Model-Free Fuzzy Adaptive Control of the Heading Angle of Fixed-Wing Unmanned Aerial Vehicles

In this paper, a novel model-free fuzzy adaptive control (MFFAC) scheme is developed to control the heading angle of fixed-wing unmanned aerial vehicles (UAVs). It is common knowledge that the aerodynamics of the heading angle of fixed-wing UAVs are difficult to accurately model and are subject to wind disturbances. Therefore, it is difficult to implement conventional model-based control to the heading angle control problem. To overcome this difficulty, the authors propose a novel data-driven control approach. First, an adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the pseudo partial derivative (PPD), which is described as an equivalent dynamic linearization (EDL) technique for unknown nonlinear systems. Secondly, an extended model-free adaptive control (MFAC) strategy is proposed to control the heading angle of fixed-wing UAVs with wind disturbances. Finally, a discrete Lyapunov-based stability analysis is presented to prove the globally asymptotic stability of the proposed control scheme. The high-fidelity semiphysical simulations illustrate that accurate and stable control is achieved in this designed control strategy. (C) 2017 American Society of Civil Engineers.