Hybrid control model of IMWNN and SNLC based on WNNI for ship fin stabilizer

A hybrid control model of inverse model wavelet neural network (IMWNN) and single neuron linear controller (SNLC) based on wavelet neural network identification (WNNI) for ship fin stabilizer system is presented in the paper. The IMWNN is employed to implement the feed-forward control, and obtain the inverse dynamics model of the process. The SNLC is adopted to carry out feedback control, and assure the stability of closed loop system and restrain the disturbances. The WNNI is used to identify the model of plant and adjust the parameters of SNLC. In simulation, the roll mode input-output signals to train the wavelet neural network off-line are obtained by introducing PRBS sequence. The simulation results illustrate the efficiency of the proposed method, and prove that the hybrid control can make sure the stability and robustness of control system and effectively improve the system adaptive ability. This method not only can be applied to ship roll-reducing control, but also can be used in other complexity, non-linearity system control.