermittent faults

Feng

Chai

et al. 2017

Intl J Robust & Nonlinear

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Summary This paper deals with the intermittent fault estimation problem for a class of nonlinear time‐delay systems with measurement noise. The time delays are assumed to occur in state vector, nonlinear term as well as output vector, thus reflecting the time delays influence in reality more closely. The aim of the problem is to estimate the intermittent fault by using iterative learning scheme, with the property of H∞ index, hence attenuating the influence from measurement noise. Different from existing fault estimating schemes, the state error information and fault estimating information in the previous iteration are used in the current iteration to improve the estimating results. The stability and convergence of iterative learning observer and uniform boundedness of dynamic error system are achieved by using Lyapunov function and optimal function design. Simultaneously, an improved sufficient condition for the existence of such an estimator is established in terms of the linear matrix inequality by the Schur complements and Young relations. Furthermore, the results are both suited for the systems with time‐varying delay and the systems with constant delay. Finally, two numerical examples are proposed to illustrate the effectiveness of the proposed method, and a comparability example is presented to demonstrate its superiority. Copyright © 2017 John Wiley & Sons, Ltd.

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Section: Theoremmentioning

confidence: 93%

Observer‐based fault estimators using iterative learning scheme for nonlinear time‐delay systems with intermittent faults

Feng

Chai

et al. 2017

Intl J Robust & Nonlinear

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“…According to (29), the state variable contains system state b x k ð Þ and control input at time k À τ, so when state e x k ð Þ converges, the convergence of b x k ð Þ can be ensured.…”

Section: Modeling Of Closed-loop System With Observermentioning

confidence: 99%

Aero‐Engine DCS Fault‐Tolerant Control with Markov Time Delay Based On Augmented Adaptive Sliding Mode Observer

Zhang

Xie

Zhang

et al. 2018

Asian Journal of Control

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With a focus on aero‐engine distributed control systems (DCSs) with Markov time delay, unknown input disturbance, and sensor and actuator simultaneous faults, a combined fault tolerant algorithm based on the adaptive sliding mode observer is studied. First, an uncertain augmented model of distributed control system is established under the condition of simultaneous sensor and actuator faults, which also considers the influence of the output disturbances. Second, an augmented adaptive sliding mode observer is designed and the linear matrix inequality (LMI) form stability condition of the combined closed‐loop system is deduced. Third, a robust sliding mode fault tolerant controller is designed based on fault estimation of the sliding mode observer, where the theory of predictive control is adopted to suppress the influence of random time delay on system stability. Simulation results indicate that the proposed sliding mode fault tolerant controller can be very effective despite the existence of faults and output disturbances, and is suitable for the simultaneous sensor and actuator faults condition.

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“…The AO-based fault estimation method proposed in the work of Gao and Ding 19 that can accurately estimate both the time-invariant and time-varying fault signals for input bounded disturbances are considered, whereas the fault signals are unbounded. In the work of Yang et al, 12 a robust sliding-mode observer is developed to deal with the issues of sensor fault estimation, actuator fault detection, and isolation for a class of uncertain nonlinear systems. The estimation can be online varying with the state estimation because of the scheme only based on the output estimation error.…”

Section: Introductionmentioning

confidence: 99%

“…In addition, it is further needed for the purpose of active fault tolerant control 9,10 and its capability seriously affects the reliability and safety of the industrial processes. In real applications, parameter uncertainties 11,12 are caused by linearization and model reduction, which may influence significantly the performance of fault estimation schemes. Besides, most of the uncertain systems are with nonlinearities owing to the complex design and structure in practical scenario.…”

Section: Introductionmentioning

confidence: 99%

Iterative learning scheme to design intermittent fault estimators for nonlinear systems with parameter uncertainties and measurement noise

Feng

Chai

et al. 2018

Adaptive Control & Signal

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In this paper, an iterative learning estimator is proposed to deal with period intermittent fault estimation problem in a class of nonlinear uncertain systems. First, state observer is designed for state reconstruction, followed by the Lyapunov function is presented to guarantee the convergence of the system output. Then, the iterative learning scheme-based fault estimator is presented to track the fault signal and the optimal function is established to ensure tracking error convergence. Moreover, linear matrix inequalities and Schur complements are utilized to obtain the sufficient conditions for the existence of iterative learning estimator. Compared with the existing results, error augmented systems should not satisfy the strictly positive realness assumption. Besides, previous state estimation error is used for current fault estimation such that to improve the estimating accuracy. Finally, 2 numerical examples are given to illustrate the effectiveness and validity of the proposed methods. KEYWORDS fault estimation, intermittent fault, iterative learning scheme, LMI, nonlinear uncertain systems 994

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Robust sliding-mode observer-based sensor fault estimation, actuator fault detection and isolation for uncertain nonlinear systems

Cited by 86 publications

References 27 publications

Observer‐based fault estimators using iterative learning scheme for nonlinear time‐delay systems with intermittent faults

Observer‐based fault estimators using iterative learning scheme for nonlinear time‐delay systems with intermittent faults

Aero‐Engine DCS Fault‐Tolerant Control with Markov Time Delay Based On Augmented Adaptive Sliding Mode Observer

Iterative learning scheme to design intermittent fault estimators for nonlinear systems with parameter uncertainties and measurement noise

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