Model Reference Adaptive Control For Gust Load Allevation of Nonlinear Aeroelastic

2026-03-19

AI Summary

This study addresses the challenge of suppressing nonlinear aeroelastic loads on flexible aircraft under gust disturbances by introducing, for the first time, model reference adaptive control (MRAC) to this domain. Leveraging Lyapunov stability theory, a nonlinear reduced-order model is constructed using Taylor expansion and eigenvector projection. A comprehensive MRAC architecture is developed, integrating a reference model, adaptive gain tuning, and stability guarantees, with the adaptation rate matrix identified as the critical parameter balancing convergence speed, peak load reduction, and actuator effort. Simulations on both a three-degree-of-freedom wing and a Global Hawk UAV model demonstrate that MRAC significantly reduces wingtip deflection under discrete gusts, outperforming H∞ control, and achieves enhanced load mitigation in von Kármán turbulence as the adaptation rate increases.

Technology Category

• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Intelligent Robots: Behavior Learning & Control
• Machine Learning: Hardware-aware ML

Application Category

• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Model Reference Adaptive Control based on Lyapunov stability theory is developed for gust load alleviation of nonlinear aeroelastic systems. The controller operates on a nonlinear reduced-order model derived from Taylor series expansion and eigenvector projection of the coupled fluid-structure-flight dynamic equations. The complete MRAC formulation is presented, including the reference model design that encodes desired closed-loop damping characteristics, the adaptive control law with real-time gain adjustment, and the Lyapunov derivation of the adaptation law that guarantees asymptotic tracking in the linear case and bounded tracking under a Lipschitz condition on the nonlinear residual. The adaptation rate matrix is identified as the single most important design parameter, governing the trade-off between convergence speed, peak load reduction, and actuator demand. Two test cases are considered, a 3DOF aerofoil with cubic stiffness nonlinearities, and a Global Hawk type unmanned aerial vehicle. For the UAV under a discrete gusts, MRAC achieves significant wing-tip deflection reductions, outperforming the H infinity robust control benchmark with comparable control effort. Under Von Karman stochastic turbulence, meaningful reductions are also obtained, with performance scaling with the adaptation rate. The results demonstrate that MRAC provides an effective framework for GLA of flexible aircraft operating in both deterministic and stochastic disturbance environments.

Problem

• Gust Load Alleviation
• Nonlinear Aeroelasticity
• Flexible Aircraft
• Disturbance Rejection
• Adaptive Control

Innovation

• Model Reference Adaptive Control
• Gust Load Alleviation
• Nonlinear Aeroelasticity
• Lyapunov Stability
• Adaptive Rate Matrix