Linear Dynamic Systems and Signals


Book Description

The author's twelve years of experience with linear systems and signals are reflected in this comprehensive book. The book contains detailed linear systems theory essentials. The intent of this book is to develop the unified techniques to recognize and solve linear dynamical system problems regardless of their origin. Includes Space state techniques as the time domain approach for studying linear systems. Provides a solid foundation on linear dynamic systems and corresponding systems using the dynamic system point of view. Parallels continuous- and discrete-time linear systems throughout to help users grasp the similarities and differences of each. Three part organization: Part I covers frequency-domain approach to linear dynamic systems, Part II covers the time-domain approach to linear dynamic systems, and Part III discusses the linear system approach to electrical engineering, to allow the user to focus of the subject matter as it pertains to their needs. For anyone interested in linear systems and signals




Recent Advances in Control and Filtering of Dynamic Systems with Constrained Signals


Book Description

This book introduces the principle theories and applications of control and filtering problems to address emerging hot topics in feedback systems. With the development of IT technology at the core of the 4th industrial revolution, dynamic systems are becoming more sophisticated, networked, and advanced to achieve even better performance. However, this evolutionary advance in dynamic systems also leads to unavoidable constraints. In particular, such elements in control systems involve uncertainties, communication/transmission delays, external noise, sensor faults and failures, data packet dropouts, sampling and quantization errors, and switching phenomena, which have serious effects on the system’s stability and performance. This book discusses how to deal with such constraints to guarantee the system’s design objectives, focusing on real-world dynamical systems such as Markovian jump systems, networked control systems, neural networks, and complex networks, which have recently excited considerable attention. It also provides a number of practical examples to show the applicability of the presented methods and techniques. This book is of interest to graduate students, researchers and professors, as well as R&D engineers involved in control theory and applications looking to analyze dynamical systems with constraints and to synthesize various types of corresponding controllers and filters for optimal performance of feedback systems.




Linear Systems and Signals


Book Description

Incorporating new problems and examples, the second edition of Linear Systems and Signals features MATLAB® material in each chapter and at the back of the book. It gives clear descriptions of linear systems and uses mathematics not only to prove axiomatic theory, but also to enhance physical and intuitive understanding.




Identification of Dynamic Systems


Book Description

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.




Fundamentals of Signals and Control Systems


Book Description

The aim of this book is the study of signals and deterministic systems, linear, time-invariant, finite dimensions and causal. A set of useful tools is selected for the automatic and signal processing and methods of representation of dynamic linear systems are exposed, and analysis of their behavior. Finally we discuss the estimation, identification and synthesis of control laws for the purpose of stabilization and regulation. The study of signal characteristics and properties systems and knowledge of mathematical tools and treatment methods and analysis, are lately more and more importance and continue to evolve. The reason is that the current state of technology, particularly electronics and computing, enables the production of very advanced processing systems, effective and less expensive despite the complexity.




Identification of Dynamic Systems


Book Description

Precise dynamic models of processes are required for many applications, ranging from control engineering to the natural sciences and economics. Frequently, such precise models cannot be derived using theoretical considerations alone. Therefore, they must be determined experimentally. This book treats the determination of dynamic models based on measurements taken at the process, which is known as system identification or process identification. Both offline and online methods are presented, i.e. methods that post-process the measured data as well as methods that provide models during the measurement. The book is theory-oriented and application-oriented and most methods covered have been used successfully in practical applications for many different processes. Illustrative examples in this book with real measured data range from hydraulic and electric actuators up to combustion engines. Real experimental data is also provided on the Springer webpage, allowing readers to gather their first experience with the methods presented in this book. Among others, the book covers the following subjects: determination of the non-parametric frequency response, (fast) Fourier transform, correlation analysis, parameter estimation with a focus on the method of Least Squares and modifications, identification of time-variant processes, identification in closed-loop, identification of continuous time processes, and subspace methods. Some methods for nonlinear system identification are also considered, such as the Extended Kalman filter and neural networks. The different methods are compared by using a real three-mass oscillator process, a model of a drive train. For many identification methods, hints for the practical implementation and application are provided. The book is intended to meet the needs of students and practicing engineers working in research and development, design and manufacturing.




Circuits, Signals, and Systems


Book Description

These twenty lectures have been developed and refined by Professor Siebert during the more than two decades he has been teaching introductory Signals and Systems courses at MIT. The lectures are designed to pursue a variety of goals in parallel: to familiarize students with the properties of a fundamental set of analytical tools; to show how these tools can be applied to help understand many important concepts and devices in modern communication and control engineering practice; to explore some of the mathematical issues behind the powers and limitations of these tools; and to begin the development of the vocabulary and grammar, common images and metaphors, of a general language of signal and system theory. Although broadly organized as a series of lectures, many more topics and examples (as well as a large set of unusual problems and laboratory exercises) are included in the book than would be presented orally. Extensive use is made throughout of knowledge acquired in early courses in elementary electrical and electronic circuits and differential equations. Contents:Review of the "classical" formulation and solution of dynamic equations for simple electrical circuits; The unilateral Laplace transform and its applications; System functions; Poles and zeros; Interconnected systems and feedback; The dynamics of feedback systems; Discrete-time signals and linear difference equations; The unilateral Z-transform and its applications; The unit-sample response and discrete-time convolution; Convolutional representations of continuous-time systems; Impulses and the superposition integral; Frequency-domain methods for general LTI systems; Fourier series; Fourier transforms and Fourier's theorem; Sampling in time and frequency; Filters, real and ideal; Duration, rise-time and bandwidth relationships: The uncertainty principle; Bandpass operations and analog communication systems; Fourier transforms in discrete-time systems; Random Signals; Modern communication systems. William Siebert is Ford Professor of Engineering at MIT. Circuits, Signals, and Systemsis included in The MIT Press Series in Electrical Engineering and Computer Science, copublished with McGraw-Hill.




Identification of Linear Systems


Book Description

This book concentrates on the problem of accurate modeling of linear systems. It presents a thorough description of a method of modeling a linear dynamic invariant system by its transfer function. The first two chapters provide a general introduction and review for those readers who are unfamiliar with identification theory so that they have a sufficient background knowledge for understanding the methods described later. The main body of the book looks at the basic method used by the authors to estimate the parameter of the transfer function, how it is possible to optimize the excitation signals. Further chapters extend the estimation method proposed. Applications are then discussed and the book concludes with practical guidelines which illustrate the method and offer some rules-of-thumb.




Analysis of Linear Dynamic Systems


Book Description




Continuous Signals and Systems with MATLAB


Book Description

Designed for a one-semester undergraduate course in continuous linear systems, Continuous Signals and Systems with MATLAB®, Second Edition presents the tools required to design, analyze, and simulate dynamic systems. It thoroughly describes the process of the linearization of nonlinear systems, using MATLAB® to solve most examples and problems. With updates and revisions throughout, this edition focuses more on state-space methods, block diagrams, and complete analog filter design. New to the Second Edition • A chapter on block diagrams that covers various classical and state-space configurations • A completely revised chapter that uses MATLAB to illustrate how to design, simulate, and implement analog filters • Numerous new examples from a variety of engineering disciplines, with an emphasis on electrical and electromechanical engineering problems Explaining the subject matter through easy-to-follow mathematical development as well as abundant examples and problems, the text covers signals, types of systems, convolution, differential equations,Fourier series and transform, the Laplace transform, state-space representations, block diagrams, system linearization, and analog filter design. Requiring no prior fluency with MATLAB, it enables students to master both the concepts of continuous linear systems and the use of MATLAB to solve problems.