Parameters Identification for Quantized Control Systems Based on Stochastic Test

This paper studies identification of quantized control systems subjected to communication constraints. An auxiliary model based identification method for quantized systems is introduced by employing repeated stochastic empirical measurements. The system features and two-step identification strategies are first presented. It is shown that the quantized system based on repeated stochastic empirical measurements involves time-varying estimation error, and the persistent exciting condition for parameter identification is derived. The auxiliary model based quantized multi-innovation recursive algorithm for quantized systems is also given then. Convergence analysis of the auxiliary model based algorithm provides an upper bound computation way for parameter identification error estimation. It is demonstrated that under some certain conditions, recursive algorithm is consistently convergence. Last, the simulation results show the correctness of the conclusions.