In this paper, under the weak assumptions such as only the step changes of system set points being the exciting signal, unknown structures and the dynamic parameters, approximate linear dynamic model and the least squ...
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In this paper, under the weak assumptions such as only the step changes of system set points being the exciting signal, unknown structures and the dynamic parameters, approximate linear dynamic model and the least squares estimation method, for the linear slow time-varying large-scale system, the steady-state gain estimate of the system is formed from the estimates of the parameters and a parallel identification algorithm is put forward. The consistency of the estimate and the convergence of the parallel iteration are analyzed. Based on this consistency theorem, a pragmatic method to get the strony consistent estimate of the steady-state model of the large-scale system is presented. Simulation study has already proved this.
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