Abstract
In this paper, an online adaptive dynamic programming (ADP) scheme is proposed to achieve the optimal regulation control of navigation control systems subject to time delays with input constraints. The optimal control strategy is developed in virtue of Lyapunov theories and neural networks (NNs) techniques. From a robust control perspective, we investigate the stability on navigation time delay systems concerning input constraints by means of linear matrix inequalities (LMIs) and set up the optimal control policy, on which basis that a novel NN-based approach is proposed. A single NN is used to estimate the performance function, the constrained control and consequently the optimal control policy with the weights online tuned. Finally, numerical examples are demonstrated to illustrate our results.
This research was supported in part by the National Natural Science Foundation of China under Grant 61603179, in part by the China Postdoctoral Science Foundation under Grant 2016M601805, and in part by the Fundamental Research Funds for the Central Universities under Grant NJ20170005.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Zhu, J., Hou, Y. (2019). Optimal Control of Navigation Systems with Time Delays Using Neural Networks. In: Zhai, X., Chen, B., Zhu, K. (eds) Machine Learning and Intelligent Communications. MLICOM 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 294. Springer, Cham. https://doi.org/10.1007/978-3-030-32388-2_60
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