文献类型：会议论文

英文题名：Optimal Tracking Control of the Ship Course System with Partially-unknown Dynamics

作者：Huang, Zhenkai[1];Zhuo, Yongqiang[1];Li, Tieshan[2]

机构：[1]Guangdong Ocean Univ, Nav Coll, Zhanjiang, Peoples R China;[2]Dalian Maritime Univ, Nav Coll, Dalian, Peoples R China

会议论文集：4th International Conference on Information, Cybernetics and Computational Social Systems (ICCSS)

会议日期：JUL 24-26, 2017

会议地点：Dalian, PEOPLES R CHINA

语种：英文

外文关键词：MATLAB - Iterative methods - Adaptive control systems - Navigation - Reinforcement learning - Riccati equations

外文摘要：In this paper, an online adaptive optimal controller is obtained by using the policy iteration (PI) based integral reinforcement learning (IRL) technique for the ship course tracking control the ship course-tracking system with partially unknown dynamics. The performance index is defined to be quadratic with respect to the state and control input to obtain the linear quadratic tracking algebraic Riccati equation (LQT ARE). The IRL technique is employed to solve the LQT ARE problem online without the need for complete knowledge of the system dynamics. The simulation results via Matlab verified the effectiveness of the algorithm.