On the impact of regularization in data-driven predictive control
Model predictive control (MPC) is a control strategy widely used in industrial applications.
However, its implementation typically requires a mathematical model of the system being …
However, its implementation typically requires a mathematical model of the system being …
Data-based control design for output-error linear discrete-time systems with probabilistic stability guarantees
In this letter we propose a novel method for direct data-based design of an output feedback
controller for output-error processes in the single-input-single-output case. We consider a …
controller for output-error processes in the single-input-single-output case. We consider a …
A practitioner's guide to noise handling strategies in data-driven predictive control
Today's increasing availability of data is having a remarkable impact on control design.
However, for data-driven control approaches to become widespread in practical …
However, for data-driven control approaches to become widespread in practical …
Closed-loop Data-Enabled Predictive Control and its equivalence with Closed-loop Subspace Predictive Control
Factors like improved data availability and increasing system complexity have sparked
interest in data-driven predictive control (DDPC) methods like Data-enabled Predictive …
interest in data-driven predictive control (DDPC) methods like Data-enabled Predictive …