| 1. |
- Barenthin, Märta, et al.
(author)
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Validation of stability for an induction machine drive using power iterations
- 2005
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In: Proceedings of the 16th IFAC World Congress, 2005. - Prague. - 9783902661753 ; , s. 892-897
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Conference paper (peer-reviewed)abstract
- This work is an extension of the paper (Mosskull et al., 2003), in which the modelling, identification and stability of an nonlinear induction machine drive is studied. The validation of the stability margins of the system is refined by an improved estimate of the induced L2 loop gain of the system. This is done with a procedure called power iterations where input sequences suitable for estimating the gain are generated iteratively through experiments on the system. The power iterations result in higher gain estimates compared to the experiments previously presented. This implies that more accurate estimates are obtained as, in general, only lower bounds can be obtained as estimates for the gain. The new gain estimates are well below one, which suggests that the feedback system is stable. The experiments are performed on an industrial hardware/software simulation platform. in this paper we also discuss the power iterations from a more general point of view. The usefulness of the method for gain estimation of nonlinear systems is illustrated through simulation examples. The basic principles of the method are provided.
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| 2. |
- Eng, Frida, 1977-, et al.
(author)
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System Identification using Measurements Subject to Stochastic Time Jitter
- 2005
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In: Proceedings of the 16th IFAC World Congress. - 9783902661753 ; , s. 197-197
-
Conference paper (peer-reviewed)abstract
- When the sensors readings are perturbed by an unknown stochastic time jitter, classical system identification algorithms based on additive amplitude perturbations will give biased estimates. We here outline the maximum likelihood procedure, for the case of both time and amplitude noise, in the frequency domain, based on the measurement DFT. The method directly applies to output error continuous time models, while a simple sinusoid in noise example is used to illustrate the bias removal of the proposed method.
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| 3. |
- Enqvist, Martin, 1976-, et al.
(author)
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The CDIO Initiative from an Automatic Control Project Course Perspective
- 2005
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In: Proceedings of the 16th IFAC World Congress. - 9783902661753 ; , s. 2283-2283
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Conference paper (peer-reviewed)abstract
- The CDIO (Conceive Design Implement Operate) Initiative is explained, and some of the results at the Applied Physics and Electrical Engineering program at Linköping University, Sweden, are presented. A project course in Automatic Control is used as an example. The projects within the course are carried out using the LIPS (Linköping interactive project steering) model. An example of a project, the golf playing industrial robot, and the results from this project are also covered.
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| 4. |
- Fujimori, Atsushi, et al.
(author)
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A Gain Scheduling Control of Nonlinear Systems along a Reference Trajectory
- 2005
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In: Proceedings of the 16th IFAC World Congress. - 9783902661753 ; , s. 609-609
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Conference paper (peer-reviewed)abstract
- This paper presents a gain scheduling control of a nonlinear system in which the reference trajectory is given in advance. Multiple frozen operating times are chosen on the reference trajectory and a linear time invariant model is obtained at each operating time. A linear parameter varying model is then constructed by interpolating the region between the neighbor frozen operating times. A gain scheduling state feedback law is designed by a linear matrix inequality formulation. The effectiveness is demonstrated in a numerical simulation of a traing control of a two-link robot arm.
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| 5. |
- Gillberg, Jonas, et al.
(author)
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Frequency-Domain Identification of Continuous-Time ARMA Models from Sampled Data
- 2005
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In: Proceedings of 16th IFAC World Congress. - 9783902661753 ; , s. 37-37
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Conference paper (peer-reviewed)abstract
- This paper treats identification of continuous-time output error (OE) models based on sampled data. The exact method for doing this is well known both for data given in the time and frequency domains. This approach becomes some-what complex, especially for non-uniformly sampled data. We study various ways to approximate the exact method for reasonably fast sampling. While an objective is to gain insights into the non-uniform sampling case, this paper only gives explicit results for uniform sampling.
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| 6. |
- Glad, Torkel, 1947-, et al.
(author)
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Controllers for Amplitude Limited Model Error Models
- 2005
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In: Proceedings of the 16th IFAC World Congress. - Linköping : Linköping University Electronic Press. - 9783902661753 ; , s. 662-662
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Conference paper (peer-reviewed)abstract
- In this paper, systems where information about model accuracy is contained in a model error model are considered. The validity of such a model is typically restricted to input signals that are limited in amplitude. It is then natural to require the same amplitude restriction when designing controllers. The resulting implications for controller design are investigated in both the continuous and the discrete time case.
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| 7. |
- Gunnarsson, Svante
(author)
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On Identification of a Flexible Mechanical System using Decimated Data
- 2005
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In: Proceedings of the 16th IFAC World Congress. - 9783902661753 ; , s. 12-12
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Conference paper (peer-reviewed)abstract
- System identification of a flexible mechanical system using decimated data is studied. It is illustrated how the use of decimated data can give erroneous results due to the inter-sample behavior of the signals, and an intuitive explanation to this phenomenon is proposed. The possible improvement by using alternative assumptions for the inter-sample behavior is investigated.
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| 8. |
- Hendeby, Gustaf, 1978-, et al.
(author)
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Fundamental Filtering Limitations in Linear Non-Gaussian Systems
- 2005
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In: Proceedings of the 16th IFAC World Congress. - Linköping : Linköping University Electronic Press. - 9783902661753 ; , s. 45-45
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Conference paper (peer-reviewed)abstract
- The Kalman filter is known to be the optimal linear filter for linear non-Gaussian systems. However, nonlinear filters such as Kalman filter banks and more recent numerical methods such as the particle filter are sometimes superior in performance. Here a procedure to a priori decide how much can be gained using nonlinear filters, without having to resort to Monte Carlo simulations, is outlined. The procedure is derived in terms of the posterior Cramér-Rao lower bound. Results are shown for a class of standard distributions and models in practice.
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| 9. |
- Johansson, Jimmy, et al.
(author)
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Interactive Visualization as a Tool for Analysing Time-Varying and Non-Linear Systems
- 2005
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In: Proceedings of the 16th IFAC World Congress. - 9783902661753 ; , s. 95-95
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Conference paper (peer-reviewed)abstract
- This paper shows how 3-dimensional interactive visualization can be used as a tool in system identification. Non-linear or time-dependent dynamics often leave a significant residual with linear, time-invariant models. The structure of this residual is decisive for the subsequent modelling, and by using advanced visualization techniques, the modeller may gain a deeper insight into this structure than can be obtained by standard correlation analysis.
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| 10. |
- Karlsson, Rickard, 1970-, et al.
(author)
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Position Estimation and Modeling of a Flexible Industrial Robot
- 2005
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In: Proceedings of the 16th IFAC World Congress. - 9783902661753 ; , s. 1311-1311
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Conference paper (peer-reviewed)abstract
- A sensor fusion technique is presented and it is shown to achieve good estimates of the position for a 3 degrees-of-freedom industrial robot model. By using an accelerometer the estimate of the tool position accuracy can be improved. The computation of the position is formulated as a Bayesian estimation problem and two solutions are proposed. One using the extended Kalman filter and one using the particle filter. Since the aim is to use the positions estimates to improve trajectory tracking with an iterative learning control method, no computational constraints arise. In an extensive simulation study the performance is compared to the Cramér-Rao lower bound. A significant improvement in position accuracy is achieved using the sensor fusion technique.
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