Abstract
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.
Published Version
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