RBFNN-Based Anti-Input Saturation Control for Hypersonic Vehicles
In hypersonic flight control, characterized by challenges posed by input saturation, model parameter uncertainties, and external disturbances, this paper introduces a pioneering anti-input saturation control method based on RBFNN adaptivity. We have developed adaptive laws to enhance control system...
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Veröffentlicht in: | Aerospace 2024-01, Vol.11 (2), p.108 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | In hypersonic flight control, characterized by challenges posed by input saturation, model parameter uncertainties, and external disturbances, this paper introduces a pioneering anti-input saturation control method based on RBFNN adaptivity. We have developed adaptive laws to enhance control system adaptability and robustness by integrating mission profiles, actuator saturation failure modes, and self-evolving neural network design. Furthermore, our approach introduces a novel anti-input saturation auxiliary system, effectively addressing input saturation constraints. This innovation ensures system stability and precise tracking, even in severe input saturation constraints. The results reveal that the system’s steady-state tracking error remains under 2% under input saturation constraints, and the convergence speed demonstrates an impressive 20% improvement. These findings underscore this research’s substantial advancement in hypersonic flight control. It may significantly enhance the controllability and performance of hypersonic vehicles in real-world scenarios. |
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ISSN: | 2226-4310 2226-4310 |
DOI: | 10.3390/aerospace11020108 |