Abstract: In order to identify the time-varying parameters in linear system, the property that the time-varying parameters can be changed into time-invariant coefficient polynomials after Taylor expansion is used. The parameter identification method of time varying system is studied based on the time-varying auto regressive moving average (TV-ARMA) model established by using the response data from measured system. The time-invariant coefficients of the time-varying parameters are obtained by the least-square algorithm. The effect of input and output error on parameters identification as well as the amplification of algorithm to error are analyzed. According to error analysis, to reduce errors and improve efficiency and accuracy, the estimation time is divided into small intervals and the above method is used in each interval so as to be less error and more efficiency. The linear interpolation technique is used to solve discontinuity of time-varying parameters in margin of different interval, which improves the precision of identification. The fast varying, such as harmonic changing, parameters and the slow varying, such as linear changing, parameters are identified and analyzed by using the Matlab software and the appropriate segment length is given. Simulation results show that, under certain error condition, the identified time-varying parameters obtained by the method are in good agreement with the theoretical value, and the measures taken have strong anti-interference and high efficiency.

Key words: Identification, Input error, Output error, Taylor expansion, Time-varying parameter