Fixed-time disturbance observer based fixed-time back-stepping control for an air-breathing hypersonic vehicle

Area of Science:

• Aerospace Engineering
• Control Systems Theory
• Hypersonic Flight Dynamics

Background:

• Hypersonic vehicles face significant challenges due to high speeds, atmospheric uncertainties, and inherent system flexibilities.
• Traditional control methods struggle with rapid convergence and robustness against complex disturbances in hypersonic flight.
• Backstepping control, while effective, can suffer from the 'explosion of complexity' issue in higher-order systems.

Purpose of the Study:

• To develop a fixed-time backstepping control scheme for flexible air-breathing hypersonic vehicles.
• To ensure fixed-time convergence of the system states, improving response speed.
• To address and compensate for uncertainties and flexible effects during the tracking process.

Main Methods:

• Integration of fixed-time control theory with backstepping design for guaranteed finite-time convergence.
• Implementation of a fixed-time super-twisting disturbance observer to estimate and counteract system uncertainties and flexible effects.
• Utilization of a nonlinear first-order filter to mitigate the 'explosion of complexity' problem inherent in traditional backstepping.

Main Results:

• The proposed control scheme achieves fixed-time convergence, outperforming traditional methods in speed.
• The disturbance observer effectively estimates and compensates for uncertainties and flexible effects, enhancing tracking accuracy.
• Lyapunov analysis confirms semi-global uniform ultimate fixed-time boundedness of the closed-loop system.

Conclusions:

• The developed fixed-time backstepping control scheme offers a robust and efficient solution for controlling flexible air-breathing hypersonic vehicles.
• The approach successfully guarantees fixed-time stability and performance, validated by simulation results.
• This method provides a significant advancement in hypersonic vehicle control, particularly for systems with complex dynamics and uncertainties.