Research on Fuzzy PID Intelligent Agricultural Temperature Control System Based on PSO Optimization

摘要

Aiming at the problems of nonlinearity, large lag and difficulty in parameter tuning of traditional PID control in intelligent agricultural greenhouse environment, a Fuzzy PID control strategy based on Particle Swarm Optimization (PSO) is proposed. Firstly, the mathematical model of the greenhouse temperature control system is established, and the characteristics of large inertia and pure lag are analyzed. Secondly, a fuzzy PID controller is designed. A PSO optimization model with ITAE (Integral of Time-weighted Absolute Error) as the fitness function is constructed to globally optimize the quantization factors and scaling factors of the fuzzy controller, solving the defects of subjectivity and local optimum in manual parameter tuning. Finally, simulation models of traditional PID, fuzzy PID and PSO-fuzzy PID control systems are built in MATLAB/Simulink. The simulation results show that, compared with the traditional PID control, the overshoot of the fuzzy PID control system optimized by PSO has decreased from 4.5% to 0, and the regulation time has been shortened from 481 seconds to 326 seconds. This significantly improves the dynamic response speed and steady-state accuracy of the system. This research provides an effective technical path for solving the nonlinear and time-delay problems in the environmental control of agricultural greenhouses.