Linear Dynamic Systems And Signals

Linear Dynamic Systems and Signals

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

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.

Fundamentals of Stochastic Signals, Systems and Estimation Theory with Worked Examples