Nonlinear adaptive control method based on global identification strategy
ZHANG Zheng-xuan
YANG Yi-zhuo
DAI Wei
ZHOU Ping
YANG Chun-yu
Abstract：For a class of unknown dynamic nonlinear systems composed in discrete time,the traditional adaptive control method has the problem of poor control performance caused by low identification accuracy.To solve this problem,a new adaptive control method with unmodeled dynamic compensation based on global identification strategy is proposed.First,the equivalent correspondence between random vector function link(RVFL)network and low-order linear model and high-order unmodeled dynamic terms is mined by using the linear and enhanced structure characteristics.Then,the weight deviation penalty term is integrated to design the online updating algorithm of network model parameters to identify nonlinear system parameters.In addition,the one-step ahead optimal control strategy is used to design the linear controller and unmodeled dynamic compensator based on online identification of linear model parameters and unmodeled dynamic estimatorsl.Numerical experiments show that the proposed method is superior to the nonlinear adaptive control method based on alternating identification,and the industrial example verifies the industrial applicability of the proposed method.The potential problems of this control method in practical application and the relaxation of theoretical constraints are analyzed and prospected.
Keywords：random vector function link networknonlinearadaptive controlunmodeled dynamicoutput weight deviation penalty
Publication Date：2023-11-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 2039-2048 )