Identification for gain-scheduling: a balanced subspace approach

Marco Lovera (1) , Guillaume Mercère (2)

1 Dipartimento di Elettronica e Informazione
2 LAII [Poitiers] - Laboratoire d'automatique et d'informatique industrielle [EA 1219]

The problem of deriving MIMO parameter-dependent models for gain-scheduling control design from data generated by {\em local} identification experiments is considered and a numerically sound approach is proposed, based on subspace identification ideas combined with the use of suitable properties of balanced state space realisations. Simulation examples are used to demonstrate the performance of the proposed approach.

Domaines: Automatique / Robotique

Marco Lovera, Guillaume Mercère. Identification for gain-scheduling: a balanced subspace approach. American Control Conference 2007, ACC'07, Jul 2007, New York, United States. pp.CDROM. ⟨hal-00164365⟩