Adaptive neural fuzzy PID control of common rail pressure for diesel engine
                                                        XU Long, CHEN Guo jin, ZHU Ling jun, CHEN Chang
                         (School of Mechanical Engineering, Hangzhou Dianzi University, Hangzhou 310018, China)

Abstract: Aiming at the precise control of the common rail pressure of the high pressure common rail diesel engine, the control method of the common rail pressure was summarized, and a common rail pressure control algorithm based on the adaptive neuro fuzzy inference system (ANFIS) and PID controller was proposed.Firstly, in the Matlab / Simulink environment, the simulation model of the control algorithm of rail pressure was established by using the adaptive neural fuzzy PID controller, and the simulation was compared with the conventional PID control. Secondly, the fluctuation curve of the common rail pressure was monitored by experiment, the control effect of the two control methods under the two kinds of transition conditions of starting and accelerating was observed. The results indicate that the steady state, dynamic characteristics and the adaptive neural fuzzy PID control are obviously better than those of conventional PID control. At the same time, under the two transition conditions of starting and accelerating, the fluctuation range of common rail pressure is small, meeting the requirement of common rail pressure stability in practical application.

Key words: high pressure common rail; common rail pressure; adaptive neuro fuzzy inference system; PID control