Predictive Control PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Predictive Control PDF full book. Access full book title Predictive Control.
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 | : 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 | : 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 | : 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 | : Matthew Ellis |
Publisher | : Springer |
Total Pages | : 311 |
Release | : 2016-07-27 |
Genre | : Technology & Engineering |
ISBN | : 331941108X |
Download Economic Model Predictive Control Book in PDF, ePub and Kindle
This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes: Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics. The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples. The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes.In addition to being mathematically rigorous, these methods accommodate key practical issues, for example, direct optimization of process economics, time-varying economic cost functions and computational efficiency. Numerous comments and remarks providing fundamental understanding of the merging of process economics and feedback control into a single framework are included. A control engineer can easily tailor the many detailed examples of industrial relevance given within the text to a specific application. The authors present a rich collection of new research topics and references to significant recent work making Economic Model Predictive Control an important source of information and inspiration for academics and graduate students researching the area and for process engineers interested in applying its ideas.
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 | : Luigi Del Re |
Publisher | : Springer |
Total Pages | : 291 |
Release | : 2010-03-11 |
Genre | : Technology & Engineering |
ISBN | : 1849960712 |
Download Automotive Model Predictive Control Book in PDF, ePub and Kindle
Automotive control has developed over the decades from an auxiliary te- nology to a key element without which the actual performances, emission, safety and consumption targets could not be met. Accordingly, automotive control has been increasing its authority and responsibility – at the price of complexity and di?cult tuning. The progressive evolution has been mainly ledby speci?capplicationsandshorttermtargets,withthe consequencethat automotive control is to a very large extent more heuristic than systematic. Product requirements are still increasing and new challenges are coming from potentially huge markets like India and China, and against this ba- ground there is wide consensus both in the industry and academia that the current state is not satisfactory. Model-based control could be an approach to improve performance while reducing development and tuning times and possibly costs. Model predictive control is a kind of model-based control design approach which has experienced a growing success since the middle of the 1980s for “slow” complex plants, in particular of the chemical and process industry. In the last decades, severaldevelopments haveallowedusing these methods also for “fast”systemsandthis hassupporteda growinginterestinitsusealsofor automotive applications, with several promising results reported. Still there is no consensus on whether model predictive control with its high requi- ments on model quality and on computational power is a sensible choice for automotive control.
Author | : James Blake Rawlings |
Publisher | : |
Total Pages | : 770 |
Release | : 2017 |
Genre | : Control theory |
ISBN | : 9780975937754 |
Download Model Predictive Control Book in PDF, ePub and Kindle
Author | : José M. Maestre |
Publisher | : Springer Science & Business Media |
Total Pages | : 601 |
Release | : 2013-11-10 |
Genre | : Technology & Engineering |
ISBN | : 9400770065 |
Download Distributed Model Predictive Control Made Easy Book in PDF, ePub and Kindle
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. This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those who want to gain a deeper insight in the wide range of distributed MPC techniques available.
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.