A NEURAL NET CONTROLLER FOR UNDERWATER ROBOTIC VEHICLES

Underwater robotic vehicles have become an important tool to explore the secret life undersea. They are used for various purposes: Inspection, recovery, construction, etc. With the increased utilization of the vehicles in subsea applications, the development of autonomous vehicles becomes highly desirable to enhance operator efficiency. However, engineering problems associated with the high density, nonuniform, and unstructured seawater environment and the nonlinear response of the vehicle make a high degree of autonomy difficult to achieve. In this paper, results of the recent study on the application of neural networks to the underwater robotic vehicle control system are presented. The robustness of the control system with respect to the nonlinear dynamic behavior and parameter uncertainties is investigated by computer simulation. The results show the feasibility of using neural networks to control the vehicle in the presence of unpredictable changes in the dynamics of the vehicle and its environment. © 1990 IEEE