Reliable Control of Nonlinear System with Input Saturation by Adaptive Iterative Learning Control

被引:0
|
作者
Zhang, Ruikun [1 ,3 ]
Chi, Ronghu [2 ]
机构
[1] Qingdao Univ Sci & Technol, Sch Math & Phys, Qingdao 266061, Peoples R China
[2] Qingdao Univ Sci & Technol, Sch Automat & Elect Engn, Qingdao 266042, Peoples R China
[3] Qingdao Univ Sci & Technol, Sch Math & Phys, Big Data Res Ctr, Qingdao 266061, Peoples R China
基金
中国国家自然科学基金;
关键词
Reliable control; input saturation; nonlinear system; adaptive iterative learning control; BATCH PROCESSES; DELAY;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
In this paper, reliable control strategy is studied for nonlinear system with input saturation by adaptive iterative learning control. The system dynamic function is described by a class of nonlinearly parameterized functions with input saturation and actuator faults. In order to address nonlinearity of system, input saturation and the actuator fault term, we design the adaptive iterative learning reliable controller (AILRC), which is a feedback P-type ILC controller. Based on the constructed composite energy function (CEF) and some necessary assumptions, the convergence analysis is given, which shows that the system tracking error converges to zero when the iteration number tends to infinity. Finally, simulation is given to illustrate the correctness of the proposed AILRC.
引用
收藏
页码:1001 / 1005
页数:5
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