Fuzzy Neural Network Control and Identification for Uncertain Nonlinear Systems
In this paper, the problem of identi.cation and control of uncertain nonlinear systems is investigated based on fuzzy neural network. The considered systems are unknown and with external disturbances, so fuzzy neural networks are employed to approximate the unknown system functions. By doing this, an identi.cation model of the controlled system can be obtained. Based on this model, a controller with adaptive mechanism can be designed for the system. The controller can attenuate the external disturbance to a given level, and guarantee the stability of the closed-loop system. Satisfactory identification and control of the system can be realized at the same time. Simulation example is given to demonstrate the effectiveness of the proposed controller.
Neural network Adaptive Control Identification Nonlinear system
Xiu-Huan Ji
College of Information, Linyi Normal University, Linyi 276005, China
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
4237-4242
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）