A control design of robotics using the genetic algorithm

Abstract

This paper presents a new and practical method for a control design of a robotic system. In general, actuators in robotic systems are set with gears whose characteristics are elastic. Since a state feedback-type digital controller is usually used for such a robotic system, the design of the feedback gain of the controller is important, because undesirable vibrations or an overshoot in responses occur for high gains. Therefore the desired response, the output of a reference model, is designed first, and the feedback gains are determined so that the response will coincide with the desired response, which is an optimization problem. The gradient method works to some extent, but it takes a long time to get a satisfactory result. Thus we applied the genetic algorithm (GA) to this nonlinear optimization problem, which gave the very first convergence. The gains obtained have many useful applications. The results of a simulation are also given.