Abstract
This paper investigates the optimal performance control problem for the trajectory tracking control for a stratospheric airship with external disturbance. A reinforcement learning adaptive tracking control for a stratospheric airship is proposed. First, according to the knowledge of dynamics and kinematics, we establish the model of a stratospheric airship used in this paper. Then, to solve external disturbance problem and enhance the system performance, a controller is proposed by means of a reinforcement learning (RL) method that is primarily based on two neural networks (NNs). In the last place, the stability analysis and numerical simulations are given to verify that the designed controller is effective.
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Acknowledgments
This work was supported by Beijing Natural Science Foundation (No.4202038) and Fundamental Research Funds for the Central Universities (No. YWF-20-BJ-J-419).
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Wang, K., Liu, Y., Zheng, Z., Zhu, M. (2021). Reinforcement Learning Adaptive Tracking Control for a Stratospheric Airship. In: Jia, Y., Zhang, W., Fu, Y. (eds) Proceedings of 2020 Chinese Intelligent Systems Conference. CISC 2020. Lecture Notes in Electrical Engineering, vol 705. Springer, Singapore. https://doi.org/10.1007/978-981-15-8450-3_56
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DOI: https://doi.org/10.1007/978-981-15-8450-3_56
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