Observer-based wing rock motion suppression using the Fourier series expansion as uncertainty approximator

The motion of wing rock varies unpredictably with changes in the angle of attack (AOA) and is highly susceptible to external disturbances. This paper presents a robust adaptive control strategy based on an observer, utilizing Fourier Series (FS) polynomials to estimate uncertainties and suppress wing rock oscillations. The unmodeled dynamics, external disturbances, and uncertainties are first modeled using the Fourier series. The adaptation laws, obtained through analyzing the stability, are subsequently used to adjust its coefficients. A distinctive feature of the suggested design is that it does not require a precise model of the plant or any data about roll rate signal measurements and uncertainties, which enhances cost-effectiveness and applicability in real-world systems. The paper employs the Lyapunov lemma to ensure that the error signals in the controlled system stay uniformly ultimately bounded (UUB). Simulation results showcase the effectiveness and versatility of the proposed approach. The outcomes are compared with two advanced approximation techniques to demonstrate the precision and effectiveness of the suggested controller design.