A Method of Hybrid Neural Network Adaptive Control for Flight Control System
It is difficult to establish accurate models for complex flight control systems, but neural network has arbitrary nonlinear approximation ability. In order to overcome modeling errors and disturbances, a method of hybrid flight control is proposed. Firstly, inverse model of the object is identified online through neural networks and the feedback linearization control system is reached. And then circle theorem is used to design linear robust controller to control the state variables follow the input. A dynamic longitudinal model of a high-performance aircraft is considered to demonstrate the effectiveness of the proposed control scheme. Simulation results show designed controllers are highly adaptive and anti-interference ability.
adaptive inverse control neural network PID control Flight control
Gu Wei Li Dan Zhang Weiguo Liu Xiaoxiong
College of Automation Northwestern Polytechnical University, Xian, Shaanxi, 710072, China
国际会议
长沙
英文
160-163
2010-05-11（万方平台首次上网日期，不代表论文的发表时间）