Adaptive neural output feedback control for stochastic nonlinear time-delay systems with input and output quantization

Yang, Yekai; Yu, Zhensheng; Li, Shugang

doi:10.1016/j.neucom.2017.12.023

Cited by 12 publications

(12 citation statements)

References 47 publications

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“…But these systems in References 37‐39 are delay‐free. In Reference 40, we have studied the adaptive quantized tracking control for a class of stochastic nonlinear time‐delay systems in the presence of both input and output quantization. However, it is requisite to note that the considered systems in References 37‐40 are irrelevant to switching behavior and do not involve the limitation of actuator saturation.…”

Section: Introductionmentioning

confidence: 99%

Command‐filter‐based adaptive output feedback quantized tracking control for switched stochastic nonlinear time‐delay systems with actuator saturation

Yang

et al. 2022

Intl J Robust & Nonlinear

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This work addresses the adaptive output feedback quantized control for a class of switched stochastic nonstrict-feedback nonlinear time-delay systems with input and output quantization and actuator saturation under arbitrary switching. A novel state observer including the quantized output signal and the saturated input signal is designed to estimate the unknown system states. Then, the command-filtered backstepping method is introduced to avoid the "explosion of complexity" in the adaptive backstepping recursive design. Moreover, the design challenges from input and output quantization errors and actuator saturation are overcome by combining the auxiliary variable approach and some special techniques. Instead of the traditional quartic Lyapunov-Krasovskii functional, the common quadratic Lyapunov-Krasovskii functional is constructed to develop the adaptive quantized tracking control scheme for such systems.By means of the proposed common controller independent of switching signal, all closed-loop signals are mean-square semi-globally uniformly ultimately bounded, while the tracking error will remain in a small neighborhood of the origin. Finally, stability analysis and simulation results are provided to show the effectiveness and performance of the proposed design methodology.

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Section: Introductionmentioning

confidence: 99%

Command‐filter‐based adaptive output feedback quantized tracking control for switched stochastic nonlinear time‐delay systems with actuator saturation

Yang

et al. 2022

Intl J Robust & Nonlinear

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“…A fuzzy adaptive approach for stochastic strict‐feedback nonlinear systems with quantized input signal was discussed in the work of Niu et al Three adaptive control schemes with input or state quantization were investigated for uncertain systems with unknown control direction and guaranteed transient performance in the other works . Adaptive output feedback control was presented for a class of nonlinear systems with quantized input and output in the other works . Moreover, finite‐horizon H‐infinity state estimation was investigated for periodic neural networks over fading channels in the work of Li et al…”

Section: Introductionmentioning

confidence: 99%

“…[23][24][25] Adaptive output feedback control was presented for a class of nonlinear systems with quantized input and output in the other works. [26][27][28] Moreover, finite-horizon H-infinity state estimation was investigated for periodic neural networks over fading channels in the work of Li et al 29 Although the problem of adaptive quantized control has been studied based on hysteresis quantizer by backstepping method for single-input-single-output and multi-input-multi-output nonlinear systems in the other works, 16,28 their considered systems did not include unmodeled dynamics and dynamical uncertainties as well as output constraints. In this paper, we focus on the output feedback tracking control problem of uncertain nonlinear systems with input quantization and unmodeled dynamics as well as output constraints.…”

Section: Introductionmentioning

confidence: 99%

Adaptive neural output feedback control for uncertain nonlinear systems with input quantization and output constraints

Wang

Zhang

Yang

2020

Adaptive Control & Signal

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Summary In this paper, we are concerned with the problem of adaptive output‐feedback tracking control for nonlinear systems with input quantization, unmodeled dynamics, and output constraints. A novel quantizer with the advantages of hysteresis and uniform quantizer is introduced to handle input signals. A barrier Lyapunov function is employed to solve the output constraints. The state unmodeled dynamics is solved by using a Lyapunov description, and neural networks are used to approximate the unknown smooth functions produced in the adaptive control design process. The controller design is simplified by combining the new quantizer with dynamic surface control method. The mathematical derivation shows the stability of the closed‐loop system and the effectiveness of output constraints. Simulation illustrates and clarifies the theoretical findings.

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“…the stability of a class of nonlinear uncertain stochastic timedelay systems, and a sufficient delay-dependent criterion was established by constructing a new Lyapunov-Krasovskii function. The output feedback adaptive tracking control problem for a class of stochastic nonlinear time-delay systems was studied in [12], and an observer-based adaptive neural quantization tracking control scheme was proposed. For other excellent results, the reader is referred to [13]- [15] and references therein.…”

Section: Introductionmentioning

confidence: 99%

Finite-Time H_∞ Control for Itô-Type Nonlinear Time-Delay Stochastic Systems

et al. 2020

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The finite-time H ∞ control problem for an Itô-type stochastic system with nonlinear perturbation and time delay is investigated. First, the finite-time H ∞ control problem for a nonlinear time-delay stochastic system is presented taking into consideration both the transient performance and the capability to attenuate the disturbance of a closed-loop system in a given finite-time interval. Second, using the Lyapunov-Krasoviskii functional method and the matrix inequality technique, some sufficient conditions for the existence of finite-time H ∞ state feedback controller and dynamic-output feedback controller for nonlinear time-delay stochastic systems are obtained. These conditions guarantee the mean-square finitetime bounded-ness of the closed-loop systems and determine the H ∞ control performance index. Third, this problem is transformed into an optimization problem with matrix inequality constraints, and the corresponding algorithms are given to optimize the H ∞ performance index and obtain the maximum timedelay. Finally, a numerical example is used to illustrate the effectiveness of the proposed method. INDEX TERMS Stochastic systems, nonlinear perturbations, finite-time stability, H ∞ control, time-delay.

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Adaptive neural output feedback control for stochastic nonlinear time-delay systems with input and output quantization

Cited by 12 publications

References 47 publications

Command‐filter‐based adaptive output feedback quantized tracking control for switched stochastic nonlinear time‐delay systems with actuator saturation

Command‐filter‐based adaptive output feedback quantized tracking control for switched stochastic nonlinear time‐delay systems with actuator saturation

Adaptive neural output feedback control for uncertain nonlinear systems with input quantization and output constraints

Finite-Time H_∞ Control for Itô-Type Nonlinear Time-Delay Stochastic Systems

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Adaptive neural output feedback control for stochastic nonlinear time-delay systems with input and output quantization

Cited by 12 publications

References 47 publications

Command‐filter‐based adaptive output feedback quantized tracking control for switched stochastic nonlinear time‐delay systems with actuator saturation

Command‐filter‐based adaptive output feedback quantized tracking control for switched stochastic nonlinear time‐delay systems with actuator saturation

Adaptive neural output feedback control for uncertain nonlinear systems with input quantization and output constraints

Finite-Time H∞ Control for Itô-Type Nonlinear Time-Delay Stochastic Systems

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Finite-Time H_∞ Control for Itô-Type Nonlinear Time-Delay Stochastic Systems