Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C)
DOI: 10.1109/robot.1999.772394
|View full text |Cite
|
Sign up to set email alerts
|

New results in NPID control: tracking, integral control, friction compensation and experimental results

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

2
49
0

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 23 publications
(51 citation statements)
references
References 18 publications
2
49
0
Order By: Relevance
“…Ferretti, Magnani and Zavala Río 7 proposed to apply during the impact a feedforward determined empirically combined with the force regulator, in order to avoid contact losses. The switching of parameters was introduced in force control by B. Armstrong et al 8,9 , in a study similar to the present work. The authors switch the gain matrix according to the state of the system.…”
Section: Introductionmentioning
confidence: 70%
“…Ferretti, Magnani and Zavala Río 7 proposed to apply during the impact a feedforward determined empirically combined with the force regulator, in order to avoid contact losses. The switching of parameters was introduced in force control by B. Armstrong et al 8,9 , in a study similar to the present work. The authors switch the gain matrix according to the state of the system.…”
Section: Introductionmentioning
confidence: 70%
“…In addition, it is doubtful that our sensors would achieve the required resolution [3]. Since the prospects for increasing performance with linear feedback are limited, we turned our attention to a class of nonlinear controllers -nonlinear pd controllers [4] which are known to be able to deal with dry friction while preserving a smooth response. These controllers come in many types.…”
Section: Methodsmentioning
confidence: 99%
“…However, the use of a fixed gain may lead to control input saturation and even the generation of limit cycles. To overcome this, a nonlinear gain-scheduling strategy can be introduced [21]. Fig.…”
Section: R Eal-time Eva L Uat I O Nmentioning
confidence: 99%