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International Conference on Intelligent Robotics and Applications

ICIRA 2010: Intelligent Robotics and Applications pp 246–256Cite as

Modeling and Fault Tolerant Controller Design for PM Spherical Actuator

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6424))

Abstract

This paper presents a method based on neural networks for achieving fault tolerant control in the PM spherical actuator control scheme. The model of a PM spherical actuator was developed. Tuning rules of the RBF networks which guarantees the stability of the fault system were derived and the on-line fault tolerant control scheme was developed. The control scheme does not need fault detection and diagnosis modules. An application tracking control problem for the tracking errors and Euler angles of an actuator driven by independent stator and rotor pairs is solved by using the controller. The effectiveness of the proposed method is illustrated by performing the simulation of a space trajectory tracking control.

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Author information

Authors and Affiliations

  1. School of Electrical Engineering and Information Science, Hebei University of Science and Technology, Shijiazhuang, 050018, China

    Zheng Li

Authors
  1. Zheng Li
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Editor information

Editors and Affiliations

  1. School of Creative Technologies, The University of Portsmouth, PO1 2DJ, Portsmouth, UK

    Honghai Liu

  2. Robotics Institute, Shanghai Jiao Tong University, 200240, Shanghai, China

    Han Ding , Zhenhua Xiong  & Xiangyang Zhu ,  & 

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© 2010 Springer-Verlag Berlin Heidelberg

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Li, Z. (2010). Modeling and Fault Tolerant Controller Design for PM Spherical Actuator. In: Liu, H., Ding, H., Xiong, Z., Zhu, X. (eds) Intelligent Robotics and Applications. ICIRA 2010. Lecture Notes in Computer Science(), vol 6424. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16584-9_23

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  • DOI: https://doi.org/10.1007/978-3-642-16584-9_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16583-2

  • Online ISBN: 978-3-642-16584-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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