Advanced Mathematical Tools For Automatic Control Engineers

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

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

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

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

Issues such as logistics, the coordination of different teams, and automatic control of machinery become more difficult when dealing with large, complex projects. Yet all these activities have common elements and can be represented by mathematics. Linking theory to practice, Industrial Control Systems: Mathematical and Statistical Models and Techniques presents the mathematical foundation for building and implementing industrial control systems. The book contains mathematically rigorous models and techniques generally applicable to control systems with specific orientation toward industrial systems. An amalgamation of theoretical developments, applied formulations, implementation processes, and statistical control, the book covers: Industrial innovations and systems analysis Systems fundamentals Technical systems Production systems Systems filtering theory Systems control Linear and nonlinear systems Switching in systems Systems communication Transfer systems Statistical experimental design models (factorial design and fractional factorial design) Response surface models (central composite design and Box–Behnken design) Examining system fundamentals and advanced topics, the book includes examples that demonstrate how to use the statistical designs to develop feedback controllers and minimum variance controller designs for industrial applications. Clearly detailing concepts and step-by-step procedures, it matches mathematics with practical applications, giving you the tools to achieve system control goals.

In recent years, automatic control systems have been rapidly increasing in importance in all fields of engineering. The applications of control systems cover a very wide range, from the design of precision control devices such as delicate electronic equipment to the design of massive equipment such as that used for the manufacture of steel or other industrial processes. Microprocessors have added a new dimension to the capability of control systems. New applications for automatic controls are continually being discovered. This book offers coverage of control engineering beginning with discussions of how typical control systems may be represented by block diagrams. This is accomplished by first demonstrating how to represent each component or part of a system as a simple block diagram, then explaining how these individual diagrams may be connected to form the overall block diagram, just as the actual components are connected to form the complete control system. Because actual control systems frequently contain nonlinear components, considerable emphasis is given to such components. The book goes on to show that important information concerning the basic or inherent operating characteristics of a system may be obtained from knowledge of the steady-state behavior. Continuing on in the book's coverage, readers will find information involving: how the linear differential equations that describe the operation of control systems may be solved algebraically by the use of Laplace transforms; general characteristics of transient behavior; the application of the root-locus method to the design of control systems; the use of the analog computer to simulate control systems; state-space methods;digital control systems; frequency-response methods; and system compensation.

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.