Practical Design and Application of Model Predictive Control (eBook)
262 Seiten
Elsevier Science (Verlag)
978-0-12-813919-6 (ISBN)
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
Dr. Khaled has extensive industrial and academic experience in the field of dynamics, controls and IoT solutions. He is the Controls and Engineering Systems Manager at Dover. He is an innovator with more than 30 patents and patent applications in the fields of smart systems and energy. He is the author of 'Virtual Reality for Matlab and Simulink Users'. He also has numerous publications in the field of controls and autonomous navigation. Dr. Khaled is a green-belt six sigma certified. He received the status of 'Outstanding Researcher' granted by the U.S Government in 2012. You can contact him by visiting: https://www.practicalmpc.com/
Practical Design and Application of Model Predictive Control is a self-learning resource on how to design, tune and deploy an MPC using MATLAB(R) and Simulink(R). 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(R). 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(R) and Simulink(R) 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(R) and Simulink(R) Bridges the gap in providing a number of realistic problems with very hands-on training Provides MATLAB(R) and Simulink(R) 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
Erscheint lt. Verlag | 18.5.2018 |
---|---|
Sprache | englisch |
Themenwelt | Technik ► Bauwesen |
Technik ► Elektrotechnik / Energietechnik | |
Technik ► Maschinenbau | |
ISBN-10 | 0-12-813919-6 / 0128139196 |
ISBN-13 | 978-0-12-813919-6 / 9780128139196 |
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