Abstract
In this paper, a finite-horizon optimal tracking control scheme is proposed for a class of nonlinear discrete-time switched systems. First, via system transformation, the optimal tracking problem is converted into designing an optimal regulator for the tracking error dynamics. Then, with convergence analysis in terms of value function and control policy, the iterative adaptive dynamic programming algorithm is introduced to obtain the finite-horizon optimal tracking controller which makes the value function close to its optimal value function. Finally, the effectiveness of the proposed control method is demonstrated using a simulation example.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China (U1504615), the He’nan Postdoctoral Science Foundation funded project (2014039), the Science and Technology Development Program of He’nan Province (172102210190, 162102210401, 162102210022), the China Postdoctoral Science Foundation funded project (2015M572103), and the Scientific Research Key Foundation of Higher Education Institutions of He’nan Province (16A413001, 16A413002).
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Qin, C., Liu, X., Liu, G., Wang, J., Zhang, D. (2017). Finite Horizon Optimal Tracking Control for Nonlinear Discrete-Time Switched Systems. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, ES. (eds) Neural Information Processing. ICONIP 2017. Lecture Notes in Computer Science(), vol 10634. Springer, Cham. https://doi.org/10.1007/978-3-319-70087-8_82
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DOI: https://doi.org/10.1007/978-3-319-70087-8_82
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