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International Conference in Swarm Intelligence

ICSI 2012: Advances in Swarm Intelligence pp 437–443Cite as

Research of Triple Inverted Pendulum Based on Neural Network of Genetic Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7331))

Abstract

In the topic, I carried out the simulation of triple inverted pendulum system by intelligent control, which was combinated of neural network and genetic algorithm. Neural network oriented genetic algorithm was put forward and discussed its realization, it overcomed the shortcoming of slow convergent speed, immature convergence and lots of iterations.

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References

  1. Huang, X., Niu, Q.: The Realization of Second-order Linear Optimal Control in the Inverted Pendulum System. Computer Measurement and Control 14(12), 1641–1642, 1662 (2006)

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Author information

Authors and Affiliations

  1. Technology Insitute of Yongjiang University, Nanning, 530200, China

    Xiaoping Huang & Ying Zhang

  2. Guangxi Electric Power Institute of Vocational Training, Nanning, 530007, China

    Junlong Zheng

Authors
  1. Xiaoping Huang
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  2. Ying Zhang
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  3. Junlong Zheng
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception (MOE), Peking University, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, Suzhou, China

    Yuhui Shi

  3. Shenzhen City Key Laboratory of Embedded System Design, College of Computer Science and Software Engineering, Shenzhen University, 518060, Shenzhen, China

    Zhen Ji

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Huang, X., Zhang, Y., Zheng, J. (2012). Research of Triple Inverted Pendulum Based on Neural Network of Genetic Algorithm. In: Tan, Y., Shi, Y., Ji, Z. (eds) Advances in Swarm Intelligence. ICSI 2012. Lecture Notes in Computer Science, vol 7331. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30976-2_53

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  • DOI: https://doi.org/10.1007/978-3-642-30976-2_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-30975-5

  • Online ISBN: 978-3-642-30976-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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