Advanced Mathematical Tools For Control Engineers Volume 1
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| Author | : Alexander S. Poznyak |
| Publisher | : Elsevier |
| Total Pages | : 803 |
| Release | : 2010-07-07 |
| Genre | : Mathematics |
| ISBN | : 0080556108 |
Advanced Mathematical Tools for Control Engineers: Volume 1 provides a blend of Matrix and Linear Algebra Theory, Analysis, Differential Equations, Optimization, Optimal and Robust Control. It contains an advanced mathematical tool which serves as a fundamental basis for both instructors and students who study or actively work in Modern Automatic Control or in its applications. It is includes proofs of all theorems and contains many examples with solutions. It is written for researchers, engineers, and advanced students who wish to increase their familiarity with different topics of modern and classical mathematics related to System and Automatic Control Theories. - Provides comprehensive theory of matrices, real, complex and functional analysis - Provides practical examples of modern optimization methods that can be effectively used in variety of real-world applications - Contains worked proofs of all theorems and propositions presented
| Author | : Alexander S. Poznyak |
| Publisher | : Elsevier |
| Total Pages | : 568 |
| Release | : 2009-08-13 |
| Genre | : Technology & Engineering |
| ISBN | : 0080914039 |
Advanced Mathematical Tools for Automatic Control Engineers, Volume 2: Stochastic Techniques provides comprehensive discussions on statistical tools for control engineers. The book is divided into four main parts. Part I discusses the fundamentals of probability theory, covering probability spaces, random variables, mathematical expectation, inequalities, and characteristic functions. Part II addresses discrete time processes, including the concepts of random sequences, martingales, and limit theorems. Part III covers continuous time stochastic processes, namely Markov processes, stochastic integrals, and stochastic differential equations. Part IV presents applications of stochastic techniques for dynamic models and filtering, prediction, and smoothing problems. It also discusses the stochastic approximation method and the robust stochastic maximum principle. - Provides comprehensive theory of matrices, real, complex and functional analysis - Provides practical examples of modern optimization methods that can be effectively used in variety of real-world applications - Contains worked proofs of all theorems and propositions presented
| Author | : Alex Poznyak |
| Publisher | : Elsevier Science |
| Total Pages | : 567 |
| Release | : 2009-11-05 |
| Genre | : Technology & Engineering |
| ISBN | : 9780080446738 |
Advanced Mathematical Tools for Automatic Control Engineers, Volume 2: Stochastic Techniques provides comprehensive discussions on statistical tools for control engineers. The book is divided into four main parts. Part I discusses the fundamentals of probability theory, covering probability spaces, random variables, mathematical expectation, inequalities, and characteristic functions. Part II addresses discrete time processes, including the concepts of random sequences, martingales, and limit theorems. Part III covers continuous time stochastic processes, namely Markov processes, stochastic integrals, and stochastic differential equations. Part IV presents applications of stochastic techniques for dynamic models and filtering, prediction, and smoothing problems. It also discusses the stochastic approximation method and the robust stochastic maximum principle. Provides comprehensive theory of matrices, real, complex and functional analysis Provides practical examples of modern optimization methods that can be effectively used in variety of real-world applications Contains worked proofs of all theorems and propositions presented
| Author | : Roland Burns |
| Publisher | : Butterworth-Heinemann |
| Total Pages | : 158 |
| Release | : 2001-11-07 |
| Genre | : Science |
| ISBN | : 9780750651004 |
Advanced Control Engineering provides a complete course in control engineering for undergraduates of all technical disciplines. Included are real-life case studies, numerous problems, and accompanying MatLab programs.
| Author | : Vladimir G. Boltyanski |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 440 |
| Release | : 2011-11-06 |
| Genre | : Science |
| ISBN | : 0817681523 |
Covering some of the key areas of optimal control theory (OCT), a rapidly expanding field, the authors use new methods to set out a version of OCT’s more refined ‘maximum principle.’ The results obtained have applications in production planning, reinsurance-dividend management, multi-model sliding mode control, and multi-model differential games. This book explores material that will be of great interest to post-graduate students, researchers, and practitioners in applied mathematics and engineering, particularly in the area of systems and control.
