Digital Twin Development and Deployment on the Cloud: Developing Cloud-Friendly Dynamic Models Using Simulink®/SimscapeTM and Amazon AWS

Description

Digital Twin Development and Deployment in the Cloud: Developing Cloud-Friendly Dynamic Models Using Simulink®/SimscapeTM and Amazon AWS promotes a physics-based approach to the field of digital twins. Through the use of multiphysics models running in the cloud, significant improvement to the diagnostics and prognostic of systems can be attained. The book draws a clear definition of digital twins, helping business leaders clearly identify the value it brings. In addition, it outlines the key elements needed for deployment, including the hardware and software tools needed. Special attention is paid to the process of developing and deploying the multi-physics models of the digital twins. Provides a high-level overview of digital twins and their underutilization in the field of asset management and maintenanceProposes a streamline process to create digital twins for a wide variety of applications using MATLAB® Simscape™Deploys developed digital twins on Amazon Web ServicesIncludes MATLAB and Simulink codes available for free download on MATLAB centralCovers popular prototyping hardwares, such as Arduino and Raspberry Pi Digital Twin Development and Deployment on the Cloud Copyright 1 - Added value of digital twins and IoT 1.1 Introduction 1.2 Motivation to write this book 1.3 Digital twins 1.4 On-board and off-board diagnostics 1.5 Modeling and simulation software 1.6 Organization and outline of the book References 2 - Cloud and IoT technologies 2.1 Overview 2.2 History of cloud 2.3 Evolution of cloud technologies 2.4 Connecting machines to the cloud 2.5 Applications 2.5.1 Enterprise Resource Planning 2.5.2 Automotive and asset management 2.5.3 Equipment monitoring 2.5.4 Farming 2.5.5 Charity 2.5.6 Biomedical 2.5.7 Miscellaneous applications 2.6 Considerations for cloud services 2.6.1 Security 2.6.2 General Data Protection Regulation 2.6.3 Shadow IT services 2.6.4 Cloud cost optimization 2.7 What is edge computing? 2.8 Edge computing versus cloud computing 2.9 Edge and cloud computing examples 2.10 Will 5G accelerate cloud computing? 3 - Digital twin model creation of a robotic arm 3.1 Introduction 3.2 Hardware parameters 3.3 Simulation process 3.3.1 Initial conditions 3.3.2 Base structure 3.3.3 Upper body 3.3.4 Upper arm 3.3.5 Gripper arm 3.3.6 Motion 3.3.7 Simulation of a failed system 3.4 Application problem 4 - Ball on plate modeling 4.1 Introduction 4.2 Ball on plate hardware 4.3 Block diagram of the ball on plate system 4.4 Failure modes and diagnostics concept for the ball on plate 4.5 Simscape model for the ball on plate 4.6 Ball Plate Interaction 4.7 S-function for the Ball Plate Interaction 4.8 Simulation of the model 4.8.1 Application problem 1 4.8.2 Application problem 2 4.8.3 Application problem 3 5 - Digital twin model creation of double mass spring damper system 5.1 Introduction 5.2 Hardware parameters 5.3 Simulation process 5.3.1 Initial conditions and first spring+mass damper combo 5.3.2 Position and velocity of first spring+mass damper combo 5.3.3 Second spring+mass damper combo and position and velocity of second spring+mass damper combo 5.3.4 Force input for double spring+mass damper system 5.3.5 Scope for double spring+mass damper system outputs 5.3.6 Simulation of a failed system 5.4 Application problem 5.4.1 Application problem 1 5.4.2 Application problem 2 6 - Digital twin model creation of solar panels 6.1 Introduction 6.2 Photovoltaic hardware setup 6.2.1 Block diagram of the solar panel system 6.2.2 Failure modes and diagnostics concept for the PV system 6.3 Experimental data collection for model creation 6.4 PV system simscape model 6.5 Solar cell modeling of the PV system 6.6 Solar cell modeling of the PV subsystem 6.7 Simulation results 6.8 Application problem References 7 - Digital twin development for an inverter circuit for motor drive systems 7.1 Introduction 7.2 Block diagram of the motor drive inverter system 7.3 Failure modes and diagnostics concept of the motor drive inverter system 7.4 Simscape model of the motor drive inverter system 7.5 Fault injection and diagnostic algorithm development 7.6 Application problem Reference 8 - Digital Twin development and cloud deployment for a Hybrid Electric Vehicle 8.1 Introduction 8.2 Hybrid Electric Vehicle physical asset/hardware setup 8.3 Block diagram of the Hybrid Electric Vehicle system 8.4 Failure modes and diagnostic concept of Hybrid Electric Vehicle system 8.5 Simscape™ model of a Hybrid Electric Vehicle system 8.6 EDGE device setup and cloud connectivity 8.7 Digital Twin Modeling and calibration 8.8 Off-board diagnostics algorithm development for Hybrid Electric Vehicle system 8.9 Deploying digital twin Hybrid Electric Vehicle system model to cloud 8.10 Application problem References 9 - Digital Twin Development and cloud deployment for a DC Motor Control embedded system 9.1 Introduction 9.2 Setting up Real-Time Embedded Controller Hardware and Software for DC Motor Speed Control 9.2.1 Hardware requirements and familiarization 9.2.2 Software requirements 9.3 Open-Loop Data Collection and Closed-Loop PID Controller Development for the DC Motor Hardware 9.3.1 Running DC motor in open-loop steady-state points using Simulink® 9.3.2 DC motor nonlinearity analysis using collected data 9.3.3 Open-Loop Feedforward and Closed-Loop PID controller design and deployment for DC Motor Speed Control 9.4 Developing Simscape™ Digital Twin model for the DC motor 9.5 Parameter tuning of the SimscapeTM DC Motor Model with data from DC motor hardware using Simulink® parameter estimation TM tool 9.6 Adding AWS cloud connectivity to real-time embedded hardware for DC Motor Speed Control 9.6.1 Hardware setup to communicate between Arduino and ESP32 9.6.2 Software setup for ESP32 programming 9.6.3 Simulink model updates for communication between Arduino and ESP32 9.6.4 ESP32 Arduino software for communication between Arduino and ESP32 9.6.5 DC motor hardware connectivity to AWS cloud and real-time data transfer 9.7 Off-Board Diagnostics/prognostics algorithm development for DC Motor Controller Hardware 9.8 Deploying the Simscape™ Digital Twin Model to the AWS cloud 9.9 Application problem References 10 - Digital twin development and deployment for a wind turbine 10.1 Introduction 10.2 Physical asset setup and considerations: wind turbine hardware 10.3 Understanding the input–output behavior of the wind turbine SimscapeTM model 10.3.1 Wind turbine model components 10.3.2 Input–output response of the model 10.3.3 Customizing the model as per the digital twin requirements 10.3.3.1 Target speed 10.3.3.2 Steady-state speed in STARTUP state 10.3.3.3 Proportional (P) and I (Integral) gains change in the pitch actuation control logic 10.3.3.4 Increasing the simulation time 10.3.4 Developing relationship between wind speed and generator speed 10.4 Developing the driver SimscapeTM model for the hardware and communicating to AWS 10.4.1 Developing the driver SimscapeTM model for the hardware 10.4.2 DC motor hardware communication to AWS 10.5 Deploying the SimscapeTM digital twin model to the AWS cloud and performing Off-BD 10.6 Application problem Reference Index A B C D E F G H I M O P R S T U V W