Affiliations: Aerospace Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran | Center of Excellence in Computational Aerospace, Aerospace Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran | Medical Engineering Department, Amirkabir University of Technology (Tehran Polytechnic), Tehran, Iran
Abstract: The fuzzy sliding mode control based on the multi-objective genetic algorithm is proposed to design the altitude autopilot of a UAV. This case presents an interesting challenge due to non-minimum phase characteristic, nonlinearities and uncertainties of the altitude to elevator relation. The response of this autopilot is investigated through various criteria such as time response characteristics, robustness with respect to parametric uncertainties, and robustness with respect to unmodeled dynamics. The parametric robustness is investigated with reduction in significant longitudinal stability coefficients. Also, a nonlinear model in presence of the coupling terms is used to investigate the robustness with respect to unmodeled dynamics. In spite of a designed classic autopilot, it is shown by simulation that combining of the sliding mode control robustness and the fuzzy logic control independence of system model can guarantee the acceptable robust performance and stability with respect to unmodeled dynamics and parametric uncertainty, while the number of FSMC rules is smaller than that for the conventional fuzzy logic control.
