University of Wollongong
Browse

Optimum dynamic balancing of planar parallel manipulators

Download (598.32 kB)
conference contribution
posted on 2024-11-13, 22:38 authored by Gursel AliciGursel Alici, B Shirinzadeh
This paper presents a methodology for optimum dynamic balancing of planar parallel manipulators typified with a variable speed 2 DOF parallel manipulator articulated with revolute joints. The dynamic balancing is formulated as an optimisation problem such that a sum-squared values of bearing forces, driving torques, shaking moment, and the deviation of the angular momentum from its mean value are minimized throughout an operation range of the manipulator, provided that a set of balancing constraints consisting of the shaking force balancing conditions, the sizes of some inertial and geometric parameters are satisfied. Sets of optimisation results corresponding to various combinations of the elements of the objective function are evaluated in order to quantify their influence on the resulting bearing forces, the driving torques, shaking moment and force. The results prove that the proposed optimisation approach can be used to minimize any desired combination of the forces, moments, and torques involved in any parallel mechanism by choosing a suitable set of weighting factors. The method is systematic, versatile and easy to implement for the optimum balancing of the parallel manipulator and more general parallel manipulators.

History

Citation

This article was originally published as: Alici, G and Shirinzadeh, B, Optimum Dynamic Balancing of Planar Parallel Manipulators, Proceedings IEEE International Conference on Robotics and Automation (ICRA-2004), 26 April-1 May 2004, vol 5, 4527-4532. Copyright IEEE 2004.

Parent title

Proceedings - IEEE International Conference on Robotics and Automation

Volume

2004

Issue

5

Pagination

4527-4532

Language

English

RIS ID

10764

Usage metrics

    Categories

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC