Pareto-front analysis of a monotonie PI control law for slip suppression in a robotic manipulator

Anna Prach, John John Cabibihan, Nitish V. Thakor, Dennis S. Bernstein

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

This paper presents a novel slip-suppression controller for a two-fingered robotic manipulator, where the goal is to minimize the slip distance without using excessive force. To do this, we consider monotonic PI (MPI) control, which is a nonlinear extension of linear proportional-integral (PI) control. The advantage of MPI control is the fact that the normal force of the gripper is prohibited from decreasing during the transition from predominantly proportional control to predominantly integral control as occurs in the case of linear PI control. The performance of the MPI control is compared to linear PI control for a range of controller parameters, and the tradeoff between the maximum normal force and the total slip distance is efficiently captured by Pareto-front analysis. The robustness of MPI is assessed by considering uncertainty in the body mass and friction parameters, as well as the effect of measurement noise and actuator dynamics.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2728-2733
Number of pages6
ISBN (Electronic)9781538637418
DOIs
StatePublished - Mar 23 2018
Externally publishedYes
Event2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017 - Macau, China
Duration: Dec 5 2017Dec 8 2017

Publication series

Name2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
Volume2018-January

Other

Other2017 IEEE International Conference on Robotics and Biomimetics, ROBIO 2017
Country/TerritoryChina
CityMacau
Period12/5/1712/8/17

ASJC Scopus subject areas

  • Artificial Intelligence
  • Mechanical Engineering
  • Control and Optimization
  • Modeling and Simulation

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