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质量管理图中趋势模态及阶跃模态的模糊神经网络识别 被引量:10
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作者 李孟清 张春良 +1 位作者 杨叔子 陈志祥 《中国机械工程》 EI CAS CSCD 北大核心 2004年第22期1998-2001,共4页
建立了智能识别趋势模态及阶跃模态的模糊神经网络模型 ,讨论了模糊神经网络模型的结构、训练样本的构造及训练算法 ,最后用实验数据对该模型作了测验。结果证明该模型的反应速度及精度都优于BP网 。
关键词 趋势模态 阶跃模态 模糊神经网络 模型 质量管理图
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Multi-model Predictive Control of Ultra-supercritical Coal-fired Power Unit 被引量:6
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作者 王国良 阎威武 +2 位作者 陈世和 张曦 邵惠鹤 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2014年第7期782-787,共6页
The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi... The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming(LP) combined with quadratic programming(QP) is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. load, main steam temperature and main steam pressure). The step response models for the dynamic matrix control(DMC) are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in simulation with satisfactory performance. 展开更多
关键词 Ultra-supercritical power unit Coordinated control Multi-model constrained predictive control
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