Multi-Scenario Multi-Objective Optimization of a Fuzzy Motor Controller for the Szabad(ka)-II Hexapod Robot

Abstract

The aim of this research was to develop a robust motor controller for the Szabad(ka)-II hexapod robot.A Fuzzy-PI controller that utilized a lookup table was chosen because of its reported promising performance and its ability to be embedded in the microcontrollers of the robot.The variables of the controller were defined by a particle swarm optimization method to minimize the five quality objectives related to the walking of the robot.The preferences of the five objectives were successfully expressed by a biasedweighted geometric mean utility function.The resulting optimal solutions were significantly altered by changing the bias and exponential weights of preferences.Therefore, we checked the robustness of the solution against the controller's variables as a secondary objective.