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Author : Danielle Lee Dougherty
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (58 download)
Download or read book Multiple Model Adaptive Strategy for Model Predictive Control written by Danielle Lee Dougherty and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Danielle Dougherty
Publisher :
ISBN 13 :
Total Pages : 30 pages
Book Rating : 4.:/5 (51 download)
Download or read book A Multiple Model Adaptive Strategy for Multivariable Model Predictive Control written by Danielle Dougherty and published by . This book was released on 2001 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Eduardo F. Camacho
Publisher : Springer Science & Business Media
ISBN 13 : 1447130081
Total Pages : 250 pages
Book Rating : 4.4/5 (471 download)
Download or read book Model Predictive Control in the Process Industry written by Eduardo F. Camacho and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : R Murray-Smith
Publisher : CRC Press
ISBN 13 : 1000162761
Total Pages : 360 pages
Book Rating : 4.0/5 (1 download)
Download or read book Multiple Model Approaches To Nonlinear Modelling And Control written by R Murray-Smith and published by CRC Press. This book was released on 2020-11-26 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work presents approaches to modelling and control problems arising from conditions of ever increasing nonlinearity and complexity. It prescribes an approach that covers a wide range of methods being combined to provide multiple model solutions. Many component methods are described, as well as discussion of the strategies available for building a successful multiple model approach.
Author : Maciej Ławryńczuk
Publisher : Springer Nature
ISBN 13 : 3030838153
Total Pages : 358 pages
Book Rating : 4.0/5 (38 download)
Download or read book Nonlinear Predictive Control Using Wiener Models written by Maciej Ławryńczuk and published by Springer Nature. This book was released on 2021-09-21 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents computationally efficient MPC solutions. The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model's structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances. An alternative is to use the computationally demanding MPC scheme with on-line nonlinear optimisation repeated at each sampling instant. A linear approximation of the Wiener model or the predicted trajectory is found on-line. As a result, quadratic optimisation tasks are obtained. Furthermore, parameterisation using Laguerre functions is possible to reduce the number of decision variables. Simulation results for ten benchmark processes show that the discussed MPC algorithms lead to excellent control quality. For a neutralisation reactor and a fuel cell, essential advantages of neural Wiener models are demonstrated.
Author : Elena Zattoni
Publisher : Springer Nature
ISBN 13 : 3030853187
Total Pages : 1441 pages
Book Rating : 4.0/5 (38 download)
Download or read book 15th European Workshop on Advanced Control and Diagnosis (ACD 2019) written by Elena Zattoni and published by Springer Nature. This book was released on 2022-06-13 with total page 1441 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, published in two volumes, embodies the proceedings of the 15th European Workshop on Advanced Control and Diagnosis (ACD 2019) held in Bologna, Italy, in November 2019. It features contributed and invited papers from academics and professionals specializing in an important aspect of control and automation. The book discusses current theoretical research developments and open problems and illustrates practical applications and industrial priorities. With a focus on both theory and applications, it spans a wide variety of up-to-date topics in the field of systems and control, including robust control, adaptive control, fault-tolerant control, control reconfiguration, and model-based diagnosis of linear, nonlinear and hybrid systems. As the subject coverage has expanded to include cyber-physical production systems, industrial internet of things and sustainability issues, some contributions are of an interdisciplinary nature, involving ICT disciplines and environmental sciences. This book is a valuable reference for both academics and professionals in the area of systems and control, with a focus on advanced control, automation, fault diagnosis and condition monitoring.
Author : Maciej Ławryńczuk
Publisher : Springer Science & Business Media
ISBN 13 : 3319042297
Total Pages : 336 pages
Book Rating : 4.3/5 (19 download)
Download or read book Computationally Efficient Model Predictive Control Algorithms written by Maciej Ławryńczuk and published by Springer Science & Business Media. This book was released on 2014-01-24 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: · A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. · Implementation details of the MPC algorithms for feed forward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. · The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). · The MPC algorithms with neural approximation with no on-line linearization. · The MPC algorithms with guaranteed stability and robustness. · Cooperation between the MPC algorithms and set-point optimization. Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require demanding on-line nonlinear optimization. The presented simulation results demonstrate high accuracy and computational efficiency of the algorithms. For a few representative nonlinear benchmark processes, such as chemical reactors and a distillation column, for which the classical MPC algorithms based on linear models do not work properly, the trajectories obtained in the suboptimal MPC algorithms are very similar to those given by the ``ideal'' MPC algorithm with on-line nonlinear optimization repeated at each sampling instant. At the same time, the suboptimal MPC algorithms are significantly less computationally demanding.
