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Trajectory Tracking Control for Under-Actuated Hovercraft Using Differential Flatness and Reinforcement Learning-Based Active Disturbance Rejection Control

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Abstract

This paper proposes a scheme of trajectory tracking control for the hovercraft. Since the model of the hovercraft is under-actuated, nonlinear, and strongly coupled, it is a great challenge for the controller design. To solve this problem, the control scheme is divided into two parts. Firstly, we employ differential flatness method to find a set of flat outputs and consider part of the nonlinear terms as uncertainties. Consequently, we convert the under-actuated system into a full-actuated one. Secondly, a reinforcement learning-based active disturbance rejection controller (RL-ADRC) is designed. In this method, an extended state observer (ESO) is designed to estimate the uncertainties of the system, and an actorcritic-based reinforcement learning (RL) algorithm is used to approximate the optimal control strategy. Based on the output of the ESO, the RL-ADRC compensates for the total uncertainties in real-time, and simultaneously, generates the optimal control strategy by RL algorithm. Simulation results show that, compared with the traditional ADRC method, RL-ADRC does not need to manually tune the controller parameters, and the control strategy is more robust.

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Authors and Affiliations

  1. School of Automation, Beijing Institute of Technology, Beijing, 100190, China

    Xiangyu Kong, Yuanqing Xia, Rui Hu, Min Lin, Zhongqi Sun & Li Dai

Authors
  1. Xiangyu Kong
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  2. Yuanqing Xia
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  3. Rui Hu
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  4. Min Lin
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  5. Zhongqi Sun
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  6. Li Dai
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Corresponding author

Correspondence to Yuanqing Xia.

Additional information

This paper was supported by the National Natural Science Foundation of China under Grant No. 61720106010.

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Kong, X., Xia, Y., Hu, R. et al. Trajectory Tracking Control for Under-Actuated Hovercraft Using Differential Flatness and Reinforcement Learning-Based Active Disturbance Rejection Control. J Syst Sci Complex 35, 502–521 (2022). https://doi.org/10.1007/s11424-022-2037-0

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  • DOI: https://doi.org/10.1007/s11424-022-2037-0

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