| 1. |
- Forssell, Urban, et al.
(författare)
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A Projection Method for Closed-Loop Identification
- 1997
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- A new method for closed-loop identification that allows fitting the model to the data with arbitrary frequency weighting is described and analyzed. Just as the direct method, this new method is applicable to systems with arbitrary feedback mechanisms. This is in contrast to other methods, such as the indirect method and the two-stage method, that assume linear feedback. The finite sample behavior of the proposed method is illustrated in a simulation study.
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| 2. |
- Forssell, Urban, et al.
(författare)
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Closed-Loop Identification Revisited
- 1997
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Identification of systems operating in closed loop has long been of prime interest in industrial applications. The problem offers many possibilities, and also some fallacies, and a wide variety of approaches have been suggested, many quite recently. The purpose of the current contribution is to place most of these approaches in a coherent framework, thereby showing their connections and display similarities and differences in the asymptotic properties of the resulting estimates. The common framework is created by the basic prediction error method, and it is shown that most of the common methods correspond to different parameterizations of the dynamics and noise models. The so-called indirect methods, e.g., are indeed “direct” methods employing noise models that contain the regulator. The asymptotic properties of the estimates then follow from the general theory and take different forms as they are translated to the particular parameterizations. We also study a new projection approach to closed-loop identification with the advantage of allowing approximation of the open-loop dynamics in a given, and user-chosen frequency domain norm, even in the case of an unknown, nonlinear regulator.
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| 3. |
- Forssell, Urban, et al.
(författare)
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Combining Semi-Physical and Neural Network Modeling : An Example of Its Usefulness
- 1997
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Ingår i: Proceedings of the 11th IFAC Symposium on System Identification. - Linköping : Linköping University Electronic Press. - 0080425925 ; , s. 795-798
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper illustrates the power of combining semi-physical and neural network modeling in an application example. It is argued that some of the problems related to the use of neural networks, such as high dimensionality of the parameter space and problems with undesired local minima, can be alleviated by this approach.
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| 4. |
- Forssell, Urban
(författare)
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Identification for Control : Unification of some Existing Schemes
- 1997
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper shows how the identification step in several identification for control schemes can be performed in a unified and simplified manner. We utilize a particularly simple indirect method for closed-loop identification and show how the fix noise model/prefilter should be chosen in order to match the identification and control criteria
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| 5. |
- Forssell, Urban, et al.
(författare)
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Identification of Unstable Systems using Output Error and Box-Jenkins Model Structures
- 1997
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- It is well known that the output error and Box-Jenkins model structures cannot be used for prediction error identification of unstable systems. The reason for this is that the predictors in this case generically will be unstable. Typically this problem is handled by projecting the parameter vector into the region of stability which gives erroneous results when the underlying system is unstable. The main contribution of this work is that we derive modified, but asymptotically equivalent, versions of these model structures that can be applied also in the case of unstable systems.
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| 6. |
- Forssell, Urban, et al.
(författare)
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Issues in Closed-Loop Identification
- 1997
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this contribution we study the statistical properties of a number of closed-loop identification methods and parameterizations. A focus will be on asymptotic variance expressions for these methods. By studying the asymptotic variance for the parameter vector estimates we show that indirect methods fail to give better accuracy than the direct method. Some new results for bias distribution in closed-loop experiments will also be presented. It is also shown how different methods correspond to different parameterizations and how direct and indirect identification can be linked together via the noise model
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| 7. |
- Forssell, Urban
(författare)
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Properties and Usage of Closed-loop Identification Methods
- 1997
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- System identification deals with the construction of mathematical models of dynamical systems using measured data. Closed-loop identification is what results when performing the identification experiment under output feedback, that is, in closed loop. In this thesis we study a number of closed-loop identification methods, both classical and more recently suggested ones. A common feature of the methods considered is that they all are derived in the prediction error framework. We provide a comprehensive treatment of the statistical properties of the different methods for closed-loop identification. A focus will be on accuracy aspects of different closed-loop identification methods and we show that indirect and joint input-output methods fail to give better accuracy than the direct method.The question of whether is is possible to design a closed-loop method that allows fitting the model to the data with arbitrary frequency weighting has long been open. We describe and analyze a new method for closed-loop identication - the projection method - that has this desirable property. A strong feature of the projection method is that it can be applied to systems with arbitrary feedback mechanisms, just as the direct method. A drawback is that the projection method gives worse accuracy than the direct method.Substantial interest has been devoted to the problem of linking identification and control. One mainstream approach has been to try to match the identification and control criteria by using proper frequency weighting in the identification. Obviously the projection method is well suited for this problem. In the literature various indirect methods have been employed. The motivation for this has been that by using indirect methods the bias error will be shaped by the sensitivity function which generally is considered advantageous. We show how the identification step in several identification-for-control schemes based on this idea can be performed in a unified manner using a simple indirect method.A related approach to identification for control is to try to minimize the degradation in closed-loop performance due to control design based on identified models by carefully tuning the experiment design parameters. We focus on closed-loop issues and starting with a quite general problem formulation we show how to optimally choose the feedback regulator and the reference signal.
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| 8. |
- Forssell, Urban, et al.
(författare)
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Tracking Time-Varying Systems : Revisiting Some Basic Trade-offs
- 1997
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Ingår i: Proceedings of the 11th IFAC Symposium on System Identification. - Linköping : Linköping University Electronic Press. - 0080425925 ; , s. 1759-1764
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The trade-off between tracking ability and noise sensitivity inadaptive algorithms is a classical research topic. In this paper we will revisit some of the main results. An input/output view of the archetypical algorithms for recursive identification will be taken, thus enabling the links to H∞ and H2 norms. We will shed some light on the H∞ optimality of the LMS algorithm and also show the corresponding merits of the RLS-type algorithms. Furthermore, the role of the distribution of the noise will be illustrated.
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| 9. |
- Ljung, Lennart, 1946-, et al.
(författare)
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An Alternative Motivation for the Indirect Approach to Closed-Loop Identification
- 1997
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Direct prediction error identification of systems operating in closed loop may lead to biased results due to the correlation between the input and the output noise. The authors study this error, what factors affect it, and how it may be avoided. In particular, the role of the noise model is discussed and the authors show how the noise model should be parameterized to avoid the bias. Apart from giving important insights into the properties of the direct method, this provides a nonstandard motivation for the indirect method.
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| 10. |
- Ljung, Lennart, 1946-, et al.
(författare)
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Variance Results for Closed-Loop Identification Methods
- 1997
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Ingår i: Proceedings of the 36th IEEE Conference on Decision and Control. - Linköping : Linköping University Electronic Press. - 0780341872 ; , s. 2435-2440
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this contribution we study the statistical properties of a number of closed-loop identification methods and parameterizations. A focus will be on asymptotic variance expressions for these methods and by studying the asymptotic variance for the parameter vector estimates we show that indirect methods fail to give better accuracy than the direct method.
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