Webinar

Abstract:

Tracking of time-varying output signals with a pre-defined maximal allowed error is challenging. A control strategy successfully solving this task for a comparatively large system class is funnel control, a high-gain output feedback. In this talk, we propose a novel Model Predictive Control (MPC) scheme using funnel-inspired stage costs. This MPC scheme yields improved performance w.r.t. tracking accuracy, requirements on the sampling rate, and control effort. Moreover, we establish initial and recursive feasibility without stabilizing terminal ingredients and independently of the length of the prediction horizon. Finally, we briefly indicate potential extensions towards learning.