Abstract
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.
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Takahashi, K. (2001). Controller Applications Using Radial Basis Function Networks. In: Howlett, R.J., Jain, L.C. (eds) Radial Basis Function Networks 2. Studies in Fuzziness and Soft Computing, vol 67. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1826-0_9
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DOI: https://doi.org/10.1007/978-3-7908-1826-0_9
Publisher Name: Physica, Heidelberg
Print ISBN: 978-3-7908-2483-4
Online ISBN: 978-3-7908-1826-0
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