High-fidelity simulation testing of intelligent and adaptive aircraft control laws

This paper compares the robustness of seven popular adaptive and intelligent control approaches using a high fidelity aircraft simulation. The control laws were originally developed and tuned using a lower fidelity simulation of the same aircraft, which is significantly different from the high fidelity simulation used to generate all results in, this paper. The control law approaches examined are fuzzy logic, linearly and nonlinearly parameterized neural network approaches, an indirect adaptive version of dynamic inversion, variable structure, and a hybrid approach that combines direct and indirect adaptive elements. In addition, a conventional scheduled dynamic inversion controller is used as baseline. The approaches are demonstrated on a high fidelity six degree-of-freedom simulation with nonlinear aerodynamic and engine models, actuator models with position and rate saturations, and turbulence. Simulation results are given for single and multi-axis pitch and roll maneuvers in both nominal and failed cases.