论文信息 - Choices of Prefilters and Forgetting Factors in Noise-Free Identification

Choices of Prefilters and Forgetting Factors in Noise-Free Identification

In this contribution we consider the situation where no disturbances act on the system to be identified, but where - as always - it is not possible to find a model structure that exactly accommodates the true systems. The transient and asymptotic properties of the obtained estimates in this situation are considered. Special attention is paid to the practical problem of obtaining good adaptation properties by appropriate choices of forgetting factor refilters.

L. Ljung

[1] L. Ljung. A non-probabilistic framework for signal spectra , 1985, 1985 24th IEEE Conference on Decision and Control.

[2] T. W. Parks,et al. Digital Filter Design , 1987 .

[3] Philip Parker,et al. Frequency domain descriptions of linear systems , 1988 .

[4] Yan Tang,et al. Adaptive Frequency Response Identification using the Lagrange Filter , 1990 .

[5] Michael Athans,et al. Some design guidelines for discrete-time adaptive controllers , 1984, Autom..

[6] L. Valavani,et al. A Frequency-Domain Estimator for Use in Adaptive Control Systems , 1987 .

[7] Robert Kosut. Adaptive calibration: An approach to uncertainty modeling and on-line robust control design , 1986, 1986 25th IEEE Conference on Decision and Control.

[8] R. Kosut. Adaptive Robust Control via Transfer Function Uncertainty Estimation , 1988, 1988 American Control Conference.

[9] Robert L. Kosut. Adaptive Uncertainty Modeling: On-Line Robust Control Design , 1987, 1987 American Control Conference.

[10] L. Ljung,et al. Asymptotic properties of black-box identification of transfer functions , 1985 .

[11] L. Ljung. System Identification in a Noise Free Environment , 1990 .

[12] Karl Johan Åström,et al. Practical issues in the implementation of self-tuning control , 1984, Autom..