Abstract
An intelligent robust disturbance rejection controller is designed for Unmanned Aerial Vehicle (UAV) which is highly nonlinear, and uncertain model, strong coupling and affected by variable interference. In order to design Linear Extended State Observer (LESO), the system is extended by one dimension. Design LESO to estimate the internal and external disturbances of the system. Since the LESO estimation error of the total disturbance cannot be compensated, an intelligent robust disturbance rejection controller is proposed. H∞ control theory proves the stability of the designed intelligent robust disturbance rejection control system. What is more, a Deep Reinforcement Learning (DRL) algorithm is incorporated to strengthen the transient performance of the system. A simulation example verifies the adaptability of the control strategy.
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Huang, H., Xu, F., Cheng, H., Guo, Y., Xu, S. (2022). Intelligent Robust Disturbance Rejection Control via Deep Reinforcement Learning. In: Wu, M., Niu, Y., Gu, M., Cheng, J. (eds) Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021). ICAUS 2021. Lecture Notes in Electrical Engineering, vol 861. Springer, Singapore. https://doi.org/10.1007/978-981-16-9492-9_218
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DOI: https://doi.org/10.1007/978-981-16-9492-9_218
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