Norm- and linear-inequality-constrained state estimation: An LMI approach

Published

Conference Paper

© 2017 IEEE. This paper proposes a method for state estimation that incorporates norm- and linear-inequality constraints using Linear Matrix Inequalities (LMIs). This is accomplished by adopting a prediction-correction filter form and calculating the observer gain matrix by solving a convex optimization problem with LMI constraints where the state constraints are expressed as LMIs. The state constraints considered in this study include norm and linear inequalities. Simulation results are included to assess the performance of the proposed filter in a scenario involving a mobile robot moving within a constrained area taking range and bearing measurements of known landmarks. The filter's performance is compared with a traditional EKF.

Full Text

Duke Authors

Cited Authors

  • Chee, SA; Bridgeman, L; Forbes, JR

Published Date

  • October 6, 2017

Published In

  • 1st Annual Ieee Conference on Control Technology and Applications, Ccta 2017

Volume / Issue

  • 2017-January /

Start / End Page

  • 1356 - 1361

International Standard Book Number 13 (ISBN-13)

  • 9781509021826

Digital Object Identifier (DOI)

  • 10.1109/CCTA.2017.8062647

Citation Source

  • Scopus