Adjacent errors for assessing estimation and modeling algorithm performance

Some modeling errors of the RLS algorithm are defined. Inequalities among the variances of these errors are obtained. These inequalities show how the RLS algorithm behaves as it tracks process parameters. By simulation it is shown that virtually all algorithms like the RLS algorithm exhibit the same error behavior.

[1]  S. Bittanti,et al.  Deterministic convergence analysis of RLS estimators with different forgetting factors , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.

[2]  Yung-Chun Wu,et al.  Modified recursive least-squares algorithm for parameter identification , 1992 .

[3]  Richard M. Johnstone,et al.  Exponential convergence of recursive least squares with exponential forgetting factor , 1982, 1982 21st IEEE Conference on Decision and Control.

[4]  David D. Falconer,et al.  Tracking properties and steady-state performance of RLS adaptive filter algorithms , 1986, IEEE Trans. Acoust. Speech Signal Process..

[5]  N. Sinha,et al.  Robust recursive least-squares method with modified weights for bilinear system identification , 1989 .

[6]  S. Bittanti,et al.  Recursive least-squares identification algorithms with incomplete excitation: convergence analysis and application to adaptive control , 1990 .

[7]  T. R. Fortescue,et al.  Implementation of self-tuning regulators with variable forgetting factors , 1981, Autom..

[8]  Paolo Bolzern,et al.  Adaptive identification via prediction-error directional-forgetting factor: convergence analysis , 1989 .

[9]  Rudolf Kulhavý Directional Tracking of Regressiontype Model Parameters , 1987 .

[10]  J. Holst,et al.  Recursive forgetting algorithms , 1992 .

[11]  O. Malik,et al.  An Adaptive Synchronous Machine Stabilizer , 1986, IEEE Transactions on Power Systems.

[12]  Lennart Ljung,et al.  Adaptation and Tracking in System Identification , 1988 .

[13]  J. Norton,et al.  Estimation technique for tracking rapid parameter changes , 1987 .

[14]  David Q. Mayne,et al.  Deterministic convergence of a self-tuning regulator with variable forgetting factor , 1981 .

[15]  Paolo Bolzern,et al.  TRACKING OF NONSTATIONARY SYSTEMS BY MEANS OF DIFFERENT PREDICTION ERROR DIRECTION FORGETTING TECHNIQUES , 1987 .

[16]  Om P. Malik,et al.  An adaptive power system stabilizer based on the self-optimizing pole shifting control strategy , 1993 .

[17]  Lennart Ljung,et al.  Adaptation and tracking in system identification - A survey , 1990, Autom..

[18]  E. Eweda,et al.  Convergence of an adaptive linear estimation algorithm , 1984 .

[19]  Tore Hägglund,et al.  Adaptive Control of Systems Subject to Large Parameter Changes , 1984 .

[20]  S. Haykin,et al.  Adaptive Filter Theory , 1986 .

[21]  P. Barbini,et al.  Comparison of algorithms for tracking short-term changes in arterial circulation parameters , 1992, IEEE Transactions on Biomedical Engineering.

[22]  Bernard Widrow,et al.  Adaptive Signal Processing , 1985 .

[23]  Peter Andersson,et al.  Adaptive Forgetting in Recursive Identification through Multiple Models , 1985 .

[24]  Edward J. Powers,et al.  Time-varying spectral estimation using AR models with variable forgetting factors , 1991, IEEE Trans. Signal Process..

[25]  Tore Hägglund,et al.  The problem of forgetting old data in recursive estimation , 1983 .