Fuzzy-genetic optimal control for robotic systems

Abstract

In this paper, we present optimal control for movement and trajectory planning of a various degrees-of-freedom robots using fuzzy logic (FL) and genetic algorithms (GAs). We have evaluated and shown comparative analysis for three degree-of-freedom (3 DOF) and four degree-of-freedom (4 DOF) robotics arm to compensate the uncertainties like; Movement, friction and settling time in robotic arm movement. This paper describes genetic algorithms, which is designed to optimize robot movement and trajectory. Though the model represents is a general model for redundant structures and could represent any n-link structures. Results shows optimal angular movement of joints, it converges too quickly even if the population is very large. The result also shows the complete trajectory planning with FL and GAs and also demonstrating the flexibility of this technique.   Key words: Inverse kinematics, genetic algorithms (GAs), fuzzy logic (FL), robotic arm.