The Analysis Method of Performance Comprehensive Performance Optimization Design for Multi-body Unmanned Boat

Abstract

Abstract In order to compare and analyze the comprehensive performance of multi-hull unmanned boats under specific conditions, this paper conducts in-depth research on the multi-objective decision-making theory and intelligent optimization algorithms of boat type design. First of all, this paper establishes the corresponding ship type and resistance database using the response surface fitting method through the drag resistance test of the ship model. Secondly, comprehensively considering the impact of the three major performances of multi-hull unmanned craft on the design of the boat’s speed, maneuverability and seakeeping, a comprehensive optimization mathematical model was established, and the comprehensive optimization design software was adapted. Then, using genetic algorithm, particle swarm algorithm, and chaos algorithm to conduct a preliminary calculation and analysis of the comprehensive performance of the two ship types. By comparing the calculation results, it is concluded that the particle swarm algorithm is the best algorithm among the three intelligent algorithms. Finally, the particle swarm algorithm is used to compare and analyze the comprehensive performance of the two ship types in the multi-hull unmanned craft. It is concluded that the overall performance of the three-hull unmanned craft is better at the same speed and displacement. This paper discusses the pros and cons of the three intelligent algorithms, compares and analyzes the calculation results of each optimization algorithm, and provides a practical way and method for the selection of multihull unmanned boats under the same speed and same displacement.