Robust model predictive control (84 résultats)

Etat : New.

Paperback. Etat : New.

Etat : New.

Etat : New. In English.

Paperback. Etat : New.

Etat : New.

Hardcover. Etat : Very Good.

Hardcover. Etat : Fine. Still Sealed in Plastic. Never used.

Etat : New. pp. 168.

Etat : New.

Hardback. Etat : New. Most physical systems possess parametric uncertainties or unmeasurable parameters and, since parametric uncertainty may degrade the performance of model predictive control (MPC), mechanisms to update the unknown or uncertain parameters are desirable in application. One possibility is to apply adaptive extensions of MPC in which parameter estimation and control are performed online. This book proposes such an approach, with a design methodology for adaptive robust nonlinear MPC (NMPC) systems in the presence of disturbances and parametric uncertainties. One of the key concepts pursued is the concept of set-based adaptive parameter estimation, which provides a mechanism to estimate the unknown parameters as well as an estimate of the parameter uncertainty set. The knowledge of non-conservative uncertain set estimates is exploited in the design of robust adaptive NMPC algorithms that guarantee robustness of the NMPC system to parameter uncertainty. Topics covered include: a review of nonlinear MPC; extensions for performance improvement; introduction to adaptive robust MPC; computational aspects of robust adaptive MPC; finite-time parameter estimation in adaptive control; performance improvement in adaptive control; adaptive MPC for constrained nonlinear systems; adaptive MPC with disturbance attenuation; robust adaptive economic MPC; setbased estimation in discrete-time systems; and robust adaptive MPC for discrete-time systems.…

Etat : New. pp. 400.

Taschenbuch. Etat : Neu. Efficient robust model predictive control via convex optimization | Efficiently incorporating robustness using linear | Zhaoyang Wan (u. a.) | Taschenbuch | Englisch | 2017 | AV Akademikerverlag | EAN 9786202203906 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. …

Etat : As New. Unread book in perfect condition.

Etat : New.

Taschenbuch. Etat : Neu. The Robustness and Stability Analysis of Model Predictive Control | using robust control and absolute stability theories | Guang Li | Taschenbuch | 172 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838350295 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Etat : New. pp. 300.

Etat : New.

Etat : New. In English.

Taschenbuch. Etat : Neu. Decentralized Robust Nonlinear Model Predictive Control for UAS | Nonlinear and Robust Control Applied to Aircraft | Gonzalo Garcia | Taschenbuch | 168 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659554056 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

Paperback. Etat : New.

paperback. Etat : New. Paperback.Pub Date:2022-04-01 Pages:180 Language:Chinese Publisher:Science Press In the control of constraint systems. invariant set properties and control laws in set theory. constraint satisfaction and Lyapunov functions are closely related to mathematics relation. Set theory and model predictive control for constrained systems have become the focus of theoretical research. Robust Model Predictive Control for Constrained Uncertain Systems Based on Set Theory focuses on the performance. stab.…

Hardback. Etat : New. Most physical systems possess parametric uncertainties or unmeasurable parameters and, since parametric uncertainty may degrade the performance of model predictive control (MPC), mechanisms to update the unknown or uncertain parameters are desirable in application. One possibility is to apply adaptive extensions of MPC in which parameter estimation and control are performed online. This book proposes such an approach, with a design methodology for adaptive robust nonlinear MPC (NMPC) systems in the presence of disturbances and parametric uncertainties. One of the key concepts pursued is the concept of set-based adaptive parameter estimation, which provides a mechanism to estimate the unknown parameters as well as an estimate of the parameter uncertainty set. The knowledge of non-conservative uncertain set estimates is exploited in the design of robust adaptive NMPC algorithms that guarantee robustness of the NMPC system to parameter uncertainty. Topics covered include: a review of nonlinear MPC; extensions for performance improvement; introduction to adaptive robust MPC; computational aspects of robust adaptive MPC; finite-time parameter estimation in adaptive control; performance improvement in adaptive control; adaptive MPC for constrained nonlinear systems; adaptive MPC with disturbance attenuation; robust adaptive economic MPC; setbased estimation in discrete-time systems; and robust adaptive MPC for discrete-time systems.…

Etat : As New. Unread book in perfect condition.

