| 1. |
- Andersson, Sören, et al.
(författare)
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An adaptive array for mobile communication systems
- 1991
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Ingår i: IEEE Transactions on Vehicular Technology. - Toronto, Ont, Can : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9545 .- 1939-9359. ; 40:1 pt 2, s. 230-236, s. 3289-3292
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Tidskriftsartikel (refereegranskat)abstract
- The use of adaptive antenna techniques to increase the channel capacity is discussed. Directional sensitivity is obtained by using an antenna array at the base station, possibly both in receiving and transmitting modes. A scheme for separating several signals at the same frequency is proposed. The method is based on high-resolution direction-finding followed by optimal combination of the antenna outputs. Comparison with a method based on reference signals is made. Computer simulations are carried out to test the applicability of the technique to scattering scenarios that typically arise in urban areas. The proposed scheme is found to have great potential in rejecting cochannel interference, albeit at the expense of high computational requirements.
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| 2. |
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| 3. |
- Bodin, Per, et al.
(författare)
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Thresholding in high order transfer function estimation
- 1994
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Ingår i: Decision and Control, 1994., Proceedings of the 33rd IEEE Conference on. ; , s. 3400-3405
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Konferensbidrag (refereegranskat)abstract
- A problem in prediction error system identification methods is estimation of pole locations. Typically, iterative numerical optimization methods are used. Reliable initial values are then necessary for good results. The parameterization is often done in the coefficients of transfer function polynomials or some canonical form. In this contribution we discuss a couple of issues related to the above problem. First, we study how all-pass systems can be used to generate suitable model structures. This analysis is based on the relation between balanced realizations of all-pass filters and orthonormal basis transfer functions. Next, we investigate the effects of a priori fixed pole locations, such as in Laguerre and Kautz models. One idea is to use very flexible high-order models. However, the corresponding estimation problem has to be regularized in order to reduce the variance errors due to noise. We will discuss how this can be done by using thresholding of the estimated coefficients
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| 4. |
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| 5. |
- Finn, Cory K., et al.
(författare)
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Constrained predictive control using orthogonal expansions
- 1993
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Ingår i: AIChE Journal. - : Wiley. - 0001-1541 .- 1547-5905. ; 39, s. 1810-1826
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we approximate bounded operators by orthogonal expansion. The rate of convergence depends on the choice of basis functions. Markov-Laguerre functions give rapid convergence for open-loop stable systems with long delay. The Markov-Kautz model can be used for lightly damped systems, and a more general orthogonal expansion is developed for modeling multivariable systems with widely scattered poles. The finite impulse response model is a special case of these models. A-priori knowledge about dominant time constants, time delay and oscillatory modes is used to reduce the model complexity and to improve conditioning of the parameter estimation algorithm. Algorithms for predictive control are developed, as well as conditions for constraint compatibility, closed-loop stability and constraint satisfaction for the ideal case. An H8-like design technique proposed guarantees robust stability in the presence of input constraints; output constraints may give ￜchatter.ￜ A chatter-free algorithm is proposed.
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| 6. |
- Gunnarsson, Svante, et al.
(författare)
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Some asymptotic results in recursive identification using Laguerre models
- 1991
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Ingår i: International Journal of Adaptive Control and Signal Processing. - : Wiley. - 0890-6327 .- 1099-1115. ; 5:5, s. 313-333
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Tidskriftsartikel (refereegranskat)abstract
- This paper deals with recursive identification of time-varying systems using Laguerre models. Laguerre models generalize finite impulse response (FIR) models by using a priori information about the dominating time constants of the system to be identified. Three recursive algorithms are considered: the stochastic gradient algorithm, the recursive least squares algorithm and a Kalman-filter-like recursive identification algorithm. Simple and explicit expressions for the model quality are derived under the assumptions that the system varies slowly, that the model is updated slowly and that the model order is high. The derived expressions show how the use of Laguerre models affects the model quality with respect to tracking capability and disturbance rejection.
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| 7. |
- Gunnarsson, Svante, et al.
