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| Author | : Timm Faulwasser |
| Publisher | : Springer Nature |
| Total Pages | : 250 |
| Release | : 2021-04-17 |
| Genre | : Science |
| ISBN | : 3030632814 |
Download Recent Advances in Model Predictive Control Book in PDF, ePub and Kindle
This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role. The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders.
| 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 | : 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 | : Frank Allgöwer |
| Publisher | : Birkhäuser |
| Total Pages | : 463 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 3034884079 |
Download Nonlinear Model Predictive Control Book in PDF, ePub and Kindle
During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland. The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonlinear model predictive control, including systems theory, computations, modeling and applications.
| Author | : David Clarke |
| Publisher | : Oxford Science Publications |
| Total Pages | : 0 |
| Release | : 1994 |
| Genre | : Science |
| ISBN | : 9780198562924 |
Download Advances in Model-based Predictive Control Book in PDF, ePub and Kindle
Model based predictive control (MBPC) is arguably the most important approach to the advance control of complex interacting industrial processes. Unique among modern theories, MBPC can handle real-time state and actuator constraints in a natural way, enabling plants to maximize their profits. In addition, the wide range of model structures, prediction horizons, and optimization criteria allows for tailor-made MBPC applications--whether they be for high-speed machine tools or large-scale industrial processes. This timely edited volume, based on a conference held at Oxford University and devoted exclusively to MBPC, brings the field up to date with the latest theoretical and practical advances. Topics include how MBPC is expanding to include variants in the basic themes (such as new prediction and optimization approaches, nonlinear models, and two-dimensional problems), general stabilization ideas for constrained plant, and unsolved problems in MBPC. This excellent volume is the introduction to the theory, current applications, and hot research areas in MBPC that students and professionals in control systems have been waiting for.
| 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 | : 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 | : Tao Zheng |
| Publisher | : BoD – Books on Demand |
| Total Pages | : 434 |
| Release | : 2011-07-05 |
| Genre | : Technology & Engineering |
| ISBN | : 9533072989 |
Download Advanced Model Predictive Control Book in PDF, ePub and Kindle
Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request of modeling accuracy and robustness to complicated process plants, MPC has been widely accepted in many practical fields. As the guide for researchers and engineers all over the world concerned with the latest developments of MPC, the purpose of "Advanced Model Predictive Control" is to show the readers the recent achievements in this area. The first part of this exciting book will help you comprehend the frontiers in theoretical research of MPC, such as Fast MPC, Nonlinear MPC, Distributed MPC, Multi-Dimensional MPC and Fuzzy-Neural MPC. In the second part, several excellent applications of MPC in modern industry are proposed and efficient commercial software for MPC is introduced. Because of its special industrial origin, we believe that MPC will remain energetic in the future.
| Author | : Yugeng Xi |
| Publisher | : John Wiley & Sons |
| Total Pages | : 392 |
| Release | : 2019-06-28 |
| Genre | : Technology & Engineering |
| ISBN | : 1119119588 |
Download Predictive Control Book in PDF, ePub and Kindle
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 nonlinear MPC and its related algorithms, the diversification development of MPC with respect to control structures and optimization strategies, and robust MPC. Finally, applications of MPC and its generalization to optimization-based dynamic problems other than control will be discussed. Systematically introduces fundamental concepts, basic algorithms, and applications of MPC Includes a comprehensive overview of MPC development, emphasizing recent advances and modern approaches Features numerous MPC models and structures, based on rigorous research Based on the best-selling Chinese edition, which is a key text in China Predictive Control: Fundamentals and Developments is written for advanced undergraduate and graduate students and researchers specializing in control technologies. It is also a useful reference for industry professionals, engineers, and technicians specializing in advanced optimization control technology.
| Author | : Carlos Bordons |
| Publisher | : Springer Nature |
| Total Pages | : 266 |
| Release | : 2019-09-12 |
| Genre | : Technology & Engineering |
| ISBN | : 3030245705 |
Download Model Predictive Control of Microgrids Book in PDF, ePub and Kindle
The book shows how the operation of renewable-energy microgrids can be facilitated by the use of model predictive control (MPC). It gives readers a wide overview of control methods for microgrid operation at all levels, ranging from quality of service, to integration in the electricity market. MPC-based solutions are provided for the main control issues related to energy management and optimal operation of microgrids. The authors present MPC techniques for case studies that include different renewable sources – mainly photovoltaic and wind – as well as hybrid storage using batteries, hydrogen and supercapacitors. Experimental results for a pilot-scale microgrid are also presented, as well as simulations of scheduling in the electricity market and integration of electric and hybrid vehicles into the microgrid. in order to replicate the examples provided in the book and to develop and validate control algorithms on existing or projected microgrids. Model Predictive Control of Microgrids will interest researchers and practitioners, enabling them to keep abreast of a rapidly developing field. The text will also help to guide graduate students through processes from the conception and initial design of a microgrid through its implementation to the optimization of microgrid management. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
