Isbn: 9783030838140 - nonlinear predictive control using wiener models: computationally efficient approaches for polynomial and neural structures: 389 (studies in systems, decision and control, 389) (11 resultados)

Condición: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.

Condición: New. In English.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents computationally efficient MPC solutions. The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model's structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances. An alternative is to use the computationally demanding MPC scheme with on-line nonlinear optimisation repeated at each sampling instant.A linear approximation of the Wiener model or the predicted trajectory is found on-line. As a result, quadratic optimisation tasks are obtained. Furthermore, parameterisation using Laguerre functions is possible to reduce the number of decision variables. Simulation results for ten benchmark processes show that the discussed MPC algorithms lead to excellent control quality. For a neutralisation reactor and a fuel cell, essential advantages ofneural Wiener models are demonstrated.…

Condición: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.

Hardcover. Condición: Brand New. 366 pages. 9.25x6.10x9.21 inches. In Stock.

Condición: new. Questo è un articolo print on demand.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents computationally efficient MPC solutions. The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model's structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances. An alternative is to use the computationally demanding MPC scheme with on-line nonlinear optimisation repeated at each sampling instant.A linear approximation of the Wiener model or the predicted trajectory is found on-line. As a result, quadratic optimisation tasks are obtained. Furthermore, parameterisation using Laguerre functions is possible to reduce the number of decision variables. Simulation results for ten benchmark processes show that the discussed MPC algorithms lead to excellent control quality. For a neutralisation reactor and a fuel cell, essential advantages of neural Wiener models are demonstrated. 368 pp. Englisch.…

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model s structure is limited, and it gives poor.…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Introduction to Model Predictive Control.- MPC Algorithms Using Input-Output Wiener Models.- MPC Algorithms Using State-Space Wiener Models.- Conclusions.- Index.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 368 pp. Englisch.…

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.