Tuning and Retuning of PID Controller for Unstable Systems Using Evolutionary Algorithm

Abstract EN

Proportional + integral + derivative (PID) controllers are widely used in industrial applications to provide optimal and robust performance for stable, unstable, and nonlinear processes.

In this paper, particle swarm optimization (PSO) algorithm is proposed to tune and retune the PID controller parameter for a class of time-delayed unstable systems.

The proposal is to search the optimal controller parameters like Kp, Ki, and Kd by minimising the cost function.

The integral of squared error (ISE) criterion is considered as the cost function, which guides the PSO algorithm to get the optimised controller parameters.

The procedure for PID parameter tuning and retuning is presented in detail.

A comparative study is done with the conventional PID tuning methods proposed in the literature.

The simulation results show that the PSO-based PID controller tuning approach provides improved performance for the setpoint tracking, load disturbance rejection, error minimization, and measurement noise attenuation for a class of unstable systems.