Observability And Controllability Of General Linear Systems
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Observability and Controllability of General Linear Systems
Observability and Controllability of General Linear Systems treats five different families of the linear systems, three of which are new. The book begins with the definition of time together with a brief description of its crucial properties. It presents further new results on matrices, on polynomial matrices, on matrix polynomials, on rational matrices, and on the new compact, simple and elegant calculus that enabled the generalization of the transfer function matrix concept and of the state concept, the proofs of the new necessary and sufficient observability and controllability conditions for all five classes of the studied systems. Features • Generalizes the state space concept and the complex domain fundamentals of the control systems unknown in previously published books by other authors. • Addresses the knowledge and ability necessary to overcome the crucial lacunae of the existing control theory and drawbacks of its applications. • Outlines new effective mathematical means for effective complete analysis and synthesis of the control systems. • Upgrades, completes and broadens the control theory related to the classical self-contained control concepts: observability and controllability. • Provides information necessary to create and teach advanced inherently upgraded control courses.
Trackability and Tracking of General Linear Systems
Trackability and Tracking of General Linear Systems deals with five classes of the systems, three of which are new, begins with the definition of time together with a brief description of its crucial properties and with the principles of the physical uniqueness and continuity of physical variables. They are essential for the natural tracking control synthesis. The book presents further new results on the new compact, simple and elegant calculus that enabled the generalization of the transfer function matrix concept and of the state concept, the completion of the trackability and tracking concepts together with the proofs of the trackability and tracking criteria, as well as the natural tracking control synthesis for all five classes of the systems. Features • Crucially broadens the state space concept and the complex domain fundamentals of the dynamical systems to the control systems. • Addresses the knowledge and ability necessary to study and design control systems that will satisfy the fundamental control goal. • Outlines new effective mathematical means for effective complete analysis and synthesis of the control systems. • Upgrades, completes and essentially generalizes the control theory beyond the existing boundaries. • Provides information necessary to create and teach advanced inherently upgraded control courses.
Mathematical Methods in Robust Control of Linear Stochastic Systems
Author: Vasile Dragan
language: en
Publisher: Springer Science & Business Media
Release Date: 2013-10-04
This second edition of Mathematical Methods in the Robust Control of Linear Stochastic Systems includes a large number of recent results in the control of linear stochastic systems. More specifically, the new results presented are: - A unified and abstract framework for Riccati type equations arising in the stochastic control - Stability and control problems for systems perturbed by homogeneous Markov processes with infinite number of states - Mixed H2 / H∞ control problem and numerical procedures - Linear differential equations with positive evolution on ordered Banach spaces with applications for stochastic systems including both multiplicative white noise and Markovian jumps represented by a Markov chain with countable infinite set of states - Kalman filtering for stochastic systems subject both to state dependent noise and Markovian jumps - H∞ reduced order filters for stochastic systems The book will appeal to graduate students, researchers in advanced control engineering, finance, mathematical systems theory, applied probability and stochastic processes, and numerical analysis. From Reviews of the First Edition: This book is concerned with robust control of stochastic systems. One of the main features is its coverage of jump Markovian systems. ... Overall, this book presents results taking into consideration both white noise and Markov chain perturbations. It is clearly written and should be useful for people working in applied mathematics and in control and systems theory. The references cited provide further reading sources. (George Yin, Mathematical Reviews, Issue 2007 m) This book considers linear time varying stochastic systems, subjected to white noise disturbances and system parameter Markovian jumping, in the context of optimal control ... robust stabilization, and disturbance attenuation. ... The material presented in the book is organized in seven chapters. ... The book is very well written and organized. ... is a valuable reference for all researchers and graduate students in applied mathematics and control engineering interested in linear stochastic time varying control systems with Markovian parameter jumping and white noise disturbances. (Zoran Gajic, SIAM Review, Vol. 49 (3), 2007)