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Tolerance Synthesis of Delta-like Parallel Robots Using a Nonlinear Optimisation Method

التفاصيل البيبلوغرافية
العنوان: Tolerance Synthesis of Delta-like Parallel Robots Using a Nonlinear Optimisation Method
المؤلفون: Allaoua Brahmia, Adlen Kerboua, Ridha Kelaiaia, Ameur Latreche
المصدر: Applied Sciences, Vol 13, Iss 19, p 10703 (2023)
بيانات النشر: MDPI AG, 2023.
سنة النشر: 2023
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: Delta parallel robot, modelling, tolerance synthesis, nonlinear optimisation, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: Robotic systems require high accuracy in manipulating objects. Positioning errors are influenced by geometric tolerances and various sources. This paper introduces a new technique based on the interior-point algorithm optimisation method to allocate tolerances to the geometric parameters of a robot. This method consists of three steps. First, a method for modelling the kinematic problem as well as the geometric errors must be used. The Denavit–Hartenberg rule is the most suitable method for this modelling case. Then, a mathematical model for tolerance allocation is developed and used as a nonlinear multivariable optimisation problem. Finally, the “interior-point” algorithm is used to solve this optimisation problem. The accuracy and efficiency of the proposed method, in determining the tolerance allocations for a Delta parallel robot, is illustrated via calculation and simulation results. The values of the dimensional tolerances found are optimal. As a result, these values always keep the accuracy less than or equal to the imposed value.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/13/19/10703; https://doaj.org/toc/2076-3417
DOI: 10.3390/app131910703
URL الوصول: https://doaj.org/article/b0771defad304398970fa58329503902
رقم الأكسشن: edsdoj.b0771defad304398970fa58329503902
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app131910703