A First Course In Predictive Control PDF Download
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Author | : J.A. Rossiter |
Publisher | : CRC Press |
Total Pages | : 463 |
Release | : 2018-04-17 |
Genre | : Technology & Engineering |
ISBN | : 1351597159 |
Download A First Course in Predictive Control Book in PDF, ePub and Kindle
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 advanced research topics. Sample problems for readers are embedded throughout the chapters, and in-text questions are designed for readers to demonstrate an understanding of concepts through numerical simulation.
Author | : Jan Marian Maciejowski |
Publisher | : Pearson Education |
Total Pages | : 362 |
Release | : 2002 |
Genre | : Psychology |
ISBN | : 9780201398236 |
Download Predictive Control Book in PDF, ePub and Kindle
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 | : Eduardo F. Camacho |
Publisher | : Springer Science & Business Media |
Total Pages | : 405 |
Release | : 2013-01-10 |
Genre | : Technology & Engineering |
ISBN | : 0857293982 |
Download Model Predictive Control Book in PDF, ePub and Kindle
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 and enable the student to follow results more closely even when the tutor isn't present.
Author | : Sunan Huang |
Publisher | : Springer Science & Business Media |
Total Pages | : 276 |
Release | : 2013-03-09 |
Genre | : Mathematics |
ISBN | : 1447137256 |
Download Applied Predictive Control Book in PDF, ePub and Kindle
This focused treatment includes the fundamentals and some state-of-the-art developments in the field of predictive control. A substantial part of the book addresses application issues in predictive control, providing several interesting case studies for more application-oriented readers.
Author | : Basil Kouvaritakis |
Publisher | : Springer |
Total Pages | : 387 |
Release | : 2015-12-01 |
Genre | : Technology & Engineering |
ISBN | : 3319248537 |
Download Model Predictive Control Book in PDF, ePub and Kindle
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 the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplicative and stochastic model uncertainty. The book provides: extensive use of illustrative examples; sample problems; and discussion of novel control applications such as resource allocation for sustainable development and turbine-blade control for maximized power capture with simultaneously reduced risk of turbulence-induced damage. Graduate students pursuing courses in model predictive control or more generally in advanced or process control and senior undergraduates in need of a specialized treatment will find Model Predictive Control an invaluable guide to the state of the art in this important subject. For the instructor it provides an authoritative resource for the construction of courses.
Author | : Liuping Wang |
Publisher | : Springer Science & Business Media |
Total Pages | : 398 |
Release | : 2009-02-14 |
Genre | : Technology & Engineering |
ISBN | : 1848823312 |
Download Model Predictive Control System Design and Implementation Using MATLAB® Book in PDF, ePub and Kindle
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 the theoretical presentation, coverage is given to three industrial applications. The subject of quadratic programming, often associated with the core optimization algorithms of MPC is also introduced and explained. The technical contents of this book is mainly based on advances in MPC using state-space models and basis functions. This volume includes numerous analytical examples and problems and MATLAB® programs and exercises.
Author | : Francesco Borrelli |
Publisher | : Cambridge University Press |
Total Pages | : 447 |
Release | : 2017-06-22 |
Genre | : Mathematics |
ISBN | : 1107016886 |
Download Predictive Control for Linear and Hybrid Systems Book in PDF, ePub and Kindle
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 |
Publisher | : Springer Science & Business Media |
Total Pages | : 250 |
Release | : 2012-12-06 |
Genre | : Technology & Engineering |
ISBN | : 1447130081 |
Download Model Predictive Control in the Process Industry Book in PDF, ePub and Kindle
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 in industry. Focusing on implementation issues for Model Predictive Controllers in industry, it fills the gap between the empirical way practitioners use control algorithms and the sometimes abstractly formulated techniques developed by researchers. The text is firmly based on material from lectures given to senior undergraduate and graduate students and articles written by the authors.
Author | : Ding Baocang |
Publisher | : CRC Press |
Total Pages | : 117 |
Release | : 2018-10-03 |
Genre | : Technology & Engineering |
ISBN | : 1439859671 |
Download Modern Predictive Control Book in PDF, ePub and Kindle
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 a future period. However, only the current control move is applied to the plant. This complete, step-by-step exploration of various approaches to MPC: Introduces basic concepts of systems, modeling, and predictive control, detailing development from classical MPC to synthesis approaches Explores use of Model Algorithmic Control (MAC), Dynamic Matrix Control (DMC), Generalized Predictive Control (GPC), and Two-Step Model Predictive Control Identifies important general approaches to synthesis Discusses open-loop and closed-loop optimization in synthesis approaches Covers output feedback synthesis approaches with and without a finite switching horizon This book gives researchers a variety of models for use with one- and two-step control. The author clearly explains the variations between predictive control methods—and the root of these differences—to illustrate that there is no one ideal MPC and that one should remain open to selecting the best possible model in each unique circumstance.
Author | : Nassim Khaled |
Publisher | : Butterworth-Heinemann |
Total Pages | : 262 |
Release | : 2018-05-04 |
Genre | : Technology & Engineering |
ISBN | : 0128139196 |
Download Practical Design and Application of Model Predictive Control Book in PDF, ePub and Kindle
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