反推
控制理论(社会学)
非线性系统
有界函数
李雅普诺夫函数
计算机科学
理论(学习稳定性)
跟踪误差
Lyapunov稳定性
自适应控制
泰勒级数
边界(拓扑)
数学优化
数学
控制(管理)
数学分析
物理
量子力学
人工智能
机器学习
作者
Lei Chu,Tian Gao,Mingxin Wang,Yu‐Qun Han,Shan‐Liang Zhu
摘要
Abstract This paper investigates the adaptive decentralized control problem for a class of large‐scale nonlinear systems with finite‐time output constraints. In order to ensure that the tracking errors are constrained within a predefined boundary in finite time, a novel adaptive barrier Lyapunov function (BLF) control method is proposed by combining the modified finite‐time performance function (FTPF) in the first step of backstepping process. Besides, the mean value theorem and regulating functions are employed to handle the difficulties caused by interconnection functions in large‐scale systems. Subsequently, with the approximation performance of multi‐dimensional Taylor network (MTN), a MTN‐based adaptive decentralized tracking control scheme is developed to guarantee that the tracking errors satisfy the prescribed performance and all signals of the closed‐loop systems are bounded. Finally, the stability theory analysis and simulation results demonstrate the effectiveness of the proposed method.
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