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Neurofuzzy network modelling and control of steam pressure in 300 MW steam-boiler system

机译:300 MW蒸汽锅炉系统的神经模糊网络建模与蒸汽压力控制。

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In boiler-generation system, steam pressure is an important factor affecting the total combustion system. A properly boiler system must maintain a desired steam pressure at the outlet of the drum. Modelling and control of 300 MW steam-boiler combustion system using neurofuzzy methodology is discussed in this paper. Associate memory network (AMN) is chosen to represent the nonlinear model of steam pressure system based on local mechanism model and dynamic experiments. With the established neurofuzzy model, a relative fuzzy PI controller is constituted. The performance of the control system has been verified by the simulation process and then tested on real-time process in distributed control system (DCS) under the setpoint tracking and load disturbance.
机译:在锅炉发电系统中,蒸汽压力是影响整个燃烧系统的重要因素。正确的锅炉系统必须在滚筒的出口处保持所需的蒸汽压力。本文讨论了使用神经模糊方法对300 MW蒸汽锅炉燃烧系统进行建模和控制的方法。基于局部机理模型和动态实验,选择关联记忆网络(AMN)来表示蒸汽压力系统的非线性模型。利用建立的神经模糊模型,构造了相对模糊的PI控制器。通过仿真过程验证了控制系统的性能,然后在设定值跟踪和负载扰动下,在分布式控制系统(DCS)中对实时过程进行了测试。

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