Predictive Control for Linear and Hybrid Systems

• Author : Francesco Borrelli,Alberto Bemporad,Manfred Morari
• Publisher : Cambridge University Press
• Release Date : 2017-06-22
• ISBN : 9781107016880

With a simple approach that includes real-time applications and algorithms, this book covers the theory of model predictive control (MPC).

• Author : Eduardo F. Camacho,Carlos Bordons Alba
• Publisher : Springer Science & Business Media
• Release Date : 2013-01-10
• ISBN : 9780857293985

The second edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners. The book demonstrates that a powerful technique does not always require complex control algorithms. Many new exercises and examples have also been added throughout. Solutions available for download from the authors' website save the tutor time

• Author : Eduardo F. Camacho,Carlos A. Bordons
• Publisher : Springer Science & Business Media
• Release Date : 2012-12-06
• ISBN : 9781447130086

Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of posing the process control problem in the time domain. The Model Predictive Control formulation integrates optimal control, stochastic control, control of processes with dead time, multivariable control and future references. The finite control horizon makes it possible to handle constraints and non linear processes in general which are frequently found

• Author : Lars Grüne,Jürgen Pannek
• Publisher : Springer
• Release Date : 2016-11-09
• ISBN : 9783319460246

This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. An introduction

• Author : J.A. Rossiter
• Publisher : CRC Press
• Release Date : 2018-04-17
• ISBN : 9781351597159

The book presents a significant expansion in depth and breadth of the previous edition. It includes substantially more numerical illustrations and copious supporting MATLAB code that the reader can use to replicate illustrations or build his or her own. The code is deliberately written to be as simple as possible and easy to edit. The book is an excellent starting point for any researcher to gain a solid grounding in MPC concepts and algorithms before moving into application or more

• Author : Yugeng Xi,Dewei Li
• Publisher : John Wiley & Sons
• Release Date : 2019-09-16
• ISBN : 9781119119548

This book is a comprehensive introduction to model predictive control (MPC), including its basic principles and algorithms, system analysis and design methods, strategy developments and practical applications. The main contents of the book include an overview of the development trajectory and basic principles of MPC, typical MPC algorithms, quantitative analysis of classical MPC systems, design and tuning methods for MPC parameters, constrained multivariable MPC algorithms and online optimization decomposition methods. Readers will then progress to more advanced topics such as

• Author : Nassim Khaled,Bibin Pattel
• Publisher : Butterworth-Heinemann
• Release Date : 2018-05-04
• ISBN : 9780128139196

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

• Author : Ding Baocang
• Publisher : CRC Press
• Release Date : 2018-10-03
• ISBN : 9781420085310

Modern Predictive Control explains how MPC differs from other control methods in its implementation of a control action. Most importantly, MPC provides the flexibility to act while optimizing—which is essential to the solution of many engineering problems in complex plants, where exact modeling is impossible. The superiority of MPC is in its numerical solution. Usually, MPC is employed to solve a finite-horizon optimal control problem at each sampling instant and obtain control actions for both the present time and

• Author : Saša V. Raković,William S. Levine
• Publisher : Springer
• Release Date : 2018-09-01
• ISBN : 9783319774893

Recent developments in model-predictive control promise remarkable opportunities for designing multi-input, multi-output control systems and improving the control of single-input, single-output systems. This volume provides a definitive survey of the latest model-predictive control methods available to engineers and scientists today. The initial set of chapters present various methods for managing uncertainty in systems, including stochastic model-predictive control. With the advent of affordable and fast computation, control engineers now need to think about using “computationally intensive controls,” so the second part

• Author : Tao Zheng
• Publisher : IntechOpen
• Release Date : 2011-07-05
• ISBN : 9533072989

Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request of modeling accuracy and robustness to complicated process plants, MPC has been widely accepted in many practical fields. As the guide for researchers and engineers all over the world concerned with the latest developments of MPC, the purpose of "Advanced Model Predictive Control" is to show the readers the recent achievements in

• Author : Rolf Findeisen,Frank Allgöwer,Lorenz Biegler
• Publisher : Springer
• Release Date : 2007-09-08
• ISBN : 9783540726999

Thepastthree decadeshaveseenrapiddevelopmentin the areaofmodelpred- tive control with respect to both theoretical and application aspects. Over these 30 years, model predictive control for linear systems has been widely applied, especially in the area of process control. However, today’s applications often require driving the process over a wide region and close to the boundaries of - erability, while satisfying constraints and achieving near-optimal performance. Consequently, the application of linear control methods does not always lead to satisfactory performance, and here nonlinear methods

• Author : Lars Grüne,Jürgen Pannek
• Publisher : Springer Science & Business Media
• Release Date : 2011-04-11
• ISBN : 9780857295019

Nonlinear Model Predictive Control is a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. NMPC schemes with and without stabilizing terminal constraints are detailed and intuitive examples illustrate the performance of different NMPC variants. An

• Author : J.A. Rossiter
• Publisher : CRC Press
• Release Date : 2003-06-27
• ISBN : 9780203503966

Model Predictive Control (MPC) has become a widely used methodology across all engineering disciplines, yet there are few books which study this approach. Until now, no book has addressed in detail all key issues in the field including apriori stability and robust stability results. Engineers and MPC researchers now have a volume that provides a complete overview of the theory and practice of MPC as it relates to process and control engineering. Model-Based Predictive Control, A Practical Approach, analyzes predictive

• Author : Liuping Wang
• Publisher : Springer Science & Business Media
• Release Date : 2009-02-14
• ISBN : 9781848823310

Model Predictive Control System Design and Implementation Using MATLAB® proposes methods for design and implementation of MPC systems using basis functions that confer the following advantages: - continuous- and discrete-time MPC problems solved in similar design frameworks; - a parsimonious parametric representation of the control trajectory gives rise to computationally efficient algorithms and better on-line performance; and - a more general discrete-time representation of MPC design that becomes identical to the traditional approach for an appropriate choice of parameters. After

• Author : Venkata Yaramasu,Bin Wu
• Publisher : John Wiley & Sons
• Release Date : 2016-12-19
• ISBN : 9781118988589

Model Predictive Control of Wind Energy Conversion Systems addresses the predicative control strategy that has emerged as a promising digital control tool within the field of power electronics, variable-speed motor drives, and energy conversion systems. The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital