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Fuzzy-based sensor validation for a nonlinear bench-mark boiler under MPC

机译:MPC下非线性基准锅炉的基于模糊的传感器验证

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Most of the power plants are automated with complete closed loop control systems. For this purpose, numerous sensors are required to monitor the proper functioning of the plant. Due to various reasons, these sensors may not be able record actual value of the measured variable. This misleads the controller taking faulty actions on manipulated variables. It is very important to monitor the measured parameters which help not only for operating the plant safely and also predicting the incipient failures of the sensors. In this paper, a fuzzy based data validation algorithm is implemented to a bench mark boiler which is controlled by a model predictive control is presented. A non-linear bench boiler model has been taken for study and a model predictive control(MPC) is implemented and tested on its combustion control unit. Sensor data validation algorithm is developed for oxygen sensor which measures the excess oxygen present on the air/fuel rate of the combustion control unit.
机译:大多数发电厂通过完整的闭环控制系统实现自动化。为此,需要大量传感器来监视设备的正常运行。由于各种原因,这些传感器可能无法记录测量变量的实际值。这会误导控制器对受控变量采取错误的操作。监视所测量的参数非常重要,这不仅有助于工厂安全运行,而且还可以预测传感器的早期故障。本文提出了一种基于模糊的数据验证算法,用于基准锅炉,该算法由模型预测控制来控制。采用了非线性台式锅炉模型进行研究,并在其燃烧控制单元上实施了模型预测控制(MPC)并对其进行了测试。针对氧气传感器开发了传感器数据验证算法,该算法可测量燃烧控制单元的空燃比上存在的过量氧气。

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