(författare)
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Some asymptotic results in recursive identification using Laguerre models
- 1990
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - Honolulu, HI, USA : Linköping University. ; , s. 1068-1073
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Konferensbidrag (refereegranskat)abstract
- Frequency domain expressions for the quality of recursively identified Laguerre models are presented. These models generalize finite impulse response (FIR) models by using a priori information about the dominating time constants of the system to be identified. Expressions for the model quality are derived under the assumptions that the system varies slowly, that the model is updated slowly, and that the model order is high. The model quality is evaluated by investigating the properties of the estimated transfer function, and explicit expressions for the mean square error (MSE) of the transfer function, and explicit expressions for the mean square error of the transfer function estimate are derived.
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| 8. |
- Gustafsson, Fredrik, et al.
(författare)
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Blind Equalization by Direct Examination of the Input Sequences
- 1992
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Ingår i: Proceedings of the 1992 IEEE International Conference on Acoustics, Speech and Signal Processing. - 0780305329 ; , s. 701-704 vol.4
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Konferensbidrag (refereegranskat)abstract
- The authors' approach to blind equalization examines the possible input sequences directly by using a bank of filters and, in contrast to common approaches, does not try to find an approximative inverse of the channel dynamics. The identifiability question of a noise-free finite impulse response (FIR) model is investigated. A sufficient condition for the input sequence (persistently exciting of a certain order) is given which guarantees that both the channel model and the input sequence can be determined exactly in finite time. A recursive algorithm is given for a time-varying infinite impulse response (IIR) channel model with additive noise, which does not require a training sequence. The estimated sequence is an arbitrarily good approximation of the maximum a posteriori estimate. The proposed method is evaluated on a Rayleigh fading communication channel. It shows fast convergence properties and good tracking ability.
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| 9. |
- Gustafsson, Fredrik, et al.
(författare)
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Identifiability in Blind Equalization
- 1993
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Ingår i: Proceedings of the 12th IFAC World Congress. - 9780080422121
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Konferensbidrag (refereegranskat)
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| 10. |
- Gustafsson, Fredrik, et al.
(författare)
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On simultaneous system and input sequence estimation
- 1993
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Ingår i: IFAC Symposia Series. - Grenoble, Fr. ; , s. 11-16
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Konferensbidrag (refereegranskat)abstract
- Equalization is concerned with estimation of the input sequence of a linear system given noisy measurements of the output signal. In case the system description is unknown we have the problem of blind equalization. A scheme for blind equalization which is based on the assumption that the input signal belongs to a finite alphabet is proposed. A finite impulse response model can be directly estimated by the least-squares method if the input sequence is known. Since we know that the number of possible input sequences is limited, we can associate one system estimate to each possible input sequence. This allows us to determine the a posteriori probability of an input sequence given output observations. The maximum a posteriori (MAP) input sequence estimate is then taken as the most probable input sequence. Sufficient conditions for identifiability of the input signal and the system are given. The complexity of this scheme increases exponentially with time. A recursive approximate MAP estimator of fixed complexity is obtained by, at each time update, only keeping the K most probable input sequences. This method is evaluated on a Rayleigh fading communication channel.
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| 11. |
- Hjalmarsson, Håkan, 1962-, et al.
(författare)
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Assessing model quality from data
- 1991
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Ingår i: Modeling, estimation and control of systems with uncertainty. - : Birkhäuser Verlag. ; , s. 167-187
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Bokkapitel (refereegranskat)
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| 12. |
- Homer, John, et al.
(författare)
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LMS Estimation of Sparsely Parametrized Channels via Structural Detection
- 1994
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Ingår i: Proceedings of the 33rd IEEE Conference on Decision and Control. - 0780319680 ; , s. 257-262 vol.1
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Konferensbidrag (refereegranskat)abstract
- Considers the LMS estimation of “long” channels which have time domain impulse responses consisting of sparsely spaced nonzero taps or groups of taps. Standard LMS estimation of such long sparsely parametrized channels, in which all taps are estimated, suffers from poor transient and/or asymptotic performance. Analyses carried out by the authors indicate that performance improvements can be achieved by estimating only those taps which are nonzero or “active”. The authors develop a simple procedure, based on the least squares method, which for sufficiently large N (the number of sample intervals) detects the correct number and position of active taps. Using this structure detection procedure the authors propose an LMS based estimation algorithm. Simulations indicate that this “LMS-structure detection” algorithm provides considerable performance improvement over the standard LMS algorithm.
