A Novel Nonsingular Fast Fixed-Time Sliding Mode Control and Its Application to Satellite Attitude Control

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Robust and Nonlinear Control Pub Date : 2024-12-17 DOI:10.1002/rnc.7787
Saumitra Barman, Manoranjan Sinha
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Abstract

In this paper, a Lyapunov-like sufficient condition for the fast fixed-time stability of autonomous systems is proposed. The proposed fast fixed-time stability theorem ensures a smaller upper bound on the convergence time than the existing fixed-time stability theorems. The fixed-time sliding mode controls require switching from the fixed-time sliding surface to the general sliding surface in the vicinity of the origin to avoid non-differentiability at that point. It is demonstrated that the switching method converges the system states either to a residual set around the equilibrium point or directly to the equilibrium point, depending on the tuning parameter settings. To address this issue, a new nonsingular sliding surface is proposed based on the fast fixed-time stability theorem. This approach ensures singularity-free convergence of the system states to the equilibrium point without additional switching logic for the sliding surfaces or any constraints on tuning parameters. Furthermore, a novel continuous adaptive fast fixed-time sliding mode control (AFFTSMC) law is proposed for attitude control of a satellite in the presence of the satellite inertia uncertainty and unknown upper-bounded external disturbance torques. The proposed AFFTSMC law ensures chattering-free and singularity-free satellite attitude control. Simulation results are presented for both rest-to-rest and tracking attitude maneuvers of a satellite, demonstrating the superiority of the proposed controller.

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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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