Adaptive fuzzy decentralized tracking fault-tolerant control for stochastic nonlinear large-scale systems with unmodeled dynamics

Tong, Shaocheng; Sui, Shuai; Li, Yongming

doi:10.1016/j.ins.2014.06.042

Cited by 53 publications

(21 citation statements)

References 45 publications

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“…Remark It is worth pointing out that the aforementioned two assumptions are common assumptions in the FTC literature . We can obtain from Assumption that the function

{sans-serifg}_{i, j} false(x false)

is strictly either negative or positive.…”

Section: Problem Description and Preliminariesmentioning

confidence: 96%

Global decentralized sampled‐data output feedback stabilization for a class of large‐scale nonlinear systems with sensor and actuator failures

Shi

Xiang

2019

Intl J Robust & Nonlinear

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Summary In this paper, we investigate global decentralized sampled‐data output feedback stabilization problem for a class of large‐scale nonlinear systems with time‐varying sensor and actuator failures. The considered systems include unknown time‐varying control coefficients and inherently nonlinear terms. Firstly, coordinate transformations are introduced with suitable scaling gains. Next, a reduced‐order observer is designed to estimate unmeasured states. Then, a decentralized sampled‐data fault‐tolerant control scheme is developed with an allowable sampling period. By constructing an appropriate Lyapunov function, it can be shown that all states of the resulting closed‐loop system are globally uniformly ultimately bounded. Finally, the validity of the proposed control approach is verified by using two examples.

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“…Remark It is worth pointing out that the aforementioned two assumptions are common assumptions in the FTC literature . We can obtain from Assumption that the function

{sans-serifg}_{i, j} false(x false)

is strictly either negative or positive.…”

Section: Problem Description and Preliminariesmentioning

confidence: 96%

Global decentralized sampled‐data output feedback stabilization for a class of large‐scale nonlinear systems with sensor and actuator failures

Shi

Xiang

2019

Intl J Robust & Nonlinear

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“…Hence, the tracking control problem has been solved by many methods. 5,[40][41][42][43][44][45] There have been many neural network-based approaches to handle the FTC problem of large-scale nonlinear systems, but there are a few results on the direct adaptive design scheme without neural networks to address the FTC problem for large-scale unknown nonlinear systems with input quantization.…”

Section: Introductionmentioning

confidence: 99%

Adaptive decentralized fault‐tolerant tracking control for large‐scale nonlinear systems with input quantization

Wang

Yang

2018

Intl J Robust & Nonlinear

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Summary In this paper, an adaptive decentralized tracking control scheme is designed for large‐scale nonlinear systems with input quantization, actuator faults, and external disturbance. The nonlinearities, time‐varying actuator faults, and disturbance are assumed to exist unknown upper and lower bounds. Then, an adaptive decentralized fault‐tolerant tracking control method is designed without using backstepping technique and neural networks. In the proposed control scheme, adaptive mechanisms are used to compensate the effects of unknown nonlinearities, input quantization, actuator faults, and disturbance. The designed adaptive control strategy can guarantee that all the signals of each subsystem are bounded and the tracking errors of all subsystems converge asymptotically to zero. Finally, simulation results are provided to illustrate the effectiveness of the designed approach.

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“…The desired control design is expected to compensate the actuator failures by effectively compensating the uncertainties. To remove this restrictive condition, the latest work in [21][22][23][24][25][26][27][28][29][30] considered the actuator failure compensation problem for unknown nonlinear systems, in which neural networks (NNs) or fuzzy logic systems (FLSs) were employed to approximate the unknown nonlinearities. Adaptive mechanisms show suitable performance in presence of uncertainties in failed actuators.…”

Section: Introductionmentioning

confidence: 99%

“…So far, varieties of fault compensation methods especially adaptive approaches have been developed [1][2][3][4][5][6][7][8][9][10]. Because of NNs or FLSs ability to approximate the uncertain nonlinear smooth functions, NNs and FLSs have been extensively used for modeling and controller design for uncertain nonlinear systems [21][22][23][24][25][26][27][28][29][30][31]. Some important results of adaptive control of systems with actuator failures exist in [5][6][7][8][9][10] for linear systems and in [11][12][13][14][15][16][17][18][19][20] for nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

“…Adaptive mechanisms show suitable performance in presence of uncertainties in failed actuators. The proposed failure compensation methods in [21][22][23][24][25][26][27][28] were based on the backstepping design method, and the proposed methods in [29,30] were based on the dynamic surface control (DSC) approach. However, the considered nonlinearities in [11][12][13][14][15][16][17][18][19][20] were known or should be linearly parameterized.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive neural dynamic surface control of MIMO nonlinear time delay systems with time‐varying actuator failures

Hashemi

2016

Adaptive Control & Signal

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In this paper, an adaptive dynamic surface control approach is developed for a class of multi-input multioutput nonlinear systems with unknown nonlinearities, bounded time-varying state delays, and in the presence of time-varying actuator failures. The type of the considered actuator failure is that some unknown inputs may be stuck at some time-varying values where the values, times, and patterns of the failures are unknown. The considered actuator failure can cover most failures that may occur in actuators of the systems. With the help of neural networks to approximate the unknown nonlinear functions and combining the dynamic surface control approach with the backstepping design method, a novel control approach is constructed. 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 neighborhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark as well as a chemical reactor system. The simulation results show the effectiveness of the proposed method. of the traditional backstepping design method [32,33]. The problem of 'explosion of complexity' is the complexity of the controller that grows drastically as the order of the system increases. The 'explosion of complexity' is caused by repeated differentiation of certain nonlinear functions.One of the other serious problems that are frequently encountered in many practical control systems and brings uncertainties to the systems is time delays. Because of the effect of time delays, these systems may own instability and poor performance [34]. So far, considerable attention has been devoted to the stability analysis and control design for time delay systems [35][36][37][38][39][40][41][42][43][44]. The existence of time delays renders the actuator failure compensation problem much more complex and difficult. Many valuable research and practical results have been achieved in actuator failure compensation for linear time delay systems [45][46][47][48][49][50][51][52]. To the best of the author's knowledge, relatively, a few papers were published regarding actuator failure compensation for nonlinear time delay systems [53][54][55][56][57][58]. In [53], an adaptive actuator failure compensation scheme was developed for a class of multi-input nonlinear time delay systems with known parameters, nonlinearity, constant delay, constant control gains, and unknown actuator failure parameters. In [54], a robust state feedback controller was presented for time delay multi-input systems with known parameters, known constant control gains, unknown nonlinearity, and unknown constant delays. The proposed robust actuator failure compensator in [54] promised the boundedness of all the signals in the closed-loop system; however, the tracking problem was not considered. In [55][56][57], the adaptive actuator failure compensation schemes were presented for paramet...

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Adaptive fuzzy decentralized tracking fault-tolerant control for stochastic nonlinear large-scale systems with unmodeled dynamics

Cited by 53 publications

References 45 publications

Global decentralized sampled‐data output feedback stabilization for a class of large‐scale nonlinear systems with sensor and actuator failures

Global decentralized sampled‐data output feedback stabilization for a class of large‐scale nonlinear systems with sensor and actuator failures

Adaptive decentralized fault‐tolerant tracking control for large‐scale nonlinear systems with input quantization

Adaptive neural dynamic surface control of MIMO nonlinear time delay systems with time‐varying actuator failures

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