Abstract
With the growing deployments of Internet of Things (IoT) systems, the importance of the concept of a digital avatar of a physical thing has gathered significant interest in the recent years. Digital twin means a virtual copy of a system in operation to measure, monitor, and analyze the operational performance through continuous collection of real-time data. Evolution of sensor technology, investment in infrastructure to capture digital data of physical product, and innovation in analytical software platforms over the years is helping adoption of digital twin technology in the industry. Here we are using the open modelica software for simulation of the model. In this paper, a nonlinear model-based approach is developed for controlling pressure of an actuator chamber. Through sliding mode control approach, the controller utilizes a on/off solenoid valve to implement pressure control task.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Acknowledgements
We are very grateful to our Professor Dr. SANTOSH R DESAI who provided insight and expertise that greatly assisted the project.
We thank Mr. PAVAN for assistance with Open Modelica Software to make the digital twin of the physical model. We would also like to show our gratitude to the Mr. CHANDRABABU for sharing their pearls of wisdom with us during the course of this project.
Symmetric solutions for supporting us with the components and their support and maintenance.
We want to grate everyone, who has supported the creation of this work.
Author information
Authors and Affiliations
Corresponding authors
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Desai, N., Ananya, S.K., Bajaj, L., Periwal, A., Desai, S.R. (2020). Process Parameter Monitoring and Control Using Digital Twin. In: Auer, M., Ram B., K. (eds) Cyber-physical Systems and Digital Twins. REV2019 2019. Lecture Notes in Networks and Systems, vol 80. Springer, Cham. https://doi.org/10.1007/978-3-030-23162-0_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-23162-0_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-23161-3
Online ISBN: 978-3-030-23162-0
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)