Frontiers of Mechanical Engineering >

2010 , Vol. 5 >Issue 4: 418 - 422

DOI: https://doi.org/10.1007/s11465-010-0117-7

RESEARCH ARTICLE

PID neural network control of a membrane structure inflation system

  • Qiushuang LIU , 1 ,
  • Xiaoli XU 2
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  • 1. School of Mechanical & Vehicular Engineering, Beijing Institute of Technology, Beijing 100081, China
  • 2. Beijing Key Laboratory (Measurement and Control of Mechanical and Electrical System), Beijing Information Science & Technology University, Beijing 100081, China

Received date: 04 Jun 2010

Accepted date: 07 Jul 2010

Published date: 05 Dec 2010

Copyright

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
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Abstract

Because it is difficult for the traditional PID algorithm for nonlinear time-variant control objects to obtain satisfactory control results, this paper studies a neuron PID controller. The neuron PID controller makes use of neuron self-learning ability, complies with certain optimum indicators, and automatically adjusts the parameters of the PID controller and makes them adapt to changes in the controlled object and the input reference signals. The PID controller is used to control a nonlinear time-variant membrane structure inflation system. Results show that the neural network PID controller can adapt to the changes in system structure parameters and fast track the changes in the input signal with high control precision.

Key words： PID; neural network; membrane structure

Cite this article

Qiushuang LIU , Xiaoli XU . PID neural network control of a membrane structure inflation system[J]. Frontiers of Mechanical Engineering, 2010 , 5(4) : 418 -422 . DOI: 10.1007/s11465-010-0117-7

Acknowledgments

This work was sponsored by the Key Laboratory of Modern Measurement & Control Technology (Beijing Information Science & Technology University), Ministry of Education and National Natural Science Foundation of China (Grant No. 50975020), Key Project of Science and Technique Development Plan Supported by Beijing Municipal Commission of Education(KZ200910772001), Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipalipality (PHR20090518), and Open Project Supported by Beijing Key Laboratory on Measurement and Control of Mechanical and Electrical System (KF20091123206, KF2009112302).

References

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