Adaptive Modeling And Control

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Model-Reference Adaptive Control

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Author : Nhan T. Nguyen
Publisher : Springer
ISBN 13 : 3319563939
Total Pages : 453 pages
Book Rating : 4.3/5 (195 download)

Book Synopsis Model-Reference Adaptive Control by : Nhan T. Nguyen

Download or read book Model-Reference Adaptive Control written by Nhan T. Nguyen and published by Springer. This book was released on 2018-03-01 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides readers with a good working knowledge of adaptive control theory through applications. It is intended for students beginning masters or doctoral courses, and control practitioners wishing to get up to speed in the subject expeditiously. Readers are taught a wide variety of adaptive control techniques starting with simple methods and extending step-by-step to more complex ones. Stability proofs are provided for all adaptive control techniques without obfuscating reader understanding with excessive mathematics. The book begins with standard model-reference adaptive control (MRAC) for first-order, second-order, and multi-input, multi-output systems. Treatment of least-squares parameter estimation and its extension to MRAC follow, helping readers to gain a different perspective on MRAC. Function approximation with orthogonal polynomials and neural networks, and MRAC using neural networks are also covered. Robustness issues connected with MRAC are discussed, helping the student to appreciate potential pitfalls of the technique. This appreciation is encouraged by drawing parallels between various aspects of robustness and linear time-invariant systems wherever relevant. Following on from the robustness problems is material covering robust adaptive control including standard methods and detailed exposition of recent advances, in particular, the author’s work on optimal control modification. Interesting properties of the new method are illustrated in the design of adaptive systems to meet stability margins. This method has been successfully flight-tested on research aircraft, one of various flight-control applications detailed towards the end of the book along with a hybrid adaptive flight control architecture that combines direct MRAC with least-squares indirect adaptive control. In addition to the applications, understanding is encouraged by the use of end-of-chapter exercises and associated MATLAB® files. Readers will need no more than the standard mathematics for basic control theory such as differential equations and matrix algebra; the book covers the foundations of MRAC and the necessary mathematical preliminaries.

Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics

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Author : Jing Na
Publisher : Academic Press
ISBN 13 : 0128136847
Total Pages : 338 pages
Book Rating : 4.1/5 (281 download)

Book Synopsis Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics by : Jing Na

Download or read book Adaptive Identification and Control of Uncertain Systems with Non-smooth Dynamics written by Jing Na and published by Academic Press. This book was released on 2018-06-12 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Identification and Control of Uncertain Systems with Nonsmooth Dynamics reports some of the latest research on modeling, identification and adaptive control for systems with nonsmooth dynamics (e.g., backlash, dead zone, friction, saturation, etc). The authors present recent research results for the modelling and control designs of uncertain systems with nonsmooth dynamics, such as friction, dead-zone, saturation and hysteresis, etc., with particular applications in servo systems. The book is organized into 19 chapters, distributed in five parts concerning the four types of nonsmooth characteristics, namely friction, dead-zone, saturation and hysteresis, respectively. Practical experiments are also included to validate and exemplify the proposed approaches. This valuable resource can help both researchers and practitioners to learn and understand nonlinear adaptive control designs. Academics, engineers and graduate students in the fields of electrical engineering, control systems, mechanical engineering, applied mathematics and computer science can benefit from the book. It can be also used as a reference book on adaptive control for servo systems for students with some background in control engineering. - Explains the latest research outputs on modeling, identification and adaptive control for systems with nonsmooth dynamics - Provides practical application and experimental results for robotic systems, and servo motors

Adaptive Internal Model Control

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Author : Aniruddha Datta
Publisher : Springer Science & Business Media
ISBN 13 : 0857293311
Total Pages : 166 pages
Book Rating : 4.8/5 (572 download)

Book Synopsis Adaptive Internal Model Control by : Aniruddha Datta

Download or read book Adaptive Internal Model Control written by Aniruddha Datta and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written in a self-contained tutorial fashion, this monograph successfully brings the latest theoretical advances in the design of robust adaptive systems to the realm of industrial applications. It provides a theoretical basis for verifying some of the reported industrial successes of existing adaptive control schemes and enables readers to synthesize adaptive versions of their own robust internal model control schemes.

