Research On Manoeuvring And Control Of Collision Avoidance Strategy Optimization For Large Twin-propeller Twin-rudder Ship

With the rapid development of waterway transport and shipbuilding industry, a good number of large-scale, high-speed ships arise to meet the need of domestic and international seaway transportation and requirements for ship maneuvering and control ability become increasingly higher. In order to be safe, efficient, energy-saving and environmental protecting, a large twin-propeller twin-rudder container ship (the displacement is 0.25 million tons), which could carry 18000 TEU, was built and put into operation in 2013. Because of twin-propeller twin-rudder, a large ship has more flexible autonomous maneuverability. Research on modeling and manoeuvring control for large twin-propeller twin-rudder ship has important theoretical and engineering significance.According to research hull, rudder, propeller and outside distraction respectively, a mathematical model of twin-propeller twin-rudder ships is built based on MMG model, and the model is verified by the contrast of calculated test curve of acutual ship.According to analysis multi-objective optimization algorithm, clonal selecting algorithm and quantum calculating method, the parallelism of quantum calculating and the ergodicity of chaos searching are used to optimize clonal selecting algorithm. Chaos Quantum Immune Clonal Multi-objective Algorithm (CQCMEA) is proposed in this paper. Antibodies in colonies are coded by quantum bits and updated by quantum rotation gate mutation operator, Searching speed is faster and the diversity of antibody population is increased. Comparing to other multi-objective algorithm, the experimental results indicate that the effectiveness of this algorithm.In ship safety field, CQCMEA is proposed to optimize ship collision avoidance strategy. According to the principle of ARPA trial test, the concerned parameters of ship collision avoidance operation are encoding as the antibodies of CQCMEA, the affinity of antibody is evaluated by safety, economy and smooth. The optimized strategy is found by using multiple criteria decision making (MCDM). The experimental results indicate that CQCMEA can find a valid collision avoidance strategy.