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

• Published in: IEEE transactions on industrial electronics (1982) Vol. 67; no. 7; pp. 5637 - 5646
• Main Authors: Qi, Zhi, Shi, Qian, Zhang, Hui
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Controller area network; Controller area network (CAN); D C motors; DC motors; Delays; Feedback control; Linear quadratic regulator; Mathematical model; Mathematical models; Optimization algorithms; Output feedback; Parameter identification; Particle swarm optimization; particle swarm optimization (PSO); Product design; Proportional integral derivative; proportional-integral-derivative (PID) tuning method; Stability analysis; static output feedback (SOF); Stochastic processes; Time delay systems; Tuning; Velocity control
• ISSN: 0278-0046; 1557-9948
• DOI: 10.1109/TIE.2019.2934030

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.