Neural Network Adaptive Control of High-Precision Flight Simulator: Theory and Experiments

摘要：

This paper developed a control scheme of neural network based on feedforward and PD(proportional and derivative) control for high-precision flight simulator. A radial basis-function neural network (RBFNN) controller was used to learn and to compensate the unknown model dynamics, parameter variation and disturbance of the system on-line. The iterative algorithm of RBFNN parameters is got by Lyapunov stability theory. The effectiveness of the proposed control scheme is evaluated by simulation results and a real-time flight simulator system experiment. It is found that the proposed scheme can reduce the plants sensitivity to parameter variation and disturbance and high precision performance of flight simulator can be obtained.

作者: Hu Hongjie Zhan Ping Li Dedi

作者单位: School of Automation Science and Electrical Engineering,Beihang University,No.37,Xueyuan Road,Haidian District,Beijing,100191,China

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Information and Automation(2009年 IEEE信息与自动化国际学术会议)

会议地点: 珠海、澳门

会议语种:英文

页码: 1172-1176

在线出版日期: 2009-06-22（万方平台首次上网日期，不代表论文的发表时间）