| 1. |
- Rojas, Cristian R., 1980-, et al.
(författare)
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Equivalence between Transfer-Matrix and Observed-State Feedback Control
- 2006
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Ingår i: IEE Proceedings - Control Theory and Applications. - : Institution of Engineering and Technology (IET). - 1350-2379 .- 1359-7035. ; 153:2, s. 147-155
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Tidskriftsartikel (refereegranskat)abstract
- An observed-state feedback is built for a given multiple input-multiple Output (MIMO) control loop, where the controller is specified in transfer-matrix form. This contribution solves for the first time, for MIMO systems, the classical problem of finding a feedback gain and an observer gain such that the observed-state feedback control loop has the same sensitivity as that provided by a one-degree-of-freedom classical control loop.
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| 2. |
- Goodwin, Graham C., et al.
(författare)
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Good, Bad and Optimal Experiments for Identification
- 2006
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Ingår i: Forever Ljung in System Identification - Workshop on the occasion of Lennart Ljung’s 60th birthday. - Lund, Sweden : Studentlitteratur. - 9144020511
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Bokkapitel (övrigt vetenskapligt/konstnärligt)
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| 3. |
- 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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| 4. |
- Olofsson, K. Erik J., et al.
(författare)
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Vector dither experiment design and direct parametric identification of reversed-field pinch normal modes
- 2009
-
Ingår i: Proceedings of the IEEE Conference on Decision and Control. - 9781424438716 ; , s. 1348-1353
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Konferensbidrag (refereegranskat)abstract
- Magnetic confinement fusion (MCF) research ambitiously endeavours to develop a major future energy source. MCF power plant designs, typically some variation on the tokamak, unfortunately suffer from magnetohydrodynamic (MHD) instabilities. One unstable mode is known as the resistive-wall mode (RWM) which is a macroscopically global type of perturbation that can degrade or even terminate the plasma in the reactor if not stabilized. In this work the topic of RWMs is studied for the reversed-field pinch (RFP), another toroidal MCF concept, similar to the tokamak. The problem of identifying RWM dynamics during closed-loop operation is tackled by letting physics-based parametric modeling join forces with convex programming experiment design. An established MHD normal modes description is assessed for the RFP by synthesizing a multivariable dither signal where spatial fourier modes are spectrally shaped, with regard to real experiment constraints, to yield minimum variance parameter estimates in the prediction-error framework. The dithering is applied to the real RFP plant EXTRAP-T2R, and experimental MHD spectra are obtained by an automated procedure.
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| 5. |
- Rojas, Cristian R., 1980-, et al.
(författare)
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A Receding Horizon Algorithm to Generate Binary Signals with a Prescribed Autocovariance
- 2007
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Ingår i: 2007 AMERICAN CONTROL CONFERENCE, VOLS 1-13. - 9781424409884 ; , s. 122-127
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Konferensbidrag (refereegranskat)abstract
- Optimal test signals are frequently specified in terms of their second order properties, e.g. autocovariance or spectrum. However, to utilize these signals in practice, one needs to be able to produce realizations whose second order properties closely approximate the prescribed properties. Of particular interest are binary waveforms since they have the highest form-factor in the sense that they achieve maximal energy for a given amplitude. In this paper we utilize ideas from model predictive control to generate a binary waveform whose sampled autocovariance is as close as possible to some prescribed autocovariance. Several simulated examples are presented verifying the veracity of the algorithm. Also, a proof of convergence is given for the special case of bandlimited white noise. This proof is based on expressing the system in the form of a switched linear system.
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| 6. |
- Rojas, Cristian R., 1980-, et al.
(författare)
-
Consistent estimation of real NMP zeros in stable LTI systems of arbitrary complexity
- 2009
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Ingår i: 15th IFAC Symposium on System Identification, SYSID 2009. - : Elsevier BV. ; , s. 922-927
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Konferensbidrag (refereegranskat)abstract
- In this contribution we show that under certain conditions it is possible to estimate a non-minimum phase zero consistently using a very simple 2 parameter finite impulse response model, for arbitrarily complex finite dimensional stable linear time invariant systems.
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| 7. |
- Rojas, Cristian R., 1980-, et al.
(författare)
-
Fundamental Limitations on the Variance of Estimated Parametric Models
- 2009
-
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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| 8. |
- Rojas, Cristian R., 1980-, et al.
(författare)
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Input design for asymptotic robust H2-filtering
- 2009
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Ingår i: 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009. ; , s. 476-481
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Konferensbidrag (refereegranskat)abstract
- In this paper we study the problem of robust discrete-time H-2 filtering using a Linear Matrix Inequality approach. By assuming that the number of samples available for the identification of the system is large enough, we describe the filter design problem as a semidefinite program. Afterwards, the problem of designing an input signal for the identification of the system, to improve the performance of the conceived filter, is examined, and we show how to solve this problem using convex optimization.
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| 9. |
- Rojas, Cristian R., 1980-, et al.
(författare)
-
MIMO experiment design based on asymptotic model order theory
- 2009
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - Shanghai. - 9781424438716 ; , s. 488-493
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Konferensbidrag (refereegranskat)abstract
- In this paper we investigate the problem of designing an input signal for a Multi-Input Multi-Output plant to minimize a control-oriented criterion. By employing Ljung's asymptotic (in model order and sample size) covariance formulas, we determine closed form expressions for the optimal input, which provide direct insight into the effect of the principal directions and gains of the open- and closed-loop transfer functions on the kind of experiment to be applied.
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| 10. |
- Rojas, Cristian R., 1980-, et al.
(författare)
-
The cost of complexity in identification of FIR systems
- 2008
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Ingår i: 17th World Congress, International Federation of Automatic Control, IFAC. ; , s. 11451-11456
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Konferensbidrag (refereegranskat)abstract
- In this paper we investigate the minimum amount of input power required to estimate a given linear system with a prescribed degree of accuracy, as a function of the model complexity. This quantity is defined to be the "cost of complexity". The degree of accuracy considered is the maximum variance of the discrete-time transfer function estimator over a frequency range [-ωB, ωB]. It is commonly believed that the cost increases as the model complexity increases. The objective of this paper is to quantify this dependence. In particular, we establish several properties of the cost of complexity. We find, for example, a lower bound for the cost asymptotic in the model order. For simplicity, we consider only systems described by FIR models and assume that there is no undermodelling.
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