Performance optimization analysis of the catamaran unmanned vehicle based on improved particle swarm optimization algorithm

Shi Yan, Yang Songling, Huang xiaoyu, Cai Chengqi, Cheng Zhanyuan

The rapidity, maneuverability, seakeeping resistance and capsizing resistance of unmanned craft are important aspects for evaluating its performance. In the design of ship form, the influence degree of each performance should be considered comprehensively. In this paper a catamaran unmanned craft, determine the catamaran type unmanned craft performance (stability, quickness, maneuverability and seakeeping) evaluation function and comprehensive optimization objective function, the selected design variable and its scope and constraints, comprehensive optimization mathematical model is established, and the mathematical model and the four kinds of intelligent optimization algorithm, the combination of design and write a comprehensive optimization procedure is suitable for the catamaran unmanned craft, and a comprehensive optimization calculation and analysis. The optimal results are obtained by using a single particle swarm optimization algorithm with different computational algebra, fixed weight, maximum particle velocity and interval probability. Secondly, the particle swarm optimization algorithm was improved by using hierarchical and parallel strategies, and the hybrid algorithm and parallel computation of key design variables were carried out. By comparing the fitness function values, it is found that the optimization ability could be greatly improved by adding both hierarchical and parallel strategies. Finally, the optimal method and parameters of each system are obtained. The results show that the optimization system based on the improved particle swarm optimization algorithm is more efficient and the optimization results are reliable. The results can be used as a reference for solving the multi-objective, multi-variable and multi-constraint optimization problems of the performance optimization of the catamaran.

https://dx.doi.org/10.31873/IJEAS.6.7.2019.18