Affiliation:
1. Qingdao University of Science and Technology
Abstract
A mathematical model of engine throttle as the controlled object is established and then the neural network algorithms and PID control are combined. With the self -learning function of the neural network, self -tunings of PID parameters are realized. The method overcomes disadvantages of PID as parameters which are difficult to determine and embodies better intelligence and robustness of the neural network, the simulation is researched by Matlab and the results show that the PID neural network controller is more accurate and adaptive than conventional PID.
Publisher
Trans Tech Publications, Ltd.
Reference8 articles.
1. H. Li, W.X. Li and D.J. Zhang. Transactions of CSICE, 2003, 21 (4): 253-256. (In Chinese).
2. M.S. Castiglione, G. Stecklein and R. Senseney. Development of transmission hardware- in-the-loop test system . SAE Paper 2003-01-1027, (2003).
3. W.Q. Ai, Q.S. Feng and C.L. Yin. Chinese Internal Combustion Engine Engineering , 2006 , 27 (5) : 57-61. ( In Chinese).
4. B.W. Li, Y. Gao, Z.H. Jia. Micromotors Servo Technique, 2000, 33(1): 21-23. (In Chinese).
5. J.K. Liu. Predictive PID control and its MATLAB simulation. Beijing: Publishing House of Electronics Industry, 2003. (In Chinese).