ADAPTIVE BACKSTEPPING CONTROL FOR A CLASS OF NONLINEAR UNCERTAIN SYSTEMS USING FUZZY NEURAL NETWORKS

摘要：

In this study, an adaptive backstepping control scheme using fuzzy neural networks is proposed for a class of nonlinear uncertain systems.Two kinds of fuzzy neural networks (FNNs) are used to estimate the unknown system functions.According to the estimated value of the FNNs, the control input can be chosen by backstepping design procedures, and then the system output follows the desired trajectory.Based on the Lyapunov approach, the adaptive laws and stability analysis were obtained.Finally, computer simulation results are shown to demonstrate the performances of our approach.

关键词： Nonlinear systems Back stepping Fuzzy neural network Adaptive control

作者: CHING-HUNG LEE BO-REN CHUNG FU-KAI CHANG SHENG-KAI CHANG

作者单位: Department of Electrical Engineering, Yuan Ze University, Chungli, Taoyuan, TAIWAN

会议类型: 国际会议

会议名称: 2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

会议地点: 香港

会议语种:英文

页码: 431-436

在线出版日期: 2007-08-19（万方平台首次上网日期，不代表论文的发表时间）