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Model Predictive Control

Model Predictive Control
  • Author : Eduardo F. Camacho
  • Publsiher : Springer Science & Business Media
  • Release : 10 January 2013
  • ISBN : 0857293982
  • Pages : 405 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKModel Predictive Control

Summary:
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.


Model Predictive Control

Model Predictive Control
  • Author : Eduardo F. Camacho,Carlos Bordons Alba
  • Publisher : Springer Science & Business Media
  • Release : 10 January 2013
GET THIS BOOKModel Predictive Control

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


Predictive Control

Predictive Control
  • Author : Jan Marian Maciejowski
  • Publisher : Pearson Education
  • Release : 01 March 2021
GET THIS BOOKPredictive Control

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.


Nonlinear Model Predictive Control

Nonlinear Model Predictive Control
  • Author : Lars Grüne,Jürgen Pannek
  • Publisher : Springer Science & Business Media
  • Release : 11 April 2011
GET THIS BOOKNonlinear Model Predictive Control

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


Predictive Control

Predictive Control
  • Author : Yugeng Xi,Dewei Li
  • Publisher : John Wiley & Sons
  • Release : 16 September 2019
GET THIS BOOKPredictive Control

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


Handbook of Model Predictive Control

Handbook of Model Predictive Control
  • Author : Saša V. Raković,William S. Levine
  • Publisher : Springer
  • Release : 01 September 2018
GET THIS BOOKHandbook of Model Predictive Control

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


Model-Based Predictive Control

Model-Based Predictive Control
  • Author : J.A. Rossiter
  • Publisher : CRC Press
  • Release : 12 July 2017
GET THIS BOOKModel-Based Predictive Control

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


A First Course in Predictive Control

A First Course in Predictive Control
  • Author : J.A. Rossiter
  • Publisher : CRC Press
  • Release : 17 April 2018
GET THIS BOOKA First Course in Predictive Control

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


Model Predictive Control in the Process Industry

Model Predictive Control in the Process Industry
  • Author : Eduardo F. Camacho,Carlos A. Bordons
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKModel Predictive Control in the Process Industry

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


Model Predictive Control

Model Predictive Control
  • Author : Carlos Bordons Alba
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKModel Predictive Control

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


Model Predictive Control System Design and Implementation Using MATLAB®

Model Predictive Control System Design and Implementation Using MATLAB®
  • Author : Liuping Wang
  • Publisher : Springer Science & Business Media
  • Release : 04 March 2009
GET THIS BOOKModel Predictive Control System Design and Implementation Using MATLAB®

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


Model Predictive Control

Model Predictive Control
  • Author : Basil Kouvaritakis,Mark Cannon
  • Publisher : Springer
  • Release : 01 December 2015
GET THIS BOOKModel Predictive Control

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


Assessment and Future Directions of Nonlinear Model Predictive Control

Assessment and Future Directions of Nonlinear Model Predictive Control
  • Author : Rolf Findeisen,Frank Allgöwer,Lorenz Biegler
  • Publisher : Springer
  • Release : 08 September 2007
GET THIS BOOKAssessment and Future Directions of Nonlinear Model Predictive Control

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


Distributed Model Predictive Control Made Easy

Distributed Model Predictive Control Made Easy
  • Author : José M. Maestre,Rudy R. Negenborn
  • Publisher : Springer Science & Business Media
  • Release : 10 November 2013
GET THIS BOOKDistributed Model Predictive Control Made Easy

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.


Adaptive Prediction and Predictive Control

Adaptive Prediction and Predictive Control
  • Author : Partha Pratim Kanjilal
  • Publisher : IET
  • Release : 01 March 1995
GET THIS BOOKAdaptive Prediction and Predictive Control

This monograph is concerned with the prediction and control of processes expressed by discrete-time models. It is assumed that the characteristics of the process may vary over time. The processes concerned may be linear or nonlinear, periodic or nonperiodic, single input/single output or simply output-only time series. The primary aim of the work is to provide comprehensive coverage of the principles, perspectives and methods of adaptive prediction. There is also an introduction to the popular methods of predictive control.


Model Predictive Control on Open Water Systems

Model Predictive Control on Open Water Systems
  • Author : Peter-Jules van Overloop
  • Publisher : IOS Press
  • Release : 01 March 2021
GET THIS BOOKModel Predictive Control on Open Water Systems

"In the research Model Predictive Control on Open Water Systems, the relatively new control methodology Model Predictive Control is configured for application of water quantity control on open water systems, especially on irrigation canals and large drainage systems. The methodology applies an internal model of the open water system, by which optimal control actions are calculated over a prediction horizon. As internal model, two simplified models are used, the Integrator Delay model and the Saint Venant model. Kalman filtering is