Digital Twin Development and cloud deployment for a DC Motor Control embedded system

Khaled, Nassim; Pattel, Bibin; Siddiqui, Affan

doi:10.1016/b978-0-12-821631-6.00009-8

Cited by 3 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Detailed instructions on running various MATLAB, Simulink, and Simscape multiphysics simulation models on the Amazon cloud were created by Khaled et al [48]. The authors did not use containers but aimed to promote physics-based models running on the cloud to improve real assets' diagnostics and prognostics.…”

Section: Related Workmentioning

confidence: 99%

Reference Architecture for Running Computationally Intensive Physics-Based Digital Twins of Heavy Equipment in a Heterogeneous Execution Environment

2022

View full text Add to dashboard Cite

Physics-based digital twins for heavy equipment provide a powerful tool for improving operation and maintenance activities. In contrast to data-driven models, they present more explainable and confident results but require more computational power. Besides the problem of physics-based digital twins creation, there is a task of managing their lifecycle, including their execution, maintenance, storage, and updating. The features distinguishing this kind of digital twins are the mobility of the real counterpart, operation in remote locations, long lifecycle, information sensitivity, and gaps in information technology awareness among the equipment owners and users. This paper presents a methodology and reference architecture for a set of interconnected systems capable of running digital twins of heavy equipment in such conditions. A data model for preserving digital twin-related information for decades of machine operation is described. Operating-system-level virtualization technologies are used to run digital twins in a heterogeneous execution environment. An example of the reference architecture implementation is presented for the physics-based digital twins of a mobile log crane. The experimental part of the paper includes a comparison of computing time for different types of digital twins in different execution environments. It highlights the peculiarities related to running physics-based digital twins in containers. Experiments were performed using the Amazon cloud platform, an edge computing system represented by a single-board microcomputer based on ARM architecture, and a virtual machine on a desktop personal computer. Experimental results show that physics-based digital twins for the analysis of the multi-body dynamics can be run within the proposed architecture with real-time performance in all three types of execution environments. The paper demonstrates the practical implementation of physics-based digital twins for heavy equipment and defines directions for future research in this field.

show abstract

Section: Related Workmentioning

confidence: 99%

Reference Architecture for Running Computationally Intensive Physics-Based Digital Twins of Heavy Equipment in a Heterogeneous Execution Environment

2022

View full text Add to dashboard Cite

show abstract

“…When designing a DC Motor Control system, it is important to consider the type of motor and its use case [24,25,26]. When one has chosen a type of motor and its application, the next thing to consider is which parameter should be controlled i.e.…”

Section: Theoretical Considerationsmentioning

confidence: 99%

Feedforward and Feedback DC Motor Control Methods of Control Systems

2020

IJETER

View full text Add to dashboard Cite

DC motors are the most popular transducers used in the industry. Their versatility allows them to be used and configured in many different varieties, therefore, it is important to know which method to use for controlling them as there are currently many designs for different DC motors and different applications. This paper focuses on comparing the feedforward and feedback motor control methods. The DC motor design that the paper will consider is a voltage-controlled armature driven DC motor. The group will use MATLAB to simulate the two methods and will implement them to the motor. In addition to that, setpoint command tracking will also be a parameter to be considered in determining the performance of the two methods. Furthermore, a comparison of their performance against each other will be done by introducing a load disturbance in the armature-controlled DC motor in order to determine their sensitivity to possible noise in the system.

show abstract