The Permanent Magnet Linear Motor Control Based on Data-driven Control Theory

作     者：Rongmin Cao~(1,2),Huixing Zhou~1,Zhongsheng Hou~3 1.School of Industry,China Agricultural University,Beijing 100083,China 2.School of Automation,Beijing Information Science & Technology University,Beijing 100192,China 3.Advanced Control Systems Laboratory,Beijing Jiaotong University,Beijing 100044,China 

会议名称：《2010 Chinese Control and Decision Conference》

会议日期：2010年

学科分类：080801[工学-电机与电器] 0808[工学-电气工程] 08[工学] 

基　　金：supported General Program of Beijing Nature Science Foundation(3102013) science and technology project of Beijing Municipal Commission of Education KM200811232007 

关 键 词：Data-driven control Adaptive Predictive Control Model-free Adaptive Control Nonlinear Systems Linear Motor 

摘      要：正Data-driven control methods have no relations with any structural information,and it is designed only by the I/O data of the controlled *** model-free direct adaptive nonlinear predictive control（MFDANPC） algorithm of linearization of tight format of a class of SISO of a generalized predictive control（GPC） based on data-driven control theory is applied to permanent magnet linear motor speed and position *** design of controller is based directly on estimate and prediction of pseudo-partial-derivatives（PPD） derived on-line from the input and output information of the motor motion model using a novel parameter estimation algorithm,predicted by approach for multi-degree ***,validity and robustness against exogenous disturbance are proved for nonlinear systems with vaguely known dynamics by the simulation examples and real experiments.