IFT-LPV : data-based tuning of fixed structure controllers for LPV systems

S.T. Navalkar, T.A.E. Oomen, J.W. Wingerden, van

Research output: Contribution to journalConference articlepeer-review

1 Downloads (Pure)


Fixed structure controllers are widely used, however the tuning thereof can be cumbersome and gives no guarantee of optimality, especially when the system is Linear Parameter-Varying (LPV). Iterative Feedback Tuning (IFT) is a technique for the optimisation of a parameterised controller based on closed-loop experiments. This paper extends the applicability of IFT to LPV systems for the case where the LPV scheduling parameters are measurable but cannot be controlled. The closed-loop LPV system matrices are factorised such that the effect of the scheduling parameter on the IFT gradient estimates can be compensated. A suffcient number of IFT experiments are performed to estimate the cost gradient and tune the parameters. The method is validated successfully via a simulation study for a special case with an LPV system.
Original languageEnglish
Pages (from-to)721-726
Issue number28
Publication statusPublished - 2015
Event17th IFAC Symposium on System Identification (SYSID 2015) - Beijing International Convention Center, Beijing, China
Duration: 19 Oct 201521 Oct 2015
Conference number: 17


Dive into the research topics of 'IFT-LPV : data-based tuning of fixed structure controllers for LPV systems'. Together they form a unique fingerprint.

Cite this