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.