A Variable-Parameter-Model-Based Feedforward Compensation Method for Tracking Control

作     者：Dailin Zhang Zining Wang Masayoshi Tomizuka Dailin Zhang;Zining Wang;Masayoshi Tomizuka

作者机构：School of Mechanical Science and EngineeringState Key Laboratory of Digital Manufacturing Equipment and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Department of Mechanical EngineeringUniversity of California at BerkeleyBerkeley CA 94720 USA IEEE 

出 版 物：《IEEE/CAA Journal of Automatica Sinica》 (自动化学报（英文版）)

年 卷 期：2020年第7卷第3期

页      面：693-701页

核心收录：

学科分类：0711[理学-系统科学] 07[理学] 0811[工学-控制科学与工程] 

基　　金：supported in part by the National Natural Science Foundation of China(51775215 51535004)。 

主　　题：Disturbance observer feedforward compensation iterative learning control parameter identification system model 

摘      要：Base on the accurate inverse of a system, the feedforward compensation method can compensate the tracking error of a linear system dramatically. However, many control systems have complex dynamics and their accurate inverses are difficult to obtain. In the paper, a variable parameter model is proposed to describe a system and a multi-step adaptive seeking approach is used to obtain its parameters in real time. Based on the proposed model, a variable-parameter-model-based feedforward compensation method is proposed, and a disturbance observer is used to overcome the influence of the model uncertainty. Theoretical analysis and simulation results show that the variable-parametermodel-based feedforward compensation method can obtain better performance than the traditional feedforward compensation.