0492001 20240103220315.520180807235959.9 85071589401 10.5220/0006933803880394 Approximate recursive Bayesian estimation of state space model with uniform noise 7 s. C cav_un_epca*0491939978-989-758-321-62184-2809ICINCO 2018 : Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics388-394SetubalINSTICC, SCITEPRESS.2018MadaniKuroshGusikhinOleg probabilistic state-space model approximate state estimation linear systems bounded noise Bayesian estimation cav_un_auth*0101175 Department of Adaptive Systems Pavelková Lenka UTIA-B Adaptivní systémy Department of Adaptive Systems AS AS Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101119 Jirsa Ladislav UTIA-B Adaptivní systémy Department of Adaptive Systems AS AS Department of Adaptive Systems Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2018/AS/pavelkova-0492001.pdf cav_un_auth*0362986 GA18-15970S GA ČR CZ This paper proposes a recursive algorithm for the state estimation of a linear stochastic state space model. A model with discrete-time inputs, outputs and states is considered. The model matrices are supposed to be known. A noise of the involved model is described by a uniform distribution. The states are estimated using Bayesian approach. Without using an approximation, the complexity of the posterior probability density function (pdf) increases with time. The paper proposes an approximation of this complex pdf so that a feasible support of the posterior pdf is kept during the estimation. The state estimation consists of two stages, namely the time and data update including the mentioned approximation. The behaviour of the proposed algorithm is illustrated by simulations and compared with other methods. cav_un_auth*0362881 15th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2018) 20180729 20180731 Porto PT BC 20000 20200 20205 2019 2 PR RVO:67985556 http://hdl.handle.net/11104/0285675 S 2018 85071589401 SCOPUS PUBMED WOS cav_un_epca*0491939 ICINCO 2018 : Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics INSTICC, SCITEPRESS. 2018 Setubal 388 394 978-989-758-321-6 2184-2809 340 Madani Kurosh 340 Gusikhin Oleg