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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 online tuned by a sequential learning RBF network, whose hidden units and connecting parameters are adapted online. The RBFnetworkbased PID controller simplifies modeling procedure by learning inputoutput 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
. On- Line Tuning of a Neural PID Controller BasedonVariableStructureRBFNetwork Jianchuan Yin, Gexin Bi, and Fang Dong College of Navigation, Dalian Maritime University, 1 Linghai Road, Dalian. scheme. The parameters of PID control are on- line tuned by a sequential learn- ing RBF network, whose hidden units and connecting parameters are adapted on- line. The RBF- network -based PID controller. structure adaptation (DOSA) algorithm. The algorithm can achieve compact network structure by employing a small num- ber of parameters. It takes advantage of a sliding data window for monitoring system