Model Predictive Control in the Process Industry

• 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 : 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 : 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 : 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 : Basil Kouvaritakis,Mark Cannon
• Publisher : Springer
• Release Date : 2015-12-01
• ISBN : 9783319248530

For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing

• Author : J.A. Rossiter
• Publisher : CRC Press
• Release Date : 2017-07-12
• ISBN : 9781351988599

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 : 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 : José M. Maestre,Rudy R. Negenborn
• Publisher : Springer Science & Business Media
• Release Date : 2013-11-10
• ISBN : 9789400770065

The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems.

• 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 : 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 : Yugeng Xi,Dewei Li
• Publisher : John Wiley & Sons
• Release Date : 2019-11-12
• 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 : Alfeu Sguarezi
• Publisher : Elsevier
• Release Date : 2022-01-21
• ISBN : 9780323903233

Model Predictive Control for Doubly-Fed Induction Generators and Three-Phase Power Converters describes the application of model predictive control techniques with modulator and finite control sets to squirrel cage induction motor and in doubly-fed induction generators using field orientation control techniques as both current control and direct power control. Sections discuss induction machines, their key modulation techniques, introduce the utility of model predictive control, review core concepts of vector control, direct torque control, and direct power control alongside novel approaches of

• Author : Jan Marian Maciejowski
• Publisher : Pearson Education
• Release Date : 2002
• ISBN : 0201398230

Model predictive control is an indispensable part of industrial control engineering and is increasingly the "method of choice" for advanced control applications. Jan Maciejowski's book provides a systematic and comprehensive course on predictive control suitable for final year students and professional engineers. The first book to cover constrained predictive control, the text reflects the true use of the topic in industry.

• 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 : 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