Yan Zhang, Hongtao Dang, Yingqi Tang
School of Electronic Information, Xijing University, Shanxi, Xi’an 710123, China
In the process of performance testing of precision devices in the aerospace field, it is difficult to apply the traditional PID control to the high-precision incubators, which is unable to achieve the ideal control accuracy. For this problem, fuzzy PID is optimized by using nonlinear piecewise Logistic chaos mapping to initiate particle group, optimize the parameters of ACPSO-Fuzzy-PID and introduce shrinkage factor to ensure the convergence of the algorithm, making the overall and local search capability of particle group more efficient. Firstly, the algorithm was tested by standard functions, and finally, PID, fuzzy PID, PSO-Fuzzy-PID, ACPSO-Fuzzy-PID were contrast simulated by SIMULINK at a constant temperature of 75℃. Simulation results show that the ACPSO-Fuzzy-PID control system has faster response time, less overshoot, shorter adjustment time, temperature control fluctuation more stable and stronger anti-disturbance ability, which significantly improves the temperature control accuracy of the incubator in the aerospace field.
Logistic mapping, Acpso, Fuzzy pid, Contraction factor, Chaos initialization, Adaptive adjustment
Yan Zhang, Hongtao Dang, Yingqi Tang. Research on Temperature Control of Incubator Based on Chaotic Particle Swarm Optimization and Fuzzy PID. International Journal of Frontiers in Engineering Technology (2022), Vol. 4, Issue 7: 21-25. https://doi.org/10.25236/IJFET.2022.040705.
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