GWO-Based Optimal Tuning of Controllers for Shape Memory Alloy Wire Actuators

Abstract

The purpose of this paper is to design the optimal controllers for nonlinear processes with Shape Memory Alloy (SMA) wire actuators viewed as controlled processes. Optimal process models are first derived. A comparative analysis is done between the evolved Takagi-Sugeno-Kang (TSK) fuzzy models of SMA wire actuators, two linear dynamic system models with parameters optimally tuned using the recent metaheuristic Grey Wolf Optimiser (GWO) algorithm and one linear dynamic system model obtained in a previous paper using the System Identification Toolbox. Measured input-output data is involved in this comparison. The parameters of two Proportional-Integral-Derivative controllers, a type-1 fuzzy controller and an interval type-2 fuzzy controller are next optimally tuned using GWO, and a comparative analysis of these linear and nonlinear controllers is done. The simulation results illustrate that the type-2 fuzzy controller ensure good performance for these processes.