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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Windsor, J. Silverberg, L. Lee, G.K. |
| Copyright Year | 1994 |
| Description | Author affiliation: Mars Mission Res. Center, North Carolina State Univ., Raleigh, NC, USA (Windsor, J.; Silverberg, L.; Lee, G.K.) |
| Abstract | Control design of complex systems offer many challenges, particularly under system uncertainty. System identification, and in particular, parameter estimation is one of the crucial steps for many control strategies requiring a reasonable system model. Then the issue becomes one of selecting the parameter identifier in such a way that convergence can be obtained within a relatively fast period while the control is compensating under uncertainty. In this paper, a convergence rate analysis procedure is developed for multivariable parameter identification. The method allows the designer to select the appropriate initial conditions in order to satisfy a desired convergence rate through an error weighting matrix. Further, this paper develops an exact continuous-time solution in the recursive least squares problem and relates the results to the classical discrete-time case; time-scaling and traditional discrete recursive approaches are shown to be appropriate approximations to this continuous-time result. Finally, the parameter identifier procedure is applied to an example to illustrate the effects of selecting the initial auxiliary matrix to satisfy convergence and the effects of time-scaling on discrete-time and continuous time recursive least squares estimation. |
| Starting Page | 465 |
| Ending Page | 469 |
| File Size | 305865 |
| Page Count | 5 |
| File Format | |
| ISBN | 0780317831 |
| DOI | 10.1109/ACC.1994.751780 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1994-06-29 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Convergence Least squares approximation Parameter estimation Recursive estimation Least squares methods Mars Control design Uncertainty System identification Current measurement |
| Content Type | Text |
| Resource Type | Article |
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