Author : Jinfeng Liu
Publisher : MDPI
ISBN 13 : 303897420X
Total Pages : 231 pages
Book Rating : 4.0/5 (389 download)
Download or read book New Directions on Model Predictive Control written by Jinfeng Liu and published by MDPI. This book was released on 2019-01-16 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "New Directions on Model Predictive Control" that was published in Mathematics
Author : Dirk Thiele
Publisher :
ISBN 13 :
Total Pages : 266 pages
Book Rating : 4.:/5 (457 download)
Download or read book Novel Methods that Improve Feedback Performance of Model Predictive Control with Model Mismatch written by Dirk Thiele and published by . This book was released on 2009 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model predictive control (MPC) has gained great acceptance in the industry since it was developed and first applied about 25 years ago (1). It has established its place mainly in the advanced control community. Traditionally, MPC configurations are developed and commissioned by control experts. MPC implementations have usually been only worthwhile to apply on processes that promise large profit increase in return for the large cost of implementation. Thus the scale of MPC applications in terms of number of inputs and outputs has usually been large. This is the main reason why MPC has not made its way into low-level loop control. In recent years, academia and control system vendors have made efforts to broaden the range of MPC applications. Single loop MPC and multiple PID strategy replacements for processes that are difficult to control with PID controllers have become available and easier to implement. Such processes include deadtime-dominant processes, override strategies, decoupling networks, and more. MPC controllers generally have more "knobs" that can be adjusted to gain optimum performance than PID. To solve this problem, general PID replacement MPC controllers have been suggested. Such controllers include forward modeling controller (FMC)(2), constraint LQ control(3) and adaptive controllers like ADCO(4). These controllers are meant to combine the benefits of predictive control performance and the convenience of only few (more or less intuitive) tuning parameters. However, up until today, MPC controllers generally have only succeeded in industrial environments where PID control was performing poorly or was too difficult to implement or maintain. Many papers and field reports (5) from control experts show that PID control still performs better for a significant number of processes. This is on top of the fact that PID controllers are cheaper and faster to deploy than MPC controllers. Consequently, MPC controllers have actually replaced only a small fraction of PID controllers. This research shows that deficiencies in the feedback control capabilities of MPC controllers are one reason for the performance gap between PID and MPC. By adopting knowledge from PID and other proven feedback control algorithms, such as statistical process control (SPC) and Fuzzy logic, this research aims to find algorithms that demonstrate better feedback control performance than methods commonly used today in model predictive controllers. Initially, the research focused on single input single output (SISO) processes. It is important to ensure that the new feedback control strategy is implemented in a way that does not degrade the control functionality that makes MPC superior to PID in multiple input multiple output (MIMO) processes.
Author : Shaoyuan Li
Publisher : John Wiley & Sons
ISBN 13 : 1118921593
Total Pages : 421 pages
Book Rating : 4.1/5 (189 download)
Download or read book Distributed Model Predictive Control for Plant-Wide Systems written by Shaoyuan Li and published by John Wiley & Sons. This book was released on 2017-05-02 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: DISTRIBUTED MODEL PREDICTIVE CONTROL FOR PLANT-WIDE SYSTEMS In this book, experienced researchers gave a thorough explanation of distributed model predictive control (DMPC): its basic concepts, technologies, and implementation in plant-wide systems. Known for its error tolerance, high flexibility, and good dynamic performance, DMPC is a popular topic in the control field and is widely applied in many industries. To efficiently design DMPC systems, readers will be introduced to several categories of coordinated DMPCs, which are suitable for different control requirements, such as network connectivity, error tolerance, performance of entire closed-loop systems, and calculation of speed. Various real-life industrial applications, theoretical results, and algorithms are provided to illustrate key concepts and methods, as well as to provide solutions to optimize the global performance of plant-wide systems. Features system partition methods, coordination strategies, performance analysis, and how to design stabilized DMPC under different coordination strategies. Presents useful theories and technologies that can be used in many different industrial fields, examples include metallurgical processes and high-speed transport. Reflects the authors’ extensive research in the area, providing a wealth of current and contextual information. Distributed Model Predictive Control for Plant-Wide Systems is an excellent resource for researchers in control theory for large-scale industrial processes. Advanced students of DMPC and control engineers will also find this as a comprehensive reference text.
