Multiple models second level adaptive control of multivariable periodic systems

被引：0
|
作者：
Wang Y. [1 ]
Wang X. [2 ]
Wang Z.-L. [1 ]
机构：
[1] Key Laboratory of Advanced Control and Optimization for Chemical Processes, East China University of Science and Technology, Shanghai
[2] Electrical and Electronic Experimental Teaching Center, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai
来源：
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2021年 / 38卷 / 03期
基金：
中国国家自然科学基金; 上海市自然科学基金;
关键词：
Multiple models; Multivariate; Periodic system; Second level adaptive;
D O I：
10.7641/CTA.2020.00240
中图分类号：
学科分类号：
摘要：
For a class of multivariable periodic systems with unknown parameters, the traditional adaptive control method has the problem of slow parameter convergence, which leads to poor transient response of the system and unsatisfactory control effect. Therefore, a multiple models second level adaptive controller is designed for multivariable periodic systems. Firstly, according to the prior knowledge, the range of the uncertain region is determined, and multiple adaptive models are built in the uncertain region. Secondly, the first level identification equation is obtained according to Lyapunov theory. In the second level, the identification error is fully considered and the weight adaptive law is determined to obtain the virtual model for improving the convergence rate of parameters. Then, a second level adaptive controller is designed by using the parameters of virtual model, which improves the transient performance of the system on the basis of ensuring the stability of the system. Finally, the simulation results show that the multiple model second level adaptive controller improves the convergence rate of parameters and the transient performance of the system. © 2021, Editorial Department of Control Theory & Applications South China University of Technology. All right reserved.
引用
收藏
页码：391 / 397
页数：6
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