Alexander S. Poznyak's Books

Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

Stochastic Systems

By: Alexander S. Poznyak

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Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

Stochastic Systems

By: Alexander S. Poznyak

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

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Page Count

568

Publisher

Elsevier

Published Date

ISBN 10

0080914039

ISBN 13

9780080914039

Advanced Mathematical Tools for Control Engineers: Volume 1

Deterministic Systems

By: Alexander S. Poznyak

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Advanced Mathematical Tools for Control Engineers: Volume 1

Deterministic Systems

By: Alexander S. Poznyak

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

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803

Publisher

Elsevier

Published Date

ISBN 10

0080556108

ISBN 13

9780080556109

The Robust Maximum Principle

Theory and Applications

By: Vladimir G. Boltyanski,Alexander S. Poznyak

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The Robust Maximum Principle

Theory and Applications

By: Vladimir G. Boltyanski,Alexander S. Poznyak

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.

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Page Count

440

Publisher

Springer Science & Business Media

Published Date

ISBN 10

0817681523

ISBN 13

9780817681524

Classical and Analytical Mechanics

Theory, Applied Examples, and Practice

By: Alexander S. Poznyak

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Classical and Analytical Mechanics

Theory, Applied Examples, and Practice

By: Alexander S. Poznyak

Classical and Analytical Mechanics: Theory, Applied Examples, and Practice provides a bridge between the theory and practice related to mechanical, electrical, and electromechanical systems. It includes rigorous mathematical and physical explanations while maintaining an interdisciplinary engineering focus. Applied problems and exercises in mechanical, mechatronic, aerospace, electrical, and control engineering are included throughout and the book provides detailed techniques for designing models of different robotic, electrical, defense, and aerospace systems. The book starts with multiple chapters covering kinematics before moving onto coverage of dynamics and non-inertial and variable mass systems. Euler's dynamic equations and dynamic Lagrange equations are covered next with subsequent chapters discussing topics such as equilibrium and stability, oscillation analysis, linear systems, Hamiltonian formalism, and the Hamilton-Jacobi equation. The book concludes with a chapter outlining various electromechanical models that readers can implement and adapt themselves. - Bridges theory and practice by providing readers techniques for solving common problems through mechanical, electrical, and electromechanical models alongside the underlying theoretical foundations - Describes variable mass, non-inertial systems, dynamic Euler's equations, gyroscopes, and other related topics - Includes a broad offering of practical examples, problems, and exercises across an array of engineering disciplines

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Page Count

526

Publisher

Elsevier

Published Date

ISBN 10

0323898890

ISBN 13

9780323898898

Ozonation and Biodegradation in Environmental Engineering

Dynamic Neural Network Approach

By: Tatyana Poznyak,Jorge Isaac Chairez Oria,Alexander S. Poznyak

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Ozonation and Biodegradation in Environmental Engineering

Dynamic Neural Network Approach

By: Tatyana Poznyak,Jorge Isaac Chairez Oria,Alexander S. Poznyak

Ozonation and Biodegradation in Environmental Engineering: Dynamic Neural Network Approach gives a unified point-of-view on the application of DNN to estimate and control the application of ozonation and biodegradation in chemical and environmental engineering. This book deals with modelling and control design of chemical processes oriented to environmental and chemical engineering problems. Elimination in liquid, solid and gaseous phases are all covered, along with processes of laboratory scale that are evaluated with software sensors and controllers based on DNN technique, including the removal of contaminants in residual water, remediation of contaminated soil, purification of contaminated air, and more. The book also explores combined treatments using both ozonation and biodegradation to test the sensor and controller. - Defines a novel researching trend in environmental engineering processes that deals with incomplete mathematical model description and other non-measurable parameters and variables - Offers both significant new theoretical challenges and an examination of real-world problem-solving - Helps students and practitioners learn and inexpensively implement DNN using commercially available, PC-based software tools

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548

Publisher

Elsevier

Published Date

ISBN 10

0128128488

ISBN 13

9780128128480

Differential Neural Networks for Robust Nonlinear Control

Identification, State Estimation and Trajectory Tracking

By: Alexander S. Poznyak,Edgar N. Sanchez,Wen Yu (profesor titular.)

