Bibliography

Conference Paper (international conference)

Bayesian State Estimation Using Constrained Zonotopes

: Proceedings of the 20th International Conference on Informatics in Control, Automation and Robotics (ICINCO), p. 189-194 , Eds: Gini Giuseppina, Nijmeijer Henk, Filev Dimitar

: International Conference on Informatics in Control, Automation and Robotics 2023 (ICINCO 2023) /20./, (Řím, IT, 20231113)

: GC23-04676J, GA ČR

: stochastic systems, recursive state estimation, bounded noise, constrained zonotope, state-space model, linear system, approximate estimation

: 10.5220/0012230900003543

: http://library.utia.cas.cz/separaty/2023/AS/kuklisova-0578233.pdf

(eng): This paper proposes an approximate Bayesian recursive algorithm for the state estimation of a linear discrete-time stochastic state-space model. The involved state and observation noises are assumed to be bounded and uniformly distributed. The support of a posterior probability density function (pdf) is approximated by a constrained zonotope of an adjustable complexity. The behaviour of the proposed algorithm is illustrated by simulations and compared with other methods.

: BC

: 20205