MRAC Control with Prior Model Knowledge for Asymmetric Damaged Aircraft

Area of Science:

• Aerospace Engineering
• Control Systems Theory
• Structural Health Monitoring

Background:

• Aircraft control systems face challenges with asymmetric structural damage, leading to performance degradation.
• Existing control methods may struggle to adapt effectively to varying damage conditions.
• Prior knowledge of plant models is crucial for robust control system design.

Purpose of the Study:

• To develop a novel state-tracking multivariable model reference adaptive control (MRAC) technique for damaged aircraft.
• To enhance aircraft control performance despite asymmetric structural damage.
• To reduce the computational cost and input information required for adaptive control.

Main Methods:

• A modified linear model representation was developed.
• A polytope linear parameter varying (LPV) model was derived using prior knowledge of structural damage.
• An MRAC method was designed for the polytope model, with theoretical guarantees on stability and convergence.

Main Results:

• The proposed MRAC technique demonstrated effective recovery of control performance in simulations.
• Stability and asymptotic error convergence were theoretically proven for the developed control method.
• The technique successfully reduced the number of adaptable parameters, decreasing computational load.

Conclusions:

• The novel MRAC approach offers a robust solution for controlling aircraft with asymmetric structural damage.
• Utilizing prior knowledge within a polytope LPV framework enhances adaptive control effectiveness.
• The method provides a computationally efficient and data-light alternative for aircraft control applications.