A Multibody Toolbox for Hybrid Dynamic System Modeling Based on Nonholonomic Symbolic Formalism

2018 ◽  
Author(s):  
Jiamin Wang ◽  
Vinay R. Kamidi ◽  
Pinhas Ben-Tzvi
Keyword(s):  
Multibody Dynamics ◽  
Multibody System ◽  
Dynamic Properties ◽  
System Modeling ◽  
Design Tools ◽  
Hybrid Automata ◽  
Constrained Dynamics ◽  
Modular Modeling ◽  
Hybrid Dynamic System ◽  
Dynamic System Modeling

This paper proposes a hybrid multibody dynamics formalism with a symbolical multibody toolbox developed in MATLAB Environment. The toolbox can generate the dynamic model of a multibody system with hybrid and nonholonomic dynamic properties. The framework and software structure of the toolbox are briefly demonstrated. The paper discusses the recursive kinematics and modular modeling theories that help improve the modeling performance and offer accessibility into the dynamic elements. The formalism that offers a symbolic solution to nonholonomic and constrained dynamics is explained in detail. The toolbox also provides design tools and auto-compilation of hybrid automata. Two exemplary models and their simulations are presented to verify the feasibility of the formalism and demonstrate the performance of the toolbox.

PERTURBATION PARAMETERS TUNING OF MULTI-OBJECTIVE OPTIMIZATION DIFFERENTIAL EVOLUTION AND ITS APPLICATION TO DYNAMIC SYSTEM MODELING

2015 ◽  
Vol 75 (11) ◽  
Author(s):  
Mohd Zakimi Zakaria ◽  
Hishamuddin Jamaluddin ◽  
Robiah Ahmad ◽  
Azmi Harun ◽  
Radhwan Hussin ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Dynamic System ◽  
Dynamic Systems ◽  
System Modeling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Structure Selection ◽  
Dynamic System Modeling ◽  
Perturbation Parameters ◽  
Model Structure Selection

This paper presents perturbation parameters for tuning of multi-objective optimization differential evolution and its application to dynamic system modeling. The perturbation of the proposed algorithm was composed of crossover and mutation operators.  Initially, a set of parameter values was tuned vigorously by executing multiple runs of algorithm for each proposed parameter variation. A set of values for crossover and mutation rates were proposed in executing the algorithm for model structure selection in dynamic system modeling. The model structure selection was one of the procedures in the system identification technique. Most researchers focused on the problem in selecting the parsimony model as the best represented the dynamic systems. Therefore, this problem needed two objective functions to overcome it, i.e. minimum predictive error and model complexity.  One of the main problems in identification of dynamic systems is to select the minimal model from the huge possible models that need to be considered. Hence, the important concepts in selecting good and adequate model used in the proposed algorithm were elaborated, including the implementation of the algorithm for modeling dynamic systems. Besides, the results showed that multi-objective optimization differential evolution performed better with tuned perturbation parameters.

scholarly journals Dynamic system modeling of thermally-integrated concentrated PV-electrolysis

2021 ◽  
Vol 46 (18) ◽  
pp. 10666-10681
Author(s):  
Isaac Holmes-Gentle ◽  
Saurabh Tembhurne ◽  
Clemens Suter ◽  
Sophia Haussener
Keyword(s):  
Dynamic System ◽  
System Modeling ◽  
Dynamic System Modeling

Flexible Multibody Dynamics Formulation by Hamilton’s Equations

2010 ◽  
Author(s):  
Martin M. Tong
Keyword(s):  
Multibody Dynamics ◽  
Multibody System ◽  
Mass Matrix ◽  
Equations Of Motion ◽  
Flexible Multibody Dynamics ◽  
Flexible Body ◽  
Flexible Multibody System ◽  
Generalized Coordinates ◽  
Flexible Multibody ◽  
The Matrix

Numerical solution of the dynamics equations of a flexible multibody system as represented by Hamilton’s canonical equations requires that its generalized velocities q˙ be solved from the generalized momenta p. The relation between them is p = J(q)q˙, where J is the system mass matrix and q is the generalized coordinates. This paper presents the dynamics equations for a generic flexible multibody system as represented by p˙ and gives emphasis to a systematic way of constructing the matrix J for solving q˙. The mass matrix is shown to be separable into four submatrices Jrr, Jrf, Jfr and Jff relating the joint momenta and flexible body mementa to the joint coordinate rates and the flexible body deformation coordinate rates. Explicit formulas are given for these submatrices. The equations of motion presented here lend insight to the structure of the flexible multibody dynamics equations. They are also a versatile alternative to the acceleration-based dynamics equations for modeling mechanical systems.

Dynamic System Modeling Based on Recurrent Neural Network

2021 ◽  
Author(s):  
Wenjie Cao ◽  
Cheng Zhang ◽  
Zhenzhen Xiong ◽  
Ting Wang ◽  
Junchao Chen ◽  
...  
Keyword(s):  
Neural Network ◽  
Dynamic System ◽  
Recurrent Neural Network ◽  
System Modeling ◽  
Dynamic System Modeling

Model Pengelolaan Wilayah Pesisir Dalam Rangka Pelestarian Hutan Mangrove

2017 ◽  
Vol 2 (1) ◽  
pp. 98-114
Author(s):  
Arter Datunsolang
Keyword(s):  
Local Government ◽  
Dynamic Systems ◽  
System Modeling ◽  
Coastal Zone Management ◽  
Integrated System ◽  
Economic Conditions ◽  
Mangrove Forests ◽  
Important Conclusion ◽  
Zone Management ◽  
Dynamic System Modeling

This study aimed is to develop a model of coastal zone management that would be best to solve the problems. This study also to identify the bio-physical, social economic conditions of the coastal, and mangrove forests in the area. Using the dynamic system modeling version 2.5, the reseacher found several important conclusion. First, the potential of the coastal areas could be developed in a integrated system. It is based on the consideration that the results of the simulation model through dynamic systems showed changes in the condition of mangrove forests and socio-economic conditions of society. Second, institutional support and infrastructure are also needed for the management of mangrove forests. Local government needs to manage the coastal in a integration manner from all component and it has supported by regulation of local government itself.

Multibody Dynamics — Modeling and Analysis Methods

1991 ◽  
Vol 44 (3) ◽  
pp. 109-117 ◽  
Author(s):  
R. L. Huston
Keyword(s):  
Multibody Dynamics ◽  
Multibody Systems ◽  
System Modeling ◽  
Space Structures ◽  
Dynamics Modeling ◽  
Research Activity ◽  
Modeling And Analysis ◽  
Physical Systems ◽  
Systems Research ◽  
Recent Developments

A review of recent developments in multibody dynamics modeling and analysis is presented. Multibody dynamics is one of the fastest growing fields of applied mechanics. Multibody systems are increasingly being employed as models of physical systems such as robots, mechanisms, chains, cables, space structures, and biodynamic systems. Research activity in multibody dynamics has stimulated research in a number of subfields including formulation methods, system modeling, numerical procedures, and graphical representations. These are also discussed and reviewed.

A localized adaptive soft sensor for dynamic system modeling

2014 ◽  
Vol 111 ◽  
pp. 350-363 ◽  
Author(s):  
Wangdong Ni ◽  
Steven D. Brown ◽  
Ruilin Man
Keyword(s):  
Dynamic System ◽  
System Modeling ◽  
Soft Sensor ◽  
Dynamic System Modeling
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