A Simplified Adaptive Fixed Time Control of Pure-Feedback Stochastic Nonlinear Systems Subject to Full State Constraints

IF 3.9 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Adaptive Control and Signal Processing Pub Date : 2025-01-30 DOI:10.1002/acs.3976

Nan Wang, Fazhan Tao, Pengyu Fan, Mengyang Li, Zhumu Fu

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Abstract

In this paper, a novel fixed time adaptive fuzzy control scheme for pure-feedback stochastic nonlinear systems with full state constraints is proposed based on dynamic surface control (DSC) technique and barrier Lyapunov functions (BLFs) method. Firstly, the mean value theorem is utilized to transform the pure-feedback structure of the considered systems into strict-feedback ones, which make it possible for the utilization of backstepping method to design the controller. Then, DSC technique is used to reduce the computational complexity problem caused by backstepping method. Fuzzy logic systems are exploited to approximate the unknown nonlinear functions. Moreover, combine BLFs method with fixed time stability theorem, the fixed time adaptive fuzzy controller is constructed, which guarantees that all states do not violate the prescribed constraints and all signals are semi-globally uniform ultimately bounded. Finally, a simulation example is given to verify the effectiveness of the studied control.

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全状态约束下纯反馈随机非线性系统的简化自适应固定时间控制

基于动态面控制（DSC）技术和barrier Lyapunov函数（blf）方法，提出了一种具有全状态约束的纯反馈随机非线性系统的固定时间自适应模糊控制方法。首先，利用中值定理将所考虑系统的纯反馈结构转化为严格反馈结构，使得利用反推法设计控制器成为可能；然后，利用DSC技术降低了反演法的计算复杂度。利用模糊逻辑系统来逼近未知的非线性函数。将blf方法与定时稳定性定理相结合，构造了定时自适应模糊控制器，保证了系统的所有状态不违反规定约束，且所有信号都是半全局一致最终有界的。最后通过仿真算例验证了所研究控制的有效性。

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来源期刊

International Journal of Adaptive Control and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

16.10%

发文量

163

审稿时长

5 months

期刊介绍： The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.