A Study of PID Control System Based on BP Neural Network
To deal with the defects of the steepest descent in slowly converging and easily immerging in partialm in imum,this paper proposes a new type of PID control system based on the BP neural network, which is a combination of the neural network and the PID strategy. It has the merits of both neural network and PID controller. Moreover, Fletcher-Reeves conjugate gradient in controller can make the training of network faster and can eliminate the disadvantages of steepest descent in BP algorithm. The parameters of the neural network PID controller are modified on line by the improved conjugate gradient. The programming steps under MATLAB are finally described. Simulation result shows that the controller is effective.
Back-propagation (BP) Neural network Improved conjugate gradient Proportional-integral-derivative(PID) control
Wei Liu Jianjun Cai Xipin Fan
Department of Personnel, Hebei chemical & pharmaceutical college, China College of Mechanial & Electronic Engineering, Hebei University of Science and Technology,Chinac Department of Electrical and Mechanical Engineering, Hebei chemical & pharmaceutical college,China
国际会议
2011 International Conference on Mechatronics and Materials Processing(2011年机电一体化与材料加工国际会议 ICMMP)
广州
英文
1908-1911
2011-11-18(万方平台首次上网日期,不代表论文的发表时间)