Study on Model Identification for Predictive Control of Boiler Superheated Steam Temperature Model based on Improved Gray Wolf Optimizer

Jianjun Zhu; Binghong Wei

doi:10.6919/ICJE.202412_10(12).0017

Authors

Jianjun Zhu
Binghong Wei

DOI:

https://doi.org/10.6919/ICJE.202412_10(12).0017

Keywords:

Temperature; Gray Wolf Optimizer; Particle Swarm Algorithm; Model Identification; Model Predictive Control.

Abstract

For the boiler superheated steam temperature control system there is a large inertia, large time lag caused by the traditional control method of control accuracy is not high, put forward a fusion of multi-strategy to improve the Gray wolf optimizer to identify the temperature model of the model predictive controller, MATLAB simulation verification, to build a semi-physical simulation platform, through the OPC communication connection between MATLAB and PCS7, and then on the SMPT-1000 Boiler superheated steam temperature control system for experimental verification, the experimental results show that the fusion of multi-strategy to improve the Gray wolf optimizer to identify the temperature model model than other algorithms accuracy method is higher, faster, and the model predictive control of the control indexes are better than the PID control.

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