Optimization of ROV Control Based on Genetic Algorithm

Abstract

In order to make the ROV more adaptive, a new control method, with the optimization of ROV control based on genetic algorithm, is proposed in this paper. Genetic algorithm(GA) is used to adjust the fuzzy control in the complicated environment, indirectly changing the fuzzy control membership function size. Thus, we can make the fuzzy control rules adjustable. This method enhances the self-learning ability and robustness of fuzzy PID. On the basis of proposed control theory, we developed an open-shelf remote operated vehicle(ROV). The ROV is equipped with four 260W brushless underwater motors. Out of the four motors, two are vertically fitted and the other two are horizontally fitted. The former two motors take the role of going up and down while the later two motors are designed to take responsibility for steering. Both numerical stimulation and in water experiments proves the proposed method provides a new idea for the automatic control of underwater robots.