Highlights A static inertial-matrix free attitude controller is designed to guarantee the tracking performance of the spacecraft. A reinforcement learning based parameter tuning scheme is developed to optimize controller gain adaptively. The preassigned tracking performance is achieved under the learning based adaptive attitude controller.

    Abstract This paper investigates the attitude tracking control problem of a rigid spacecraft subject to inertial uncertainties, uncertain space perturbations and actuator saturation. Firstly, a static inertial-matrix free attitude controller is designed to guarantee the appointed-time convergence and tracking accuracy indicators of the spacecraft. Then, two-layer critic-action NNs are used to tune and optimize the control gains adaptively to improve the robustness and tracking performance of the devised static attitude controller via exploring the reinforcement learning (RL) technique. Compared with the existing attitude control methods, the prominent advantage of our work is that the devised controller is inertial-matrix free with a simple RL-based adaptive parameter tuning scheme, which reduces the conservativeness of the traditional attitude controllers with fixed control gains and is also easy to be achieved. Finally, two groups of illustrative examples are organized to validate the effectiveness of the proposed attitude control method.


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    Title :

    On adaptive attitude tracking control of spacecraft: A reinforcement learning based gain tuning way with guaranteed performance


    Contributors:
    Wei, Caisheng (author) / Xiong, Yunwen (author) / Chen, Qifeng (author) / Xu, Dan (author)

    Published in:

    Advances in Space Research ; 71 , 11 ; 4534-4548


    Publication date :

    2023-01-11


    Size :

    15 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English