Induced L2-norm control for LPV systems with bounded parameter variation rates

TLDR: This work uses a bounding technique based on a parameter-dependent Lyapunov function, and then solves the control synthesis problem by reformulating the existence conditions into a semi-infinite dimensional convex optimization.

Abstract: A linear, finite-dimensional plant, with state-space parameter dependence, is controlled using a parameter-dependent controller. The parameters whose values are in a compact set, are known in real time. Their rates of variation are bounded and known in real time also. The goal of control is to stabilize the parameter-dependent closed-loop system, and provide disturbance/error attenuation as measured in induced L2 norm. Our approach uses a bounding technique based on a parameter-dependent Lyapunov function, and then solves the control synthesis problem by reformulating the existence conditions into a semi-infinite dimensional convex optimization. We propose finite dimensional approximations to get sufficient conditions for successful controller design.