Whale Optimization Algorithm-Based Tuning of Low-Cost Fuzzy Controllers with Reduced Parametric Sensitivity

This paper proposes a novel application of Whale Optimization Algorithm (WOA) as solution for solving a complex control design and tuning problem concerning fuzzy control systems that control processes modeled as second-order servo systems with an integral component and variable parameters. The minimization of objective functions containing the error of the controlled process and the output sensitivity functions of the sensitivity models defined with respect to the parametric variations of the controlled process (the servo system) defines the optimization problem. WOA is integrated with the aim of obtaining optimal controller parameters therefore obtaining a new generation of Takagi-Sugeno-Kang proportional-integral fuzzy controllers. For this, a design method is defined and experimentally validated with the aid of a laboratory nonlinear servo system.