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| 13. |
- Krishnamurthy, Vikram, et al.
(författare)
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Factorizations that relax the positive real condition in continuous-time and fast-sampled ELS schemes
- 1990
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Ingår i: International journal of adaptive control and signal processing (Print). - : Wiley. - 0890-6327 .- 1099-1115. ; 4:5, s. 389-414
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Tidskriftsartikel (refereegranskat)abstract
- This paper proposes extended least-squares (ELS) for ARMAX model identification of continuous-time and certain discrete-time systems. The schemes have a relaxed strictly positive real (SPR) condition for global convergence. The relaxed SPR scheme is achieved by introducing overparametrization and prefiltering but without introducing ill-conditioning. The schemes presented are the first such proposed for continuous-time systems. The concepts developed in continuous time carry through to fast-sampled continuous-time systems and associated discrete-time ELS algorithms. For such situations, in comparison with previously proposed discrete-time schemes, the degree of overparametrization required in the proposed scheme of this paper is significantly lower. The reduction is achieved by using more suitable prefiltering and overparametrization techniques than previously proposed. We also establish the persistence of excitation (PE) of the regression vectors in the proposed ELS schemes to assure strong consistency, obtain convergence rates and provide robustness to unmodelled dynamics. To prove the PE of continuous-time regression vectors, we develop output reachability characterization for MIMO linear continuous-time systems.
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| 14. |
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| 15. |
- Lindskog, Peter, et al.
(författare)
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Applications of Kautz Models in System Identification
- 1993
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Ingår i: Proceedings of the 12th IFAC World Congress. - Linköping : Linköping University. - 9780080422121 ; , s. 309-312
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- FIR, ARX or AR model structures can be used to describe many industrial processes. Simple linear regression techniques can be applied to estimate such models from experimental data. However, for low signal to noise ratios in combination with transfer function poles and noise model zeros close to the unit circle, a large number of model parameters are needed to generate adequate models. The Kautz model structure generalizes FIR, ARX and AR models. By using a priori knowledge about the dominating time constants and damping factors of the system, the model complexity is reduced, and the linear regression structure is retained. The objective of this contribution is to study an industrial example, where Kautz models have distinct advantages. The data investigated corresponds to aircraft flight flutter, which is a state when an aircraft component starts to oscillate.
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| 16. |
- Ljung, Lennart, et al.
(författare)
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Influence of model order on change detection in noise-free complex system
- 1990
-
Ingår i: Proceedings of the American Control Conference. - San Diego, CA, USA. ; , s. 2388-2393
-
Konferensbidrag (refereegranskat)abstract
- A study is made of the accuracy that could be obtained in the transfer function estimate. The system is noise-free but complex. It is found that it is better to use a (very) high-order model in combination with suitable regularization (prior). The reason is that the potential problem with an ill-conditioned regression matrix (high variance) is counteracted by the regularization. The bandpass filters cause information delay in the transient phase and degrade model-error attenuation in the stationary phase. It is also shown how set membership identification can handle model errors and provide hard (and in the example provided, somewhat conservative) error bounds. For this, the a priori information and the fact that the system is noise-free are used. An additive, bounded disturbance would not cause problems. The actual set membership estimate (the center of the model set) does not differ very much from the least-squares estimate in the example (because of the particular choice of prior).
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| 17. |
- Ljung, Lennart, et al.
(författare)
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Model quality : The roles of prior knowledge and data information
- 1992
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Ingår i: Proceedings of the IEEE Conference on Decision and Control. - Brighton, Engl. ; , s. 273-278
-
Konferensbidrag (refereegranskat)abstract
- The authors discuss the basic issues involved in the problem of estimating a model's reliability. In particular, the role of prior information is scrutinized. The modeling errors can be divided into two categories, namely, systematic/bias errors and variability/random errors. All serious system identification experiments contain a model validation step. For an unfalsified model, the bias error has not been found to be significantly larger than the random errors. Hence, the traditional, statistical way to provide estimated standard deviations for the model is relevant for unfalsified models. In case of many unfalsified models, a sound scientific approach is to choose the most powerful unfalsified one. The definition of most powerful depends on the intended application. For example, in robust control design an unfalsified model can be said to be most powerful if the H∞ error bound is minimized. How this concept relates to minimizing the mean square errors is discussed. A number of questions for further research are identified.
