Free Online Productivity Tools
i2Speak
i2Symbol
i2OCR
iTex2Img
iWeb2Print
iWeb2Shot
i2Type
iPdf2Split
iPdf2Merge
i2Bopomofo
i2Arabic
i2Style
i2Image
i2PDF
iLatex2Rtf
Sci2ools

AUTOMATICA

2007

2007

This paper deals with state estimation problem for linear systems with state equality constraints. Using noisy measurements which are available from the observable system, we construct the optimal estimate which also satisﬁes linear equality constraints. For this purpose, after reviewing modeling problems in linear stochastic systems with state equality constraints, we formulate a projected system representation from a descriptor system form. By using the constrained Kalman ﬁlter for the projected system and comparing its ﬁlter Riccati Equation with those of the unconstrained and the projected Kalman ﬁlters, we reach the conclusion that the current constrained estimator outperforms other ﬁlters for estimating the constrained system. We extend the same procedures from discrete-time to the continuous-time case. Finally, a numerical example is presented, which demonstrates performance diﬀerences among those ﬁlters. Key words: Estimation; Constraints; Kalman ﬁlters; Projec...

Related Content

Added |
17 Dec 2010 |

Updated |
17 Dec 2010 |

Type |
Journal |

Year |
2007 |

Where |
AUTOMATICA |

Authors |
Sangho Ko, Robert R. Bitmead |

Comments (0)