The Study of Trajectory Automatic Control Based on RBF Neural Network PID Control

被引：0
|
作者：
Du Zhenmian [1 ]
Ye Zhengmao [1 ]
Zhang Hui [1 ]
Bai Hua [1 ]
Xu Yuanli [2 ]
Jiang Xianguo [2 ]
机构：
[1] Harbin Inst Technol, Sch Mechatron Engn, Harbin, Peoples R China
[2] Nucl Power Inst China, Reactor Engn Res Inst, Chengdu, Peoples R China
来源：
PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON FLUID POWER AND MECHATRONICS - FPM 2015 | 2015年
关键词：
Hydraulic excavator; Trajectory control; PID; RBF;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
For the hot and difficult issues of trajectory automatic control based on single bucket hydraulic excavator, this paper introduce the control method of combining RBF neural network with traditional PID. By setting up the mathematical model of machine-electricity-hydraulic control system, using the MATLAB-Simulink simulation analysts to get the conclusion that based on RBF neural network PID control is superior to the conventional PID control. This control method can make the system have the adaptability, automatically adjust the control parameters, adapt to the changes in the charged process, improve the control performance and reliability and provide a theory basis to further realize the excavator trajectory intelligent control.
引用
收藏
页码：1234 / 1238
页数：5
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