Derivation of an optimal boundary layer width for the smooth variable structure filter
| dc.contributor.author | Gadsden SA | |
| dc.contributor.author | Sayed ME | |
| dc.contributor.author | Habibi SR | |
| dc.contributor.department | Mechanical Engineering | |
| dc.date.accessioned | 2025-02-27T19:33:58Z | |
| dc.date.available | 2025-02-27T19:33:58Z | |
| dc.date.issued | 2011-06-01 | |
| dc.date.updated | 2025-02-27T19:33:57Z | |
| dc.description.abstract | In this paper, an augmented form of the smooth variable structure filter (SVSF) is proposed. The SVSF is a state estimation strategy based on variable structure and sliding mode concepts. It uses a smoothing boundary to remove chattering (excessive switching along an estimated state trajectory). In its current form, the SVSF defines the boundary layer by an upper-bound on the uncertainties present in the estimation process (i.e., modeling errors, magnitude of noise, etc.). This is a conservative approach as one would be limiting the gain by assuming a larger smoothing boundary subspace than what is necessary. A more well-defined boundary layer will yield more accurate estimates. This paper derives a solution for an optimal boundary layer width by minimizing the trace of the a posteriori covariance matrix. The results of the derivation are simulated on a linear mechanical system for the purposes of control, and compared with the Kalman filter. © 2011 AACC American Automatic Control Council. | |
| dc.identifier.doi | https://doi.org/10.1109/acc.2011.5990970 | |
| dc.identifier.issn | 0743-1619 | |
| dc.identifier.issn | 2378-5861 | |
| dc.identifier.uri | http://hdl.handle.net/11375/31201 | |
| dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | |
| dc.subject | 4901 Applied Mathematics | |
| dc.subject | 40 Engineering | |
| dc.subject | 49 Mathematical Sciences | |
| dc.subject | 4001 Aerospace Engineering | |
| dc.title | Derivation of an optimal boundary layer width for the smooth variable structure filter | |
| dc.type | Article |
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