H∞ control is an effective approach to handle model uncertainties. However, when modeling mismatchis large, it tends to be challenging to meet the desired requirements of both stability and performance by only usinga single H∞ controller. This study presents a switching method to enhance the robust stability and performanceof H∞ control by dividing the range of dynamics into multiple uncertain models. The candidate robust controllersare designed by solving a set of linear matrix inequalities for each uncertain model. A structural scheduling logicthat selects the most proper controller into closed-loop is proposed. The selected controller can ensure boundedexponentially weighted H∞ norm of the closed-loop switching systems. This work analyses their robust stabilityand disturbance attenuation performance via a linear fractional transformation by using the small gain theorem. Theeffectiveness of this method is validated with a fist-order inertial system with pure time delay.
H∞ control is an effective approach to handle model uncertainties. However, when modeling mismatchis large, it tends to be challenging to meet the desired requirements of both stability and performance by only usinga single H∞ controller. This study presents a switching method to enhance the robust stability and performanceof H∞ control by dividing the range of dynamics into multiple uncertain models. The candidate robust controllersare designed by solving a set of linear matrix inequalities for each uncertain model. A structural scheduling logicthat selects the most proper controller into closed-loop is proposed. The selected controller can ensure boundedexponentially weighted H∞ norm of the closed-loop switching systems. This work analyses their robust stabilityand disturbance attenuation performance via a linear fractional transformation by using the small gain theorem. Theeffectiveness of this method is validated with a fist-order inertial system with pure time delay.