The fuzzy Kalman filter: State estimation using possibilistic techniques

Matı́a, Fernando; Jiménez, Agustín; Al‐Hadithi, Basil Mohammed; Rodríguez-Losada, D.; Galán, Ramón

doi:10.1016/j.fss.2006.05.003

Cited by 44 publications

(38 citation statements)

References 22 publications

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“…Algorithm 1 [4,15], EKF(c), adjust only the consequents of a fuzzy model, keeping the antecedents in its initial value. This algorithm is the fastest because needs to do fewer calculations, but it doesn't adjust antecedents and this limits their ability to model complex systems.…”

Section: Application Of the Extended Kalmanmentioning

confidence: 99%

Application of the Extended Kalman filter to fuzzy modeling: Algorithms and practical implementation

Piña¹,

Andújar²,

Torres³

et al. 2011

Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011)

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Modeling phase is fundamental both in the analysis process of a dynamic system and the design of a control system. If this phase is in-line is even more critical and the only information of the system comes from input/output data. Some adaptation algorithms for fuzzy system based on extended Kalman filter are presented in this paper, which allows obtaining accurate models without renounce the computational efficiency that characterizes the Kalman filter, and allows its implementation in-line with the process.

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Section: Application Of the Extended Kalmanmentioning

confidence: 99%

Application of the Extended Kalman filter to fuzzy modeling: Algorithms and practical implementation

Piña¹,

Andújar²,

Torres³

et al. 2011

Proceedings of the 7th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT-2011)

View full text Add to dashboard Cite

show abstract

“…Gaussian distributions are generally the most frequently used ones [20,37]. Without reducing the generality of the modelling algorithm to be presented in the sequel, only these distribution types will be accepted and expressed as…”

Section: Modelling Algorithmmentioning

confidence: 99%

“…4. One may remark that the knowledge on system dynamics is a homogenous result because both elements in the vectors in (37) are obtained from the plausibility distribution of system behaviour viz. system output.…”

Section: Modelling Algorithmmentioning

confidence: 99%

New results in modelling derived from Bayesian filtering

Pozna

Precup

Tar

et al. 2010

Knowledge-Based Systems

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“…The notion of possibilistic correlation has been used in [87]- [92]. Mizukoshi et al [91] discussed the fuzzy differential equations obtained from a deterministic differential equation introducing an uncertainty coefficient and fuzzy initial condition.…”

Section: Examples Of Applicationmentioning

confidence: 99%