Modeling and Adaptive Nonlinear Control of Electric Motors

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Author : Farshad Khorrami
Publisher : Springer Science & Business Media
ISBN 13 : 9783540009368
Total Pages : 546 pages
Book Rating : 4.0/5 (93 download)

Book Synopsis Modeling and Adaptive Nonlinear Control of Electric Motors by : Farshad Khorrami

Download or read book Modeling and Adaptive Nonlinear Control of Electric Motors written by Farshad Khorrami and published by Springer Science & Business Media. This book was released on 2003-05-21 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, modeling and control design of electric motors, namely step motors, brushless DC motors and induction motors, are considered. The book focuses on recent advances on feedback control designs for various types of electric motors, with a slight emphasis on stepper motors. For this purpose, the authors explore modeling of these devices to the extent needed to provide a high-performance controller, but at the same time one amenable to model-based nonlinear designs. The control designs focus primarily on recent robust adaptive nonlinear controllers to attain high performance. It is shown that the adaptive robust nonlinear controller on its own achieves reasonably good performance without requiring the exact knowledge of motor parameters. While carefully tuned classical controllers often achieve required performance in many applications, it is hoped that the advocated robust and adaptive designs will lead to standard universal controllers with minimal need for fine tuning of control parameters.

Adaptive Control with Recurrent High-order Neural Networks

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Author : George A. Rovithakis
Publisher : Springer Science & Business Media
ISBN 13 : 1447107853
Total Pages : 203 pages
Book Rating : 4.4/5 (471 download)

Book Synopsis Adaptive Control with Recurrent High-order Neural Networks by : George A. Rovithakis

Download or read book Adaptive Control with Recurrent High-order Neural Networks written by George A. Rovithakis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Neural networks is one of those areas where an initial burst of enthusiasm and optimism leads to an explosion of papers in the journals and many presentations at conferences but it is only in the last decade that significant theoretical work on stability, convergence and robustness for the use of neural networks in control systems has been tackled. George Rovithakis and Manolis Christodoulou have been interested in these theoretical problems and in the practical aspects of neural network applications to industrial problems. This very welcome addition to the Advances in Industrial Control series provides a succinct report of their research. The neural network model at the core of their work is the Recurrent High Order Neural Network (RHONN) and a complete theoretical and simulation development is presented. Different readers will find different aspects of the development of interest. The last chapter of the monograph discusses the problem of manufacturing or production process scheduling.

Robust Adaptive Control

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Author : Petros Ioannou
Publisher : Courier Corporation
ISBN 13 : 0486320723
Total Pages : 850 pages
Book Rating : 4.4/5 (863 download)

Book Synopsis Robust Adaptive Control by : Petros Ioannou

Download or read book Robust Adaptive Control written by Petros Ioannou and published by Courier Corporation. This book was released on 2013-09-26 with total page 850 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presented in a tutorial style, this comprehensive treatment unifies, simplifies, and explains most of the techniques for designing and analyzing adaptive control systems. Numerous examples clarify procedures and methods. 1995 edition.

Adaptive Modelling, Estimation and Fusion from Data

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Author : Chris Harris
Publisher : Springer Science & Business Media
ISBN 13 : 9783540426868
Total Pages : 346 pages
Book Rating : 4.4/5 (268 download)

Book Synopsis Adaptive Modelling, Estimation and Fusion from Data by : Chris Harris

Download or read book Adaptive Modelling, Estimation and Fusion from Data written by Chris Harris and published by Springer Science & Business Media. This book was released on 2002-05-13 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together for the first time the complete theory of data based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data based modelling new concepts including extended additive and multiplicative submodels are developed. All of these algorithms are illustrated with benchmark examples to demonstrate their efficiency. The book aims at researchers and advanced professionals in time series modelling, empirical data modelling, knowledge discovery, data mining and data fusion.

Model Reference Adaptive Control

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Author : Hans Butler
Publisher :
ISBN 13 :
Total Pages : 296 pages
Book Rating : 4.3/5 (91 download)

Book Synopsis Model Reference Adaptive Control by : Hans Butler

Download or read book Model Reference Adaptive Control written by Hans Butler and published by . This book was released on 1992 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work, aiming to bring adaptive control theory closer to practice, offers explanations rather than theory, and draws upon several laboratory experiments for emphasis. The first part of the book covers established subjects and the second covers solutions to some problems.

