Practical Design and Application of Model Predictive Control: MPC for MATLAB and Simulink Users
- Length: 262 pages
- Edition: 1
- Language: English
- Publisher: Butterworth-Heinemann
- Publication Date: 2018-05-23
- ISBN-10: 0128139188
- ISBN-13: 9780128139189
- Sales Rank: #1754816 (See Top 100 Books)
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.
Cover image Title page Copyright Dedication Preface Acknowledgments Chapter 1. Introducing the Book Abstract 1.1 Introducing the Authors 1.2 Practical Approach to MPC 1.3 Organization of the Book 1.4 Software and Hardware Requirements 1.5 Downloading the Source Codes Reference Further Reading Chapter 2. Theoretical Foundation of MPC Abstract 2.1 Introduction 2.2 PID or MPC 2.3 Hypothetical PID with a Prediction Horizon 2.4 Hypothetical PID with a Prediction and Control Horizon 2.5 Introduction to MPC 2.6 Solving the Real-Time Optimization Problem in MPC 2.7 Mathworks and MPC Reference Further Reading Chapter 3. MPC Design of a Double-Mass Spring System Abstract 3.1 Introduction 3.2 Model-Based Design Framework 3.3 System Identification Process 3.4 Double-Mass Spring System 3.5 System Identification for a Double-Mass Spring Plant 3.6 MPC Control Design 3.7 Integrating MPC With Simulink Model 3.8 Application Problem References Chapter 4. System Identification for a Ship Abstract 4.1 Introduction 4.2 Plant Model of a Ship 4.3 Data-Based Linear Approximation of the Ship’s Dynamics 4.4 Application Problem: System Identification of Ship Dynamics References Chapter 5. Single MPC Design for a Ship Abstract 5.1 Introduction 5.2 Understanding the Requirements for the Controller 5.3 Requirements for the Ship Controller 5.4 Physical Constraints of the Ship 5.5 Handling Constraints in MPC 5.6 Designing a MPC Controller for the Ship Using MATLAB 5.7 Integrating MPC with Simulink Model 5.8 Application Problem: Impact of Tuning on Robustness References Chapter 6. Multiple MPC Design for a Ship Abstract 6.1 Introduction 6.2 Defining the Operating Regions for the System 6.3 Steady State Simulations for the Operating Points 6.4 Analysis of Steady State Simulations 6.5 Creating Linear Models for the Entire Operating Space 6.6 Designing a Multimode MPC 6.7 Simulink Model for Multiple MPC 6.8 Multiple MPC Controller Simulation Results 6.9 Application Problem References Chapter 7. Monte-Carlo Simulations and Robustness Analysis for a Multiple MPC of a Ship Abstract 7.1 Introduction 7.2 Introducing Uncertainties in Weather Conditions 7.3 Monte-Carlo Simulations Process 7.4 Monte-Carlo Simulation Results for Original MPC Tune 7.5 Impact of Tuning on Robustness of MPC 7.6 Application Problem Reference Chapter 8. MPC Design for Photovoltaic Cells Abstract 8.1 Introduction 8.2 Introducing the Photovoltaic Thermoelectrical Model 8.3 Controller Reference Generation 8.4 System Identification for Photovoltaic Module 8.5 Physical Constraints of the System 8.6 Designing a MPC Controller for the PV Module 8.7 Integrating MPC With the Simulink Model 8.8 Controller Performance References Chapter 9. Real Time Embedded Target Application of MPC Abstract 9.1 Introduction 9.2 Control Problem 9.3 Hardware Requirements and Familiarization 9.4 Simulink Support Package for Arduino 9.5 Hardware Setup for the DC Motor Control 9.6 Data Collection for Response Curve Generation 9.7 Analyzing System Nonlinearity 9.8 System Identification 9.9 MPC Controller Design 9.10 Integrating MPC Controllers With Simulink Model 9.11 Multimode MPC Controller Deployment on the Hardware 9.12 Single MPC Controller Deployment on the Hardware 9.13 Application Problem References Chapter 10. MPC Design for Air-Handling Control of a Diesel Engine Abstract 10.1 Introduction 10.2 Air-handling Control Survey 10.3 Engine Architecture 10.4 Air-handling Architecture 10.5 Torque Curve and Duty Cycle 10.6 System Identification 10.7 MPC Controller Structure 10.8 Controller Deployment 10.9 Experimental Results 10.10 Robustness Analysis 10.11 Summary References Index
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