Paper
5 June 2024 Design and validation of industrial equipment based on MPC-PID control
Zhiyuan Zhou, Yi Bao, Ruoxiao Qin
Author Affiliations +
Proceedings Volume 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024); 1316309 (2024) https://doi.org/10.1117/12.3030647
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 2024, Xi'an, China
Abstract
The issues of low temperature control accuracy and poor stability in industrial water temperature control systems are addressed in this article. A PID-based temperature control system that combines Model Predictive Control (MPC) with PID control is proposed. A simulation system for water temperature control is designed using Simulink, and adaptive tuning of PID parameters is implemented. In the process of constructing the experimental platform, temperature changes are controlled by driving the hot and cold valves with a temperature control board. It is demonstrated that high temperature control accuracy, fast heating rate, and good stability are achieved by the proposed system, thus meeting the temperature control requirements of the system. The physical model and linearized model of an industrial boiler are introduced, and the discretization of the model and its improvements are discussed. Additionally, the working principles of the PID control algorithm and MPC module are outlined, and experimental results and analysis are presented.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Zhiyuan Zhou, Yi Bao, and Ruoxiao Qin "Design and validation of industrial equipment based on MPC-PID control", Proc. SPIE 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 1316309 (5 June 2024); https://doi.org/10.1117/12.3030647
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Temperature control

Control systems

Design

Data modeling

Matrices

Systems modeling

Chemical process control

Back to Top