Parametric Robust Generalized Minimum Variance Control

This work presents a hybridization of the Generalized Minimum Variance control (GMVC) with Parametric Robust Control (RPC) for Linear Time Invariant (LTI) Uncertain Systems. A linear parametric uncertainties model is used to describe system dynamic behavior. The controller synthesis based on PID low-pass filter and formulated as convex optimization problem which takes in account desired closed-loop performance parameters. Then, robust parameters, that represent best solution all possible models assign poles within region s-plane, are transferred GMVC by Tustin’s method, resulting generalized minimum variance (PRGMV) controller, was compared two other approaches, carrying out several simulation essays Matlab environment. In order emphasize its performances efficiency, index sensitivity analysis were assessed. results confirmed proposed ensures better robustness reference tracking disturbance rejection.