Author(s)

Meili Chen, Yuan Wang

Key Laboratory of Fundamental Science for National Defense-Advanced Design Technology of Flight Vehicle, Nanjing University of Aeronautics and Astronautics, Nanjing, China.

In this paper, a real-time online data-driven adaptive method is developed to deal with uncertainties such as high nonlinearity, strong coupling, parameter perturbation and external disturbances in attitude control of fixed-wing unmanned aerial vehicles (UAVs). Firstly, a model-free adaptive control (MFAC) method requiring only input/output (I/O) data and no model information is adopted for control scheme design of angular velocity subsystem which contains all model information and up-mentioned uncertainties. Secondly, the internal model control (IMC) method featured with less tuning parameters and convenient tuning process is adopted for control scheme design of the certain Euler angle subsystem. Simulation results show that, the method developed is obviously superior to the cascade PID (CPID) method and the nonlinear dynamic inversion (NDI) method.

Data-Driven, Adaptive Method, Attitude Control, Unmanned Aerial Vehicles (UAV), Internal Model Control

Chen, M. and Wang, Y. (2019) A Data-Driven Adaptive Method for Attitude Control of Fixed-Wing Unmanned Aerial Vehicles. Advances in Aerospace Science and Technology, 4, 1-15. doi: 10.4236/aast.2019.41001.