Taschenbuch. Etat : Neu. Model Predictive Control | Classical, Robust and Stochastic | Basil Kouvaritakis (u. a.) | Taschenbuch | xiii | Englisch | 2019 | Springer | EAN 9783319796895 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplicative and stochastic model uncertainty. The book provides: extensive use of illustrative examples; sample problems; and discussion of novel control applications such as resource allocation for sustainable development and turbine-blade control for maximized power capture with simultaneously reduced risk of turbulence-induced damage. Graduate students pursuing courses in model predictive control or more generally in advanced or process control and senior undergraduates in need of a specialized treatment will find Model Predictive Control an invaluable guide to the state of the art in this important subject. For the instructor it provides an authoritative resource for the construction of courses.…

Hardcover. Etat : new. Hardcover. This book offers a comprehensive and practical guide to the design of advanced model predictive control (MPC) strategies for the three-dimensional motion control of autonomous underwater vehicles (AUVs). It addresses the full six-degrees-of-freedom dynamics of AUVs using convex optimization-based MPC techniques, making the resulting control problems computationally tractable.The book adopts a structured two-stage approach. The first stage provides a self-contained tutorial on advanced MPC design for uncertain systems, including strategies to ensure closed-loop stability. This equips students, academic researchers and engineers with the theoretical and practical foundations needed to understand and apply advanced MPC to complex systems. The second stage applies these methods to the real-world challenge of three-dimensional AUV motion control, offering novel control formulations that outperform conventional methods.Throughout the book, special attention is given to robustness, constraint handling and optimization structure. Through detailed case studies and extensive simulations, including downloadable MATLAB implementations in many cases, the book validates the proposed strategies against conventional methods using quantitative performance metrics to demonstrate improved control accuracy, robustness and efficiency. This makes Robust Model Predictive Control for Autonomous Underwater Vehicles a valuable resource not only for researchers and postgraduate students, but also for practicing engineers working on marine robotics and model-based control system design. mso-themecolor: text2;">This book offers a comprehensive and practical guide to the design of advanced model predictive control (MPC) strategies for the three-dimensional motion control of autonomous underwater vehicles (AUVs). Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Etat : Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This monograph addresses the stability, robustness and performance analysis of Model Predictive Control (MPC) using absolute stability theory and an advanced robust control theory, called Integral Quadratic Constraints (IQC). The main problems of many existing analysis approaches for MPC systems are from the difficulty of explicitly incorporating the model uncertainties into the MPC formulations and the shortage of the efficient and systematic methods capable of implementing the stability, robustness and performance tests. The objective of this monograph is to cast the MPC system into a standard framework such that the abundant results in the classical nonlinear control and robust control theory can be utilized. This is realized by exploring the properties inherent in the MPC controller and representing the MPC controller by an operator with these properties in analysis. Within this general framework, two approaches are proposed: one is based on the IQC theory, the other is based on the absolute stability analysis of Lur''e system.…

Hardback. Etat : New. Most physical systems possess parametric uncertainties or unmeasurable parameters and, since parametric uncertainty may degrade the performance of model predictive control (MPC), mechanisms to update the unknown or uncertain parameters are desirable in application. One possibility is to apply adaptive extensions of MPC in which parameter estimation and control are performed online. This book proposes such an approach, with a design methodology for adaptive robust nonlinear MPC (NMPC) systems in the presence of disturbances and parametric uncertainties. One of the key concepts pursued is the concept of set-based adaptive parameter estimation, which provides a mechanism to estimate the unknown parameters as well as an estimate of the parameter uncertainty set. The knowledge of non-conservative uncertain set estimates is exploited in the design of robust adaptive NMPC algorithms that guarantee robustness of the NMPC system to parameter uncertainty. Topics covered include: a review of nonlinear MPC; extensions for performance improvement; introduction to adaptive robust MPC; computational aspects of robust adaptive MPC; finite-time parameter estimation in adaptive control; performance improvement in adaptive control; adaptive MPC for constrained nonlinear systems; adaptive MPC with disturbance attenuation; robust adaptive economic MPC; setbased estimation in discrete-time systems; and robust adaptive MPC for discrete-time systems.…

Etat : As New. Unread book in perfect condition.