Adaptive fixed-time tracking control based on a novel command filter for uncertain nonlinear systems with asymmetric time-varying constraints

IF 3.8 2区数学 Q1 MATHEMATICS, APPLIED

Communications in Nonlinear Science and Numerical Simulation Pub Date : 2025-09-19 DOI:10.1016/j.cnsns.2025.109312

Xiaohong Cheng , Shuang Liu , Shaomeng Gu , Wenbo Wang

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引用次数: 0

Abstract

In this paper, an adaptive fixed-time tracking control method is proposed for uncertain nonlinear systems under asymmetric time-varying constraints to enhance control performance and stability, which includes a novel command filter, a series of newly designed adaptive laws, and a fixed-time controller. First, an improved fixed-time command filtering framework incorporating dynamic error compensation is proposed to effectively address the “complexity explosion” problem caused by the backstepping technology. Second, novel adaptive laws are designed based on radial basis function neural networks (RBFNN) to handle the uncertain nonlinear term and disturbance. Subsequently, based on the time-varying asymmetric barrier Lyapunov function (TABLF), a fixed-time controller is designed to track the reference signal, and all system states can be remained within asymmetric time-varying constraints. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed control method.

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非对称时变约束下不确定非线性系统基于新型命令滤波器的自适应定时跟踪控制

本文针对非对称时变约束下的不确定非线性系统，提出了一种自适应定时跟踪控制方法，该方法包括一种新的命令滤波器、一系列新设计的自适应律和一个定时控制器，以提高控制性能和稳定性。首先，提出了一种改进的包含动态误差补偿的定时命令滤波框架，有效地解决了回溯技术带来的“复杂度爆炸”问题。其次，基于径向基函数神经网络（RBFNN）设计了新的自适应律来处理不确定的非线性项和干扰；随后，基于时变非对称势垒Lyapunov函数（TABLF），设计定时控制器对参考信号进行跟踪，使系统的所有状态保持在非对称时变约束下。最后，通过两个仿真实例验证了所提控制方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Communications in Nonlinear Science and Numerical Simulation MATHEMATICS, APPLIED-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

CiteScore

6.80

自引率

7.70%

发文量

378

审稿时长

78 days

期刊介绍： The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science and complexity. The submission of manuscripts with cross-disciplinary approaches in nonlinear science and complexity is particularly encouraged. Topics of interest: Nonlinear differential or delay equations, Lie group analysis and asymptotic methods, Discontinuous systems, Fractals, Fractional calculus and dynamics, Nonlinear effects in quantum mechanics, Nonlinear stochastic processes, Experimental nonlinear science, Time-series and signal analysis, Computational methods and simulations in nonlinear science and engineering, Control of dynamical systems, Synchronization, Lyapunov analysis, High-dimensional chaos and turbulence, Chaos in Hamiltonian systems, Integrable systems and solitons, Collective behavior in many-body systems, Biological physics and networks, Nonlinear mechanical systems, Complex systems and complexity. No length limitation for contributions is set, but only concisely written manuscripts are published. Brief papers are published on the basis of Rapid Communications. Discussions of previously published papers are welcome.