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International Symposium on Neural Networks

ISNN 2007: Advances in Neural Networks – ISNN 2007 pp 292–301Cite as

On Neural Network Switched Stabilization of SISO Switched Nonlinear Systems with Actuator Saturation

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4491))

Abstract

As we know, saturation, deadzone, backlash, and hysteresis are the most common actuator nonlinearities in practical control system applications. Saturation nonlinearity is unavoidable in most actuators. In this paper, we address the Neural Network saturation compensation for a class of switched nonlinear systems with actuator saturation. An actuator saturation compensation switching scheme for switched nonlinear systems with its subsystem in Brunovsky canonical form is presented using Neural Network. The actuator saturation is assumed to be unknown and the saturation compensator is introduced into a feed-forward path. The scheme that leads to switched stability and disturbance rejection is rigorously proved. The tracking performance of switched nonlinear system is guaranteed based on common Lyapunov approach under the designed switching strategy.

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Author information

Authors and Affiliations

  1. The Provincial Key Lab of Playing-Go Strategy and Control System, College of Science, Guizhou University, Guiyang 550025, Guizhou, P.R. China

    Fei Long & Wei Wei

Authors
  1. Fei Long
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  2. Wei Wei
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering (M/C 154), University of Illinois at Chicago, 851 S. Morgan Street, 60607-7053, Chicago, IL, USA

    Derong Liu

  2. School of Automation, Southeast University, 210096, Nanjing, China

    Shumin Fei

  3. Laboratory of Complex Systems, Institute of Automation, Chinese Adacemy of Sciences, 100080, Beijing, P. R. China

    Zeng-Guang Hou

  4. School of Information Science and Engineering, Northeast University, Shenyang, 110004, China

    Huaguang Zhang

  5. School of Electrical Engineering, Hohai University, Nanjing, 210098, China

    Changyin Sun

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© 2007 Springer-Verlag Berlin Heidelberg

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Long, F., Wei, W. (2007). On Neural Network Switched Stabilization of SISO Switched Nonlinear Systems with Actuator Saturation. In: Liu, D., Fei, S., Hou, ZG., Zhang, H., Sun, C. (eds) Advances in Neural Networks – ISNN 2007. ISNN 2007. Lecture Notes in Computer Science, vol 4491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72383-7_35

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  • DOI: https://doi.org/10.1007/978-3-540-72383-7_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72382-0

  • Online ISBN: 978-3-540-72383-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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