Fuzzy Neural Network Control for Nonlinear Networked Control System
A nonlinear networked control system based on FNN (fuzzy neural network) control which is used to solve uncertainty problems was proposed in view of that the nonlinear systems are often involved in uncertainties, complex architecture and difficulty in modeling and simulating under network conditions. Based on the Matlab/Simulink modularized TPCS (two inverted pendulums coupled by a spring) modeling in combination with the TrueTime communication network, the uncertainties due to the object to be modeled and the network-induced time delays were both processed synthetically by a FNN controller we designed. The simulation results showed that the proposed method not only reduces the complexity of nonlinear system modeling but also restrains the performance effect of control system that induced by uncertainties of nonlinear networked control system efficiently, and represents pretty robust.
FNN Networked Control System Nonlinear System TPCS Model Uncertainty
E Da-zhi PAN Feng CHEN Da-li XUE Ding-yu
College of Information Science and Engineering, Northeastern University, Shenyang, 110004
国际会议
2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)
广西桂林
英文
1569-1573
2009-06-17（万方平台首次上网日期，不代表论文的发表时间）