|
|
|
|
LEADER |
03785nam a22006015i 4500 |
001 |
978-1-84800-233-3 |
003 |
DE-He213 |
005 |
20151204170834.0 |
007 |
cr nn 008mamaa |
008 |
100301s2008 xxk| s |||| 0|eng d |
020 |
|
|
|a 9781848002333
|9 978-1-84800-233-3
|
024 |
7 |
|
|a 10.1007/978-1-84800-233-3
|2 doi
|
040 |
|
|
|d GrThAP
|
050 |
|
4 |
|a TJ212-225
|
072 |
|
7 |
|a TJFM
|2 bicssc
|
072 |
|
7 |
|a TEC004000
|2 bisacsh
|
082 |
0 |
4 |
|a 629.8
|2 23
|
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
|
337 |
|
|
|a computer
|b c
|2 rdamedia
|
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)
|