IQC-based robust stability analysis for LPV control of doubly-fed induction generators

Abstract

Parameters of electrical machines are usually varying with time in a smooth way due to changing operating conditions, such as variations in the machine temperature and/or the magnetic saturation. This paper is concerned with robust stability analysis of controlled Doubly-Fed Induction Generators (DFIGs) that takes into account the time-varying nature of the parameter variations as well as bounds on their rate-of-variations. First, a self-scheduled Linear Parameter Varying (LPV) current controller design for the inner rotor-side loop is presented. The design is based on viewing the mechanical angular speed as an uncertain yet online measurable parameter and on subsuming the problem into the framework of LPV controller synthesis. Then the parameter-dependent model of the machine is transform into a Linear Fractional Representation, which allows to perform a stability analysis based on a specifically chosen set of Integral Quadratic Constraints (IQCs). Some simulation and analysis test results are given to demonstrate the robustness margins that result with this control algorithm. Index Terms-Doubly-fed induction generator (DFIG), linear parameter varying (LPV) systems, slowly time-varying parameter, robust stability, integral quadratic constraints (IQC).

Finite Horizon Worst-Case Analysis of Linear Time-Varying Systems Applied to Launch Vehicle

“…This timedomain formulation of IQCs is given in Section III-B. The time-domain approach allowed the extension to cover linear parameter varying [20], [21] or nonlinear polynomial systems [22] under perturbations. They provide sufficient conditions on worst case input/output gains based on a BRL-like condition.…”