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Pruning Based Robust Backpropagation Training Algorithm for RBF Network Tracking Controller

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Abstract

A pruning based robust backpropagation training algorithm is proposed for the online tuning of the Radial Basis Function(RBF) network tracking control system. The structure of the RBF network controller is derived using a filtered error approach. The proposed method in this paper begins with a relatively large network, and certain neural units of the RBF network are dropped by examining the estimation error increment. A complete convergence proof is provided in the presence of disturbance.

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Authors and Affiliations

  1. School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore, 639798, Singapore

    Jie Ni & Qing Song

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  1. Jie Ni
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  2. Qing Song
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Correspondence to Qing Song.

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Ni, J., Song, Q. Pruning Based Robust Backpropagation Training Algorithm for RBF Network Tracking Controller. J Intell Robot Syst 48, 375–396 (2007). https://doi.org/10.1007/s10846-006-9093-x

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  • DOI: https://doi.org/10.1007/s10846-006-9093-x

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