Parametric Data-driven Control Method of Hybrid System via Virtual Reference Feedback Tuning
作者单位：School of AutomationHarbin University of Science and Technology Department of Electrical Engineering and AutomationAalto University
会议名称：《第36届中国控制会议》
主办单位：Chinese Acad Sci;Acad Math & Syst Sci;China Soc Ind & Appl Math;Liaoning Assoc Automat;Shenyang Univ Chem Technol;Liaoning Univ Sci & Technol;Asian Control Assoc;IEEE Control Syst Soc;Inst Control Robot & Syst;Soc Instrument & Control Engineers;Chinese Assoc Automat;Tech Comm Control Theory;Syst Engn Soc China;Dalian Univ Technol
会议日期：2017年
学科分类：08[工学] 0802[工学-机械工程] 0835[工学-软件工程] 080201[工学-机械制造及其自动化]
基 金：supported by the Academy of Finland under Grant 135225 Finnish Funding Agency for Technology and Innovation(TEKES)
关 键 词：hybrid system data-driven control global model reference optimization parameterized controller design
摘 要：This paper presents a data-driven method to design parameterized controller for a class of hybrid *** method relies on the virtual reference feedback tuning（VRFT） that is ongoing does not derive any detailed model knowledge of hybrid *** other model-based control methods,the VRFT method direct use of the measurement I/O data and select desired controllers by employing optimization tools from virtual reference ***,the optimal variables are directly as the control parameters of the hybrid *** improve the efficiency of control parameter optimization,a particle swarm optimization（PSO） algorithm with a ε-dominance strategy is used to implement the developed *** addition,the effectiveness of the method is demonstrated experimentally on a leader-following tracking task of multiple unmanned aerial vehicles（multi-UAVs） formation flight.