An adaptive flight control system for a flapping wing aircraft

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Issue Date
2018-01-07
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Authors
Chandrasekaran, Balaji K.
Steck, James E.
Advisor
Citation

Chandrasekaran, B. K., & Steck, J. E. (2018). An adaptive flight control system for a flapping wing aircraft. Paper presented at the AIAA Guidance, Navigation, and Control Conference, 2018, (210039) doi:10.2514/6.2018-1836 Retrieved from www.scopus.com

Abstract

In the present age of increased demand for unmanned aerial vehicles, flapping wing unmanned aerial vehicle applications have become of interest, primarily because of their ability to fly silently and at lower speeds. This work explores new territory through the development of an adaptive flight controller for a bird-like flapping wing aircraft, using modified strip theory to model the aircraft’s aerodynamics and Newtonian equations of motion for the flight dynamics developed by Rashid. The aircraft model is validated using existing data from the Slow Hawk Ornithopter given by zakaria. The goal of this paper is to explore various adaptive flight control architectures, such as Model Reference Adaptive Control and Adaptive Neural Network Inverse Control, leading to an advanced controller to govern the longitudinal flight characteristics of the flapping wing aircraft. An approximate math model of the slow hawk ornithopter was developed in MATLAB/Simulink. A Model Reference Adaptive Controller with Adaptive Bias Corrector was successfully able to adapt to uncertainties and improved the tracking performance compared to no adaptation. It was observed that with a B-Matrix failure the Adaptive controller was not able to reduce the tracking error to zero. The same observation was also made for system with adaptation and a PD controller. Another controller architecture in the form of Optimal Control Modification was utilized to control the system and the performance of different architectures were studied using the error metrics. OCM was able to adapt to the errors but higher learning rates exhibited a poor tracking performance and time delay margin. It was observed that OCM adaptation was able to successfully dampen the oscillations in system response.

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