PID Parameter Optimization of Temperature Control for Plastic Extruder Based on ISA‐PSO Algorithm

In order to improve the control accuracy of the temperature control system for the plastic extruder and better achieve optimal control between the parameter settings and the temperature of the plastic extruder, an intelligent algorithm combining improved simulated annealing (ISA) algorithm and parti...

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Published inModelling and Simulation in Engineering Vol. 2025; no. 1
Main Authors Ji, Peng-fei, Zhang, Tian-Peng, Li, Yang, Lu, Chao
Format Journal Article
LanguageEnglish
Published New York John Wiley & Sons, Inc 01.01.2025
Wiley
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Abstract In order to improve the control accuracy of the temperature control system for the plastic extruder and better achieve optimal control between the parameter settings and the temperature of the plastic extruder, an intelligent algorithm combining improved simulated annealing (ISA) algorithm and particle swarm optimization (PSO) algorithm is studied. This algorithm is utilized to achieve automatic optimization of the PID parameters of the temperature control system, thereby making parameter optimization faster and more accurate. The benchmark test function was employed to evaluate the performance of the improved PSO (IPSO) algorithm, genetic algorithm improved PSO (GA‐PSO), simulated annealing PSO (SA‐PSO), and ISA‐PSO. The results demonstrated that the ISA‐PSO algorithm possesses stronger global optimization capability and superior convergence performance. Finally, MATLAB simulation and experimental test results indicate that, compared to the control effects of IPSO, GA‐PSO, and SA‐PSO, the PID controller optimized by the ISA‐PSO algorithm exhibits better accuracy and robustness. The temperature fluctuation of the charging barrel is significantly reduced, with the maximum value of the absolute temperature deviation being only 0.6°C and the average value of the absolute temperature deviation being approximately 0.35°C. This effectively enhances the accuracy and robustness of the temperature control system for the plastic extruder.
AbstractList In order to improve the control accuracy of the temperature control system for the plastic extruder and better achieve optimal control between the parameter settings and the temperature of the plastic extruder, an intelligent algorithm combining improved simulated annealing (ISA) algorithm and particle swarm optimization (PSO) algorithm is studied. This algorithm is utilized to achieve automatic optimization of the PID parameters of the temperature control system, thereby making parameter optimization faster and more accurate. The benchmark test function was employed to evaluate the performance of the improved PSO (IPSO) algorithm, genetic algorithm improved PSO (GA‐PSO), simulated annealing PSO (SA‐PSO), and ISA‐PSO. The results demonstrated that the ISA‐PSO algorithm possesses stronger global optimization capability and superior convergence performance. Finally, MATLAB simulation and experimental test results indicate that, compared to the control effects of IPSO, GA‐PSO, and SA‐PSO, the PID controller optimized by the ISA‐PSO algorithm exhibits better accuracy and robustness. The temperature fluctuation of the charging barrel is significantly reduced, with the maximum value of the absolute temperature deviation being only 0.6°C and the average value of the absolute temperature deviation being approximately 0.35°C. This effectively enhances the accuracy and robustness of the temperature control system for the plastic extruder.
Audience Academic
Author Ji, Peng-fei
Zhang, Tian-Peng
Lu, Chao
Li, Yang
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Copyright © 2025 Peng-fei Ji et al. Modelling and Simulation in Engineering published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License (the “License”), which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. https://creativecommons.org/licenses/by/4.0
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SubjectTerms Accuracy
Agricultural production
Algorithms
Artificial intelligence
Control equipment
Control systems
Controllers
Cooling
Deep learning
Fuzzy logic
Mathematical optimization
Neural networks
Optimization
Temperature control
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Title PID Parameter Optimization of Temperature Control for Plastic Extruder Based on ISA‐PSO Algorithm
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