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 maintenance - Proposes a streamline process to create digital twins for a wide variety of applications using MATLAB® SimscapeTM - Deploys developed digital twins on Amazon Web Services - Includes MATLAB and Simulink codes available for free download on MATLAB central - Covers popular prototyping hardwares, such as Arduino and Raspberry Pi
About this book · Gives the reader hands on example-base experience for simulating dynamical models in MATLAB®/Simulink® and animating them in VRML · More than 150 images describe each step in the model realizations helping readers to understand them visually · Diverse examples and profound problem treatment enable the reader to animate complex dynamical problems m-files, Simulink models, VRML files and jpegs available for download provide full solutions for the end-of-chapter problems Virtual Reality and Animation for MATLAB® and Simulink® Users demonstrates the simulation and animation of physical systems using the MATLAB® Virtual Reality Toolbox (virtual models are created in V-Realm Builder). The book is divided into two parts; the first addresses MATLAB® and the second Simulink®. The presentation is problem-based with each chapter teaching the reader a group of essential principles in the context of a step-by-step solution to a particular issue. Examples of the systems covered include mass-spring-dampers, a crank-slider mechanism and a moving vehicle. The examples are given in ascending level of difficulty and contain MATLAB®/Simulink® codes deliberately simplified so that readers can focus on: • understanding how to link a 3-d virtual scene to MATLAB®/Simulink®; and • manipulating the 3-d virtual scene in MATLAB®/Simulink®. When studied in sequence, the chapters of this text form a coherent whole enabling the reader to gain a thorough expertise in virtual simulation and animation of dynamical models using MATLAB®/Simulink®. Individual chapters stand on their own, however, so that readers interested in a particular system can concentrate on it easily. Problems are provided in each chapter to give practice in the techniques demonstrated and to extend the range of the systems studied, for example, into the control sphere. Solution code for these problems can be downloaded from insert URL. Whether modeling the dynamics of a simple pendulum, a robot arm or a moving car, animation of a dynamical model can enliven and encourage understanding of mechanical systems and thus contribute to control design. Virtual Reality and Animation for MATLAB® and Simulink® Users will be instructive and interesting to anyone, researcher or student, working with the dynamics of physical systems. Readers are assumed to have some familiarity with MATLAB®.
Practical Design and Application of Model Predictive Control is a self-learning resource on how to design, tune and deploy an MPC using MATLAB® and Simulink®. This reference is one of the most detailed publications on how to design and tune MPC controllers. Examples presented range from double-Mass spring system, ship heading and speed control, robustness analysis through Monte-Carlo simulations, photovoltaic optimal control, and energy management of power-split and air-handling control. Readers will also learn how to embed the designed MPC controller in a real-time platform such as Arduino®. The selected problems are nonlinear and challenging, and thus serve as an excellent experimental, dynamic system to show the reader the capability of MPC. The step-by-step solutions of the problems are thoroughly documented to allow the reader to easily replicate the results. Furthermore, the MATLAB® and Simulink® codes for the solutions are available for free download. Readers can connect with the authors through the dedicated website which includes additional free resources at www.practicalmpc.com. - Illustrates how to design, tune and deploy MPC for projects in a quick manner - Demonstrates a variety of applications that are solved using MATLAB® and Simulink® - Bridges the gap in providing a number of realistic problems with very hands-on training - Provides MATLAB® and Simulink® code solutions. This includes nonlinear plant models that the reader can use for other projects and research work - Presents application problems with solutions to help reinforce the information learned
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 maintenance - Proposes a streamline process to create digital twins for a wide variety of applications using MATLAB® SimscapeTM - Deploys developed digital twins on Amazon Web Services - Includes MATLAB and Simulink codes available for free download on MATLAB central - Covers popular prototyping hardwares, such as Arduino and Raspberry Pi
Practical Design and Application of Model Predictive Control is a self-learning resource on how to design, tune and deploy an MPC using MATLAB® and Simulink®. This reference is one of the most detailed publications on how to design and tune MPC controllers. Examples presented range from double-Mass spring system, ship heading and speed control, robustness analysis through Monte-Carlo simulations, photovoltaic optimal control, and energy management of power-split and air-handling control. Readers will also learn how to embed the designed MPC controller in a real-time platform such as Arduino®. The selected problems are nonlinear and challenging, and thus serve as an excellent experimental, dynamic system to show the reader the capability of MPC. The step-by-step solutions of the problems are thoroughly documented to allow the reader to easily replicate the results. Furthermore, the MATLAB® and Simulink® codes for the solutions are available for free download. Readers can connect with the authors through the dedicated website which includes additional free resources at www.practicalmpc.com. - Illustrates how to design, tune and deploy MPC for projects in a quick manner - Demonstrates a variety of applications that are solved using MATLAB® and Simulink® - Bridges the gap in providing a number of realistic problems with very hands-on training - Provides MATLAB® and Simulink® code solutions. This includes nonlinear plant models that the reader can use for other projects and research work - Presents application problems with solutions to help reinforce the information learned
About this book · Gives the reader hands on example-base experience for simulating dynamical models in MATLAB®/Simulink® and animating them in VRML · More than 150 images describe each step in the model realizations helping readers to understand them visually · Diverse examples and profound problem treatment enable the reader to animate complex dynamical problems m-files, Simulink models, VRML files and jpegs available for download provide full solutions for the end-of-chapter problems Virtual Reality and Animation for MATLAB® and Simulink® Users demonstrates the simulation and animation of physical systems using the MATLAB® Virtual Reality Toolbox (virtual models are created in V-Realm Builder). The book is divided into two parts; the first addresses MATLAB® and the second Simulink®. The presentation is problem-based with each chapter teaching the reader a group of essential principles in the context of a step-by-step solution to a particular issue. Examples of the systems covered include mass-spring-dampers, a crank-slider mechanism and a moving vehicle. The examples are given in ascending level of difficulty and contain MATLAB®/Simulink® codes deliberately simplified so that readers can focus on: • understanding how to link a 3-d virtual scene to MATLAB®/Simulink®; and • manipulating the 3-d virtual scene in MATLAB®/Simulink®. When studied in sequence, the chapters of this text form a coherent whole enabling the reader to gain a thorough expertise in virtual simulation and animation of dynamical models using MATLAB®/Simulink®. Individual chapters stand on their own, however, so that readers interested in a particular system can concentrate on it easily. Problems are provided in each chapter to give practice in the techniques demonstrated and to extend the range of the systems studied, for example, into the control sphere. Solution code for these problems can be downloaded from insert URL. Whether modeling the dynamics of a simple pendulum, a robot arm or a moving car, animation of a dynamical model can enliven and encourage understanding of mechanical systems and thus contribute to control design. Virtual Reality and Animation for MATLAB® and Simulink® Users will be instructive and interesting to anyone, researcher or student, working with the dynamics of physical systems. Readers are assumed to have some familiarity with MATLAB®.
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