Standoff tracking control of underwater glider to moving target

Abstract

The standoff tracking control of underwater glider to moving targets has non-negligible potentials in oceanic observations. To perform such operations, this study presents an integrated standoff tracking method that focuses on dealing with the coupled motions and under-actuated characteristics of the gliders as well as offsetting the dilemma caused by lacking of navigation system. The proposed approach contains guidance algorithm, basic controller, and reinforcement learning optimizer to improve the tracking accuracy. The verified simulation model for the OUC-III glider is utilized to develop the algorithm and evaluate the effectiveness of tracking. The adaptive navigation law called Lyapunov guidance vector field method generates the desired heading in this framework. The guidance only requires positioning information that is accessible through dead-reckoning. For the deficiency that the glider’s state controlled by the proportional integral differential controller can not immediately reach the required state, the reinforcement learning optimizer is introduced. The gliding status constitutes optimizer input while the compensating rotation signals are outputted to actuate the movable mass. The reward function of the optimizer is designed for maintaining the glider position error within 1 m with respect to the standoff circle. On this basis, the objective is set to maximize the rewards and consequently to guarantee the best accuracy. Three reinforcement learning algorithms are adopted and tested in our proposed framework. In the training phase, the training speeds of composite methods and pure reinforcement learning algorithms are compared. To test the stability, we design different types of moving targets, standoff radium and disturbance in the validation simulation, which have not appeared in the training. This study can provide patterns and solutions for the standoff tracking applications of underwater gliders. Also, it enlarges the glider’s scope of deployment based on the existing hardware.