Describing nonlinear dynamic systems by linear parameter-varying models has become an attractive tool for control of complex systems with regimedependent (linear) behavior. For the identification of LPV models from experimental data a number of methods has been presented in the literature but a full picture of the underlying identification problem is still missing. In this contribution a solid system theoretic basis for the description of model structures for LPV models is presented, together with a general approach to the LPV identification problem. Use is made of a series expansion approach to LPV modeling, employing orthogonal basis function expansions.
|Title of host publication||Proceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday|
|Editors||K.M. Hangos, L. Nádai|
|Place of Publication||Budapest|
|Publication status||Published - 2009|
Hof, Van den, P. M. J., Toth, R., & Heuberger, P. S. C. (2009). Model structures for identification of linear parameter-varying (LPV) models. In K. M. Hangos, & L. Nádai (Eds.), Proceedings of the Workshop on Systems and Control Theory in honor of József Bokor on his 60th Birthday (pp. 15-34). Budapest: MTA.