Nonlinear Dynamic System Control with PID Neural Networks
Author(s): CAO Hai-yun LI Shou-ju LIU Ying-xi
Pages: 38-40
Year: 2007 Issue: S1
Journal: Control Engineering of China
Keyword: nonlinear system eontrol; PID neural network; nonlinear optimization; BP algorithm;
Abstract: An neural network-based controller is designed and analyzed for a class of single-input nonlinear system.In order to optimize the ob- ject function through training on-line and learning,neural network’s weights are adjusted by BP(Error Back Propagation)algorithm.The con- troller makes the best of BP neural network algorithm’s ability of approaching all continuous,nonlinear functions,which shows the potential of neural network in solving the nonlinear system.Compared with other nonlinear modehng techniques for control purposes,it has several specific advantages that make it suited to particular applications.The simulation results show that the proposed control system with PID neural network is flexible and efficient,and it can fetch the favorable control results.
Pages: 38-40
Year: 2007 Issue: S1
Journal: Control Engineering of China
Keyword: nonlinear system eontrol; PID neural network; nonlinear optimization; BP algorithm;
Abstract: An neural network-based controller is designed and analyzed for a class of single-input nonlinear system.In order to optimize the ob- ject function through training on-line and learning,neural network’s weights are adjusted by BP(Error Back Propagation)algorithm.The con- troller makes the best of BP neural network algorithm’s ability of approaching all continuous,nonlinear functions,which shows the potential of neural network in solving the nonlinear system.Compared with other nonlinear modehng techniques for control purposes,it has several specific advantages that make it suited to particular applications.The simulation results show that the proposed control system with PID neural network is flexible and efficient,and it can fetch the favorable control results.
Related Articles