Research Of Particle Swarm Optimization Algorithm And Its Application In Ship Engineering

Researchers have focused on developing novel intelligence optimization methods to address the complexity, constraint, nonlinearity, multiple local minimum as well as the modeling difficulties in lots of scientific and engineering problems. Swarm intelligence optimization technique is such an algorithm developed from mimicking social behavior of animals in the natural environment. The algorithm can be used to solve complicated optimization problem, without requiring centralized control and global modeling.In this dissertation, focus is on particle swarm optimization (PSO), one branch in the swarm optimization. Given the limitations of the existing PSO and its general application fields, several approaches are proposed to revise and improve the existing techniques. And application strategies of these improved algorithms in the field of shipping engineering are investigated.The research in this dissertation is to improve the existing PSO such that it can effectively solve the problems including optimization of complex multimodal problems. The main contributions of the dissertation include:â… . A kind of method to select PSO parameter based on universal multi-factor is given, which can offset the shortage of normal method to select PSO parameter based on single factor. Basic steps of the method include: in the beginning, parameters bound are limited by the PSO parameter restriction method, then parameters are confirmed by uniform design from number theory and statistics. This kind of method to select optimum parameter can give a group of good parameter quickly in spite of coupling and restriction in the middle of parameters. Otherwise, generalization ability of parameter is researched. Research results show that: the speed of algorithm to select parameter is fast, and effect is good, it is universal to select parameter in all kinds of PSO algorithms improved.â…¡. A kind of PSO algorithm based on multi-species space compress strategy is given, which can solve some difficulties in normal PSO algorithm to optimize multidimensional, large range of value and multimodal problems. Incomplete searching strategy is imported to PSO, and searching is divided into several phases. To every phase, next searching space is confirmed by optimum swarm in every a specie. A lot of invalid searching is avoided by compressing constantly space searched, which can improve searching speed and quality. At the same time, the method is suited to multicomputer team working without special team working plat. Test results show that: the algorithm can compress space effetely and improve searching efficiency.â…¢. Usually, population is brought randomly in normal PSO algorithm, which leads into randomcity of searching quality and speed. So these normal algorithms can not be used to some engineering problem that can not be optimized many times but real time. In order to solve above problem, a kind of PSO algorithm based on uniform design to confirm key population in some one generation is given. Initial population of PSO algorithm is brought by uniform design, so distributing of swarms in searching space can keep uniform dispersity much better. Four kinds of methods to bring population is given, test results show that: uniform design method based on range of value division can improve searching efficiency.â…¤. Consciousness selection in social psychology is imported into PSO algorithm, so a kind of asynchronism PSO with selection consciousness is given, which can make swarm has selection ability not to follow blindly preponderant swarm. Test results show that: compared with synchronization model, the algorithm can keep fast convergence speed and good searching quality.â…¥. A kind of immune PID autopilot combining immune algorithm is designed. And the asynchronism PSO algorithm with selection consciousness is used to optimize parameters real time in the new PID autopilot system. Optimization step and method are introduced in a detail. Simulation results show that: the PSO algorithm can improve the robustness of autopilot designed and at the same time, rapidity of the PSO algorithm improved to solve searching problem can proved.â…¦. Nowadays, simplex degaussing targets and difficult optimization decision are main shortages in warships and submarines degaussing system. So a kind of new optimization method based on multi-species space compress strategy PSO is applied to optimization decision of warships and submarines degaussing, which can solve engineering difficulties in warships and submarines degaussing such as variable with large range of value and object functions with multimodal. Steps, results and analyses of the method are discussed in a detail. Simulation results show that: the method can improve speed and quality of warships and submarines degaussing optimization decision and bring good efficiency to warships and submarines degaussing winding system optimization.â…§. The electrical network reconfiguration of shipboard power system (SPS) is one of the most important methods to restore power supply and improve survivability. A new kind of discrete coding method based on uniform design PSO algorithm, and the algorithm is used to electrical network reconfiguration of SPS. In real engineering, methods and rules of swarm compress by fault to extract message are given. Test show that: the PSO algorithm improved is better than other methods to improve the speed of building decision, its searching quality is same with other method, but stability of optimum solution is better than others. The method has good practicability and application foreground in electrical network reconfiguration of SPS.