Neural Network Based Model Reference Control

  • Zhijun Li
  • Chenguang Yang
  • Liping Fan


In the chapter, as an extension of Chap.  8, we further develop Neural Network (NN) based direct model reference control for the angular motion subsystem. The closed-loop angular motion subsystem is guaranteed to match the reference model in a prescribed finite time. As it is noted that the forward velocity can be indirectly affected by the reference of tilt angle, in this chapter we develop an NN based reference trajectory planner for tilt angle, which is called Adaptive Generator of Implicit Control Trajectory (AGICT), such that the forward velocity can be “controlled” to follow the desired velocity asymptotically.


Tilt Angle Radial Basis Function Neural Network Forward Velocity Neural Network Weight Finite Time Horizon 
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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  • Zhijun Li
    • 1
    • 2
  • Chenguang Yang
    • 3
  • Liping Fan
    • 2
  1. 1.College of Automation Science and EngineeringSouth China University of TechnologyGuangzhouPeople’s Republic of China
  2. 2.Department of AutomationShanghai Jiao Tong UniversityShanghaiPeople’s Republic of China
  3. 3.School of Computing and MathematicsUniversity of PlymouthPlymouthUK

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