Dynamic Modeling, Predictive Control and Performance Monitoring A Data-driven Subspace Approach /

A typical design procedure for model predictive control or control performance monitoring consists of: 1. identification of a parametric or nonparametric model; 2. derivation of the output predictor from the model; 3. design of the control law or calculation of performance indices according to the p...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Huang, Biao (Συγγραφέας), Kadali, Ramesh (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: London : Springer London, 2008.
Σειρά:Lecture Notes in Control and Information Sciences, 374
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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100 1 |a Huang, Biao.  |e author. 
245 1 0 |a Dynamic Modeling, Predictive Control and Performance Monitoring  |h [electronic resource] :  |b A Data-driven Subspace Approach /  |c by Biao Huang, Ramesh Kadali. 
264 1 |a London :  |b Springer London,  |c 2008. 
300 |a XXIV, 242 p. 63 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
490 1 |a Lecture Notes in Control and Information Sciences,  |x 0170-8643 ;  |v 374 
505 0 |a I Dynamic Modeling through Subspace Identification -- System Identification: Conventional Approach -- Open-loop Subspace Identification -- Closed-loop Subspace Identification -- Identification of Dynamic Matrix and Noise Model Using Closed-loop Data -- II Predictive Control -- Model Predictive Control: Conventional Approach -- Data-driven Subspace Approach to Predictive Control -- III Control Performance Monitoring -- Control Loop Performance Assessment: Conventional Approach -- State-of-the-art MPC Performance Monitoring -- Subspace Approach to MIMO Feedback Control Performance Assessment -- Prediction Error Approach to Feedback Control Performance Assessment -- Performance Assessment with LQG-benchmark from Closed-loop Data. 
520 |a A typical design procedure for model predictive control or control performance monitoring consists of: 1. identification of a parametric or nonparametric model; 2. derivation of the output predictor from the model; 3. design of the control law or calculation of performance indices according to the predictor. Both design problems need an explicit model form and both require this three-step design procedure. Can this design procedure be simplified? Can an explicit model be avoided? With these questions in mind, the authors eliminate the first and second step of the above design procedure, a “data-driven” approach in the sense that no traditional parametric models are used; hence, the intermediate subspace matrices, which are obtained from the process data and otherwise identified as a first step in the subspace identification methods, are used directly for the designs. Without using an explicit model, the design procedure is simplified and the modelling error caused by parameterization is eliminated. 
650 0 |a Engineering. 
650 0 |a Chemical engineering. 
650 0 |a System theory. 
650 0 |a Complexity, Computational. 
650 0 |a Vibration. 
650 0 |a Dynamical systems. 
650 0 |a Dynamics. 
650 0 |a Control engineering. 
650 0 |a Robotics. 
650 0 |a Mechatronics. 
650 1 4 |a Engineering. 
650 2 4 |a Control. 
650 2 4 |a Systems Theory, Control. 
650 2 4 |a Industrial Chemistry/Chemical Engineering. 
650 2 4 |a Vibration, Dynamical Systems, Control. 
650 2 4 |a Control, Robotics, Mechatronics. 
650 2 4 |a Complexity. 
700 1 |a Kadali, Ramesh.  |e author. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9781848002326 
830 0 |a Lecture Notes in Control and Information Sciences,  |x 0170-8643 ;  |v 374 
856 4 0 |u http://dx.doi.org/10.1007/978-1-84800-233-3  |z Full Text via HEAL-Link 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647)