| 1. |
- Irshad, Yasir, 1977-, et al.
(författare)
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System identification in a networked environment using second order statistical properties
- 2013
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Ingår i: Automatica. - : Elsevier BV. - 0005-1098 .- 1873-2836. ; 49:2, s. 652-659
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Tidskriftsartikel (refereegranskat)abstract
- System identification for networked control is considered. Due to the time-delays in the network, it can be difficult to work with a discrete-time model and a continuous-time model is therefore chosen. A covariance function based method that relies on the second order statistical properties of the output signal, where it is assumed that the input signal samples are from a discrete-time white noise sequence, is proposed for estimating the parameters. The method is easy to use since the actual time instants when new input signal levels are applied at the actuator do not have to be known. An analysis of the networked system and the effects of the time-delays is made, and the results of the analysis motivate and support the chosen approach. Numerical studies indicate that the method is robust to randomly distributed time-delays, packet drop-outs, and additive measurement noise.
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| 2. |
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| 3. |
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| 4. |
- Mossberg, Magnus, et al.
(författare)
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Approximative weighting for a covariance-matching approach for identifying errors-in-variables systems
- 2011
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Ingår i: International journal of adaptive control and signal processing (Print). - : Wiley. - 0890-6327 .- 1099-1115. ; 47:2, s. 272-282
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Tidskriftsartikel (refereegranskat)abstract
- A covariance-matching approach for identifying errors-in-variables systems has previously been proposed and analyzed. It has been demonstrated that the gain in accuracy can be substantial if an optimal weighting is used. The computation of the optimal weighting requires knowledge of true parameters of signals and systems. This paper describes how the optimal weighting can be computed approximately from the available noisy data and thereby offers a way to identify errors-in-variables systems with high accuracy. Numerical examples indicate that using this approximately optimal weighting gives an accuracy that is close to the accuracy obtained by using the optimal weighting.
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| 5. |
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| 6. |
- Söderström, Torsten, et al.
(författare)
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A covariance matching approach for identifying errors-in-variables systems
- 2009
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Ingår i: Automatica. - : Elsevier BV. - 0005-1098 .- 1873-2836. ; 45:9, s. 2018-2031
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Tidskriftsartikel (refereegranskat)abstract
- The errors-in-variables identification problem concerns dynamic systems whose input and output variables are affected by additive noise. Several estimation methods have been proposed for identifying dynamic errors-in-variables models. In this paper a covariance matching approach is proposed to solve the identification problem. It applies for general types of input signals. The method utilizes a small set of covariances of the measured input–output data. This property applies also for some other methods, such as the Frisch scheme and the bias-eliminating least squares method. Algorithmic details for the proposed method are provided. User choices, for example specification of which input–output covariances to utilize, are discussed in some detail. The method is evaluated by using numerical examples, and is shown to have competitive properties as compared to alternative methods.
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| 7. |
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| 8. |
- Söderström, Torsten, et al.
(författare)
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On the accuracy of a covariance matching method for continuous-time errors-in-variables identification
- 2013
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Ingår i: Automatica. - : Elsevier BV. - 0005-1098 .- 1873-2836. ; 49:10, s. 2982-2993
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Tidskriftsartikel (refereegranskat)abstract
- An analysis of a covariance matching method for continuous-time errors-in-variables system identification from discrete-time data is made. In the covariance matching method, the noise-free input signal is not explicitly modeled and only assumed to be a stationary process. The asymptotic normalized covariance matrix, valid for a large number of data and a small sampling interval, is derived. This involves the evaluation of a covariance matrix of estimated covariance elements and estimated derivatives of such elements, and large parts of the paper are devoted to this task. The latter covariance matrix consists of two parts, where the first part contains integrals that are approximations of Riemann sums, and the second part depends on the measurement noise variances.
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| 9. |
- Irshad, Yasir, 1977-, et al.
(författare)
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A comparison of estimation concepts applied to networked control systems
- 2012
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Ingår i: 19th International Conference on Systems, Signals and Image Processing (IWSSIP), 2012. - Piscataway : IEEE Press. - 9781457721915 ; , s. 114-117
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Konferensbidrag (refereegranskat)abstract
- A continuous-time description of networked control systems is considered and the parameters are estimated. The discrete-time description is time-varying due to the random time-delays in the wireless links and therefore difficult to work with. Off-line as well as on-line situations are considered for parameter estimation. In the off-line situation, a linear regression is formed and then the parameters are estimated by the least squares method. In the on-line situation, the estimates of the parameters are recursively updated for each time instance. A comparative study of two different parameter estimation approaches is presented. In the first approach, the parameters are estimated by a simple linear regression. In the second approach, transformation of the differentiation operator to another casual and stable linear operator is made in linear regression to estimate the parameters. A numerical study of these approaches is also presented for comparison.
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| 10. |
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