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Control of Uncertain Systems

Chapter
Part of the Springer Handbooks book series (SHB)

Abstract

Novel direct adaptive robust state and output feedback controllers are presented for the output tracking control of a class of nonlinear systems with unknown system dynamics and disturbances. Both controllers employ a variable-structure radial basis function (RBF) network that can determine its structure dynamically to approximate unknown system dynamics. Radial basis functions are added or removed online in order to achieve the desired tracking accuracy and prevent to network redundancy. The raised-cosine RBF is employed to enable fast and efficient training and output evaluation of the RBF network. The direct adaptive robust output feedback controller is constructed by utilizing a high-gain observer to estimate the tracking error for the controller implementation. The closed-loop systems driven by the variable neural direct adaptive robust controllers are actually switched systems.

Keywords

Radial Basis Function Tracking Error Feedback Controller Grid Node Radial Basis Function Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abbreviations

2-D

two-dimensional

DAROFC

direct adaptive robust output feedback controller

DARSFC

direct adaptive robust state feedback controller

GRBF

Gaussian RBF

MIMO

multi-input multi-output

RBF

radial basis function

RCRBF

raised-cosine RBF

SISO

single-input single-output

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.School of Electrical and Computer EngineeringPurdue UniversityWest LafayetteUSA
  2. 2.School of Electrical and Computer EngineeringPurdue UniversityWest LafayetteUSA

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