| 1. |
- Aberger, Martin
(författare)
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Effects of Nonlinearities in Black Box Identification of an Industrial Robot
- 2000
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper discusses effects of nonlinearities in black box identification of one axis of a robot. The used data come from a commercial ABB robot, IRB1400. A three-mass flexible model for the robot was built in MathModelica. The nonlinearities in the model are nonlinear friction and backlash in the gear box.
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| 2. |
- Anderson, Kristin, 1977-, et al.
(författare)
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Broadcast Encryption and Group Codes
- 2004
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- We consider the subset difference scheme for broadcast encryption and count the number of required transmissions when using this scheme. The subset scheme organizes receivers in a tree structure and we note that isomorphic trees yield the same number of required transmissions. We then study the group properties of isomorphism classes of trees. Finally we formulate some research questions for further study of the performance of the subset difference scheme.
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| 3. |
- Anderson, Kristin, 1977-
(författare)
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Performance of the Subset Difference Scheme for Broadcast Encryption
- 2004
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This report considers the subset difference scheme for broadcast encryption and the number of broadcast transmissions required when using this scheme. For cases where the privileged users are gathered in a few groups we derive the worst case number of transmissions. We also present an upper bound for the number of transmissions based on the number of transitions between privileged and nonprivileged users in the user set.
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| 4. |
- Axehill, Daniel, et al.
(författare)
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A Preprocessing Algorithm for MIQP Solvers with Applications to MPC
- 2004
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Ingår i: Proceeding of Reglermöte 2004. - Linköping : Linköping University Electronic Press. ; , s. 2497-2502
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In this paper a preprocessing algorithm for unconstrained mixed integer quadratic programming problems and binary quadratic programming problems is presented. The algorithm applies to problems with certain properties, which are further described in the paper. When the algorithm is applied to a problem with these properties, the optimal value for some or all integer variables can be computed without approximations in polynomial time. The algorithm is first derived for the binary quadratic programming problem and the result is then extended to the mixed integer quadratic programming problem by transforming the latter problem into the first problem. Both mentioned quadratic programming problems have several important applications. In this paper, the focus is on model predictive control problems with both real-valued and binary control signals. As an illustration of the method, the algorithm is applied to two different problems of this type.
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| 5. |
- Bauer, Dietmar
(författare)
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Asymptotic Efficiency of CCA Subspace Methods in the Case of no Exogenous Inputs
- 2000
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper one of the main open questions in the area of subspace methods is answered partly. One particular algorithm, sometimes termed CCA, is shown to be asymptotically equivalent to estimates obtained by minimizing the pseudo maximum likelihood. Here asymptotically equivalent means, that the difference of the two estimators times the square root of the sample size tends to zero.
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| 6. |
- Bauer, Dietmar, et al.
(författare)
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Asymptotic Properties of Identification of Hammerstein Models with Input Saturation
- 2000
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This paper considers the estimation of Hammerstein models with input saturation. These models are characterised by a linear dynamical model acting on an input sequence which is affected by a hard saturation of unknown level. The main result of the paper lies in a specication of a set of sufficient conditions on the input sequence in order to ensure that a non-linear least-squares approach enjoys properties of consistency and asymptotic normality and furthermore, that an estimate of the parameter covariance matrix is also consistent. The set of assumptions is specied using the concept of near epoch dependence, which has been developed in the econometrics literature. Indeed, one purpose of this paper is to highlight the usefulness of this concept in the context of analysing estimation procedures for nonlinear dynamical systems.
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| 7. |
- Bauer, Dietmar
(författare)
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On Data Preprocessing for Subspace Methods
- 2000
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Ingår i: Proceedings of the 39th IEEE Conference on Decision and Control. - Linköping : IEEE. - 0780366387 ; , s. 2403-2408
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Konferensbidrag (refereegranskat)abstract
- In modern data analysis often the first step is to perform some data preprocessing, e.g. detrending or elimination of periodic components of known period length. This is normally done using least squares regression. Only afterwards black box models are estimated using either pseudo-maximum-likelihood methods, prediction error methods or subspace algorithms. In this paper it is shown, that for subspace methods this is essentially the same as including the corresponding input variables, e.g. a constant or a trend or a periodic component, as additional input variables. Here essentially means, that the estimates only dier through the choice of initial values.
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| 8. |
- Bauer, Dietmar
(författare)
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Order Estimation for Subspace Methods
- 2000
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper the question of estimating the order in the context of subspace methods is addressed. Three different approaches are presented and the asymptotic properties there of derived. Two of these methods are based on the information contained in the estimated singular values, while the third method is based on the estimated innovation variance. The case with observed inputs is treated as well as the case without exogenous inputs. The two methods based on the singular values are shown to be consistent under fairly mild assumptions, while the same result for the thirf approach is only obtained on a subset. The former can be applied to Larimore type of procedures as well as to MOESP type of procedures, where as the latter is only applied to Larimore type of algorithms. This has implications for the estimation of the order of systems, which are close to the exceptional set, as is shown in a numerical example. All the estimation methods involve the choice of a penalty term. Sufficient copnditions on the penalty term to guarantee consistency are derived. The effects of different choices of the penalty term are investigated in a simulation study.
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| 9. |
- Bauer, Dietmar, et al.
(författare)
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Some facts about the Choice of the Weighting Matrices in Larimore Type of Subspace Algorithms
- 2000
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- In this paper the effect of some weighting matrices on the asymptotic variance of the estimates of linear discrete time state space systems estimated using subspace methods is investigated. The analysis deals with systems with white or without observed inputs and refers to the Larimore type of subspace procedures. The main result expresses the asymptotic variance of the system matrix estimates in canonical form as a function of some of the user choices, clarifying the question on how to choose them optimally. It is shown, that the CCA weighting scheme leads to optimal accuracy. The expressions for the asymptotic variance can be implemented more efficiently as compared to the ones previously published.
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| 10. |
- Bauer, Dietmar, et al.
(författare)
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Subspace Algorithm Cointegration Analysis - an Application to Interest Rate Data
- 2000
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Ingår i: Proceedings of the 39th IEEE Conference on Decision and Control. - Linköping : Linköping University Electronic Press. - 0780366387 ; , s. 146-151
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Konferensbidrag (refereegranskat)abstract
- In this paper the application of so called subspace methods for the specication and estimation of cointegrated systems is examined. This method, which is based on the state space representation, is suited for the analysis of general cointegrated systems of order one, i.e. is not limited to autoregressive models, as is e.g. Johansen's method. To assess the empirical usefulness of the method we apply it to perform a cointegration analysis of the US term structure of interest rates.
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