Abstract
The principal contribution of this paper is designed a general framework for an intelligent control system used in course angle control of remotely operated vehicle (ROV). A control scheme based on reinforcement learning (RL) agent combined with radial basis function (RBF) neural network control algorithm is applied. The effectiveness of the controller is demonstrated through simulations, and implementation issues are discussed. The control law is conceptually simple and computationally easy to implement.
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