Low-order parametric state-space modeling of MIMO systems in the Loewner framework. (English) Zbl 1530.93076
Summary: In this work, we present a novel data-driven method for identifying parametric MIMO generalized state-space or descriptor systems of low order that accurately capture the frequency and time domain behavior of large-scale linear dynamical systems. The low-order parametric descriptor systems are identified from transfer matrix samples by means of two-variable Lagrange rational matrix interpolation. This is done within the Loewner framework by deploying the new matrix-valued barycentric formula given in both right and left polynomial matrix fraction forms, which enables the construction of minimal parametric descriptor systems with rectangular transfer matrices. The developed method allows the reduction of order and parameter dependence complexity of the constructed system. Stability of the system is preserved by the postprocessing technique based on flipping signs of unstable poles. The developed methodology is illustrated with a few academic examples and applied to low-order parametric state-space identification of an aerodynamic system.
MSC:
| 93B30 | System identification |
| 93C35 | Multivariable systems, multidimensional control systems |
| 93A15 | Large-scale systems |
| 93B11 | System structure simplification |
Keywords:
system identification; model-order reduction; rational interpolation; Loewner matrix; parametric state-space realizationReferences:
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