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State estimation in the presence of bounded disturbances. (English) Zbl 1149.93340
Summary: This contribution proposes a robust recursive algorithm for the state estimation of linear models with unknown but bounded disturbances corrupting both the state and measurement vectors. A novel approach based on state bounding techniques is presented. The proposed algorithm can be decomposed into two steps: time updating and observation updating that uses a switching estimation Kalman-like gain matrix. Particular emphasis will be given to the design of a weighting factor that ensures the stability of the estimation error.

MSC:
93E10 Estimation and detection in stochastic control theory
93C73 Perturbations in control/observation systems
93E15 Stochastic stability in control theory
93D21 Adaptive or robust stabilization
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