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Biomass Boiler Drum Water Level Control System using Neural Networks

机译:生物质锅炉鼓水位控制系统使用神经网络

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Biomass energy transforms solar energy into chemical energy and the energy is stored in the organisms internally with the help of the photosynthesis. In the biomass boiler combustion system, the boiler drum water level is an important parameter and it is a sign to measure regardless of whether boiler steaming water system is in balance. For a nonlinear process as water level control in boilers, conventional control theory is not an appropriate choice. In this study, a neural network based predictive controller is designed and implemented through simulation in MATLAB software for biomass boiler's drum water level control. Performance of neural network controller is compared with conventional PID (Proportional + Integral + Derivative) controller for boiler drum water level control system and it is observed that the neural network based approach is more efficient than conventional PID controller.
机译:生物质能量将太阳能转化为化学能量,并且在光合作用的帮助下,能量在内部储存在生物体中。 在生物质锅炉燃烧系统中,锅炉鼓水位是一个重要参数,无论锅炉蒸水系统是否平衡,它都是一个重要的参数。 对于作为锅炉中的水位控制的非线性过程,传统的控制理论不是适当的选择。 在本研究中,通过Matlab软件的模拟设计和实现基于神经网络的预测控制器,用于生物质锅炉的鼓水位控制。 与锅炉鼓水位控制系统的传统PID(比例+积分+衍生物)控制器进行比较神经网络控制器的性能,并且观察到基于神经网络的方法比传统的PID控制器更有效。

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