The application on fuzzy neural control in boiler liquid level control system: The application on fuzzy neural control in boiler liquid level control system

Cheng, Huanxin; Zhang, Guoqing; Li, Jing; Cheng, Li; Kong, Lingling

doi:10.1201/b19635-92

Cited by 1 publication

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“…There is a known method for controlling elements of an energy technology complex using a neural network [22], involving regulation of the water level in the drum of a power boiler unit using a Hopfield network. The disadvantage of this method is the lack of scaling in relation to various objects of heat and power engineering.…”

Section: Methodsmentioning

confidence: 99%

Combined Approach to Analysis and Regulation of Thermodynamic Processes in the Energy Technology Complex

2021

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The purpose of this work is to increase the theoretical and methodological approaches to value and regulate the dynamics of management processes. Application of these dynamics is implemented via methods of improving the quality of management of complex energy technology systems in the organization of recycling processes. As a result of the research, a technological model of a rotary kiln with a division into separate sections corresponding to the combustion zones for the production of cement clinker in recycling technology was developed. Mathematical modeling, analytical calculations of thermodynamic and gas-dynamic processes in the drums of rotating furnaces, and experimental studies were carried out. As a scientific novelty, an approximation of piecewise linear functions is obtained for modeling the processes of improving the quality of control by the criterion of reducing the error of data transmission for monitoring and regulating the thermodynamic parameters of the furnace via analog-to-digital methods. An algorithmic scheme of the method of in-depth analysis of management quality using data science tools in the concept of combining organizational, economic, technical, technological, and mathematical methods and methods of data collection, processing, and storage of big data is developed. This made it possible to apply the models in the formed energy technology complex using learning neural network algorithms. The possibilities of applying the methodology of combining methods for in-depth analysis and modeling of thermodynamic processes in an energy technological complex with any composition of equipment for the production of cement clinker are substantiated.

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Section: Methodsmentioning

confidence: 99%