Open AccessRemote parameters tuning system based on simplex‐search‐based model‐free optimisation for motor speed control
Author(s) -
Kong Xiangsong,
Tang Zeyu,
Zhu Yisheng,
Xiao Yining,
Shen Qinghang,
Jiang Shaobo
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9217
Subject(s) - computer science , matlab , process (computing) , control engineering , control system , simplex algorithm , computation , electronic speed control , control (management) , control theory (sociology) , engineering , artificial intelligence , algorithm , linear programming , electrical engineering , operating system
Motor is a very widely used control device in industry. The performance of a motor speed control system is very critical for its application. The control performance can be improved through control parameters tuning. However, the parameters tuning process is difficult to implement online automatically. The traditional parameters tuning methods for a motor control system are usually experience‐based, cumbersome and time‐consuming. In this study, taking advantage of the high computation ability of the MATLAB, a remote motor control system framework based on the wireless network was proposed. The simplex‐search‐based model‐free optimisation (MFO) was developed based on the MATLAB platform to optimise the control parameters. With this optimisation methodology, the performance of the control system can be improved iteratively by directly using measurements of the control performance online. This system has been realised and tested systematically. The effectiveness and the efficiency have been demonstrated by a series of experiments.