Improving Performance of Flight Control System in Presence of Uncertainties and Extreme Changes in Parameters using Multiple Model Adaptive Control

The design of a flying vehicle autopilot poses a significant challenge to the controller performance and the effectiveness of the flight control system. This challenge arises from uncertainties and extreme variations in parameters. To enhance the performance of the flight autopilot, the application of adaptive control techniques becomes crucial. Flight control systems extensively employ adaptive control methods due to their capacity to swiftly and automatically adapt to environmental changes and system dynamics, consequently achieving greater speed and accuracy. This paper aims to simulate scenarios where in the flight control system of an flying vehicle approach, with a specific focus on aerodynamic control in the roll, pitch, and yaw channels. The main purpose of the paper is to be able to provide an adaptive flight control system that can perform properly in the face of sharp and sudden changes in parameters. The paper compares the performance of the multiple model adaptive control method, particularly the switching and tuning technique, for the autopilot's roll, pitch, and yaw with other methods such as the reference model adaptive control used in previous research. The results demonstrate the superiority of the multiple adaptive controller utilizing switching and tuning techniques in handling parameter changes, exhibiting faster and more responsive behavior compared to traditional adaptive controllers.