Adaptive Control Design and Analysis

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Author : Gang Tao
Publisher : John Wiley & Sons
ISBN 13 : 9780471274520
Total Pages : 652 pages
Book Rating : 4.2/5 (745 download)

Book Synopsis Adaptive Control Design and Analysis by : Gang Tao

Download or read book Adaptive Control Design and Analysis written by Gang Tao and published by John Wiley & Sons. This book was released on 2003-07-09 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt: A systematic and unified presentation of the fundamentals of adaptive control theory in both continuous time and discrete time Today, adaptive control theory has grown to be a rigorous and mature discipline. As the advantages of adaptive systems for developing advanced applications grow apparent, adaptive control is becoming more popular in many fields of engineering and science. Using a simple, balanced, and harmonious style, this book provides a convenient introduction to the subject and improves one's understanding of adaptive control theory. Adaptive Control Design and Analysis features: Introduction to systems and control Stability, operator norms, and signal convergence Adaptive parameter estimation State feedback adaptive control designs Parametrization of state observers for adaptive control Unified continuous and discrete-time adaptive control L1+a robustness theory for adaptive systems Direct and indirect adaptive control designs Benchmark comparison study of adaptive control designs Multivariate adaptive control Nonlinear adaptive control Adaptive compensation of actuator nonlinearities End-of-chapter discussion, problems, and advanced topics As either a textbook or reference, this self-contained tutorial of adaptive control design and analysis is ideal for practicing engineers, researchers, and graduate students alike.

Model Free Adaptive Control

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Author : Zhongsheng Hou
Publisher : CRC Press
ISBN 13 : 1466594187
Total Pages : 400 pages
Book Rating : 4.4/5 (665 download)

Book Synopsis Model Free Adaptive Control by : Zhongsheng Hou

Download or read book Model Free Adaptive Control written by Zhongsheng Hou and published by CRC Press. This book was released on 2013-09-24 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Learning-Based Adaptive Control

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Author : Mouhacine Benosman
Publisher : Butterworth-Heinemann
ISBN 13 : 0128031514
Total Pages : 284 pages
Book Rating : 4.1/5 (28 download)

Book Synopsis Learning-Based Adaptive Control by : Mouhacine Benosman

Download or read book Learning-Based Adaptive Control written by Mouhacine Benosman and published by Butterworth-Heinemann. This book was released on 2016-08-02 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Robust and Adaptive Control

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Author : Eugene Lavretsky
Publisher : Springer Science & Business Media
ISBN 13 : 1447143965
Total Pages : 506 pages
Book Rating : 4.4/5 (471 download)

Book Synopsis Robust and Adaptive Control by : Eugene Lavretsky

Download or read book Robust and Adaptive Control written by Eugene Lavretsky and published by Springer Science & Business Media. This book was released on 2012-11-13 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust and Adaptive Control shows the reader how to produce consistent and accurate controllers that operate in the presence of uncertainties and unforeseen events. Driven by aerospace applications the focus of the book is primarily on continuous-dynamical systems. The text is a three-part treatment, beginning with robust and optimal linear control methods and moving on to a self-contained presentation of the design and analysis of model reference adaptive control (MRAC) for nonlinear uncertain dynamical systems. Recent extensions and modifications to MRAC design are included, as are guidelines for combining robust optimal and MRAC controllers. Features of the text include: · case studies that demonstrate the benefits of robust and adaptive control for piloted, autonomous and experimental aerial platforms; · detailed background material for each chapter to motivate theoretical developments; · realistic examples and simulation data illustrating key features of the methods described; and · problem solutions for instructors and MATLAB® code provided electronically. The theoretical content and practical applications reported address real-life aerospace problems, being based on numerous transitions of control-theoretic results into operational systems and airborne vehicles that are drawn from the authors’ extensive professional experience with The Boeing Company. The systems covered are challenging, often open-loop unstable, with uncertainties in their dynamics, and thus requiring both persistently reliable control and the ability to track commands either from a pilot or a guidance computer. Readers are assumed to have a basic understanding of root locus, Bode diagrams, and Nyquist plots, as well as linear algebra, ordinary differential equations, and the use of state-space methods in analysis and modeling of dynamical systems. Robust and Adaptive Control is intended to methodically teach senior undergraduate and graduate students how to construct stable and predictable control algorithms for realistic industrial applications. Practicing engineers and academic researchers will also find the book of great instructional value.

ADAPTIVE MODELING AND CONTROL.

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Author : Frederic D. Powell
Publisher :
ISBN 13 :
Total Pages : 118 pages
Book Rating : 4.:/5 (227 download)

Book Synopsis ADAPTIVE MODELING AND CONTROL. by : Frederic D. Powell

Download or read book ADAPTIVE MODELING AND CONTROL. written by Frederic D. Powell and published by . This book was released on 1970 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: Properties of and algorithms for a class of linear response-error adaptive modelers and of a class of nonlinear generalized equation error adaptive modelers using quantizers are examined. Adaptive inversion, decorrelation, orthogonalization and normalization are discussed. Control systems operating in two time-scales with preview, and using an adaptive modeler to estimate the state, dynamics, future trajectory, and step-response, etc., of the unknown plant, are developed. The analyses are supported by experimental results. (Author).

