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Author: Zhongsheng Hou
Publisher: CRC Press
ISBN: 1466594187
Category : Technology & Engineering
Languages : en
Pages : 400
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Book Description
Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.
Author: Zhongsheng Hou
Publisher: CRC Press
ISBN: 1466594187
Category : Technology & Engineering
Languages : en
Pages : 400
Get Book Here
Book Description
Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.
Author: R Murray-Smith
Publisher: CRC Press
ISBN: 100012407X
Category : Technology & Engineering
Languages : en
Pages : 361
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Book Description
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: Bela G. Liptak
Publisher: CRC Press
ISBN: 1420064002
Category : Technology & Engineering
Languages : en
Pages : 2460
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Book Description
The latest update to Bela Liptak's acclaimed "bible" of instrument engineering is now available. Retaining the format that made the previous editions bestsellers in their own right, the fourth edition of Process Control and Optimization continues the tradition of providing quick and easy access to highly practical information. The authors are practicing engineers, not theoretical people from academia, and their from-the-trenches advice has been repeatedly tested in real-life applications. Expanded coverage includes descriptions of overseas manufacturer's products and concepts, model-based optimization in control theory, new major inventions and innovations in control valves, and a full chapter devoted to safety. With more than 2000 graphs, figures, and tables, this all-inclusive encyclopedic volume replaces an entire library with one authoritative reference. The fourth edition brings the content of the previous editions completely up to date, incorporates the developments of the last decade, and broadens the horizons of the work from an American to a global perspective. Béla G. Lipták speaks on Post-Oil Energy Technology on the AT&T Tech Channel.
Author: Yiannis Boutalis
Publisher: Springer Science & Business
ISBN: 3319063642
Category : Technology & Engineering
Languages : en
Pages : 316
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Book Description
Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.
Author: Vassil Sgurev
Publisher: Springer
ISBN: 3319414380
Category : Technology & Engineering
Languages : en
Pages : 389
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Book Description
This volume is a brief, yet comprehensive account of new development, tools, techniques and solutions in the broadly perceived “intelligent systems”. New concepts and ideas concern the development of effective and efficient models which would make it possible to effectively and efficiently describe and solve processes in various areas of science and technology. Special emphasis is on the dealing with uncertainty and imprecision that permeates virtually all real world processes and phenomena, and has to properly be modeled by formal and algorithmic tools and techniques so that they be adequate and useful. The papers in this volume concern a wide array of possible techniques exemplified by, on the one hand, logic, probabilistic, fuzzy, intuitionistic fuzzy, neuro-fuzzy, etc. approaches. On the other hand, they represent the use of such systems modeling tools as generalized nets, optimization and control models, systems analytic models, etc. They concerns a variety of approaches, from pattern recognition, image analysis, education system modeling, biological and medical systems modeling, etc.
Author: Stanko Strmčnik
Publisher: Springer Science & Business Media
ISBN: 1447151763
Category : Technology & Engineering
Languages : en
Pages : 418
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Book Description
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: Roshni Maiti
Publisher: Springer Nature
ISBN: 3030971023
Category : Technology & Engineering
Languages : en
Pages : 263
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Book Description
This book details the designing of hybrid control strategies for practical systems containing time varying uncertainties, disturbances, nonlinearities, unknown parameters, unmodelled dynamics, delays, etc., concurrently. In this book, the advantages of different controllers will be brought together to produce superior control performance for the practical systems. Being aware of the advantages of adaptive controller to tackle unknown constant, time varying uncertainties and time varying disturbances, a variant of adaptive controller, namely L1 adaptive controller, is hybridized with other strategies. In this book, to facilitate optimal parameter setting of the basic L1 adaptive controller, stochastic optimization technique will be hybridized with it. The stability of the optimization technique along with the controller will be guaranteed analytically with the help of spectral radius convergence. The proposed method exhibits satisfactory exploration and exploitation capabilities. Again, this book will throw light on tackling nonlinearities along with uncertainties and disturbances by hybridizing fuzzy logic with L1 adaptive controller. The performances of the designed controllers will be compared with different control methodologies to validate their effectiveness. The overall stability of the nonlinear system with the designed controller will be guaranteed with the help of fuzzy Lyapunov function to retain the zonal behaviour of the system. This fuzzy PDC-L1 adaptive controller is efficient to tackle nonlinearities and at the same time cancels unknown constant, time varying uncertainties and time varying disturbances adequately. This book will also contain four simulation case studies to validate fruitfulness of the designed controllers. To demonstrate the superior control ability of these controllers in tackling practical system, three experimental case studies will also be provided.
Author: João M. Lemos
Publisher: Springer
ISBN: 3319068539
Category : Technology & Engineering
Languages : en
Pages : 261
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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: Alessandro Astolfi
Publisher: Springer Science & Business Media
ISBN: 1848000669
Category : Technology & Engineering
Languages : en
Pages : 302
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Book Description
The authors here provide a detailed treatment of the design of robust adaptive controllers for nonlinear systems with uncertainties. They employ a new tool based on the ideas of system immersion and manifold invariance. New algorithms are delivered for the construction of robust asymptotically-stabilizing and adaptive control laws for nonlinear systems. The methods proposed lead to modular schemes that are easier to tune than their counterparts obtained from Lyapunov redesign.
Author: Valentina Emilia Balas
Publisher: Springer
ISBN: 3662433702
Category : Technology & Engineering
Languages : en
Pages : 261
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Book Description
This research monograph presents selected areas of applications in the field of control systems engineering using computational intelligence methodologies. A number of applications and case studies are introduced. These methodologies are increasing used in many applications of our daily lives. Approaches include, fuzzy-neural multi model for decentralized identification, model predictive control based on time dependent recurrent neural network development of cognitive systems, developments in the field of Intelligent Multiple Models based Adaptive Switching Control, designing military training simulators using modelling, simulation, and analysis for operational analyses and training, methods for modelling of systems based on the application of Gaussian processes, computational intelligence techniques for process control and image segmentation technique based on modified particle swarm optimized-fuzzy entropy.
