{"title":"Dynamic modeling method for constrained system with singular mass matrices","authors":"Jin Yu , Wei Zhang , Rediet Tesfaye Zeru , Yuxi Xiao , Senchun Chai","doi":"10.1016/j.apm.2024.115780","DOIUrl":null,"url":null,"abstract":"<div><div>The dynamic model is beneficial for system control design, especially when it is related to precise force adjustment. Traditional modeling methods make it difficult to address multi-body systems with singular mass matrices or are computationally expensive. In this paper, an approach termed the Extended Rosenberg Embedding Method for dynamic modeling is presented. By incorporating the constraints directly into the Fundamental Equation, the proposed approach enables the description of the system motion in two separate equations, which can reduce the computational cost of the constrained dynamic model. This method provides a new way to establish motion equations, regardless of whether the system is subject to holonomic or non-holonomic constraints. Moreover, as the method does not impose direct requirements on the rank of the mass matrix, it is capable of handling the modeling of multi-body systems with singular mass matrices. The validity of the proposed method is substantiated through rigorous mathematical derivation, while its accuracy and computational efficiency are corroborated through the examination of two numerical examples.</div></div>","PeriodicalId":50980,"journal":{"name":"Applied Mathematical Modelling","volume":"138 ","pages":"Article 115780"},"PeriodicalIF":4.4000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Mathematical Modelling","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0307904X2400533X","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
The dynamic model is beneficial for system control design, especially when it is related to precise force adjustment. Traditional modeling methods make it difficult to address multi-body systems with singular mass matrices or are computationally expensive. In this paper, an approach termed the Extended Rosenberg Embedding Method for dynamic modeling is presented. By incorporating the constraints directly into the Fundamental Equation, the proposed approach enables the description of the system motion in two separate equations, which can reduce the computational cost of the constrained dynamic model. This method provides a new way to establish motion equations, regardless of whether the system is subject to holonomic or non-holonomic constraints. Moreover, as the method does not impose direct requirements on the rank of the mass matrix, it is capable of handling the modeling of multi-body systems with singular mass matrices. The validity of the proposed method is substantiated through rigorous mathematical derivation, while its accuracy and computational efficiency are corroborated through the examination of two numerical examples.
期刊介绍:
Applied Mathematical Modelling focuses on research related to the mathematical modelling of engineering and environmental processes, manufacturing, and industrial systems. A significant emerging area of research activity involves multiphysics processes, and contributions in this area are particularly encouraged.
This influential publication covers a wide spectrum of subjects including heat transfer, fluid mechanics, CFD, and transport phenomena; solid mechanics and mechanics of metals; electromagnets and MHD; reliability modelling and system optimization; finite volume, finite element, and boundary element procedures; modelling of inventory, industrial, manufacturing and logistics systems for viable decision making; civil engineering systems and structures; mineral and energy resources; relevant software engineering issues associated with CAD and CAE; and materials and metallurgical engineering.
Applied Mathematical Modelling is primarily interested in papers developing increased insights into real-world problems through novel mathematical modelling, novel applications or a combination of these. Papers employing existing numerical techniques must demonstrate sufficient novelty in the solution of practical problems. Papers on fuzzy logic in decision-making or purely financial mathematics are normally not considered. Research on fractional differential equations, bifurcation, and numerical methods needs to include practical examples. Population dynamics must solve realistic scenarios. Papers in the area of logistics and business modelling should demonstrate meaningful managerial insight. Submissions with no real-world application will not be considered.