Generalized Backstepping Method Based Control Chen Chaotic System Using Adaptive Neuro-Fuzzy Inference System

摘要：

In this paper, first known chaotic system, Chen equation, was selected as chaotic system. One of the best control methods that would be used for stabilization this systems, was Backstepping. In this paper this method is improved to Generalized Backstepping Method (GBM). For this new method, expose a new theorem and its proof and for showing its abilities, control Chen equation. Generalized Backstepping approach consists of parameters which accept positive values. The system responded differently for each value. Adaptive neuro-fuzzy algorithm can select appropriate and optimal values for the parameters and force the system error to decay to zero rapidly that it causes the system to have a short and optimal setting time. Fitness function also makes an optimal controller and causes overshoot to reach to its minimum value. This hybrid makes an optimal backstepping controller.

关键词： Chen chaos Lyapunov Generalized Backstepping Method ANFIS

作者: Amir Gholami Pastaki Alireza Sahab Masoud Taleb Ziabari Alireza Khalilzadeh

作者单位: Faculty of Engineering, Electrical Engineering Group, Islamic Azad University Lahijan Branch, Iran Faculty of Engineering, Mechatronic Group, Islamic Azad University Ghazvin Branch, Iran Faculty of Engineering, Computer Architecture Group, Islamic Azad University Arak Branch, Iran

会议类型: 国际会议

会议名称: 2010 International Conference on Future Information Technology(2010年未来信息技术国际会议 ICFIT 2010)

会议地点: 长沙

会议语种:英文

页码: 131-135

在线出版日期: 2010-12-14（万方平台首次上网日期，不代表论文的发表时间）