Controller Applications Using Radial Basis Function Networks

  • K. Takahashi
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 67)


Methods of designing a radial-basis-function-network-based (RBFN) controller and implementing it for servo controlling mechanical systems are presented. Focusing on the derivative of sigmoid function, we derive an RBFN controller by applying a differential operator to a neural servo controller. Applications for controlling a flexible micro-actuator and a 1-degree-of-freedom robot manipulator using RBFN controller are also described.


Sigmoid Function Radial Basis Function Network Convergence Factor Residual Vibration Rectangular Wave 
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.


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© Springer-Verlag Berlin Heidelberg 2001

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  • K. Takahashi

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