Abstract: Existing system parameter identification methods are primarily based on the input-output data which are fully available.However,owing to the sensor failure or network transmission mechanism failure in the actual system,data dropout phenomenon often occurres.For system identification problem of a class of linear systems under the condition of input or output data dropout,the data dropout phenomenon is described as a Bernoulli random sequence.And a new algorithm was presented to estimate the parameters with data dropout.Finally,a numerical example validates the effectiveness of the proposed algorithm.The results show that the proposed algorithm has a better convergence than recursive least squares method.

Key words: System identification,Bernoulli random sequence,Least-square algorithm,Data dropout