Observer-based fuzzy adaptive fault-tolerant nonlinear control for uncertain strict-feedback nonlinear systems with unknown control direction and its applications

Mushage, Baraka Olivier; Chedjou, Jean Chamberlain; Kyamakya, Kyandoghere

doi:10.1007/s11071-017-3395-3

Cited by 14 publications

(5 citation statements)

References 54 publications

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“…In order to verify the accuracy and precision of the algorithm for manifold computation, we take following examples. The first one is Lorenz system [10,11] studied by most researchers for two-dimensional stable or unstable manifold computation. And the other is a four-dimensional Hamiltonian system studied by Hinke M Osinga [19] for computing the two-dimensional invariant manifolds in fourdimensional dynamical systems.…”

Section: Numerical Methods Of Maniflod Computionmentioning

confidence: 99%

“…Nowadays, with the development of the control theory, many advanced control theories are wildly used in nonlinear systems, For instance, fuzzy adaptive finite-time fault-tolerant control for strict-feedback nonlinear systems [10] , event-triggered robust fuzzy adaptive finitetime control of nonlinear systems with prescribed performance [11] , fuzzy output tracking control and filtering for nonlinear discrete-time descriptor systems [12] ,and some theories even been applied to a robotic airship against sensor faults [13] and attitude tracking of hypersonic vehicle [14] . ROA as the stability boundary of the nonlinear system, once the system exceeds the ROA, the state of the system will diverge, which is important to guide the application of nonlinear control theories.…”

Section: Introductionmentioning

confidence: 99%

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Exact Region of Attraction Determination Based on Manifold Method

Zheng

et al. 2020

IEEE Access

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The exact region of attraction plays an important role in autonomous nonlinear system, while the results based on the conventional method, such as Lyapunov function approach, are always conservative. However, results via the manifold method, which is the main approach studied, are exact. This method optimizes the distribution of points on the circle through modifying the end point of the former trajectory and inserting/deleting point on the circle on the basis of trajectory arc length method to improve the accuracy and efficiency. First, the basic theory of manifold method is introduced. Secondly, a methodology for determining stable manifold are proposed, which is the core of the manifold method in stability boundary determining. Finally, on this basis, three examples about academic model, power system and aviation system are taken to illustrate the advantages of the method. The results show that the method can improve the accuracy and significantly reduce the calculation time, and can be widely used in engineering systems.

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Section: Numerical Methods Of Maniflod Computionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exact Region of Attraction Determination Based on Manifold Method

Zheng

et al. 2020

IEEE Access

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“…Remark 1 The Nussbaum function candidate can be selected freely in diverse forms (see [2,26,27]), such as exp(ξ 2 ) cos ((π/2)ξ), ln(ξ + 1) cos ln(ξ + 1) and ξ 2 cos ξ.…”

Section: Nussbaum Functionmentioning

confidence: 99%

“…Most of underlying failures require urgent diagnosis and timely compensation, otherwise they may lead to catastrophic wrecks, unfortunate casualties and substantial economical losses, which motivates fault-tolerant control (FTC). In recent decade, plentiful results [1][2][3][4], have been yielded to suppress the detrimental influence of system faults on control performance. However, most of the existing FTC strategies have limitation because they merely ensure asymptotic (exponential) stability, whereas they scarcely guarantee rapid transient response and achieve stable performance in short time.…”

Section: Introductionmentioning

confidence: 99%

Finite-time sliding mode fault-tolerant neural network control for nonstrict-feedback nonlinear systems

Lin

Xue

et al. 2022

Preprint

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In the paper, finite-time tracking control for a class of nonstrict-feedback nonlinear systems subject to uncertain control gains and multiple actuator faults is explored. To circumvent the issue of “complexity explosion” arisen from the standard backstepping design, second-order command filter is introduced to estimate the virtual input and its derivative in every step. By means of a useful structural attribute of neural networks, the algebraic loop problem is excluded. Besides, the unknown control gains are handled via using Nussbaum functions. To attain robust control performance against external perturbations and chattering phenomenon, a novel sliding mode fault-tolerant controller is introduced to ensure finite-time stability of the controlled system. Furthermore, simulation cases are conducted to demonstrate the practical applications of the proposed approach to one-link manipulator and electromechanical system.

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“…Therefore, it is significant to improve system reliability and safety not only by designing fault tolerant control (FTC) to compensate the effect caused by faults automatically, but also by enhancing reliability of signal components. The approaches of the fault-tolerant design can be broadly divided into two categories: the passive one [1][2][3][4][5] and the active one [6][7][8][9][10][11]. Although the passive approach is usually exploited to handle partial actuator faults [12][13][14] and complete actuator faults [15][16][17], it has also a limited capability of handling unknown actuator faults due to its passive control laws being fixed.…”

Section: Introductionmentioning

confidence: 99%