Linear parameter varying (LPV) controller synthesis is a systematic approach for designing gain-scheduled controllers. The advances in LPV controller synthesis have spurred the development of system identification techniques that deliver the required models. The aim of this paper is to present an accurate and fast frequency response function (FRF) identification methodology for LPV systems. A local parametric modeling approach is developed that exploits smoothness over frequencies and scheduling parameters. By exploiting the smoothness over frequency as well as over the scheduling parameters, increased time efficiency in experimentation time and accuracy of the FRF is obtained. Traditional approaches, i.e., the local polynomial method/local rational method, are recovered as a special case of the proposed approach. The application potential is illustrated by a simulation example as well as real-life experiments on a medical X-ray system.
- Local polynomial method
- non-parametric identification
- system identification