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Identification of multi-input systems based on correlation techniques. (English) Zbl 1209.93039

Summary: This article proposes a correlation analysis-based identification method for multi-input single-output systems. The basic idea is to estimate the equivalent FIR model parameters with the orders increasing, and to compute the parameter estimates of the original systems (i.e. each fictitious subsystem) using the system inputs and the outputs of the estimated FIR models as the least squares optimisation. Simulation results indicate that the proposed algorithm can work well.

MSC:

93B30 System identification
93C35 Multivariable systems, multidimensional control systems
93E10 Estimation and detection in stochastic control theory
93E24 Least squares and related methods for stochastic control systems
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