The convergence of model-free adaptive control MFAC algorithm can be guaranteed when\r\nthe system is subject to measurement data dropout. The system output convergent speed gets\r\nslower as dropout rate increases. This paper proposes aMFAC algorithm with data compensation.\r\nThe missing data is first estimated using the dynamical linearization method, and then the\r\nestimated value is introduced to update control input. The convergence analysis of the proposed\r\nMFAC algorithm is given, and the effectiveness is also validated by simulations. It is shown that\r\nthe proposed algorithm can compensate the effect of the data dropout, and the better output\r\nperformance can be obtained.
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