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- Goodwin, Graham C., et al.
(författare)
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Robust Identification of Process Models from Plant Data
- 2008
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Ingår i: Journal of Process Control. - : Elsevier. - 0959-1524. ; 18:9, s. 810-820
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Tidskriftsartikel (refereegranskat)abstract
- A precursor to any advanced control solution is the step of obtaining an accurate model of the process. Suitable models can be obtained from phenomenological reasoning, analysis of plant data or a combination of both. Here, we will focus on the problem of estimating (or calibrating) models from plant data. A key goal is to achieve robust identification. By robust we mean that small errors in the hypotheses should lead to small errors in the estimated models. We argue that, in some circumstances, it is essential that special precautions, including discarding some part of the data, be taken to ensure that robustness is preserved. We present several practical case studies to illustrate the results.
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| 2. |
- Agüero, Juan C., et al.
(författare)
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Fundamental Limitations on the Accuracy of MIMO Linear Models Obtained by PEM for Systems Operating in Open Loop
- 2009
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Ingår i: Proceedings of the Joint 48th IEEE Conference on Decision and Control (CDC’09) and 28th Chinese Control Conference (CCC’09). - 9781424438716 ; , s. 482-487
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Konferensbidrag (refereegranskat)abstract
- In this paper we show that the variance of estimated parametric models for open loopMultiple-Input Multiple-Output (MIMO) systems obtained by the prediction error method (PEM) satisfies a fundamental integral limitation. The fundamental limitation gives rise to a multivariable 'water-bed' effect.
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| 4. |
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| 5. |
- Rojas, Cristian R., et al.
(författare)
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On the Equivalence of Least Costly and Traditional Experiment Design for Control
- 2008
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Ingår i: Automatica. - : Elsevier BV. - 0005-1098 .- 1873-2836. ; 44:11, s. 2706-2715
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Tidskriftsartikel (refereegranskat)abstract
- In this paper we establish the equivalence between least costly and traditional experiment design for control. We consider experiment design problems for both open and closed loop systems. In open loop, equivalence is established for three specific cases, relating to different parametrisations of the covariance expression (i.e. finite and high order approximations) and model structure (i.e. dependent and independently parameterised plant and noise models). In the closed loop setting, we consider only finite order covariance expressions. H(infinity) performance specifications for control are used to determine the bounds on the covariance expression for both the open and closed loop cases.
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| 6. |
- Rojas, Cristian R., 1980-, et al.
(författare)
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Fundamental Limitations on the Variance of Estimated Parametric Models
- 2009
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Ingår i: IEEE Transactions on Automatic Control. - 0018-9286 .- 1558-2523. ; 54:5, s. 1077-1081
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Tidskriftsartikel (refereegranskat)abstract
- In this technical note fundamental integral limitations are derived on the variance of estimated parametric models, for both open and closed loop identification. As an application of these results we show that, for multisine inputs, a well known asymptotic (in model order) variance expression provides upper bounds on the actual variance of the estimated models for finite model orders. The fundamental limitations established here give rise to a 'water-bed' effect, which is illustrated in an example.
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