Research on PID Parameter Tuning Based on SIMCDE-RBF Algorithm

Aiming at large delay characteristics of the temperature control system, a radial basis function (RBF) method of superior and inferior mutation crossover strategies with storage mechanism differential evolution algorithm (SIMCDE) is proposed to tune and optimize the PID controller. The differential evolution algorithm introduces superior and inferior mutation strategies with storage mechanisms and superior and inferior crossover strategies, effectively avoiding the local optimal solutions. Then, the SIMCDE algorithm optimizes the initial parameters of RBF, and the gradient information is obtained by RBF online identification. Finally, three parameters of PID are adjusted online according to gradient information. Solving four test functions shows that the SIMCDE-RBF algorithm has good optimization ability. The simulation experiment of SIMCDE-RBF algorithm tuning PID parameters and the test of temperature control of heating furnace in a dairy company show that compared with IDE-RBF-PID, GODE-RBF-PID, and MCOBDE-RBF-PID, SIMCDE-RBF-PID has better dynamic performance, more robust anti-interference performance, and higher control accuracy.

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Publication Details

Journal
Automatic Control and Computer Sciences
Published
2025-04-01
DOI
https://doi.org/10.3103/s0146411625700142
Primary Topic
Advanced Sensor and Control Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Research on PID Parameter Tuning Based on SIMCDE-RBF Algorithm

Liu Yueting, Weihua Meng
Automatic Control and Computer Sciences
Advanced Sensor and Control Systems
article

Research on PID Parameter Tuning Based on SIMCDE-RBF Algorithm

Liu Yueting, Weihua Meng
article en

Abstract

Aiming at large delay characteristics of the temperature control system, a radial basis function (RBF) method of superior and inferior mutation crossover strategies with storage mechanism differential evolution algorithm (SIMCDE) is proposed to tune and optimize the PID controller. The differential evolution algorithm introduces superior and inferior mutation strategies with storage mechanisms and superior and inferior crossover strategies, effectively avoiding the local optimal solutions. Then, the SIMCDE algorithm optimizes the initial parameters of RBF, and the gradient information is obtained by RBF online identification. Finally, three parameters of PID are adjusted online according to gradient information. Solving four test functions shows that the SIMCDE-RBF algorithm has good optimization ability. The simulation experiment of SIMCDE-RBF algorithm tuning PID parameters and the test of temperature control of heating furnace in a dairy company show that compared with IDE-RBF-PID, GODE-RBF-PID, and MCOBDE-RBF-PID, SIMCDE-RBF-PID has better dynamic performance, more robust anti-interference performance, and higher control accuracy.

Automatic Control and Computer SciencesVol. 59(2)
Lanzhou University of Technology (CN), Shanghai Xiandai Architectural Design (CN), Jiangsu Provincial Architectural Design and Research Institute (China) (CN), Lanzhou University (CN)
Openalex Percentile: Top 82%
Advanced Sensor and Control Systems
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