Title :
Neural networks in friction compensation, velocity and acceleration measurement and PID design
Author :
Qiang, Sheng ; Gao, X.Z. ; Zhuang, Xianyi
Author_Institution :
Dept. of Control Sci. & Eng., Harbin Inst. of Technol., China
Abstract :
It is well known that in motor systems, friction is the main factor that degrades the overall servo performance. PID controllers based on the velocity and acceleration signals feedback can be used to reduce the tracking error, improve the robustness for modeling errors, as well as combat with the harmful friction. In this paper, we give an overview on the applications of neural networks in external friction compensation, velocity and acceleration measurement, and PID parameter design and tuning in servomotor systems.
Keywords :
compensation; feedback; friction; machine control; radial basis function networks; servomotors; three-term control; tuning; PID controllers; acceleration measurement; feedback; friction compensation; friction. compensation; modeling errors; parameters tuning; radial basis function neural networks; robustness; servomotor systems; velocity measurement; Acceleration; Accelerometers; Degradation; Error correction; Friction; Neural networks; Servomechanisms; Servomotors; Three-term control; Velocity control;
Conference_Titel :
Industrial Technology, 2002. IEEE ICIT '02. 2002 IEEE International Conference on
Print_ISBN :
0-7803-7657-9
DOI :
10.1109/ICIT.2002.1189865
