In order to predict the manoeuvrability of smart ship and improve its adaptive tracking controlling performance, the parameters of the manoeuvring model need to be gained. Firstly, the second-order nonlinear response model of the ship is established and discretized by the difference methods. The corresponding data are collected by the zigzag-tests conducted using a 1:200 scale KVLCC2 model. Secondly, taking speed into consideration, the optimal estimation of the manoeuvring model parameters is calculated by using LS-SVM method. Based on the dentificated manoeuvring model parameters, the ship heading PID controlling method was improved. Thirdly, different ship tracking controlling methods were tested and compared, the improved LOS controlling parameters were gained. On the basis of parameter identification, the ship's maneuverability is considered for tracking control, and the time to switch to the next waypoint is d°/ 30°, and the least two is applied. The support vector machine method identified the ship maneuvering motion model parameters, carried out a maneuverability prediction simulation, and compared with actual test data. The simulation results verified the effectiveness of the method and at the same time, combined etermined based on the ship's speed, waypoints and other information to realize the ship's adaptive track tracking control, Finally, by comparing the test results in different conditions, the test results show that the track tracking control considering the maneuverability of the ship has high accuracy. The training sample is constructed from the Z-shaped test data of the self-propelled model of $10^{\circ} /20$ with self-propelled model track tracking, The experimental results indicate that the trajectory tracking control considering ship maneuverability has high accuracy.
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