PID controller configuration and tuning based on genetic algorithms

Abstract EN

In this work, the power of the Genetic Algorithms (GA) in searching for an optimal solution (in a pre-determined hyper space) is used to design the suitable configuration and parameters of the Proportional-Integral-Derivative (PID) controller.

In most industrial plants, the PID controllers are configured either in cascade, feedback or in feed forward topologies.

Besides, for each of these configurations the tuning gains have to be fixed in order to meet the required specifications.

Therefore, GA is utilized efficiently to select the proper PID configuration in the context of signal following approach as well as the best tuning gains for the selected configuration.

The proposed design procedure is applied to linear and nonlinear plants.

It reflects a tremendous design results that heavily relied on computer to get the required controller.