Tuning digital PID controllers for discrete-time system by Election Campaign Optimization algorithm

Abstract

In this paper, Election Campaign Optimization algorithm is applied to solve the difficulty in PID control that the tuning parameters of PID controllers could not be determined well by conventional methods. Tuning PID controller parameters is a typical three variable optimization problem without constraint condition. An example is employed to test this method, It is found that the method could be find the best parameters that can bring on a optimal control performance, the simulation results is better than that in involved reference. This indicates that the tuning method is feasible.

Derivative-Free Direct Search Optimization Method for Enhancing Performance of Analytical Design Approach-Based Digital Controller for Switching Regulator

“…Reference [13] suggested the dynamic PSO (dPSO)-based optimization of digital fractional order PID (FO-PID) controller applied to the buck converter fed DC motor for optimal speed control. Similarly, optimization techniques such as PSO was employed for optimizing the parameters of the fuzzy controller applied to the Quasi-Z Source converter [14] and for fine-tuning digital PID controller parameters [15]; the magnitude optimum criterion for developing explicit analytical tuning rules for digital PID controllers [16]; the genetic optimization scheme for improving a single-input fuzzy PID controller for the buck regulator [17]; the election campaign optimization algorithm for tuning digital PID controllers for the discrete-time system [18]; the gradient descent method for refining the digital control law for ac-to-dc converters to achieve unity power factor [19]. Similarly, in Reference [20], different swarm intelligence-based optimization techniques (i.e., an artificial bee colony, cuckoo search, etc.)…”