【摘要】 粒子群优化算法是一种模拟鸟群捕食行为的群体智能算法,该算法具有简洁、易于实现、没有太多调整参数及不需要梯度信息等特点,且在大多数情况下可快速收敛于最优解.为了描述材料的磁滞特性,提出了一种粒子群优化算法结合MATLAB/Simulink动态仿真集成环境的Jiles-Atherton磁滞回线模型参数计算方法,并分别以无噪及加噪的仿真数据对2组参数值不同的Jiles-Atherton磁滞回线模型进行了数值实验.结果表明,将粒子群优化算法及MATLAB/Simulink动态仿真集成环境应用于Jiles-Atherton磁滞模型的参数计算是有效的.更多还原

【Abstract】 Particles swarm optimization algorithm was a kind of swarm intelligence algorithm simulating birds feeding behavior. The algorithm had the advantages of concision,easy implement,few control parameters,did not need the gradient information,and fast convergence to optimal solution in most cases. In order to describe the hysteresis characteristics of the material,it was proposed a method of the particle swarm optimization algorithm combination with MATLAB / Simulink dynamic simulation integration environment to calculate the JilesAtherton hysteresis loop model parameters. By means of noise-free and noisy simulation data,the numerical experiments of Jiles-Atherton hysteresis loop model with the two groups of different parameter values were carried out. The results indicated that the particle swarm optimization algorithm combination with MATLAB / Simulink dynamic simulation integration environment was an effective technique for the parameters calculation of Jiles-Atherton hysteresis model.更多还原