The Design of PID Controller Based On Hopfield Neural Network

Wenxia Du, Xiuping Zhao, Feng Lv, Hailian Du

Abstract


With the complexity increase in industrial production process, the traditional Proportion-Integration-Differentiation(PID) control can not meet the requirements of the control system performance. Because neural network has the ability of adaptive, self-learning and nonlinear function approximation, control equality of system is improved if it is combined with traditional PID. In the paper, Hopfield neural network based on Hebb rules is used to identify the parameters of system, and then the state space model is established. Hopfield Neural network has the function of optimal calculation, PID controller based on Hopfield neural network is designed for a system can optimize the parameter of PID in real-time and improve control accuracy. Simulation result show the performance index is greatly improved.

 

DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4925


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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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