Open Access Paper
12 November 2024 Optimization of parameters of fuzzy PID controller using grey wolf algorithm
Yinghui Dong, Zhanyou Ma, Jinyuan Ma, Shigang Li, Beibei Ding, Jiawei Zhang
Author Affiliations +
Proceedings Volume 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) ; 133950T (2024) https://doi.org/10.1117/12.3049213
Event: International Conference on Optics, Electronics, and Communication Engineering, 2024, Wuhan, China
Abstract
To enhance the precision of greenhouse air temperature regulation, this paper introduces an optimization approach for fuzzy Proportional-Integral-Derivative Controller (PID) control parameters utilizing the Grey Wolf Algorithm (GWO). Initially, a dynamic mathematical model for temperature control is formulated. Subsequently, GWA is employed to finetune the three key parameters of the fuzzy PID controller: proportional gain (Kp), gral gain (Ki) and derivative gain (Kd) thereby identifying the optimal controller settings. Further, the MATLAB/Simulink platform is leveraged to conduct comparative simulation studies against traditional PID control, fuzzy PID control, fractional-order PID control methodologies. The paper culminates with an evaluation of the improved GWA against other optimization techniques such as the Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Bat Algorithm (BA) for the parameter tuning of the fuzzy PID controller. The findings indicate that the fuzzy PID control system, refined through the enhanced GWO, exhibits swift response characteristics, minimal overshoot, commendable robustness, and robust stability.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yinghui Dong, Zhanyou Ma, Jinyuan Ma, Shigang Li, Beibei Ding, and Jiawei Zhang "Optimization of parameters of fuzzy PID controller using grey wolf algorithm", Proc. SPIE 13395, International Conference on Optics, Electronics, and Communication Engineering (OECE 2024) , 133950T (12 November 2024); https://doi.org/10.1117/12.3049213
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KEYWORDS
Fuzzy logic

Control systems

Temperature control

Mathematical optimization

Particle swarm optimization

Device simulation

Genetic algorithms

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