A class of interacting multiple model (IMM) estimators are regarded as one kind of instrumental tool to estimate the state of jump Markov systems, in which the overall estimate only can be considered as output. In this paper, the overall estimate is used to design output reference learning terms in the IMM estimator and they are utilized to update the mode-conditioned estimates recursively. Finally, simulations are presented to testify the validity of proposed estimator.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Interacting Multiple Model Estimator with Output Reference Learning


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Yan, Liang (editor) / Duan, Haibin (editor) / Yu, Xiang (editor) / Li, Wenling (author)


    Publication date :

    2021-10-30


    Size :

    11 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Enhanced accuracy GPS navigation using the interacting multiple model estimator

    Xiangdong Lin, / Kirubarajan, T. / Bar-Shalom, Y. et al. | IEEE | 2001


    Adaptation of the kinematic train model using the Interacting Multiple Model estimator

    Bohringer, F. / Geistler, A. | British Library Conference Proceedings | 2004




    WHEEL REFERENCE BALANCE ESTIMATOR

    GEORGIN MARC | European Patent Office | 2022

    Free access