A Particle Swarm Optimization Approach for Optimal Design of PID Controller for Temperature Control in HVAC

Particle swarm optimization (PSO) is a novel evolutionary algorithm which has a better convergence rate and computation precision compared with other evolutionary algorithms. From the perspective of optimization, the self-tuning of PID controller parameters is to find the best global optimum value in the solution space of Kp, Ki, Kd. In this paper an optimal design of PID controller based on particle swarm optimization approach for temperature control in HVAC is presented. The mathematical model of a HVAC system had been approximate near the operating point for the PSO algorithm to adjust PID parameters for the minimum integrated absolute error (IAE) condition. The results show that the adjustment of PID parameters has converted into the optimal point and the good control response based on the optimal values by the PSO technique.