Adaptive fuzzy dual‐performance fault‐tolerant control for interconnected nonlinear systems

HaoSiwen,; Xuehong,; PanYingnan,

doi:10.1002/acs.3284

Cited by 12 publications

(21 citation statements)

References 52 publications

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“…Remark In most existing literature, under the so‐called universal approximation theorem, fuzzy logic systems 60 and neural networks 61,62 are commonly utilized to approximate virtual control functions and its differential items. Although the applicability of this method is strong, the control performance is still less than satisfactory.…”

Section: Resultsmentioning

confidence: 99%

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Event‐triggered adaptive tracking control for uncertain fractional‐order nonstrict‐feedback nonlinear systems via command filtering

Wang

Zhao

et al. 2022

Intl J Robust & Nonlinear

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This article puts forward an event-triggered adaptive neural tracking control strategy for a class of uncertain fractional-order nonstrict-feedback nonlinear systems with full-state constraints and dead-zone inputs. The proposed control strategy is capable of surmounting an inherent shortcoming in most traditional backstepping control approaches which results from the repeated differentiation of virtual control functions, and enhancing the transmission efficiency of control signals by introducing an event-triggered mechanism with a dynamic threshold condition. Furthermore, by constructing a novel barrier Lyapunov function in each step of the backstepping procedure, the design difficulty arising from the system state constraints issue under fractional-order cases is resolved. It is strictly proved that the tracking error can converge into a desired small neighborhood of the origin and all signals in the closed-loop system are bounded. Finally, a simulation example is given to verify the effectiveness of our proposed control strategy.

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Section: Resultsmentioning

confidence: 99%

“…Remark 4. In most existing literature, under the so-called universal approximation theorem, fuzzy logic systems 60 and neural networks 61,62 are commonly utilized to approximate virtual control functions and its items.…”

Section: Stability Analysismentioning

confidence: 99%

Event‐triggered adaptive tracking control for uncertain fractional‐order nonstrict‐feedback nonlinear systems via command filtering

Wang

Zhao

et al. 2022

Intl J Robust & Nonlinear

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“…Using Assumption 2, there is a positive constant y r such that |y r (t)| ≤ y r . By inserting ( 15)-( 17) in (20), one has:…”

Section: Adaptive Controller Designmentioning

confidence: 99%

“…However, in many practical applications, system dynamics is unknown. It is common to approximate system unknown dynamics by intelligent approximators such as neural networks (NNs) and fuzzy logic systems (FLSs) 17–22 . A NN‐based controller has been proposed in Reference 23 for a class of nonlinear systems with state constraints and state delays.…”

Section: Introductionmentioning

confidence: 99%

“…It is common to approximate system unknown dynamics by intelligent approximators such as neural networks (NNs) and fuzzy logic systems (FLSs). [17][18][19][20][21][22] A NN-based controller has been proposed in Reference 23 for a class of nonlinear systems with state constraints and state delays. In Reference 24, an adaptive FLS-based control scheme has been designed for a class of large-scale nonlinear systems with time-varying asymmetric state constraints.…”

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confidence: 99%

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Observer‐based controller for nonaffine time‐delayed systems subject to input nonlinearities, state constraints, and unknown control direction

Mohit

Shahrokhi

Kamalamiri

2022

Adaptive Control & Signal

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In this work, an adaptive observer-based control scheme has been designed for uncertain nonaffine nonstrict feedback systems subject to state time delay, various types of input nonlinearities, time-varying asymmetric state constraints, and unknown control direction. Compared to the existing controllers for systems with state constraints, the designed control scheme in this work can be applied to state-constrained systems with nonaffine structure subject to state delays, unknown control direction, and different types of input nonlinearities, while full-states measurement is not required. Moreover, by introducing a novel saturated Nussbaum function in the present work, not only has the problem of unknown control direction been handled, but also the probability of a control shock due to applying the conventional Nussbaum functions has been eliminated. The system unknown dynamics has been approximated by using neural networks (NNs), and by updating the maximum norm of NNs weight vectors, only one adaptive law is required for the controller implementation. By employing appropriate Lyapunov functions, it has been shown that all signals in the closed-loop system are bounded, state constraints are satisfied, and the output tracking error can be made small by selecting appropriate design parameters.The effectiveness of the designed control scheme has been shown through two simulation studies. Moreover, the superiority of the proposed saturated Nussbaum function in comparison with conventional Nussbaum functions has been shown via simulation. K E Y W O R D Sinput nonlinearity, intelligent approximator, nonstrict feedback systems, state constraints, unknown control direction INTRODUCTIONRecently, control of systems with constraints has attracted a great deal of attention because many real systems are subject to constraints such as wheeled mobile robotic systems 1 and chemical processes. 2 Constraints may appear as physical restrictions, performance requirements, or safety considerations. 3 Input, state, and output constraints are the three major types of constraints investigated in the literature. For example, an adaptive controller has been designed for a class of 2122

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Adaptive neural tracking control for non‐affine switched systems with multiple time delays and actuator faults

Zhang

2022

Adaptive Control & Signal

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Summary In this article, an adaptive output feedback neural tracking control algorithm is studied for non‐affine switched systems with multiple time delays and actuator faults. First, an adaptive neural state observer, which only needs to update a parameter online, is presented to estimate the unmeasurable state, and Lipschitz condition is used to deal with delay fault so as to avoid complex delay assumption. Then, by using online estimation information and backstepping technique, a switched fault‐tolerant control mechanism is established for non‐affine switched systems, the designed controller of each subsystems can ensure that non‐affine switched systems output signal can track reference signal under switch signals with average dwell time and all closed‐loop signals are bounded in the presence of multiple time delays, actuator faults, and external disturbances. Finally, simulation results verify the effectiveness of the proposed algorithm.

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Adaptive fuzzy dual‐performance fault‐tolerant control for interconnected nonlinear systems

Cited by 12 publications

References 52 publications

Event‐triggered adaptive tracking control for uncertain fractional‐order nonstrict‐feedback nonlinear systems via command filtering

Event‐triggered adaptive tracking control for uncertain fractional‐order nonstrict‐feedback nonlinear systems via command filtering

Observer‐based controller for nonaffine time‐delayed systems subject to input nonlinearities, state constraints, and unknown control direction

Adaptive neural tracking control for non‐affine switched systems with multiple time delays and actuator faults

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