Neuro-Fuzzy Control of Industrial Systems with Actuator Nonlinearities PDF Download

Author: Frank L. Lewis
Publisher: SIAM
ISBN: 0898715059
Category : Technology & Engineering
Languages : en
Pages : 252

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Book Description
Brings neural networks and fuzzy logic together with dynamical control systems. Each chapter presents powerful control approaches for the design of intelligent controllers to compensate for actuator nonlinearities.

Author: Jelena Godjevac
Publisher: EPFL Press
ISBN: 9782880743550
Category : Fuzzy logic
Languages : en
Pages : 172

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Book Description

Author: Detlef Nauck
Publisher:
ISBN:
Category : Computers
Languages : en
Pages : 328

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Book Description
Foundations of Neuro-Fuzzy Systems reflects the current trend in intelligent systems research towards the integration of neural networks and fuzzy technology. The authors demonstrate how a combination of both techniques enhances the performance of control, decision-making and data analysis systems. Smarter and more applicable structures result from marrying the learning capability of the neural network with the transparency and interpretability of the rule-based fuzzy system. Foundations of Neuro-Fuzzy Systems highlights the advantages of integration making it a valuable resource for graduate students and researchers in control engineering, computer science and applied mathematics. The authors' informed analysis of practical neuro-fuzzy applications will be an asset to industrial practitioners using fuzzy technology and neural networks for control systems, data analysis and optimization tasks.

Author: Marcian Cirstea
Publisher: Newnes
ISBN: 9780750655583
Category : Education
Languages : en
Pages : 416

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Book Description
*Introduces cutting-edge control systems to a wide readership of engineers and students *The first book on neuro-fuzzy control systems to take a practical, applications-based approach, backed up with worked examples and case studies *Learn to use VHDL in real-world applications Introducing cutting edge control systems through real-world applications Neural networks and fuzzy logic based systems offer a modern control solution to AC machines used in variable speed drives, enabling industry to save costs and increase efficiency by replacing expensive and high-maintenance DC motor systems. The use of fast micros has revolutionised the field with sensorless vector control and direct torque control. This book reflects recent research findings and acts as a useful guide to the new generation of control systems for a wide readership of advanced undergraduate and graduate students, as well as practising engineers. The authors guide readers quickly and concisely through the complex topics of neural networks, fuzzy logic, mathematical modelling of electrical machines, power systems control and VHDL design. Unlike the academic monographs that have previously been published on each of these subjects, this book combines them and is based round case studies of systems analysis, control strategies, design, simulation and implementation. The result is a guide to applied control systems design that will appeal equally to students and professional design engineers. The book can also be used as a unique VHDL design aid, based on real-world power engineering applications.

Author: Nazmul Siddique
Publisher: Springer
ISBN: 3319021354
Category : Technology & Engineering
Languages : en
Pages : 292

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Book Description
Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller. The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined. The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area. Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control.

Author: Witold Pedrycz
Publisher: *Research Studies Press
ISBN:
Category : Computers
Languages : en
Pages : 376

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Book Description
Examines the methodology and algorithms of fuzzy sets considered mainly in the context of control engineering and system modelling and analysis. Special emphasis is focused on the processing of fuzzy information realized with the aid of fuzzy relational structures and their extensions.

Author: Chin-teng Lin
Publisher: World Scientific Publishing Company
ISBN: 9813104708
Category : Technology & Engineering
Languages : en
Pages : 152

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Book Description
A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.

Author: Jan Jantzen
Publisher: John Wiley & Sons
ISBN: 1118535596
Category : Technology & Engineering
Languages : en
Pages : 322

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Book Description
Foundations of Fuzzy Control: A Practical Approach, 2nd Edition has been significantly revised and updated, with two new chapters on Gain Scheduling Control and Neurofuzzy Modelling. It focuses on the PID (Proportional, Integral, Derivative) type controller which is the most widely used in industry and systematically analyses several fuzzy PID control systems and adaptive control mechanisms. This new edition covers the basics of fuzzy control and builds a solid foundation for the design of fuzzy controllers, by creating links to established linear and nonlinear control theory. Advanced topics are also introduced and in particular, common sense geometry is emphasised. Key features Sets out practical worked through problems, examples and case studies to illustrate each type of control system Accompanied by a website hosting downloadable MATLAB programs Accompanied by an online course on Fuzzy Control which is taught by the author. Students can access further material and enrol at the companion website Foundations of Fuzzy Control: A Practical Approach, 2nd Edition is an invaluable resource for researchers, practitioners, and students in engineering. It is especially relevant for engineers working with automatic control of mechanical, electrical, or chemical systems.

Author: Christian Moewes
Publisher: Springer
ISBN: 3642323782
Category : Technology & Engineering
Languages : en
Pages : 298

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Book Description
Complex systems and their phenomena are ubiquitous as they can be found in biology, finance, the humanities, management sciences, medicine, physics and similar fields. For many problems in these fields, there are no conventional ways to mathematically or analytically solve them completely at low cost. On the other hand, nature already solved many optimization problems efficiently. Computational intelligence attempts to mimic nature-inspired problem-solving strategies and methods. These strategies can be used to study, model and analyze complex systems such that it becomes feasible to handle them. Key areas of computational intelligence are artificial neural networks, evolutionary computation and fuzzy systems. As only a few researchers in that field, Rudolf Kruse has contributed in many important ways to the understanding, modeling and application of computational intelligence methods. On occasion of his 60th birthday, a collection of original papers of leading researchers in the field of computational intelligence has been collected in this volume.

Author: H. B. Verbruggen
Publisher: World Scientific
ISBN: 9789810238254
Category : Technology & Engineering
Languages : en
Pages : 344

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Book Description
Fuzzy logic control has become an important methodology in control engineering. This volume deals with applications of fuzzy logic control in various domains. The contributions are divided into three parts. The first part consists of two state-of-the-art tutorials on fuzzy control and fuzzy modeling. Surveys of advanced methodologies are included in the second part. These surveys address fuzzy decision making and control, fault detection, isolation and diagnosis, complexity reduction in fuzzy systems and neuro-fuzzy methods. The third part contains application-oriented contributions from various fields, such as process industry, cement and ceramics, vehicle control and traffic management, electromechanical and production systems, avionics, biotechnology and medical applications. The book is intended for researchers both from the academic world and from industry.