The Control of Fixed-Time Trajectory Tracking for Stratospheric Airships with System Uncertainties and External Disturbances
Publication: Journal of Aerospace Engineering
Volume 37, Issue 6
Abstract
In this study, we address the trajectory tracking control problem for stratospheric airships, characterized by parameter uncertainties and external disturbances. Initially, a mathematical model of the airship is constructed, from which a trajectory tracking error model is derived. Subsequently, a novel sliding mode control law is formulated to enhance control accuracy and accelerate the convergence rate of the sliding mode. Furthermore, radial basis function neural networks are utilized to estimate and compensate for uncertain system parameters and external disturbances, significantly improving the system’s robustness. Lastly, the application of Lyapunov’s theory verifies the fixed-time stability of the closed-loop system and ensures the convergence of trajectory tracking error to a near-zero vicinity within fixed time. Simulation results strongly support the efficacy of the proposed control strategy.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work is supported by the National Natural Science Foundation of China (No. 52227811, No. U23A20336, and No. 61733017).
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© 2024 American Society of Civil Engineers.
History
Received: Dec 24, 2023
Accepted: May 15, 2024
Published online: Aug 6, 2024
Published in print: Nov 1, 2024
Discussion open until: Jan 6, 2025
ASCE Technical Topics:
- Continuum mechanics
- Convergence (mathematics)
- Deformation (mechanics)
- Detection methods
- Dynamics (solid mechanics)
- Engineering fundamentals
- Engineering mechanics
- Errors (statistics)
- Mathematical models
- Mathematics
- Methodology (by type)
- Models (by type)
- Motion (dynamics)
- Parameters (statistics)
- Sliding effects
- Solid mechanics
- Statistics
- Structural mechanics
- Tracking
- Uncertainty principles
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