Generalized uniform optimization for robust adaptive Buck converter with uncertain perturbations

Abstract

This paper presents an event-triggered impulse (ETI) control mechanism with generalized uniform optimization, endowing robust adaptive for various uncertain Buck converter perturbations. An impulse compensates for the state fluctuation error, and the event triggering mechanism (ETM) is introduced into the control process of the stochastic model of the Buck converter. The mean square stability theory of linear matrix inequality (LMI) stochastic systems is provided, wherein the cost function incorporates uncertain perturbation-induced state feedback impulses and adaptive system tuning. Unlike traditional event-triggered control with manually determined triggering times, ETI is activated only when events conform to the optimal design, significantly enhancing error-tracking accuracy and adaptive capability. Moreover, the parameters of the optimal controller remain independent of the statistical characteristics of uncertain noise, ensuring globally optimal operational control and model generality. Namely, the proposed method demonstrates versatility by extending its application to DC motor control, addressing various perturbations Buck converters encounter. Finally, the designed controller can closely track the required angular velocity trajectory across sudden changes in system uncertain perturbation.