Study of optimization methods for tunning SOFC gains for manipulator control

Abstract

A comparative study of the performance of three optimization techniques, namely Cuckoo Search Algorithm (CSA), Flower Pollination Algorithm (FPA) and Genetic Algorithm (GA), is presented in this paper for tuning the gains of Self Organizing Fuzzy Controller (SOFC) applied to a two link planar rigid robotic manipulator. SOFC is an intelligent adaptive fuzzy logic control technique generally used to control nonlinear, non-stationary and time-varying complex systems. A multi-input multi-output complex structure, two-link planar rigid robotic manipulator with end-effector has been considered for study in servo as well as the regulatory problems. Based on the trajectory tracking and disturbance rejection performances efficiency of algorithms has been accessed and it has been found that CSA outperformed than FPA and GA.