Optimal, Predictive, and Adaptive Control PDF Download

Author: Edoardo Mosca
Publisher: Pearson Education
ISBN:
Category : Adaptive control systems
Languages : en
Pages : 504

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Book Description
Using a common unifying framework, this volume explores the main topics of Linear Quadratic control, predictive control, and adaptive predictive control -- in terms of theoretical foundations, analysis and design methodologies, and application-orient ed tools.Presents LQ and LQG control via two alternative approaches: the Dynamic Programming (DP) and the Polynomial Equation (PE) approach. Discusses predicable control, an important tool in industrial applications, within the framework of LQ control, and presents innovative predictive control schemes having guaranteed stability properties. Offers a unique, thorough presentation of indirect adaptive multi-step predictive controllers, with detailed proofs of globally convergent schemes for both the ideal and the bounded disturbance case. Extends the self-tuning property of one-step-ahead control to multi-step control.For engineers and mathematicians interested in the theory, analysis and design methodologies, and application-oriented tools of optimal, predictive and adaptive control.

Author: Juan M. Martín-Sánchez
Publisher: Springer
ISBN: 3319097946
Category : Technology & Engineering
Languages : en
Pages : 447

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Book Description
This book is a simple and didactic account of the developments and practical applications of predictive, adaptive predictive, and optimized adaptive control from a perspective of stability, including the latest methodology of adaptive predictive expert (ADEX) control. ADEX Optimized Adaptive Control Systems is divided into six parts, with exercises and real-time simulations provided for the reader as appropriate. The text begins with the conceptual and intuitive knowledge of the technology and derives the stability conditions to be verified by the driver block and the adaptive mechanism of the optimized adaptive controller to guaranty the desired control performance. The second and third parts present strategic considerations of predictive control and related adaptive systems necessary for the proper design of driver block and adaptive mechanism and thence their technical realization. The authors then proceed to detail the stability theory that supports predictive, adaptive predictive and optimized adaptive control methodologies. Benchmark applications of these methodologies (distillation column and pulp-factory bleaching plant) are treated next with a focus on practical implementation issues. The final part of the book describes ADEX platforms and illustrates their use in the design and implementation of optimized adaptive control systems to three different challenging-to-control industrial processes: waste-water treatment; sulfur recovery; and temperature control of superheated steam in coal-fired power generation. The presentation is completed by a number of appendices containing technical background associated with the main text including a manual for the ADEX COP platform developed by the first author to exploit the capabilities of adaptive predictive control in real plants. ADEX Optimized Adaptive Control Systems provides practicing process control engineers with a multivariable optimal control solution which is adaptive and resistant to perturbation and the effects of noise. Its pedagogical features also facilitate its use as a teaching tool for formal university and Internet-based open-education-type graduate courses in practical optimal adaptive control and for self-study.

Author: Juan Manuel Martín Sánchez
Publisher: Prentice Hall PTR
ISBN: 9780135148617
Category : Adaptive control systems
Languages : en
Pages : 0

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Book Description
This text discusses Adaptive Predictive Control Systems from their concepts to their application to the optimization in the operation of industrial plants. The book will represent the scientific and engineering background to SCAP Optimization Systems, which represent the first and only systematic implementation of Adaptive Predictive Control offered in the industrial market.

Author: Robert R. Bitmead
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 264

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Book Description
Exploring connections between adaptive control theory and practice, this book treats the techniques of linear quadratic optimal control and estimation (Kalman filtering), recursive identification, linear systems theory and robust arguments.

Author: Mouhacine Benosman
Publisher: Butterworth-Heinemann
ISBN: 0128031514
Category : Technology & Engineering
Languages : en
Pages : 282

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Book Description
Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. Includes a good number of Mechatronics Examples of the techniques. Compares and blends Model-free and Model-based learning algorithms. Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.

Author: David Sworder
Publisher:
ISBN:
Category :
Languages : en
Pages : 187

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Book Description

Author: Ronald Soeterboek
Publisher: Prentice Hall International
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 384

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Book Description
Describes in detail how several well-known predictive control schemes (for example, DMC and GPC) and other, more formal controller design methods can be formulated within a unified framework. The influence of the design parameters on control system performance and robustness is emphasized.

Author: Eduardo F. Camacho
Publisher: Springer Science & Business Media
ISBN: 1447130081
Category : Technology & Engineering
Languages : en
Pages : 250

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Book Description
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: João M. Lemos
Publisher: Springer
ISBN: 3319068539
Category : Technology & Engineering
Languages : en
Pages : 253

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Book Description
This book describes methods for adaptive control of distributed-collector solar fields: plants that collect solar energy and deliver it in thermal form. Controller design methods are presented that can overcome difficulties found in these type of plants: they are distributed-parameter systems, i.e., systems with dynamics that depend on space as well as time; their dynamics is nonlinear, with a bilinear structure; there is a significant level of uncertainty in plant knowledge. Adaptive methods form the focus of the text because of the degree of uncertainty in the knowledge of plant dynamics. Parts of the text are devoted to design methods that assume only a very limited knowledge about the plant. Other parts detail methods that rely on knowledge of the dominant plant structure. These methods are more plant specific, but allow the improvement of performance. Adaptive Control of Solar Energy Collector Systems demonstrates the dynamics of solar fields to be rich enough to present a challenge to the control designer while, at the same time, simple enough to allow analytic work to be done, providing case studies on dynamics and nonlinear control design in a simple and revealing, but nontrivial way. The control approaches treated in this monograph can be generalized to apply to other plants modelled by hyperbolic partial differential equations, especially process plants in which transport phenomena occur, plants like dryers, steam super-heaters and even highway traffic. An important example, used repeatedly throughout the text, is a distributed-collector solar field installed at Plataforma Solar de Almeria, located in southern Spain. The control algorithms laid out in the text are illustrated with experimental results generated from this plant. Although the primary focus of this monograph is solar energy collector, the range of other systems which can benefit from the methods described will make it of interest to control engineers working in many industries as well as to academic control researchers interested in adaptive control and its applications.

Author: José M. Maestre
Publisher: Springer Science & Business Media
ISBN: 9400770065
Category : Technology & Engineering
Languages : en
Pages : 600

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Book Description
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.