Particle Swarm Optimization Methods And Its Applications In Parameter Identification Of Ship Motions

In the field of ship motion control, there are two purposes to establish the ship motion model. One is to establish a ship maneuvering simulator, providing a basic simulation platform for the study about close-loop system. The other is to service the design of ship motion controller. It is difficult to guarantee the accuracy of hydrodynamic parameters obtained through theoretical calculations or experiments, so many people obtain the hydrodynamic parameters by the identification algorithm. In the process of algorithm execution, this problem can be regarded as an optimization search.Particle Swarm Optimization (PSO) algorithm is a swarm intelligence optimization algorithm proposed in the 1990s. The superiority of distributed solution model of problem in solving combinatorial optimization problem is great, and this causes large attention of the concerned fields. The practice has shown that, particle swarm optimization algorithm can well solve problems of multi-constraint optimization under complicated nonlinear conditions. This paper is mainly about particle swarm optimization algorithm and its application in the hydrodynamic parameter identification of ship motion, including:1. The basic principle of the particle swarm optimization algorithm is summarized and the topology of PSO algorithm is analyzed in detail. Then, the influence of the topology to algorithm performance is analyzed. Last, some test results about PSO algorithm of different structures to the benchmark function in different aspects, such as algorithm performance, convergence rate, and rate of searching the optimization and so on are given.2. The convergence of PSO algorithm is analyzed in detail. And the influence of parameters in PSO algorithm to some aspects, such as algorithm accuracy, rate of up to optimization and so on is analyzed in detail. Then a method which optimizes and selects parameters of the bottom PSO algorithm by using a top PSO algorithm is presented. The bottom PSO algorithm is applied to optimize function. The comparison of aloogorithm simulation and performance shows that this method can implement parameters optimization and the selection of PSO algorithm convenient effectively.3. Considered the improvements of optimization capacity and speed, PSO algorithms based on evolutionary and phased search are designed. PSO algorithm based on evolutionary introduces an evolutionary strategy to increase the diversity of particles based on the standard PSO algorithm. In the process of algorithm iteration and optimization, the evolutionary PSO algorithm is constructed and the global search capabilityof the algorithm is improved through some operations on particles such as selection, mutation and so on. Making use of parameters convergence characteristics, PSO algorithm based on phased search divides parameters into groups, then identifies them. The solution makes clear that this algorithm can identify them quickly, and verify the effectiveness of the algorithm. The algorithm is particularly suitable for high-dimensional complex identification system.4.The paper describes problem about parameter identification of ship vertical motion, and analyzes all factors to be taken into account. Then it analyzes the characteristics of these observed data, and gives a data pretreatment method. Moreover, two different modeling methods of parameters input are designed and simulated. Based on the relative theories in fuzzy CMAC neural network and the data from strip theory calculating and pool experiment, the adaptive nonlinear parameter model, which can adapt to any changes of course, speed and sea condition is built. The model provides the effective searching space of hydrodynamic parameters identification. In order to investigate the algorithm ability to adapt to noise, two simulations with and without noise are taken and compared. The result shows that the improved PSO can identify ship vertical motion hydrodynamic parameters accurately, and provides a new solution for hydrodynamic parameters identification.5.The paper also describes problem about parameter identification of ship lateral motion, and analyses problems and solutions about this problem. It comes up with a method to calculate parameters sensitivity coefficients due to the characteristic of many ship lateral movement hydrodynamic parameters and high coupling, and classifies parameters according to sensitivity coefficients, then identifies them with phased method. The simulation results indicate that this method can carry on ship lateral motion hydrodynamic parameters identification correctly and effectively.