Equality-constrained state estimation for hybrid systems

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dc.creatorWendy Y. Eras Herrera
dc.creatorAlexandre Rodrigues Mesquita
dc.creatorBruno O. S. Teixeira
dc.date.accessioned2025-05-15T13:39:58Z
dc.date.accessioned2025-09-09T00:03:19Z
dc.date.available2025-05-15T13:39:58Z
dc.date.issued2019
dc.identifier.doihttps://doi.org/10.1049/iet-cta.2018.6374
dc.identifier.issn17518644
dc.identifier.urihttps://hdl.handle.net/1843/82293
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofIET Control Theory & Applications
dc.rightsAcesso Restrito
dc.subjectKalman, Filtragem de
dc.subjectSistemas dinâmicos diferenciais
dc.subject.otherThe Kalman filter (KF) provides optimal state estimates for linear and Gaussian systems. However, additional information about the system in the form of state constraints may be useful for improving the state estimates. Many applications, dynamical systems satisfy constraints that arise from physical laws, mathematical properties or geometric considerations. One example is the task of tracking a ground vehicle whose velocity is constrained by road orientation.
dc.titleEquality-constrained state estimation for hybrid systems
dc.typeArtigo de periódico
local.citation.epage2028
local.citation.spage2018
local.citation.volume13
local.description.resumoThe authors investigate the problem of state estimation for stochastic hybrid dynamical systems with state equality constraints. They divided this problem into three categories depending on the linearity or non-linearity of equality constraints as well as on the dependence of constraints on the operating mode. For the mode-independent equality-constrained linear case, they present sufficient conditions on process dynamics and filter initial conditions so that the classical interacting multiple model (IMM) algorithm yields state estimates satisfying the linear equality constraint for all subsequent times. For both linear and non-linear systems, the mode-dependent equality constraints must be enforced over time by the filter. They present a modified version of the IMM filter to enforce the equality constraints in such cases. Their numerical results show that the proposed methods provide more accurate estimates than the IMM unconstrained estimates.
local.publisher.countryBrasil
local.publisher.departmentENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA
local.publisher.initialsUFMG
local.url.externahttps://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-cta.2018.6374

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