Operator algebras and topology by Schick T.

By Schick T.

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In: Proceedings of the 2003 American Control Conference, Denver, USA (2003) 59. : Estimating vehicle velocities using linear-parameter-varying and gain varying scheduling theories. US Patent 6618651 (2003) 60. : LPV model identification for power management of web service systems. In: IEEE International Symposium on CACSD, San Antonio, USA (2008) 61. : Modeling and Identification of Linear Parameter-Varying Systems. LNCIS, vol. 403. Springer, Heidelberg (2010) 62. : Subspace identification of bilinear and LPV systems for open- and closed-loop data.

IEEE Transactions on Control Systems Technology 10(6), 883–887 (2002) 19. : LPV model identification for gain scheduling control: An application to rotating stall and surge control problem. Control Engineering Practice 14(4), 351–361 (2006) 20. : LPV control for a wafer stage: beyond the theoretical solution. Control Engineering Practice 13, 231–245 (2005) 21. : Workshop on "glocal control". In: IEEE Multi-Conference on Systems and Control, Yokohama, Japan (2010) 22. : LPV modelling and control of a 2-DOF robotic manipulator using PCA-based parameter set mapping.

Follows by duality, and can be stated as: Proposition 5. The subspace W ∗ is such that W ∗ ⊂ K , W ∗ is A -invariant and assuming that the parameters are c-excited, it is maximal with these properties. The set of all (A , B)-invariant subspaces contained in a given subspace K , is an upper semilattice with respect to subspace addition which admits a maximum that can be computed from the (A , B)-I nvariant S ubspace A lgorithm: N A BI S A : V0 = K , Vk+1 = K ∩ A−1 i (Vk + B). 26) i=0 The limit of this algorithm will be denoted by V ∗ and its calculation needs at most n steps.

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