Author : Frank Allgöwer
Publisher : Birkhäuser
ISBN 13 : 3034884079
Total Pages : 463 pages
Book Rating : 4.0/5 (348 download)
Download or read book Nonlinear Model Predictive Control written by Frank Allgöwer and published by Birkhäuser. This book was released on 2012-12-06 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Gorazd Karer
Publisher : Springer
ISBN 13 : 3642339476
Total Pages : 261 pages
Book Rating : 4.6/5 (423 download)
Download or read book Predictive Approaches to Control of Complex Systems written by Gorazd Karer and published by Springer. This book was released on 2012-09-20 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: A predictive control algorithm uses a model of the controlled system to predict the system behavior for various input scenarios and determines the most appropriate inputs accordingly. Predictive controllers are suitable for a wide range of systems; therefore, their advantages are especially evident when dealing with relatively complex systems, such as nonlinear, constrained, hybrid, multivariate systems etc. However, designing a predictive control strategy for a complex system is generally a difficult task, because all relevant dynamical phenomena have to be considered. Establishing a suitable model of the system is an essential part of predictive control design. Classic modeling and identification approaches based on linear-systems theory are generally inappropriate for complex systems; hence, models that are able to appropriately consider complex dynamical properties have to be employed in a predictive control algorithm. This book first introduces some modeling frameworks, which can encompass the most frequently encountered complex dynamical phenomena and are practically applicable in the proposed predictive control approaches. Furthermore, unsupervised learning methods that can be used for complex-system identification are treated. Finally, several useful predictive control algorithms for complex systems are proposed and their particular advantages and drawbacks are discussed. The presented modeling, identification and control approaches are complemented by illustrative examples. The book is aimed towards researches and postgraduate students interested in modeling, identification and control, as well as towards control engineers needing practically usable advanced control methods for complex systems.
Author : Stanko Strmčnik
Publisher : Springer Science & Business Media
ISBN 13 : 1447151763
Total Pages : 418 pages
Book Rating : 4.4/5 (471 download)
Download or read book Case Studies in Control written by Stanko Strmčnik and published by Springer Science & Business Media. This book was released on 2013-06-12 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: Case Studies in Control presents a framework to facilitate the use of advanced control concepts in real systems based on two decades of research and over 150 successful applications for industrial end-users from various backgrounds. In successive parts the text approaches the problem of putting the theory to work from both ends, theoretical and practical. The first part begins with a stress on solid control theory and the shaping of that theory to solve particular instances of practical problems. It emphasizes the need to establish by experiment whether a model-derived solution will perform properly in reality. The second part focuses on real industrial applications based on the needs and requirements of end-users. Here, the engineering approach is dominant but with theoretical input of varying degree depending on the particular process involved. Following the illustrations of the progress that can be made from either extreme of the well-known theory–practice divide, the text proceeds to a third part related to the development of tools that enable simpler use of advanced methods, a need only partially met by available commercial products. Each case study represents a self-contained unit that shows an experimental application of a particular method, a practical solution to an industrial problem or a toolkit that makes control design and implementation easier or more efficient. Among the applications presented are: wastewater treatment; manufacturing of electrical motors ; temperature control of blow moulding; burn-protective garments quality assessment; and rapid prototyping. Written by contributors with a considerable record of industrially-applied research, Case Studies in Control will encourage interaction between industrial practitioners and academic researchers and be of benefit to both, helping to make theory realistic and practical implementation more thorough and efficacious. Advances in Industrial Control aims to report and encourage 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.
