| Title |
Robust Flight Control System Using Neural Networks: Dynamic Surface Design Approach |
| Authors |
유성진(Yoo, Sung-Jin) ; 최윤호(Choi, Yoon-Ho) ; 박진배(Park, Jin-Bae) |
| Keywords |
DSC ; SRWNN ; reconfigurable flight control system |
| Abstract |
This paper presents the adaptive robust control method for the flight control systems with model uncertainties. The proposed control system can be composed simply by a combination of the adaptive dynamic surface control (DSC) technique and the self recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides us with the ability to overcome the 'explosion of complexity' problem of the backstepping controller. The SRWNNs are used to observe the arbitrary model uncertainties of flight systems, and all their weights are trained on-line. From the Lyapunov stability analysis, their adaptation laws are induced and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a high performance aircraft (F-16) are utilized to validate the good tracking performance and robustness of the proposed control system. |