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| 18. |
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| 19. |
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| 20. |
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| 21. |
- Viberg, Mats, et al.
(författare)
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A statistical perspective on state-space modeling using subspace methods
- 1991
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Ingår i: Proceedings of the 30th IEEE Conference on Decision and Control. - Linköping : Linköping University. - 0780304500 ; , s. 1337-1342
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Konferensbidrag (refereegranskat)abstract
- The authors investigate aspects of subspace-based state-space identification techniques from a statistical perspective. They concentrate their efforts on a simple approach which is based on finding the range-space of the observability matrix of a state-space representation. The system description is then found using the shift-invariance property of the observability matrix. It is shown that this results in a consistent system description for multivariable output-error models if the measurement noise is white in time and independent from output to output. The asymptotic covariance of the estimated poles of the system is also derived. In the test case studied, the subspace technique performs comparably with the statistically efficient PE (prediction error) method, whereas the IV (instrumental variable) method does notably worse. Hence, the subspace technique may be a strong candidate for determining initial values for the optimization in the efficient PE method.
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| 22. |
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| 23. |
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| 24. |
- Wahlberg, Bo, 1959-
(författare)
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ARMA spectral estimation of narrow-band processes via model reduction
- 1990
-
Ingår i: IEEE Transactions on Acoustics, Speech, and Signal Processing. - : Institute of Electrical and Electronics Engineers (IEEE). - 0096-3518. ; 38:7, s. 1144-1154
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Tidskriftsartikel (refereegranskat)abstract
- The problem of estimating autoregressive moving average (ARMA) models for narrowband processes is considered. The following approach is proposed. Estimate a high-order autoregressive (AR) approximation of the process. By model reduction, based on a truncated internally balanced realization or optimal Hankel-norm model reduction, reduce the order of this high-order AR estimate to find a lower-order ARMA model. This algorithm gives ARMA spectral estimates with excellent resolution properties, without using iterative numerical minimization methods as for the maximum-likelihood method. How to take the narrowband assumption into account in the model reduction step is discussed in detail.
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| 25. |
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| 26. |
- Wahlberg, Bo, 1959-, et al.
(författare)
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Experimental and theoretical comparison of some algorithms for beamforming in single receiver adaptive arrays
- 1991
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Ingår i: IEEE Transactions on Antennas and Propagation. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-926X .- 1558-2221. ; 39:1, s. 21-28
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Tidskriftsartikel (refereegranskat)abstract
- Adaptive null steering in single receiver adaptive arrays is discussed. The single receiver structure allows only output power for a given set of weights to be measured. The problem, then, is to adaptively adjust the weights of the antenna array, based on output power measurements only, so as to reject interference signals while maintaining a fixed response in a given look direction. Current least-mean-square (LMS)-based iterative techniques use perturbations of the beamformer weights to obtain an estimate of the gradient of a given cost (power) function in order to update an initial guess. The key idea of this work is to determine the optimal beamformer weights in a single step, by estimating the covariance matrix of the array sensor outputs using a weight perturbation technique. Based on this covariance matrix estimate, three different approaches for finding the beamformer weights are studied. The first corresponds to a sample matrix inversion (SMI) scheme, with the sample covariance matrix replaced by the one obtained from the perturbation estimation method, while in the second approach the weights are determined using an eigenvalue decomposition of the covariance matrix estimate. In the third approach the directions-of-arrival (DOAs) of the incoming wavefronts are first estimated, and then, in a second step, the beamformer weights are calculated from the DOA estimates. The advantage of the third approach is that this method is not affected by correlation between the different sources. In comparison to iterative techniques, the approach offers much faster beamforming, albeit at the expense of increased susceptibility to unmodeled characteristics.
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| 27. |
- Wahlberg, Bo, 1959-, et al.
