Takagi-Sugeno-Kang fuzzy PID control for DC electrical machines

Abstract

This paper deals with Takagi-Sugeno-Kang (TSK) type fuzzy PID controllers in the context of nonlinear dynamic systems. The design framework for tuning the controller gains depends on particle swarm optimization (PSO), assuming the nonlinear system approximated by an artificial neural network, leading to an overall robust control methodology based on TSK fuzzy PID control. Obtained data and information from simulations and experimental tests considering a nonlinear dynamic process including a DC electrical machine confirm the effectiveness of the control strategy.