Command-Filter-Based Adaptive Fuzzy Finite-Time Control for Switched Nonlinear Systems Using State-Dependent Switching Method

Shi, Li; Ahn, Choon Ki; Xiang, Zhengrong

doi:10.1109/tfuzz.2020.2965917

Cited by 177 publications

(97 citation statements)

References 60 publications

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“…Remark Compared with the results in some existing literature, such as References 63‐65,71, a nonlinear feedback controller for QNNs is constructed in this article. Using the appropriate Lyapunov function and relevant inequalities techniques, the fixed‐time stabilization and the finite‐time stabilization of quaternion‐valued neural networks are obtained.…”

Section: Resultsmentioning

confidence: 99%

“…Stabilization control of neural networks has attracted more and more attention, and there are different types of stabilization, as well as different types of controllers. 45,[62][63][64][65][66] As an application of fixed-time stability, fixed-time control for RVNNs and CVNNs has received tremendous interest in recent years since it can make system stabilize within a bounded time even if the initial conditions are unknown in advance. 31,32,38,45 The fixed-time controller is added to the model to make it stabilize at a fixed-time.…”

Section: Introductionmentioning

confidence: 99%

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New feedback control techniques of quaternion fuzzy neural networks with time‐varying delay

Aouiti

Jallouli

2021

Intl J Robust & Nonlinear

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This article addresses the problems of fixed-time stabilization for a class of quaternion fuzzy neural networks (QFNNs) with time-varying delay. The QFNNs are developed by dividing our system into four real-valued parts based on the Hamilton rule. Then, based on fixed-time stability theory, some inequality techniques, and selecting the appropriate controllers and Lyapunov function, a novel criterion guaranteeing the fixed-time stabilization and the finite-time stabilization of the addressed system is derived. Finally, three numerical examples are presented to show the effectiveness of our theoretical results. K E Y W O R D S finite-time stabilization, fixed-time stabilization, fuzzy neural networks, quaternion neural networks, time-varying delay

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

New feedback control techniques of quaternion fuzzy neural networks with time‐varying delay

Aouiti

Jallouli

2021

Intl J Robust & Nonlinear

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“…Based on Equations (25), (26), (27), (28), (29), (30), the system (1) can be transformed into the following form…”

Section: Adaptive Controller Designmentioning

confidence: 99%

“…[23][24][25] Taking the finite time control problem into consideration, the variable separation method was used to solve the problem that the nonlinear function contained the entire state variable in the nonlinear system in other works. [26][27][28] Stochastic disturbance happened at practical applications and caused instability. Therefore, it was necessary and challenging to study the control problem of stochastic nonlinear systems.…”

Section: Introductionmentioning

confidence: 99%

“…A variable separation approach based on backstepping techniques was developed to overcome the difficulty from the nonstrict‐feedback structure in the work of Chen et al 20 Furthermore, backstepping‐based adaptive neural output‐feedback control was proposed for a class of nonstrict‐feedback nonlinear systems with unknown coefficient functions in the work of Yang et al 21 The variable separation method was extended to the multi‐input multi‐output (MIMO) system in the form of nonstrict feedback in the work of Du et al 22 With the help of neural networks and the backstepping technical, a fixed‐time adaptive neural control scheme was presented to deal with the nonstrict‐feedback nonlinear systems in other works 23‐25 . Taking the finite time control problem into consideration, the variable separation method was used to solve the problem that the nonlinear function contained the entire state variable in the nonlinear system in other works 26‐28 …”

Section: Introductionmentioning

confidence: 99%

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Adaptive dynamic surface control of stochastic nonstrict‐feedback constrained nonlinear systems with input and state unmodeled dynamics

Chen

Zhang

2020

Adaptive Control & Signal

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In this paper, the issue of adaptive neural control is discussed for a class of stochastic nonstrict-feedback constrained nonlinear systems with input and state unmodeled dynamics. A dynamic signal produced by the first-order auxiliary system is employed to deal with the dynamical uncertain terms. Radial basis function neural networks are used to reconstruct unknown nonlinear continuous functions. With the help of the mean value theorem and Young's inequality, only one learning parameter is adjusted online at recursive each step. Using the hyperbolic tangent function as nonlinear mapping, the output constrained stochastic nonstrict-feedback system in the presence of unmodeled dynamics is transformed into a novel unconstrained stochastic nonstrict-feedback system. Based on dynamic surface control technology and the property of Gaussian function, adaptive neural control is developed for the transformed stochastic nonstrict-feedback system. The output abides by stochastic constraints in probability. By the Lyapunov method, all signals of the closed-loop control system are proved to be semi-global uniform ultimate bounded (SGUUB) in probability. The obtained theoretical findings are verified by two numerical examples.

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Novel adaptive controller design for a class of switched nonlinear systems subject to input delay using multi‐dimensional Taylor network

Han

et al. 2021

Adaptive Control & Signal

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For the tracking control problem of a class of switched nonlinear systems with input delay, this article proposes an adaptive tracking control scheme based on multi-dimensional Taylor network (MTN) approach. First, Padé approximation and Laplace transform are employed to overcome the problem of input delay, and a new variable is introduced. Second, the MTNs are used to approximate the uncertain nonlinear structures in the process of controller design via backstepping. The results show that the controller designed in this article can keep all the signals in the closed-loop system are bounded, meanwhile, the output tracking error can be converged to arbitrarily small. It should be pointed out that MTN-based approach is applied to switched nonlinear systems subject to input delay for the first time. Finally, three examples are presented to verify the effectiveness of the proposed control strategy.

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Command-Filter-Based Adaptive Fuzzy Finite-Time Control for Switched Nonlinear Systems Using State-Dependent Switching Method

Cited by 177 publications

References 60 publications

New feedback control techniques of quaternion fuzzy neural networks with time‐varying delay

New feedback control techniques of quaternion fuzzy neural networks with time‐varying delay

Adaptive dynamic surface control of stochastic nonstrict‐feedback constrained nonlinear systems with input and state unmodeled dynamics

Novel adaptive controller design for a class of switched nonlinear systems subject to input delay using multi‐dimensional Taylor network

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