多变量强耦合时变系统的PID神经网络控制 |
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引用本文: | 舒怀林,郭秀才.多变量强耦合时变系统的PID神经网络控制[J].工矿自动化,2003(5):16-18. |
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作者姓名: | 舒怀林 郭秀才 |
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作者单位: | 1. 广州大学信息与控制技术研究所,广东,广州,510091 2. 西安科技大学电气与控制工程学院,陕西,西安,710054 |
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摘 要: | 介绍了一种新的神经网络———PID神经网络及其多变量强耦合时变控制系统。文中给出了网络的结构和算法,分析了时变对象的特点,对一组二变量强耦合时变系统进行了实时仿真。仿真结果显示:PID神经网络对多变量强耦合时变对象具有良好的解耦性能和自学习控制特性。
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关 键 词: | 多变量 时变系统 神经网络 自学习控制 解耦控制 PID |
文章编号: | 1671-251X(2003)05-0016-03 |
修稿时间: | 2003年5月16日 |
PID Neural Network Control System of Multi-variable and Strong-coupled Time-varying System |
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Abstract: | The paper introduced a new kind of neural network: PID neural network and its multi variable and strong coupled time varying system. The structure and the algorithm were given, the characteritics of the time varying system were analyzed, the real time simulation results of double variable and strong coupled time varying system were shown. It proved that the PID neural network has perfect decouple and self learning control performance for strong coupled time varying system. |
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Keywords: | multi-variable time-varying system neural network self-learning control decouple control PID |
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