Adaptive configuration of the fuzzy logic controller of unmanned aerial vehicle flight dynamics

Along with the rapidly growing demand for unmanned aerial vehicles for surveillance and reconnaissance, advanced controllers are needed for these critical systems. This article proposes a design of a flight dynamics controller that takes into account various uncertainties for a medium-range unmanned aerial vehicle. In addition to the nonlinearities of flight dynamics, three main sources of uncertainties caused by unknown controller parameters, simulation errors and external interference are considered. A reliable adaptive fuzzy logic controller responsible for nonlinear flight dynamics under the conditions of many uncertainties has been developed. Nonlinear flight dynamics relies on a soft association of local linear models. When constructing the controller, the optimal reference model is defined, which is stabilized using the linear quadratic controller procedure. Then a fuzzy logic controller is developed for the nonlinear model. In order to eliminate uncertainties, the gain coefficients of the fuzzy logic controller are reconfigured and constantly adjusted for reliable adaptation. The performance of a reliable adaptive fuzzy logic controller is evaluated in terms of stabilizing the transverse and longitudinal flight dynamics and tracking the state variables of the reference model under the conditions of various uncertainties.

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