Based on simulated annealing (SA) and reinforcement learning (RL) algorithm, a hybrid intelligent controller is proposed to ship steering. The SA algorithm is a powerful way to solve hard combinatorial optimization problems, which is used to adjust the parameters of the controller in this paper. The RL algorithm shows its particular superiority in ship steering, which just needs simple fuzzy information. With the advantages of the two algorithms, the controller can overcome the influence of the wind, wave and flow, the limitation that data are not exactly accurate. At last, the results of the simulation show that the ship course can be properly controlled when changeable wind, wave, and measure error exists.
Zhao-Heng Yin, Changhao Wang, Luis A. Pineda, Francois R. Hogan, Krishna Bodduluri, Akash Sharma, Patrick Lancaster, I Devi Vara Prasad, Mrinal Kalakrishnan, Jitendra Malik, Mike Lambeta, Tingfan Wu, Pieter Abbeel, Mustafa Mukadam
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