Published July 2007
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Estimation for Nonlinear Dynamical Systems over Packet-Dropping Networks
- Creators
- Jin, Zhipu
- Ko, Chih-Kai
-
Murray, Richard M.
Chicago
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Abstract
Two approaches, extended Kalman filter (EKF) and moving horizon estimation (MHE), are discussed for state estimation for nonlinear dynamical systems over packet-dropping networks. For EKF, we provide sufficient conditions that guarantee a bounded EKF error covariance. For MHE, a natural scheme on organizing the finite horizon window is proposed to handle intermittent observations. A nonlinear programming software package, SNOPT, is employed in MHE and the formulation for constraints is discussed in detail. Examples and simulation results are presented.
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© 2007 IEEE.Attached Files
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- 77019
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- CaltechAUTHORS:20170427-143640907
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