| 改进协同微粒群优化的模糊神经网络控制系统设计 |
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| 引用本文： | 都延丽,吴庆宪,姜长生,周丽.改进协同微粒群优化的模糊神经网络控制系统设计[J].控制与决策,2008,23(12):1327-1332. |
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| 作者姓名： | 都延丽 吴庆宪 姜长生 周丽 |
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| 作者单位： | 南京航空航天大学,自动化学院,南京,210016 |
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| 基金项目： | 国家自然科学基金
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| 摘 要： | 针对协同微粒群算法不能保证收敛到局部或全局最优值的问题,提出一种改进协同微粒群算法(ICPSO),并证明了该算法能以概率1收敛干全局最优解.应用ICPSO建立一类非线性对象的神经网络辨识模型,并对系统的模糊神经网络自适应控制器的参数进行了离线和在线优化.仿真结果表明,ICPSO能提高系统的建模精度,增强模型的泛化能力,而且由ICPSO训练的控制器可以达到良好的控制效果.
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| 关 键 词： | 改进协同微粒群算法 全局收敛 神经网络辨识 模糊神经网络控制器 |
| 收稿时间： | 2007-9-20 |
| 修稿时间： | 2008-1-10 |
Improved cooperative particle swarm optimizer for design of fuzzy neural network control system |
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| DU Yan-li,WU Qing-xian,JIANG Chang-sheng,ZHOU Li.Improved cooperative particle swarm optimizer for design of fuzzy neural network control system[J].Control and Decision,2008,23(12):1327-1332. |
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| Authors: | DU Yan-li WU Qing-xian JIANG Chang-sheng ZHOU Li |
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| Affiliation: | DU Yan-li,WU Qing-xian,JIANG Chang-sheng,ZHOU Li(College of Automation Engineering,Nanjing University of Aeronautics , Astronautics,Nanjing 210016,China. |
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| Abstract: | An improved cooperative PSO(ICPSO) is proposed for the cooperative PSO' incapable of converging at the local or global optimum.It is proved that the algorithm can converge at the global optimization solution with probability one.ICPSO is applied to the neural network modeling of a nonlinear plant,and also employed to the offline and online training of the fuzzy neural network adaptive controller in the system.Simulation results show that ICPSO has advantages of increasing the precision and enhancing the gen... |
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| Keywords: | Improved cooperative particle swarm optimization Global convergence Neural network identification Fuzzy neural network controller |
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