Adaptive Learning Methods for Nonlinear System Modeling

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Author : Danilo Comminiello
Publisher : Butterworth-Heinemann
ISBN 13 : 0128129778
Total Pages : 390 pages
Book Rating : 4.1/5 (281 download)

Book Synopsis Adaptive Learning Methods for Nonlinear System Modeling by : Danilo Comminiello

Download or read book Adaptive Learning Methods for Nonlinear System Modeling written by Danilo Comminiello and published by Butterworth-Heinemann. This book was released on 2018-06-11 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. - Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. - Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. - Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.

Applications of Neural Adaptive Control Technology

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Author : Jens Kalkkuhl
Publisher : World Scientific
ISBN 13 : 9789810231514
Total Pages : 328 pages
Book Rating : 4.2/5 (315 download)

Book Synopsis Applications of Neural Adaptive Control Technology by : Jens Kalkkuhl

Download or read book Applications of Neural Adaptive Control Technology written by Jens Kalkkuhl and published by World Scientific. This book was released on 1997 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the results of the second workshop on Neural Adaptive Control Technology, NACT II, held on September 9-10, 1996, in Berlin. The workshop was organised in connection with a three-year European-Union-funded Basic Research Project in the ESPRIT framework, called NACT, a collaboration between Daimler-Benz (Germany) and the University of Glasgow (Scotland).The NACT project, which began on 1 April 1994, is a study of the fundamental properties of neural-network-based adaptive control systems. Where possible, links with traditional adaptive control systems are exploited. A major aim is to develop a systematic engineering procedure for designing neural controllers for nonlinear dynamic systems. The techniques developed are being evaluated on concrete industrial problems from within the Daimler-Benz group of companies.The aim of the workshop was to bring together selected invited specialists in the fields of adaptive control, nonlinear systems and neural networks. The first workshop (NACT I) took place in Glasgow in May 1995 and was mainly devoted to theoretical issues of neural adaptive control. Besides monitoring further development of theory, the NACT II workshop was focused on industrial applications and software tools. This context dictated the focus of the book and guided the editors in the choice of the papers and their subsequent reshaping into substantive book chapters. Thus, with the project having progressed into its applications stage, emphasis is put on the transfer of theory of neural adaptive engineering into industrial practice. The contributors are therefore both renowned academics and practitioners from major industrial users of neurocontrol.

Adaptive Control Tutorial

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Author : Petros Ioannou
Publisher : SIAM
ISBN 13 : 0898716152
Total Pages : 401 pages
Book Rating : 4.8/5 (987 download)

Book Synopsis Adaptive Control Tutorial by : Petros Ioannou

Download or read book Adaptive Control Tutorial written by Petros Ioannou and published by SIAM. This book was released on 2006-01-01 with total page 401 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed to meet the needs of a wide audience without sacrificing mathematical depth and rigor, Adaptive Control Tutorial presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Its tutorial-style presentation of the fundamental techniques and algorithms in adaptive control make it suitable as a textbook. Adaptive Control Tutorial is designed to serve the needs of three distinct groups of readers: engineers and students interested in learning how to design, simulate, and implement parameter estimators and adaptive control schemes without having to fully understand the analytical and technical proofs; graduate students who, in addition to attaining the aforementioned objectives, also want to understand the analysis of simple schemes and get an idea of the steps involved in more complex proofs; and advanced students and researchers who want to study and understand the details of long and technical proofs with an eye toward pursuing research in adaptive control or related topics. The authors achieve these multiple objectives by enriching the book with examples demonstrating the design procedures and basic analysis steps and by detailing their proofs in both an appendix and electronically available supplementary material; online examples are also available. A solution manual for instructors can be obtained by contacting SIAM or the authors. Preface; Acknowledgements; List of Acronyms; Chapter 1: Introduction; Chapter 2: Parametric Models; Chapter 3: Parameter Identification: Continuous Time; Chapter 4: Parameter Identification: Discrete Time; Chapter 5: Continuous-Time Model Reference Adaptive Control; Chapter 6: Continuous-Time Adaptive Pole Placement Control; Chapter 7: Adaptive Control for Discrete-Time Systems; Chapter 8: Adaptive Control of Nonlinear Systems; Appendix; Bibliography; Index

Adaptive Control

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Author : Yoan D. Landau
Publisher : CRC Press
ISBN 13 : 9780824765484
Total Pages : 432 pages
Book Rating : 4.7/5 (654 download)

Book Synopsis Adaptive Control by : Yoan D. Landau

Download or read book Adaptive Control written by Yoan D. Landau and published by CRC Press. This book was released on 1979-06-01 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: