A study of expert control system of oil pump energy-saving based on genetic neural network

Autor: Li Min, He Ping, Qian Yuheng
Rok vydání: 2009
Předmět:
Zdroj: 2009 Chinese Control and Decision Conference.
DOI: 10.1109/ccdc.2009.5195163
Popis: In order to deal with the problem of light load operation of most oil pumps in oil fields, an oil pump energy-saving “intermittent start-stop” operation method based on genetic neural network and expert control is proposed in this paper. At first, the structure of fuzzy neural network reasoning machine based on rules is introduced in the paper, which is used as an inference engine to deal with the difficulty of acquiring knowledge and the weak inference. To improve the performance of the system, the genetic algorithm is used to make the off-line training of the inference engine, and the rule inference of traditional expert system is used for the transparency of system with agility in system. Finally, the structure of genetic neural network expert control system is given and used in oil pump control that achieves the desired energy-saving effects.
Databáze: OpenAIRE