(författare)
-
Factorizations that relax the positive real condition in continuous-time ELS schemes
- 1991
-
Ingår i: Proceedings of the 11th Triennial World Congress of the International Federation of Automatic Control. ; , s. 155-160
-
Konferensbidrag (refereegranskat)abstract
- This paper proposes Extended Least Squares (ELS) schemes for ARMAX model identification of continuous-time systems. The schemes have a relaxed Strictly Positive Real (SPR) condition for global convergence. The relaxed SPR scheme is achieved by introducing overparametrisation and prefiltering but without introducing ill-conditioning. The schemes presented are the first such proposed for continuous-time systems. The concepts developed here carry through to output-error, fast-sampled continuous-time systems and associated discrete-time ELS algorithms. We also state conditions for the persistence of excitation (P.E.) of the regression vectors in the proposed ELS schemes to assure strong consistency and obtain convergence rates.
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| 28. |
- Wahlberg, Bo, 1959-, et al.
(författare)
-
Hard frequency-domain model error bounds from least-squares like identification techniques
- 1992
-
Ingår i: IEEE Transactions on Automatic Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286 .- 1558-2523. ; 37:7, s. 900-912
-
Tidskriftsartikel (refereegranskat)abstract
- The problem of deriving so-called hard-error bounds for estimated transfer functions is addressed. A hard bound is one that is sure to be satisfied, i.e., the true system Nyquist plot will be confined with certainty to a given region, provided that the underlying assumptions are satisfied. By blending a priori knowledge and information obtained from measured data, it is shown how the uncertainty of transfer function estimates can be quantified. The emphasis is on errors due to model mismatch. The effects of unmodeled dynamics can be considered as bounded disturbances. Hence, techniques from set membership identification can be applied to this problem. The approach taken corresponds to weighted least-squares estimation, and provides hard frequency-domain transfer function error bounds. The main assumptions used in the current contribution are: that the measurement errors are bounded, that the true system is indeed linear with a certain degree of stability, and that there is some knowledge about the shape of the true frequency response.
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| 29. |
- Wahlberg, Bo, 1959-
(författare)
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Identification of resonant systems using Kautz filters
- 1991
-
Ingår i: Proceedings of the 30th IEEE Conference on Decision and Control Part 1 (of 3). - Linköping : Linköping University. - 0780304500 ; , s. 2005-2010
-
Konferensbidrag (refereegranskat)abstract
- It is pointed out that by approximating the impulse response of a linear time-invariant stable system by a finite sum of given exponentials, the problem of estimating the transfer function is considerably simplified. The author shows how the complexity can be reduced further by using orthogonalized exponentials. The analysis is based on the result that the corresponding normal equations will then have a Toeplitz structure. The z-transform of orthogonalized exponentials corresponds to discrete Kautz functions, which generalize discrete Laguerre functions to the several, possibly complex, poles case. Hence, by appropriate choice of time constants Kautz models give low-order useful approximations of many systems of interest. In particular, resonant systems can be well approximated using Kautz models with complex poles. Several basic results on transfer function estimation are extended to discrete Kautz models, for example, frequency-domain quality properties and efficient numerical techniques.
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| 30. |
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| 31. |
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| 32. |
- Wahlberg, Bo, 1959-, et al.
(författare)
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On Sampling of Continuous Time Stochastic Processes
- 1993
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Ingår i: Control, Theory and Advanced Technology. - 0911-0704. ; 9:1, s. 99-112
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Tidskriftsartikel (refereegranskat)abstract
- Techniques for sampling of continuous time stochastic processes are presented. To obtain flexible models and well-posed filtering problems, we assume an underlying continuous time innovations model. To sample such a model `averaged sampling' is applied. It is shown that this technique is equivalent to the following two step procedure: Determine by instantaneous (direct) sampling a discrete model for the continuous time process obtained by integrating the original innovations model. Then differentiate the sampled process to remove the discrete pole at z = 1 introduced by the integration. An advantage with this procedure is that one obtains ARMA(n, n) models, while instantaneous sampling only gives ARMA(n, n-1) models. Furthermore, the problem of updating discrete time models, without using a continuous time model, in case of a change of sampling rate - decimation/interpolation - is addressed.
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| 33. |
- Wahlberg, Bo, 1959-, et al.