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Differential Neural Networks for Robust Nonlinear Control

Identification, State Estimation and Trajectory Tracking

By: Alexander S. Poznyak,Edgar N. Sanchez,Wen Yu (profesor titular.)

This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical, etc.). Contents: Theoretical Study: Neural Networks Structures; Nonlinear System Identification: Differential Learning; Sliding Mode Identification: Algebraic Learning; Neural State Estimation; Passivation via Neuro Control; Neuro Trajectory Tracking; Neurocontrol Applications: Neural Control for Chaos; Neuro Control for Robot Manipulators; Identification of Chemical Processes; Neuro Control for Distillation Column; General Conclusions and Future Work; Appendices: Some Useful Mathematical Facts; Elements of Qualitative Theory of ODE; Locally Optimal Control and Optimization. Readership: Graduate students, researchers, academics/lecturers and industrialists in neural networks.

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Page Count

464

Publisher

World Scientific

Published Date

ISBN 10

981281129X

ISBN 13

9789812811295

Optimization and Games for Controllable Markov Chains

Numerical Methods with Application to Finance and Engineering

By: Julio B. Clempner,Alexander Poznyak

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Optimization and Games for Controllable Markov Chains

Numerical Methods with Application to Finance and Engineering

By: Julio B. Clempner,Alexander Poznyak

This book considers a class of ergodic finite controllable Markov's chains. The main idea behind the method, described in this book, is to develop the original discrete optimization problems (or game models) in the space of randomized formulations, where the variables stand in for the distributions (mixed strategies or preferences) of the original discrete (pure) strategies in the use. The following suppositions are made: a finite state space, a limited action space, continuity of the probabilities and rewards associated with the actions, and a necessity for accessibility. These hypotheses lead to the existence of an optimal policy. The best course of action is always stationary. It is either simple (i.e., nonrandomized stationary) or composed of two nonrandomized policies, which is equivalent to randomly selecting one of two simple policies throughout each epoch by tossing a biased coin. As a bonus, the optimization procedure just has to repeatedly solve the time-average dynamic programming equation, making it theoretically feasible to choose the optimum course of action under the global restriction. In the ergodic cases the state distributions, generated by the corresponding transition equations, exponentially quickly converge to their stationary (final) values. This makes it possible to employ all widely used optimization methods (such as Gradient-like procedures, Extra-proximal method, Lagrange's multipliers, Tikhonov's regularization), including the related numerical techniques. In the book we tackle different problems and theoretical Markov models like controllable and ergodic Markov chains, multi-objective Pareto front solutions, partially observable Markov chains, continuous-time Markov chains, Nash equilibrium and Stackelberg equilibrium, Lyapunov-like function in Markov chains, Best-reply strategy, Bayesian incentive-compatible mechanisms, Bayesian Partially Observable Markov Games, bargaining solutions for Nash and Kalai-Smorodinsky formulations, multi-traffic signal-control synchronization problem, Rubinstein's non-cooperative bargaining solutions, the transfer pricing problem as bargaining.

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Page Count

340

Publisher

Springer Nature

Published Date

ISBN 10

3031435753

ISBN 13

9783031435751

Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

Stochastic Systems

By: Alex Poznyak

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Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

Stochastic Systems

By: Alex Poznyak

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

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Solve jigsaw puzzle

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Page Count

567

Publisher

Elsevier Science

Published Date

ISBN 10

0080446736

ISBN 13

9780080446738

Book's by Alexander S. Poznyak

Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

Advanced Mathematical Tools for Control Engineers: Volume 1

Advanced Mathematical Tools for Control Engineers: Volume 1

The Robust Maximum Principle

The Robust Maximum Principle

Classical and Analytical Mechanics

Classical and Analytical Mechanics

Ozonation and Biodegradation in Environmental Engineering

Ozonation and Biodegradation in Environmental Engineering

Differential Neural Networks for Robust Nonlinear Control

Differential Neural Networks for Robust Nonlinear Control

Optimization and Games for Controllable Markov Chains

Optimization and Games for Controllable Markov Chains

Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

Advanced Mathematical Tools for Automatic Control Engineers: Volume 2

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