控制理论(社会学)
非线性系统
跟踪(教育)
计算机科学
自适应控制
事件(粒子物理)
控制(管理)
人工智能
物理
心理学
教育学
量子力学
作者
Dong‐Mei Wang,Shan‐Liang Zhu,W. Zhao,Yu‐Qun Han,Wenwu Wang,Zhou Qing-hua
摘要
Summary In this paper, an event‐triggered adaptive tracking control strategy is proposed for strict‐feedback stochastic nonlinear systems with predetermined finite‐time performance. Firstly, a finite‐time performance function (FTPF) is introduced to describe the predetermined tracking performance. With the help of the error transformation technique, the original constrained tracking error is transformed into an equivalent unconstrained variable. Then, the unknown nonlinear functions are approximated by using the multi‐dimensional Taylor networks (MTNs) in the backstepping design process. Meanwhile, an event‐triggered mechanism with a relative threshold is introduced to reduce the communication burden between actuators and controllers. Furthermore, the proposed control strategy can ensure that all signals of the closed‐loop system are bounded in probability and the tracking error is within a predefined range in a finite time. In the end, the effectiveness of the proposed control strategy is verified by two simulation examples.
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