Model Predictive Control, Camacho

Автор: Borrelli
Название: Predictive Control for Linear and Hybrid Systems
ISBN: 1107652871 ISBN-13(EAN): 9781107652873
Издательство: Cambridge Academ
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Цена: 9502.00 р.
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Описание: With a simple, unified approach, and with consideration of real-time applications, this book covers the theory of stability, feasibility, and robustness of model predictive control (MPC). It is for graduate and postgraduate students, as well as advanced control practitioners interested in the theory and/or implementation of predictive control.

Автор: Grune
Название: Nonlinear Model Predictive Control
ISBN: 0857295004 ISBN-13(EAN): 9780857295002
Издательство: Springer
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Цена: 22359.00 р.
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Описание: 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 introduction to nonlinear optimal control algorithms gives insight into how the nonlinear optimisation routine – the core of any NMPC controller – works. An appendix covering NMPC software and accompanying software in MATLAB® and C++(downloadable from www.springer.com/ISBN) enables readers to perform computer experiments exploring the possibilities and limitations of NMPC.

Автор: Ellis
Название: Economic Model Predictive Control
ISBN: 3319411071 ISBN-13(EAN): 9783319411071
Издательство: Springer
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Цена: 19564.00 р.
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Описание: 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.

Автор: Bari Anasse, Chaouchi Mohamed, Jung Tommy
Название: Predictive Analytics for Dummies
ISBN: 1119267005 ISBN-13(EAN): 9781119267003
Издательство: Wiley
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Цена: 4117.00 р.
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Описание: Use Big Data and technology to uncover real-world insights You don`t need a time machine to predict the future. All it takes is a little knowledge and know-how, and Predictive Analytics For Dummies gets you there fast.

Автор: Christofides P.D.
Название: Model-Based Control of Particulate Processes
ISBN: 1402009364 ISBN-13(EAN): 9781402009365
Издательство: Springer
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Цена: 23508.00 р.
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Описание: The interest in control of particulate processes has been triggered by the need to achieve tight distributed control of size distributions that greatly influence particulate product properties and quality. Drawing from recent advances in dynamics of infinite-dimensional systems and nonlinear control theory, control of particulate processes using population balances has evolved into a very active research area within the field of process control. This book - the first of its kind - presents general methods for the synthesis of nonlinear, robust and constrained feedback controllers for broad classes of particulate process models and illustrates their applications to industrially-important crystallization, aerosol and thermal spray processes. The controllers use a finite number of measurement sensors and control actuators to achieve stabilization of the closed-loop system, output tracking, attenuation of the effect of model uncertainty and handling of actuator saturation.Beginning with an introduction to control of particulate processes, the book discusses nonlinear order reduction and nonlinear, robust and constrained control of particulate spatially-homogeneous processes, and nonlinear control of spatially-homogeneous particulate processes. The synthesis of the controllers is performed by using geometric and Lyapunov-based control techniques. The book includes comparisons of the methods followed for controller synthesis with other approaches and discussions of practical implementation issues that can help researchers and engineers understand the development and application of the methods in greater depth. The methods are applied to continuous and batch crystallization processes, a titania aerosol reactor and a thermal spray process to regulate product size distribution. The resulting benefits in closed-loop performance, robustness and actuator saturation handling compared to other techniques for control of particulate processes are demonstrated through computer simulations.The book assumes a basic knowledge about population balances and nonlinear control.Researchers and graduate students in process control, particle technology and control systems theory, applied mathematicians and process control engineers will find this book a useful resource.

Автор: Lalo Magni; Davide Martino Raimondo; Frank Allg?we
Название: Nonlinear Model Predictive Control
ISBN: 3642010938 ISBN-13(EAN): 9783642010934
Издательство: Springer
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Цена: 22203.00 р.
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Описание: Over the years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to as receding horizon control or moving horizon control. This book assesses the status of the NMPC field and discusses future directions and needs.

Автор: Borrelli
Название: Predictive Control for Linear and Hybrid Systems
ISBN: 1107016886 ISBN-13(EAN): 9781107016880
Издательство: Cambridge Academ
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Цена: 19800.00 р.
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Описание: Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.