Identification of MIMO LPV models based on interpolation

This paper presents SMILE (State-space Model Interpolation of Local Estimates), a new technique to estimate linear parameter varying state-space models for multiple-input multiple-output systems whose dynamics depends on a single varying parameter, called the scheduling parameter. The SMILE technique is based on the interpolation of linear time-invariant models that are valid for fixed operating conditions of the system, that is, for constant values of the scheduling parameters. The methodology yields affine LPV models that are numerically well-conditioned and therefore suitable for LPV control synthesis procedures. The underlying interpolation technique is formulated as a nonlinear least-squares optimization problem that can be efficiently solved by standard solvers. Application of the proposed methodology to a vibroacoustic setup, whose dynamics are highly sensitive to the ambient temperature, clearly demonstrates the potential of the SMILE technique.