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Eso‐Based Adaptive Robust Control of Dual Motor Driving Servo System
Author(s) -
Ren Xuemei,
Li Dongwu,
Sun Guofa,
Zhao Wei
Publication year - 2016
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1325
Subject(s) - control theory (sociology) , backlash , feed forward , servomechanism , control engineering , nonlinear system , computer science , servo , robust control , servo control , tracking error , controller (irrigation) , initialization , engineering , servo drive , state observer , servomotor , control system , control (management) , artificial intelligence , agronomy , physics , electrical engineering , quantum mechanics , biology , programming language
Based on extended state observer (ESO), we propose an adaptive robust control (ARC) for a dual motor driving servo system, in which there exist nonlinearities affecting control performance. To apply ESO and estimate the lumped uncertainty online, backlash and friction are analyzed and the nonlinear model of the plant is derived. We achieve several control objectives. First, the bias torque is considered in order to eliminate the effect of backlash. Second, the speed feedback is used to maintain the speed synchronization of motors. Then, to achieve feedforward control, finite‐time ESO is designed to estimate the unknown nonlinearities online. Furthermore, the ESO‐based adaptive robust controller is designed to guarantee L ∞ of tracking error by an initialization method, maintaining the transient performance of tracking behavior. Finally, extensive experimental results on a practical test rig validate the effectiveness of our proposed method.