Parameter Identification of Bilinear System Based on Genetic Algorithm

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• 作者：Zhelong Wang ; Hong Gu
• 刊名：Lecture Notes in Computer Science
• 出版年：2007
• 出版时间：2007
• 年：2007
• 卷：4688
• 期：1
• 页码：83-91
• 全文大小：199 KB
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349

文摘

The paper presents a method for the identification of bilinear system parameters by using an improved Genetic Algorithm. Good results could still be obtained when the system output was influenced by Gaussian noise in the simulation. By comparing with RLS and COR through a simulation experiment to a SISO bilinear system, it is found that the method can get better result than the other two methods. Through a simulation experiment to a MIMO bilinear system, the method can get reasonably good results too. These simulations show that the method is simpler and can get better results than RLS and COR. Through a simulation study to an MIMO bilinear system, good results can still be got. In the last section, the paper describes that a hybrid GA, the combination of Genetic Algorithm and nonlinear Least Square, was developed to identify bilinear system structure and parameters simultaneously.