Research on Temperature Control System Based on IPSO Optimized Fuzzy PID

Abstract

The air source heat pump heat collection control system is a system with strong nonlinearity and large time delay. It is difficult to achieve the expected control effect on the outlet water temperature by using conventional control algorithms. In view of this problem, this paper makes up for the shortcomings of fuzzy control and PID control, and proposes an improved particle swarm optimization (IPSO) fuzzy PID control strategy to control the temperature of the effluent of the air source heat pump heat collection control system. First of all, the particle swarm optimization algorithm is easy to fall into the problem of local optimization. By increasing the vector, the optimal position of individual particles is stored to increase the range of particle search. Then use the improved particle swarm algorithm to optimize the fuzzy PID scale factor and quantization factor to modify the PID parameters in real time to improve the control accuracy of the heat pump system. Finally, a MATLAB / Simulink simulation model for the heat collection temperature control of the heat pump is established and an improved particle swarm optimization algorithm program is written, and compared with the fuzzy PID and conventional PID control algorithms. Simulation results show that the heat-collection control system based on IPSO has strong adaptability, robustness and anti-interference.