JOURNAL ARTICLE

Dynamic hybrid position/force control of robot manipulators-controller design and experiment

Takuma YoshikawaToshiharu SugieM. Tanaka

Year: 1988 Journal:   IEEE Journal on Robotics and Automation Vol: 4 (6)Pages: 699-705   Publisher: Institute of Electrical and Electronics Engineers

Abstract

An approach to designing controllers for dynamic hybrid position/force control of robot manipulators is presented, and preliminary experimental results are given. Dynamic hybrid control is an extension of an approach proposed by M.H. Raibert and J.J. Craig (1981) to the case where the full manipulator dynamics is taken into consideration and the end-effector constraint is explicitly given by the constraint hypersurfaces. This design method consists of two steps. The first step is the linearization of the manipulator dynamics by nonlinear state feedback. Formulation of the constraint by the constraint hypersurfaces plays an essential role in establishing the linearizing law. The second step is the design of position and force controllers for the linearized model using the concept of two-degrees-of-freedom servocontroller. The merit of this servocontroller is that it can take account of both the command response and the robustness of the controllers to modeling errors and disturbances. Preliminary experiments using a SCARA robot show the validity of the approach.< >

Keywords:
Control theory (sociology) SCARA Robustness (evolution) Control engineering Robot Linearization Constraint (computer-aided design) Position (finance) Nonlinear system Computer science Controller (irrigation) Engineering Control (management) Artificial intelligence Physics

Metrics

181
Cited By
4.16
FWCI (Field Weighted Citation Impact)
25
Refs
0.95
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Robot Manipulation and Learning
Physical Sciences →  Engineering →  Control and Systems Engineering
Teleoperation and Haptic Systems
Physical Sciences →  Engineering →  Mechanical Engineering
Robotic Mechanisms and Dynamics
Physical Sciences →  Engineering →  Control and Systems Engineering

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