Model-free adaptive control for the heading angle of a UAV

The difficulty of accurately modeling the aerodynamics heading angle unmanned aerial vehicles is well known. Furthermore, it difficult to control an vehicle (UAV) with a model-based method under influence wind disturbances. To address this problem, novel model-free strategy proposed. First, self-organizing type-2 fuzzy brain emotional learning network model used estimate PPD (pseudo partial derivative). Finally, stability guaranteed by designing Lyapunov function. Meanwhile, performance proposed further verified high-fidelity semi-physical simulations.