Research on Temperature Control Method of Variable Structure Thermoelectric Furnace Based on Fuzzy PID Optimized by Genetic Algorithm
The working condition of the variable structure differential temperature furnace varies with the size of the rolls being processed, and it is a nonlinear time-varying system with hysteresis and other shortcomings. The traditional PID will produce serious overshoot and vibration in the process of tem...
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Published in | 2022 2nd International Conference on Electrical Engineering and Control Science (IC2ECS) pp. 716 - 720 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
Published |
IEEE
16.12.2022
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Subjects | |
Online Access | Get full text |
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Summary: | The working condition of the variable structure differential temperature furnace varies with the size of the rolls being processed, and it is a nonlinear time-varying system with hysteresis and other shortcomings. The traditional PID will produce serious overshoot and vibration in the process of temperature control. In order to improve the control effect, this paper proposes to use genetic algorithm to optimize the fuzzy PID controller. Fuzzy control is used to adjust PID parameters adaptively, and genetic algorithm is used to automatically optimize the fuzzy rules, membership function types and shapes of the fuzzy controller. The comparison experiment demonstrates that the fuzzy PID controller based on genetic algorithm optimization has better control effect. The time to the steady state with this method is also shorter than with the other two and the overshoot is significantly reduced. In addition, no undershoot is generated and the convergence to the steady state does not produce fluctuations. |
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DOI: | 10.1109/IC2ECS57645.2022.10088146 |