Switching Fixed-Time Control for Interconnected Nonlinear Systems With Unknown Control Directions and Unmodeled Dynamics

IF 8.7 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Wei Tian;Changchun Hua;Kuo Li;Pengju Ning
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引用次数: 0

Abstract

This article investigates the fixed-time control problem for a class of uncertain p-normal interconnected nonlinear systems with output constraints. Different from the existing fixed-time control results, unmodeled dynamics are allowed in the system model and the unknown control coefficients under consideration are time varying with nonidentical signs. To deal with this challenge, by applying the adding a power integrator method, a decentralized adaptive controller is built with a switching parameter to compensate unknown parameters. Based on fixed-time control framework, a logic-based switching rule is established to tune the switching parameter online, in which the Lyapunov-like boundary functions are utilized to replace the Lyapunov function containing inexact values brought by unmodeled dynamics. Then, with the aid of Lyapunov stability theorem, it is proved that the system output never violates the prespecified constraints and all state variables converge to zero within a fixed time. Finally, the validity of the presented method is demonstrated by a numerical simulation.
具有未知控制方向和未建模动力学的互联非线性系统的切换定时控制
研究了一类具有输出约束的不确定p-正规非线性互联系统的定时控制问题。与现有的固定时间控制结果不同,系统模型允许未建模的动力学,所考虑的未知控制系数是时变的,且符号不相同。为了解决这一问题,采用添加功率积分器的方法,建立了带有开关参数的分散自适应控制器,对未知参数进行补偿。基于定时控制框架,建立基于逻辑的切换规则,在线调整切换参数,利用类Lyapunov边界函数代替未建模动力学带来的含有不精确值的Lyapunov函数。然后,借助于Lyapunov稳定性定理,证明了系统输出不违反预定约束,且所有状态变量在固定时间内收敛于零。最后,通过数值仿真验证了所提方法的有效性。
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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