The intelligent learning control using single neuron and its application in an industrial boiler
Zhang Shu-ling, Keming Xie · 2002
This paper discusses a practicable, adjustable and highly effective plan. It presents a novel and practical algorithm combing human experience with control methods to form an intelligent controller (IC). This idea is used in the combustion process of an industrial boiler. In this IC, central parameters are determined based on human experience. An industrial boiler is complex, multivariable and uncertain with time delays. A single neuron is used to regulate the control parameters. A new controller is composed of IC and the single neuron (NIC). The single neuron can change the control parameters. The simulation results show the effectiveness of the control algorithm. For a complex plant, it has strong robustness and satisfactory characteristics.