Author : Michael Mulholland
Publisher : John Wiley & Sons
ISBN 13 : 3527801618
Total Pages : 480 pages
Book Rating : 4.5/5 (278 download)
Download or read book Applied Process Control written by Michael Mulholland and published by John Wiley & Sons. This book was released on 2016-06-17 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: The basic working knowledge for the practicing control engineer in industry, offered here as a handy deluxe edition comprising two volumes each devoted to methods and practical problems. Focusing on the practical implementation, the methods volume provides readers with rapid access to process modelling and control, while including the theoretical background necessary. Throughout, the essential knowledge is built up from chapter to chapter, starting with laying the foundations in plant instrumentation and control. Modelling abilities are then developed by starting from simple time-loop algorithms and passing on to discrete methods, Laplace transforms, automata and fuzzy logic. In the end, readers have the means to design simple controllers on the basis of their own models, and to use more detailed models to test them. With its clarity and simplicity of presentation, and illustrated by more than 200 diagrams, the volume supports self-study and teaches readers how to apply the appropriate method for the application required, and how to handle problems in process control. Bridging theory and practice, the second volume contains over 200 practical exercises and their solutions to develop the problem-solving abilities of process engineers. The problems were developed by the author during his many years of teaching at university and are kept brief, taken from the fields of instrumentation, modeling, plant control, control strategy design and stability of control. The algorithm flows and codes, which are mostly based on MATLAB®, are given in many cases and allow for easy translation into applications. With a clarity and simplicity of presentation, the two volumes are similarly structured for easy orientation.
Author : Lino Marques
Publisher : World Scientific
ISBN 13 : 9814469637
Total Pages : 1309 pages
Book Rating : 4.8/5 (144 download)
Download or read book Advances In Mobile Robotics - Proceedings Of The Eleventh International Conference On Climbing And Walking Robots And The Support Technologies For Mobile Machines written by Lino Marques and published by World Scientific. This book was released on 2008-08-29 with total page 1309 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides state-of-the-art scientific and engineering research findings and developments in the area of mobile robotics and associated support technologies. It contains peer-reviewed articles presented at the CLAWAR 2008 conference. Robots are no longer confined to industrial manufacturing environments; rather, a great deal of interest is invested in the use of robots outside the factory environment. The CLAWAR conference series, established as a high-profile international event, acts as a platform for dissemination of research and development findings to address the current interest in mobile robotics in meeting the needs of mankind in various sectors of the society. These include personal care, public health, and services in the domestic, public and industrial environments. The editors of the book have extensive research experience and publications in the area of robotics in general, and in mobile robotics specifically.
Author : Raffaele Soloperto
Publisher : Logos Verlag Berlin GmbH
ISBN 13 : 383255744X
Total Pages : 172 pages
Book Rating : 4.8/5 (325 download)
Download or read book Learning-based Model Predictive Control with closed-loop guarantees written by Raffaele Soloperto and published by Logos Verlag Berlin GmbH. This book was released on 2023-11-13 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: The performance of model predictive control (MPC) largely depends on the accuracy of the prediction model and of the constraints the system is subject to. However, obtaining an accurate knowledge of these elements might be expensive in terms of money and resources, if at all possible. In this thesis, we develop novel learning-based MPC frameworks that actively incentivize learning of the underlying system dynamics and of the constraints, while ensuring recursive feasibility, constraint satisfaction, and performance bounds for the closed-loop. In the first part, we focus on the case of inaccurate models, and analyze learning-based MPC schemes that include, in addition to the primary cost, a learning cost that aims at generating informative data by inducing excitation in the system. In particular, we first propose a nonlinear MPC framework that ensures desired performance bounds for the resulting closed-loop, and then we focus on linear systems subject to uncertain parameters and noisy output measurements. In order to ensure that the desired learning phase occurs in closed-loop operations, we then propose an MPC framework that is able to guarantee closed-loop learning of the controlled system. In the last part of the thesis, we investigate the scenario where the system is known but evolves in a partially unknown environment. In such a setup, we focus on a learning-based MPC scheme that incentivizes safe exploration if and only if this might yield to a performance improvement.
Author : Isik Ilber Sirmatel
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (891 download)
Download or read book Adaptive Model Predictive Control of Constrained Multiple-Input Multiple-Output Systems and Its Application to the Quad Tank System written by Isik Ilber Sirmatel and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
