Set-based state estimation of nonlinear systems using constrained zonotopes and interval arithmetic
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Universidade Federal de Minas Gerais
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This paper proposes a novel set-valued state estimation algorithm for nonlinear discrete-time systems with unknown-but-bounded disturbances. The problem is often addressed through conservative linearization, leading to severe overestimation. By combining important properties from interval arithmetic and the recently proposed constrained zonotopes, a highly tunable and accurate state estimation algorithm is developed, capable of providing tight bounds for the set-valued state estimation problem. A numerical experiment is presented to demonstrate the performance of the proposed strategy.
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Sistemas não lineares, Kalman, Filtragem de
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State estimation , Nonlinear systems , Trajectory , Discrete-time systems , Heuristic algorithms , Kalman filters, Nonlinear Systems , System State Estimation , Estimation For Nonlinear Systems , State Estimation Problem , Discrete-time Nonlinear Systems , State Estimation Algorithm , System State , Linear System , Class Of Systems , Kalman Filter , Variable Interval , Set Of Classes , Trajectories Of System , Arithmetic Operations , Stochastic Approach , Real-valued Function , Prediction Step , Correction Step , Class Of Nonlinear Systems , Fault Detection And Isolation , Convex Polytope , Minkowski Sum , Disturbance Processes , Reachable Set , Measures Of Disturbance
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https://ieeexplore.ieee.org/document/8550353