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Multi-criteria Design Optimization of Parallel Robots

Authors: Ramazan Unal; Güllü Kiziltas; Volkan Patoglu;

Multi-criteria Design Optimization of Parallel Robots

Abstract

This paper presents a framework for multi-criteria design optimization of parallel mechanisms. Pareto methods characterizing the trade-off between multiple design criteria are advocated for multi-criteria optimization over widely used scalarization approaches and Normal Boundary Intersection method is applied to efficiently obtain the Pareto-front hyper-surface. The proposed framework is compared against sequential optimization and weighted sum approaches. Dimensional synthesis of a sample parallel mechanism (five-bar mechanism) is demonstrated through estimation of the relative weights of performance indices that are implicit in the Pareto plot. The framework is computational efficient, applicable to any set of performance indices, and extendable to include any number of design criteria that is required by the application.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Average
Top 10%
Average
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