Abstract
This paper presents the use of a variable structure radial basis function (RBF) network for identification in PID control scheme. The parameters of PID control are on-line tuned by a sequential learning RBF network, whose hidden units and connecting parameters are adapted on-line. The RBF-network-based PID controller simplifies modeling procedure by learning input-output samples while keep the advantages of traditional PID controller simultaneously. Simulation results of ship course control simulation demonstrate the applicability and effectiveness of the intelligent PID control strategy.
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Yin, J., Bi, G., Dong, F. (2009). On-Line Tuning of a Neural PID Controller Based on Variable Structure RBF Network. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_124
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DOI: https://doi.org/10.1007/978-3-642-01510-6_124
Publisher Name: Springer, Berlin, Heidelberg
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