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This volume—dedicated to Michael K. Sain on the occasion of his seventieth birthday—is a collection of chapters covering recent advances in stochastic optimal control theory and algebraic systems theory. Written by experts in their respective fields, the chapters are thematically organized into four parts: * Part I focuses on statistical control theory, where the cost function is viewed as a random variable and performance is shaped through cost cumulants. In this respect, statistical control generalizes linear-quadratic-Gaussian and H-infinity control. * Part II addresses algebraic systems theory, reviewing the use of algebraic systems over semirings, modules of zeros for linear multivariable systems, and zeros in linear time-delay systems. * Part III discusses advances in dynamical systems characteristics. The chapters focus on the stability of a discontinuous dynamical system, approximate decentralized fixed modes, direct optimal adaptive control, and stability of nonlinear systems with limited information. * Part IV covers engineering education and includes a unique chapter on theology and engineering, one of Sain's latest research interests. The book will be a useful reference for researchers and graduate students in systems and control, algebraic systems theory, and applied mathematics. Requiring only knowledge of undergraduate-level control and systems theory, the work may be used as a supplementary textbook in a graduate course on optimal control or algebraic systems theory.

Mathematics. --- Systems Theory, Control. --- Control, Robotics, Mechatronics. --- Calculus of Variations and Optimal Control; Optimization. --- Applications of Mathematics. --- Game Theory, Economics, Social and Behav. Sciences. --- Dynamical Systems and Ergodic Theory. --- Differentiable dynamical systems. --- Systems theory. --- Mathematical optimization. --- Mathématiques --- Dynamique différentiable --- Optimisation mathématique --- Nonlinear control theory. --- Stochastic control theory. --- System analysis. --- Stochastic control theory --- Nonlinear control theory --- System analysis --- Differentiable dynamical systems --- Civil & Environmental Engineering --- Operations Research --- Engineering & Applied Sciences --- Differential dynamical systems --- Dynamical systems, Differentiable --- Dynamics, Differentiable --- Network theory --- Systems analysis --- Algebra. --- Applied mathematics. --- Engineering mathematics. --- System theory. --- Calculus of variations. --- Probabilities. --- Control engineering. --- Robotics. --- Mechatronics. --- Probability Theory and Stochastic Processes. --- Differential equations --- Global analysis (Mathematics) --- Topological dynamics --- Network analysis --- Network science --- System theory --- Mathematical optimization --- Control theory --- Nonlinear theories --- Stochastic processes --- Distribution (Probability theory. --- Systems, Theory of --- Systems science --- Science --- Math --- Distribution functions --- Frequency distribution --- Characteristic functions --- Probabilities --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- Mathematics --- Philosophy --- Mechanical engineering --- Microelectronics --- Microelectromechanical systems --- Automation --- Machine theory --- Engineering --- Engineering analysis --- Control engineering --- Control equipment --- Engineering instruments --- Programmable controllers --- Probability --- Statistical inference --- Combinations --- Chance --- Least squares --- Mathematical statistics --- Risk --- Isoperimetrical problems --- Variations, Calculus of

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Mathematical Control Theory: An Introduction presents, in a mathematically precise manner, a unified introduction to deterministic control theory. With the exception of a few more advanced concepts required for the final part of the book, the presentation requires only a knowledge of basic facts from linear algebra, differential equations, and calculus. In addition to classical concepts and ideas, the author covers the stabilization of nonlinear systems using topological methods, realization theory for nonlinear systems, impulsive control and positive systems, the control of rigid bodies, the stabilization of infinite dimensional systems, and the solution of minimum energy problems. The book will be ideal for a beginning graduate course in mathematical control theory, or for self study by professionals needing a complete picture of the mathematical theory that underlies the applications of control theory. "This book is designed as a graduate text on the mathematical theory of deterministic control. It covers a remarkable number of topics...The exposition is excellent, and the book is a joy to read. A novel one-semester course covering both linear and nonlinear systems could be given...The book is an excellent one for introducing a mathematician to control theory." — Bulletin of the AMS "The book is very well written from a mathematical point of view of control theory. The author deserves much credit for bringing out such a book which is a useful and welcome addition to books on the mathematics of control theory." — Control Theory and Advance Technology "At last! We did need an introductory textbook on control which can be read, understood, and enjoyed by anyone." — Gian-Carlo Rota, The Bulletin of Mathematics Books.

Mathematics. --- Systems Theory, Control. --- Applications of Mathematics. --- Calculus of Variations and Optimal Control; Optimization. --- Control, Robotics, Mechatronics. --- Systems theory. --- Mathematical optimization. --- Mathématiques --- Optimisation mathématique --- Control theory --- Control theory. --- Operations Research --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Applied mathematics. --- Engineering mathematics. --- System theory. --- Calculus of variations. --- Control engineering. --- Robotics. --- Mechatronics. --- Dynamics --- Machine theory --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Math --- Science --- Systems, Theory of --- Systems science --- Philosophy --- Control engineering --- Control equipment --- Engineering instruments --- Automation --- Programmable controllers --- Isoperimetrical problems --- Variations, Calculus of --- Engineering --- Engineering analysis --- Mechanical engineering --- Microelectronics --- Microelectromechanical systems --- Mathematics

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The theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers  in both applied probability and finance, and provides exercises (without solutions).  

