DocumentCode :
592638
Title :
Stable PID control for robot manipulators with neural compensation
Author :
Wen Yu ; Xiaoou Li
Author_Institution :
Dept. de Control Automatico, CINVESTAVIPN, Mexico City, Mexico
fYear :
2012
fDate :
10-13 Dec. 2012
Firstpage :
5398
Lastpage :
5403
Abstract :
In order to minimize steady-state error with respect to uncertainties in robot control, the integral gain of PID control should be increased. Another method is to add a compensator to PD control, such as neural compensator, but the derivative gain of this PD control should be large enough. These two approaches deteriorate transient performances. In this paper, the popular neural PD is extended to neural PID control. The semiglobal asymptotic stability of the neural PID control is proven. The conditions give explicit selection methods for the gains of the linear PID control. A experimental study on an upper limb exoskeleton with this neural PID control is addressed.
Keywords :
asymptotic stability; compensation; industrial manipulators; linear systems; minimisation; neurocontrollers; three-term control; uncertain systems; compensator; derivative gain; explicit selection methods; integral gain; linear PID control gains; neural PID control; neural compensation; proportional-integral-derivative control; robot control uncertainties; robot manipulators; semiglobal asymptotic stability; stable PID control; steady-state error minimization; transient performances; upper limb exoskeleton; Asymptotic stability; Closed loop systems; Manipulators; PD control; Service robots; Stability analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2012 IEEE 51st Annual Conference on
Conference_Location :
Maui, HI
ISSN :
0743-1546
Print_ISBN :
978-1-4673-2065-8
Electronic_ISBN :
0743-1546
Type :
conf
DOI :
10.1109/CDC.2012.6427024
Filename :
6427024
Link To Document :
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