Title: Optimal Output Regulation for Model-Free Quanser Helicopter With Multistep Q-Learning
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| Authors: Luo, B; Wu, HN; Huang, TW
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| Author Full Names: Luo, Biao; Wu, Huai-Ning; Huang, Tingwen
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| Source: IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 65 (6):4953-4961; 10.1109/TIE.2017.2772162 JUN 2018
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| Language: English
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| Abstract: In this paper, the optimal output regulation problem is considered for the model-free 2-degree-of-freedom (2-DOF) helicopter. A multistep Q-learning (MsQL) method is developed with multistep policy evaluation. First, by introducing the Q-function, the optimal output regulation problem is converted to finding the optimal Q-function. Therefore, the MsQL algorithm is proposed and its convergence theory is established by showing that it generates a non-increasing Q-function sequence that converges to the optimal Q-function. In the MsQL, the step-size of multistep policy evaluation can be different at each iteration and an adaptive tuning rule is proposed. The MsQL learns the optimal Q-function by using real system data rather than using a system model. Finally, the developed MsQL method is employed to solve the optimal output regulation problem of the model-free 2-DOF helicopter, and its effectiveness is verified.
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| ISSN: 0278-0046
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| eISSN: 1557-9948
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| IDS Number: FW8WY
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| Unique ID: WOS:000425618900051*
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