Stabilization of bilinear power converters by affine state-feedback under input and state constraints

This brief presents a novel systematic procedure for the synthesis of affine state-feedback control laws for power converters. The proposed synthesis method is applicable to power converters with a bilinear averaged model and comes with a guarantee of closed-loop stability under hard state and input constraints. The low complexity of the resulting control law translates into a reduced cost of the control hardware, while nonconservative constraint handling yields a higher reliability of the power converter. Moreover, the incorporation of state constraints in controller synthesis can be exploited to achieve a higher power density for the converter. The effectiveness of the proposed controller synthesis method is illustrated on a buck-boost converter case study. Both simulation and real-time experimental results are reported.