Tuning of Digital PID Controllers Using Particle Swarm Optimization Algorithm for a CAN-Based DC Motor Subject to Stochastic Delays

被引：111
|
作者：
Qi, Zhi [1 ]
Shi, Qian [1 ]
Zhang, Hui [1 ,2 ]
机构：
[1] Beihang Univ, Sch Transportat Sci & Engn, Beijing 100191, Peoples R China
[2] Beihang Univ, Ningbo Inst Technol, Ningbo 315832, Peoples R China
来源：
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2020年 / 67卷 / 07期
基金：
中国国家自然科学基金;
关键词：
Controller area network (CAN); particle swarm optimization (PSO); proportional-integral-derivative (PID) tuning method; static output feedback (SOF); NETWORKED CONTROL-SYSTEMS; SPEED CONTROL; DESIGN; MODEL;
D O I：
10.1109/TIE.2019.2934030
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this article, we investigate the tuning problem of digital proportional-integral-derivative (PID) parameters for a dc motor controlled via the controller area network (CAN). First, the model of the dc motor is presented with its parameters being identified with experimental data. By studying the CAN network characteristics, we obtain the CAN-induced delays related to the load rate and the priorities. Then, considering the system model, the network properties, and the digital PID controller, the tuning problem of PID parameters for the CAN-based dc motor is transformed into a design problem of a static-output-feedback controller for a time-delayed system. To solve this problem, particle swarm optimization algorithm and linear-quadratic-regulator method are adopted by incorporating the sufficient condition of time-varying delay system. Finally, the effectiveness of the proposed PID tuning strategy is validated by experimental results.
引用
收藏
页码：5637 / 5646
页数：10
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