(författare)
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Parametric Signal Modelling using Laguerre Filters
- 1993
-
Ingår i: The Annals of Applied Probability. - : Institute of Mathematical Statistics. - 1050-5164 .- 2168-8737. ; 3:2, s. 467-496
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Tidskriftsartikel (refereegranskat)abstract
- Autoregressive (AR) modelling is generalized by replacing the delay operator by discrete Laguerre filters. The motivation is to reduce the number of parameters needed to obtain useful approximate models of stochastic processes, without increasing the computational complexity. Asymptotic statistical properties are investigated. Several AR model estimation results are extended to Laguerre models. In particular, it is shown how the choice of Laguerre time constant affects the resulting estimates. A Levinson-type algorithm for computing the Laguerre model estimates in an efficient way is also given. The Laguerre technique is illustrated by two simple examples.
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| 34. |
- Wahlberg, Bo, 1959-
(författare)
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Robust frequency domain fault detection/diagnosis
- 1991
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Ingår i: Proceedings of the 11th Triennial World Congress of the International Federation of Automatic Control. ; , s. 373-378
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Konferensbidrag (refereegranskat)abstract
- Undermodelling can lead to poor behavior of fault detection (diagnosis) algorithms based on estimated parametric models. The aim of this paper is to study how to reduce this problem by working in the frequency domain and using flexible models. Simple and practically appealing frequency domain fault detection/diagnosis schemes are derived using recent results of Ljung (1987) on a high-order black-box identification theory.
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| 35. |
- Wahlberg, Bo, 1959-
(författare)
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System identification using Kautz models
- 1994
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Ingår i: IEEE Transactions on Automatic Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286 .- 1558-2523. ; 39:6, s. 1276-1282
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Tidskriftsartikel (refereegranskat)abstract
- In this paper, the problem of approximating a linear time-invariant stable system by a finite weighted sum of given exponentials is considered. System identification schemes using Laguerre models are extended and generalized to Kautz models, which correspond to representations using several different possible complex exponentials. In particular, linear regression methods to estimate this sort of model from measured data are analyzed. The advantages of the proposed approach are the simplicity of the resulting identification scheme and the capability of modeling resonant systems using few parameters. The subsequent analysis is based on the result that the corresponding linear regression normal equations have a block Toeplitz structure. Several results on transfer function estimation are extended to discrete Kautz models, for example, asymptotic frequency domain variance expressions.
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| 36. |
- Wahlberg, Bo, 1959-
(författare)
-
System identification using Laguerre models
- 1991
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Ingår i: IEEE Transactions on Automatic Control. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9286 .- 1558-2523. ; 36:5, s. 551-562
-
Tidskriftsartikel (refereegranskat)abstract
- The traditional approach of expanding transfer functions and noise models in the delay operator to obtain linear-in-the-parameters predictor models leads to approximations of very high order in cases of rapid sampling and/or dispersion in time constants. By using prior information about the time constants of the system more appropriate expansions, related to Laguerre networks, are introduced and analyzed. It is shown that the model order can be reduced, compared to ARX (FIR, AR) modeling, by using Laguerre models. Furthermore, the numerical accuracy of the corresponding linear regression estimation problem is improved by a suitable choice of the Laguerre parameter. Consistency (error bounds), persistance of excitation conditions, and asymptotic statistical properties are investigated. This analysis is based on the result that the covariance matrix of the regression vector of a Laguerre model has a Toeplitz structure.
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| 37. |
- Wahlberg, Bo, 1959-
(författare)
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The effects of rapid sampling in system identification
- 1990
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Ingår i: Automatica. - : Elsevier. - 0005-1098 .- 1873-2836. ; 26:1, s. 167-170
-
Tidskriftsartikel (refereegranskat)abstract
- This paper deals with the effects of rapid sampling in system identification. In continuous time, noise models of non-zero relative degree imply that one has to differentiate the measured data to find the prediction error parameter estimate. This problem can be avoided by using noise models of relative degree zero or by introducing prefilters. The corresponding difficulty for the discrete time case is less obvious. However, by linking the discrete time and continuous time parameter estimation problem, we show that the same problem arises for rapid sampled systems.
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| 38. |
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