| 一种辨识Wiener-Hammerstein模型的新方法 |
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| 引用本文： | 徐小平,钱富才,王峰. 一种辨识Wiener-Hammerstein模型的新方法[J]. 控制与决策, 2008, 23(8) |
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| 作者姓名： | 徐小平 钱富才 王峰 |
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| 作者单位： | 西安理工大学,自动化与信息工程学院,西安,710048;西安交通大学,理学院,西安,710049 |
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| 基金项目： | 高等学校博士学科点专项科研项目，陕西省自然科学基金 |
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| 摘 要： | 针对非线性Wiener-Hammerstein模型,提出利用粒子群优化算法对非线性模型进行辨识的新方法.该方法的基本思想是将非线性系统的辨识问题转化为参数空间上的优化问题;然后采用粒子群优化算法获得该优化问题的解.为了进一步增强粒子群优化算法的辨识性能,提出利用一种混合粒子群优化算法.最后,仿真结果验证了该方法的有效性和可行性.
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| 关 键 词： | 辨识 混合 粒子群优化 Wiener-Hammerstein模型 |
New method for identification of Wiener-Hammerstein model |
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| XU Xiao-ping,QIAN Fu-cai,WANG Feng. New method for identification of Wiener-Hammerstein model[J]. Control and Decision, 2008, 23(8) |
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| Authors: | XU Xiao-ping QIAN Fu-cai WANG Feng |
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| Affiliation: | XU Xiao-ping1,QIAN Fu-cai1,WANG Feng2 (1.School of Automation , Information Engineering,Xi'an University of Technology,Xi'an 710048,China,2.School of Sciences,Xi'an Jiaotong University,Xi'an 710049,China.) |
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| Abstract: | For nonlinear Wiener-Hammerstein model,a method for nonlinear system identification is proposed by using particle swarm optimization(PSO) algorithm.The basic idea of the method is that the problems of nonlinear system identification is changed into optimization problems in parameter space and the PSO is then adopted to solve the optimization problem.In order to enhance the performance of the PSO identification,a hybrid particle swarm optimization(HPSO) algorithm is also adopted.Finally,simulation results sh... |
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| Keywords: | Identification Hybrid Particle swarm optimization Wiener-Hammerstein model |
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