State and Parameter Estimation Using Unscented Kalman Filter
| dc.contributor.author | Nortey, Andrew Yeboah | |
| dc.date.accessioned | 2014-01-09T10:13:55Z | |
| dc.date.accessioned | 2023-04-20T10:04:10Z | |
| dc.date.available | 2014-01-09T10:13:55Z | |
| dc.date.available | 2023-04-20T10:04:10Z | |
| dc.date.issued | 2012-12-09 | |
| dc.description | A thesis Submitted to Department of Mathematics in Partial Fulfillment of the Requirements for the Degree of Master of Philosophy College of Science.December,2012 | en_US |
| dc.description.abstract | The Extended Kalman Filter is a bayesian state estimation used for nonlinear models or systems. This filter may however fail to produce accurate results depending on the degree of nonlinearity of the system. The Unscented Kalman Filter on the other hand can be applied to highly nonlinear systems or models. Comparisons between the two filters are made using two systems. The first system is a four degrees of freedom shear building with time-varying system parameters and the second is a nonlinear hysteric damping system with unknown system parameters. The results indicated that the latter provides consistent as well as more accurate state and parameter estimates than the extended kalman filter for nonlinear systems. | en_US |
| dc.description.sponsorship | KNUST | en_US |
| dc.identifier.uri | https://ir.knust.edu.gh/handle/123456789/5482 | |
| dc.language.iso | en | en_US |
| dc.title | State and Parameter Estimation Using Unscented Kalman Filter | en_US |
| dc.type | Thesis | en_US |
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