Adaptive predefined-time prescribed performance control for spacecraft systems

Yuhan Su; Shaoping Shen; Yuhan Su; Shaoping Shen

doi:10.3934/mbe.2023256

Mathematical Biosciences and Engineering

2023, Volume 20, Issue 3: 5921-5948. doi: 10.3934/mbe.2023256

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Adaptive predefined-time prescribed performance control for spacecraft systems

Yuhan Su ,
Shaoping Shen ^,

Department of Automation, School of Aerospace Engineering, Xiamen University, Xiamen 361102, China

Academic Editor: Xiaodi Li

Received: 28 October 2022 Revised: 14 December 2022 Accepted: 02 January 2023 Published: 13 January 2023

The high-accuracy attitude maneuvering problem for spacecraft systems is investigated. A prescribed performance function and a shifting function are first employed to ensure the predefined-time stability of attitude errors and eliminate the constraints on tracking errors at the incipient stage. Subsequently, a novel predefined-time control scheme is developed by combining prescribed performance control and backstepping control procedures. Radial basis function neural network and minimum learning parameter techniques are introduced to model the function of lumped uncertainty including inertial uncertainties, actuator faults and virtual control law derivatives. According to the rigorous stability analysis, the preset tracking precision can be achieved within a predefined time and the fixed-time boundedness of all closed-loop signals is established. Finally, the efficacy of the propounded control scheme is manifested through numerical simulation results.
- predefined-time control,
- backstepping control,
- prescribed performance control,
- attitude maneuvering,
- spacecraft system
Citation: Yuhan Su, Shaoping Shen. Adaptive predefined-time prescribed performance control for spacecraft systems[J]. Mathematical Biosciences and Engineering, 2023, 20(3): 5921-5948. doi: 10.3934/mbe.2023256

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Abstract

The high-accuracy attitude maneuvering problem for spacecraft systems is investigated. A prescribed performance function and a shifting function are first employed to ensure the predefined-time stability of attitude errors and eliminate the constraints on tracking errors at the incipient stage. Subsequently, a novel predefined-time control scheme is developed by combining prescribed performance control and backstepping control procedures. Radial basis function neural network and minimum learning parameter techniques are introduced to model the function of lumped uncertainty including inertial uncertainties, actuator faults and virtual control law derivatives. According to the rigorous stability analysis, the preset tracking precision can be achieved within a predefined time and the fixed-time boundedness of all closed-loop signals is established. Finally, the efficacy of the propounded control scheme is manifested through numerical simulation results.

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