| Author | : Santo Banerjee |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 349 |
| Release | : 2011-09-06 |
| Genre | : Technology & Engineering |
| ISBN | : 3642219225 |
Chaos and nonlinear dynamics initially developed as a new emergent field with its foundation in physics and applied mathematics. The highly generic, interdisciplinary quality of the insights gained in the last few decades has spawned myriad applications in almost all branches of science and technology—and even well beyond. Wherever quantitative modeling and analysis of complex, nonlinear phenomena is required, chaos theory and its methods can play a key role. This volume concentrates on reviewing the most relevant contemporary applications of chaotic nonlinear systems as they apply to the various cutting-edge branches of engineering. The book covers the theory as applied to robotics, electronic and communication engineering (for example chaos synchronization and cryptography) as well as to civil and mechanical engineering, where its use in damage monitoring and control is explored). Featuring contributions from active and leading research groups, this collection is ideal both as a reference and as a ‘recipe book’ full of tried and tested, successful engineering applications
| Author | : Vladimir Vasilʹevich Mitin |
| Publisher | : Wiley-Interscience |
| Total Pages | : 336 |
| Release | : 2001-04-02 |
| Genre | : Mathematics |
| ISBN | : |
A convenient single source for vital mathematical concepts, writtenby engineers and for engineers. Builds a strong foundation in modern applied mathematics forengineering students, and offers them a concise and comprehensivetreatment that summarizes and unifies their mathematical knowledgeusing a system focused on basic concepts rather than exhaustivetheorems and proofs. The authors provide several levels of explanation and exercisesinvolving increasing degrees of mathematical difficulty to recalland develop basic topics such as calculus, determinants, Gaussianelimination, differential equations, and functions of a complexvariable. They include an assortment of examples ranging fromsimple illustrations to highly involved problems as well as anumber of applications that demonstrate the concepts and methodsdiscussed throughout the book. This broad treatment also offers:*Key mathematical tools needed by engineers working incommunications, semiconductor device simulation, and control theory* Concise coverage of fundamental concepts such as sets, mappings,and linearity * Thorough discussion of topics such as distance,inner product, and orthogonality * Essentials of operatorequations, theory of approximations, transform methods, and partialdifferential equationsIt makes an excellent companion to lessgeneral engineering texts and a useful reference for practitioners.
| Author | : Nabil Derbel |
| Publisher | : Walter de Gruyter GmbH & Co KG |
| Total Pages | : 334 |
| Release | : 2019-11-05 |
| Genre | : Technology & Engineering |
| ISBN | : 3110591723 |
The book presents selected, extended and peer reviewed papers from the International Multiconference on System, Automation and Control held Leipzig in 2018. These are complemented with solicited contributions by international experts. Main topics are automatic control, robotics, synthesis of automation systems. Application examples range from man-machine interaction, mechatronics, on to biological and economical models.
| Author | : Elimhan Mahmudov |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 386 |
| Release | : 2013-03-19 |
| Genre | : Mathematics |
| ISBN | : 9491216864 |
The book “Single variable Differential and Integral Calculus” is an interesting text book for students of mathematics and physics programs, and a reference book for graduate students in any engineering field. This book is unique in the field of mathematical analysis in content and in style. It aims to define, compare and discuss topics in single variable differential and integral calculus, as well as giving application examples in important business fields. Some elementary concepts such as the power of a set, cardinality, measure theory, measurable functions are introduced. It also covers real and complex numbers, vector spaces, topological properties of sets, series and sequences of functions (including complex-valued functions and functions of a complex variable), polynomials and interpolation and extrema of functions. Although analysis is based on the single variable models and applications, theorems and examples are all set to be converted to multi variable extensions. For example, Newton, Riemann, Stieltjes and Lebesque integrals are studied together and compared.
| Author | : Wojciech Rafajłowicz |
| Publisher | : Springer Nature |
| Total Pages | : 132 |
| Release | : 2021-10-25 |
| Genre | : Technology & Engineering |
| ISBN | : 3030883965 |
This book provides tools and algorithms for solving a wide class of optimization tasks by learning from their repetitions. A unified framework is provided for learning algorithms that are based on the stochastic gradient (a golden standard in learning), including random simultaneous perturbations and the response surface the methodology. Original algorithms include model-free learning of short decision sequences as well as long sequences—relying on model-supported gradient estimation. Learning is based on whole sequences of a process observation that are either vectors or images. This methodology is applicable to repetitive processes, covering a wide range from (additive) manufacturing to decision making for COVID-19 waves mitigation. A distinctive feature of the algorithms is learning between repetitions—this idea extends the paradigms of iterative learning and run-to-run control. The main ideas can be extended to other decision learning tasks, not included in this book. The text is written in a comprehensible way with the emphasis on a user-friendly presentation of the algorithms, their explanations, and recommendations on how to select them. The book is expected to be of interest to researchers, Ph.D., and graduate students in computer science and engineering, operations research, decision making, and those working on the iterative learning control.
