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Predictive control based on feedforward neural network for strong nonlinear system

By: Min Han; Jincheng Wang; Wei Guo;

2005 / IEEE / 0-7803-9048-2

Description

This item was taken from the IEEE Conference ' Predictive control based on feedforward neural network for strong nonlinear system ' The paper presents a generalized predictive control (GFC) algorithm based on feedforward neural network to control nonlinear system. In recent years, approximate linearization theory via feedback is used to control nonlinear system, but robustness can not be guaranteed. Considering neural network can accomplish nonlinear mapping from input to output, feedforward neural network is chosen as a nonlinear model of process. Based on such model, GPC is applied to control a second-order nonlinear system. To test the performance of system utilized such control algorithm, different experiments are made. Simulation results demonstrate that the performance of the system controlled by the proposed algorithm is good, and that system essentially responds in the desired manner. It is also demonstrated that the GPC based on neural network is provided with good adaptation and robustness.