文件名称:ApplicationofFuzzyNeuralNetworktoDecouplingControl
- 所属分类：
- 数值算法/人工智能
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- 上传时间：
- 2012-11-26
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- 174kb
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- 0次
- 提 供 者：
- mengxi******
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在工业生产过程中,针对纯迟延、时变、强耦合的多输入多输出现象,提出一种
基于模糊神经网络解耦和PID控制相结合,对系统进行解耦控制的方法。这种方法不需要建
立多变量对象精确的数学模型,通过对大迟延大惯性强耦合的循环流化床锅炉床温-主汽压力
对象进行仿真,其结果表明,解耦控制效果很好,具有良好的静态性、动态性及鲁棒性。
-In the industrial production process for a pure delay, time-varying, strong coupling phenomenon of multiple-input multiple-output is proposed based on fuzzy neural network PID control decoupling and combining the system decoupling control method. This method does not require the establishment of multi-variable mathematical model of the object accurately, through the strong coupling large delay and large inertia of the circulating fluidized bed boiler bed temperature- the main steam pressure simulation objects, and the results show that decoupling control works well, with good static, dynamic and robust.
基于模糊神经网络解耦和PID控制相结合,对系统进行解耦控制的方法。这种方法不需要建
立多变量对象精确的数学模型,通过对大迟延大惯性强耦合的循环流化床锅炉床温-主汽压力
对象进行仿真,其结果表明,解耦控制效果很好,具有良好的静态性、动态性及鲁棒性。
-In the industrial production process for a pure delay, time-varying, strong coupling phenomenon of multiple-input multiple-output is proposed based on fuzzy neural network PID control decoupling and combining the system decoupling control method. This method does not require the establishment of multi-variable mathematical model of the object accurately, through the strong coupling large delay and large inertia of the circulating fluidized bed boiler bed temperature- the main steam pressure simulation objects, and the results show that decoupling control works well, with good static, dynamic and robust.
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下载文件列表
模糊神经网络在解耦控制中的研究.caj