Quantitative methods (economics) --- Operational research. Game theory --- Mathematics --- Financial analysis --- toegepaste wiskunde --- stochastische analyse --- financiële analyse --- kansrekening --- Markov processes --- Programming (Mathematics) --- Stochastic control theory --- Finance --- Markov, Processus de --- Programmation (Mathématiques) --- Commande stochastique --- Finances --- Mathematical models --- Modèles mathématiques --- EPUB-LIV-FT LIVMATHE LIVSTATI SPRINGER-B

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From power plants to sugar refining, model predictive control (MPC) schemes have established themselves as the preferred control strategies for a wide variety of processes. The second edition of Model Predictive Control provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners. Model Predictive Control demonstrates that a powerful technique does not always require complex control algorithms. The text features material on the following subjects: general MPC elements and algorithms; commercial MPC schemes; generalized predictive control multivariable, robust, constrained nonlinear and hybrid MPC; fast methods for MPC implementation; applications. All of the material is thoroughly updated for the second edition with the chapters on nonlinear MPC, MPC and hybrid systems and MPC implementation being entirely new. Many new exercises and examples have also have also been added throughout and MATLAB® programs to aid in their solution can be downloaded from extras.springer.com. The text is an excellent aid for graduate and advanced undergraduate students and will also be of use to researchers and industrial practitioners wishing to keep abreast of a fast-moving field.

Predictive control. --- Modelvorming --- Optimalisering --- Procesregeling --- Stochastische processen --- Modelvorming. --- Optimalisering. --- Procesregeling. --- Stochastische processen. --- Systems Theory, Control. --- Systems theory. --- Predictive control --- Model based predictive control --- Model predictive control --- Engineering. --- Chemical engineering. --- System theory. --- Control engineering. --- Electronics. --- Microelectronics. --- Control. --- Industrial Chemistry/Chemical Engineering. --- Electronics and Microelectronics, Instrumentation. --- Microminiature electronic equipment --- Microminiaturization (Electronics) --- Electronics --- Microtechnology --- Semiconductors --- Miniature electronic equipment --- Electrical engineering --- Physical sciences --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Automation --- Programmable controllers --- Systems, Theory of --- Systems science --- Science --- Chemistry, Industrial --- Engineering, Chemical --- Industrial chemistry --- Engineering --- Chemistry, Technical --- Metallurgy --- Construction --- Industrial arts --- Technology --- Philosophy --- Control and Systems Theory. --- Control theory. --- Chemistry, Technical. --- Systems Theory, Control . --- Industrial Chemistry. --- Dynamics --- Machine theory --- Chemical technology --- Technical chemistry --- Chemistry --- Chemical engineering

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Theory of Applied Robotics: Kinematics, Dynamics, and Control is appropriate for courses in robotics that emphasize kinematics, dynamics, and control. The contents of this book are presented at a theoretical-practical level. It explains robotics concepts in detail, concentrating on their practical use. Related theorems and formal proofs are provided, as are real-life applications. Students, researchers, and practicing engineers alike will appreciate this user-friendly presentation of a wealth of robotics topics, most notably orientation, velocity, and forward kinematics. Theory of Applied Robotics: Kinematics, Dynamics, and Control includes: Richly illustrated chapters and over 200 diagrams to help readers visualize concepts. More than 300 detailed examples with fully-worked solutions which expose readers to a balanced and broad understanding of robotics in today’s world. A wealth of detailed problem sets and challenge problems for each chapter for the more advanced reader. A rich solutions manual which is available for instructors. Reza N. Jazar is an associate professor in the Mechanical Engineering Department at Manhattan College. His main research areas is nonlinear dynamic systems, including robotics, vehicles, and MEMS. He's written extensively on many diverse topics in applied mathematics and mechanical engineering subjects. He regularly teaches undergraduate and graduate-level courses on mechanical engineering.--

Engineering. --- Vibration, Dynamical Systems, Control. --- Control , Robotics, Mechatronics. --- Mechanical Engineering. --- Vibration. --- Mechanical engineering. --- Control engineering systems. --- Ingénierie --- Vibration --- Génie mécanique --- Robotics --- Mechanical Engineering --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Mechanical Engineering - General --- Civil Engineering --- Robotics. --- Dynamical systems. --- Dynamics. --- Control engineering. --- Mechatronics. --- Automation. --- Robotics and Automation. --- Control, Robotics, Mechatronics. --- Automation --- Machine theory --- Engineering, Mechanical --- Engineering --- Machinery --- Steam engineering --- Cycles --- Mechanics --- Sound --- Mechanical engineering --- Microelectronics --- Microelectromechanical systems --- Control engineering --- Control equipment --- Control theory --- Engineering instruments --- Programmable controllers --- Dynamical systems --- Kinetics --- Mathematics --- Mechanics, Analytic --- Force and energy --- Physics --- Statics --- Automatic factories --- Automatic production --- Computer control --- Engineering cybernetics --- Factories --- Industrial engineering --- Mechanization --- Assembly-line methods --- Automatic control --- Automatic machinery --- CAD/CAM systems