Adaptive Neural Network Control for a Class of Non-affine Nonlinear System Based on Fuzzy Estimator

被引：0
|
作者：
Zhao, Tong [1 ]
Li, Lingling [1 ]
机构：
[1] Qingdao Univ Sci & Technol, Sch Automatizat & Elect Engn, Qingdao, Peoples R China
来源：
2ND INTERNATIONAL CONFERENCE ON SENSORS, INSTRUMENT AND INFORMATION TECHNOLOGY (ICSIIT 2015) | 2015年
关键词：
adaptive control; neural network; fuzzy inference system; non-affine nonlinear system;
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, the adaptive neural network control is investigated for a class of SISO non-affine nonlinear dynamic systems. The proposed method obtains the adaptive laws directly employing the gradient descent algorithm to minimize the control error between the unknown ideal controller and the NN controller. A fuzzy inference system (FIS) with heuristically defined rules is introduced to provide an estimate of this error based on the past history of the system behavior. We prove that the closed-loop system is stable and all signals are bounded. Simulation results demonstrate the effectiveness of the proposed control scheme.
引用
收藏
页码：7 / 12
页数：6
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