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Adaptive Fuzzy Output-Constrained Control for Nonlinear Stochastic Systems With Input Delay and Unknown Control Coefficients | IEEE Journals & Magazine | IEEE Xplore

Adaptive Fuzzy Output-Constrained Control for Nonlinear Stochastic Systems With Input Delay and Unknown Control Coefficients


Abstract:

This article considers an adaptive fuzzy control problem for nonstrict-feedback nonlinear stochastic systems, which contain input delay, output constraints, and unknown c...Show More

Abstract:

This article considers an adaptive fuzzy control problem for nonstrict-feedback nonlinear stochastic systems, which contain input delay, output constraints, and unknown control coefficients, simultaneously. First, an original stochastic nonlinear mapping and the Pade approximation transformation techniques are developed to solve the symmetric output constraints and input delay. Then, an adaptive fuzzy controller is designed for the unknown nonlinear systems, in which the Nussbaum function is employed to deal with the unknown time-varying control coefficients. Tracking errors are ensured to converge to a small neighborhood around the origin, and the system output does not violate the predefined constrained conditions. All the signals of the closed-loop systems have proven to remain bounded in probability. Moreover, the asymmetric output-constrained control is also studied. Two simulation examples are provided to show the effectiveness of the developed method.
Published in: IEEE Transactions on Cybernetics ( Volume: 51, Issue: 11, November 2021)
Page(s): 5279 - 5290
Date of Publication: 24 November 2020

ISSN Information:

PubMed ID: 33232259

Funding Agency:


I. Introduction

In the past decades, adaptive fuzzy/neural network control for the deterministic nonlinear systems has been extensively studied based on the backstepping technique proposed first in [1], and many significant results were obtained (see [2]–[6] and the references therein). The nonlinear stochastic systems model and control were also paid much attention due to their extensive applications in economic, social, and industry systems [7]–[11], where [9] and [10] proposed the adaptive control approaches based on the event-triggering mechanism. It is noted that the above nonlinear systems are in strict-feedback (or pure-feedback) forms. The nonstrict-feedback nonlinear systems considered in [12] are more general than the strict-feedback ones. The above control strategies may be no longer effective since the higher-order variables will appear in the low-order subsystems, which can give rise to the problem of the algebraic loop by the backstepping technique. To overcome this problem, a monotone bounded increasing function was introduced into the adaptive controller design in [13] and [14]. The approach was further extended to the nonlinear stochastic systems with backlash-like hysteresis in [15]. It should be noted that these kinds of monotonic bound increasing functions may greatly limit the practical application. How to develop a new approach to overcome that limitation is one of the motivations of this article.

References

References is not available for this document.