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An improved computationally efficient identification method for errors-in-variables models based on v-gap optimisation. (English) Zbl 1421.93037

Summary: A v-gap optimisation-based frequency-domain identification method is proposed to estimate a nominal normalised right graph symbol for errors-in-variables models. The proposed method follows the similar identification idea from a previous research work but with improved computational efficiency using interior-point (IP) algorithms. By imposing an inner function constraint instead of frequency point-wise constraints to normalise the graph symbol, the number of involved equality constraints for the v-gap optimisation is related to the nominal model order instead of the data length. As a consequence, the computational complexity of the proposed IP-based identification algorithm is much lower than that of linear matrix inequalities-based algorithms. Due to the fact that the data length is typically much larger than the finite nominal model order, the number of saved equality constraints is close to that of the employed data points. Finally, two numerical simulation examples are given to verify the proposed identification method.

MSC:

93B30 System identification
93C80 Frequency-response methods in control theory
68Q17 Computational difficulty of problems (lower bounds, completeness, difficulty of approximation, etc.)
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