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PID control based on wavelet neural networks (WNN) identification and tuning is described in this paper. In this control scheme, two wavelet neural networks are employed, one is used to identify and predict the nonlinear dynamic system, and the other is used to tune the parameters of the PID controller on line. Combining the advantages offered by neural network processing with wavelet representation, this method can improve the shortcoming of poor adaptability of conventional PID control, and the control system can converge quickly with high precision and good robustness. This method is applied to ship fin stabilized control system, the simulation results illustrate the effectiveness and good performance.