omar hammami (19 Ergebnisse)

Zustand: as new. Wie neu/Like new.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 384 | Sprache: Englisch | Produktart: Bücher | This book contains all refereed papers that were accepted to the second edition of the « Complex Systems Design & Management » (CSDM 2011) international conference that took place in Paris (France) from December 7 to December 9, 2011. (Website: [LINK ENTFERNT]).These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (transport, defense & security, electronics, energy & environment, e-services), scientific & technical topics (systems fundamentals, systems architecture& engineering, systems metrics & quality, systemic  tools) and system types (transportation systems, embedded systems, software & information systems, systems of systems, artificial ecosystems).The CSDM 2011 conference is organized under the guidance of the CESAMES non-profit organization ([LINK ENTFERNT]).

Zustand: new.

Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 456 | Sprache: Englisch | Produktart: Bücher | This book presents the separation principle which is also known as the principle of separation of estimation and control and states that, under certain assumptions, the problem of designing an optimal feedback controller for a stochastic system can be solved by designing an optimal observer for the system's state, which feeds into an optimal deterministic controller for the system. Thus, the problem may be divided into two halves, which simplifies its design. In the context of deterministic linear systems, the first instance of this principle is that if a stable observer and stable state feedback are built for a linear time-invariant system (LTI system hereafter), then the combined observer and feedback are stable. The separation principle does not true for nonlinear systems in general. Another instance of the separation principle occurs in the context of linear stochastic systems, namely that an optimum state feedback controller intended to minimize a quadratic cost is optimal forthe stochastic control problem with output measurements. The ideal solution consists of a Kalman filter and a linear-quadratic regulator when both process and observation noise are Gaussian. The term for this is linear-quadratic-Gaussian control. More generally, given acceptable conditions and when the noise is a martingale (with potential leaps), a separation principle, also known as the separation principle in stochastic control, applies when the noise is a martingale (with possible jumps).

Taschenbuch. Zustand: Neu. State Estimation and Stabilization of Nonlinear Systems | Theory and Applications | Abdellatif Ben Makhlouf (u. a.) | Taschenbuch | Studies in Systems, Decision and Control | vii | Englisch | 2024 | Springer | EAN 9783031379727 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: New.

Gebunden. Zustand: New.

Zustand: New. In.

Zustand: New. In.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the separation principle which is also known as the principle of separation of estimation and control and states that, under certain assumptions, the problem of designing an optimal feedback controller for a stochastic system can be solved by designing an optimal observer for the system's state, which feeds into an optimal deterministic controller for the system. Thus, the problem may be divided into two halves, which simplifies its design. In the context of deterministic linear systems, the first instance of this principle is that if a stable observer and stable state feedback are built for a linear time-invariant system (LTI system hereafter), then the combined observer and feedback are stable. The separation principle does not true for nonlinear systems in general. Another instance of the separation principle occurs in the context of linear stochastic systems, namely that an optimum state feedback controller intended to minimize a quadratic cost is optimal forthe stochastic control problem with output measurements. The ideal solution consists of a Kalman filter and a linear-quadratic regulator when both process and observation noise are Gaussian. The term for this is linear-quadratic-Gaussian control. More generally, given acceptable conditions and when the noise is a martingale (with potential leaps), a separation principle, also known as the separation principle in stochastic control, applies when the noise is a martingale (with possible jumps).

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents the separation principle which is also known as the principle of separation of estimation and control and states that, under certain assumptions, the problem of designing an optimal feedback controller for a stochastic system can be solved by designing an optimal observer for the system's state, which feeds into an optimal deterministic controller for the system. Thus, the problem may be divided into two halves, which simplifies its design. In the context of deterministic linear systems, the first instance of this principle is that if a stable observer and stable state feedback are built for a linear time-invariant system (LTI system hereafter), then the combined observer and feedback are stable. The separation principle does not true for nonlinear systems in general. Another instance of the separation principle occurs in the context of linear stochastic systems, namely that an optimum state feedback controller intended to minimize a quadratic cost is optimal forthe stochastic control problem with output measurements. The ideal solution consists of a Kalman filter and a linear-quadratic regulator when both process and observation noise are Gaussian. The term for this is linear-quadratic-Gaussian control. More generally, given acceptable conditions and when the noise is a martingale (with potential leaps), a separation principle, also known as the separation principle in stochastic control, applies when the noise is a martingale (with possible jumps).

Taschenbuch. Zustand: Neu. Complex Systems Design & Management | Proceedings of the Second International Conference on Complex Systems Design & Management CSDM 2011 | Omar Hammami (u. a.) | Taschenbuch | xxiv | Englisch | 2014 | Springer | EAN 9783642429163 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Hardcover. Zustand: Brand New. 452 pages. 9.25x6.10x1.06 inches. In Stock.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This proceedings volume convenes works within the field of fractional calculus and its applications, presented at the International Conference on Fractional Differentiation and its Applications (ICFCA), held in Sousse, Tunisia, from December 26th to 30th, 2024.In its first rendition, the ICFCA gathers papers from several countries such as Algeria, Lebanon, Qatar, Tunisia, Türkiye, and United Arab Emirates, among others. It aims to provide a unique platform for researchers engaged in fractional calculus in a mathematical context. Covered topics range from foundational aspects, such as fractional differential equations, stability analysis, boundary value problems, and inverse problems, to more applied aspects such as fractional control systems, and the use of fractional calculus tools and techniques in physics, engineering, biology, and more.This volume fills a gap in the fractional calculus landscape by covering theoretical developments and applications in various fields while showcasing the recent findings of a new generation of researchers.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering.

Paperback. Zustand: Brand New. 2012 edition. 360 pages. 9.25x6.10x0.91 inches. In Stock.

Hardcover. Zustand: Brand New. 270 pages. 9.25x6.10x9.21 inches. In Stock.

Hardcover. Zustand: Brand New. 2012 edition. 384 pages. 9.25x6.00x1.25 inches. In Stock.