Improved Artificial Fish Swarm Algorithm and its Application in System Identification

摘要：

　　In order to solve the traditional identification method limitations,This paper presents an improved artificial fish swarm algorithm,Through the experiment of a typical Needle-in-haystack problem,Show that the improved artificial fish swarm algorithm has better ability of global optimization,faster convergence speed,higher accuracy of optimization.This algorithm is applied to the system parameter identification,Through to the linear system and nonlinear system parameter identification simulation,Results show that the algorithm has fast convergence,high accuracy advantages,Has important application value in Engineering.

关键词： Artificial Fish Swarm Algorithm Needle-in-haystack Problem Parameter Identification

作者: Junlin Zhu Hui Liu Zulin Wang

作者单位: College of Electrical Engineering and Automation Jiangxi University of Science and Technology Ganzhou,Jiangxi,China

会议类型: 国际会议

会议名称: the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT-2012)(2012年电机工程与信息技术国际会议)

会议地点: 沈阳

会议语种:英文

页码: 1994-1997

在线出版日期: 2012-09-26（万方平台首次上网日期，不代表论文的发表时间）