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Aiming at the non-linearity of state equation and observation equation of SSP (Siemen Schottel Propulsor) propulsion motor, an improved particle filter algorithm based on strong tracking extent Kalman filter (ST-EKF) was presented, and it was imported into the marine SSP propulsion motor control system. The strong tracking filter was used to update particles in the new algorithm and produce importance densities. As a result, the problems of particle degeneracy and sample impoverishment were ameliorated, the propulsion motor states and the rotor resistance were estimated simultaneously using strong track filter (STF), and the tracking ability of marine SSP propulsion motor control system was improved. Simulation result shown that the improved EPF algorithm was not only improving the prediction accuracy of the motor states and the rotor resistance, but also it can satisfy the requirement of navigation in harbor. It had the better accuracy than EPF algorithm

Optimal Control Strategy for Marine Ssp Podded Propulsion Motor Based on Strong Tracking-Epf