Discrete Adaptive Control with Multiple-Step-Guess Estimation for Brushless DC Motor
Guirong Shao*1,*2, Minling Zhu*3,, Hongbin Ma*1, and Xinghong Zhang*4
*1Beijing Institute of Technology
5 South Zhongguancun Street, Haidian District, Beijing 100081, China
*2Department of Physics and Electronic Engineering, Yuncheng University
No.1155 Fudan West Street, Yanhu District, Shanxi 044000, China
*3Beijing Information Science and Technology University
No.35 Beisihuan Middle Road, Chaoyang District, Beijing 100101, China
*4Henan Institute of Technology
No.699 Pingyuan Road, Xinxiang 453003, China
The brushless DC motor (BLDCM) speed control system has various kinds of uncertainties, such as reference speed mutation, noise and parameters change, etc. However, proportional integral (PI) control method used widely cannot handle the uncertainties in the control system well. A novel discrete adaptive control with Multiple-Step-Guess (MSG) estimation for BLDCM speed control system is proposed in this contribution. MSG estimation is firstly developed and applied in BLDCM speed control system, which estimate the BLDCM model parameters online with only five steps history information sampled from the input signal and output signal. The tracking adaptive control law is designed to ensure the speed can track reference speed rapidly and accurately. Compared with PI control and recursive least square adaptive control (RLSAC), extensive simulations verify that the BLDCM speed response under MSG adaptive control (MSGAC) has better dynamic and steady state performance in the case of reference speed mutation and BLDCM parameters change. Simulation results illustrate that the novel proposed method is effective and robust for uncertainties of BLDCM speed control system.
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