DocumentCode :
3476673
Title :
Neuro-PID Control of Hybrid Machines With 2-DOF for Trajectory Tracking Problems
Author :
Chen, Zhenghong ; Wang, Yong ; Li, Yan
fYear :
2007
fDate :
18-21 Aug. 2007
Firstpage :
2467
Lastpage :
2470
Abstract :
A hybrid-driven machine is such a machine where its drive system combines the servomotor and the constant velocity motor, and the machine has the advantage of application flexibility and low cost. In practical application, accurate trajectory control of this machine is essential. To achieve excellent tracking performance, two control approaches, the traditional proportion differential (PD) control and the Neuro-PID (proportion integral differential) control, are adopted to control a hybrid-driven five-bar mechanism in this paper. The control performance of each control approach are compared and simulation results show that the neuro-PID controller is much more effective than the PD controller in terms of the reduction in position tracking errors.
Keywords :
PD control; neurocontrollers; position control; servomechanisms; three-term control; constant velocity motor; hybrid-driven five-bar mechanism; neuro-PID control; proportion differential control; proportion integral differential control; servomotor; trajectory tracking problems; Control systems; Costs; Mechanical engineering; Neural networks; PD control; Pi control; Proportional control; Servomotors; Trajectory; Velocity control; BP; Neuro-PID control; PD control; hybrid machine;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automation and Logistics, 2007 IEEE International Conference on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-1531-1
Type :
conf
DOI :
10.1109/ICAL.2007.4338992
Filename :
4338992
Link To Document :
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