4 papers · 1 filter
Simultaneous State Estimation and Online Model Learning in a Soft Robotic System
Jan-Hendrik Ewering, Max Bartholdt, Simon F. G. Ehlers +3
Operating complex real-world systems, such as soft robots, can benefit from precise predictive control schemes that require accurate state and model knowledge. This knowledge is ty…
Accounts of using the Tustin-Net architecture on a rotary inverted pendulum
Stijn van Esch, Fabio Bonassi, Thomas B. Schön
In this report we investigate the use of the Tustin neural network architecture (Tustin-Net) for the identification of a physical rotary inverse pendulum. This physics-based archit…
On the equivalence of direct and indirect data-driven predictive control approaches
Per Mattsson, Fabio Bonassi, Valentina Breschi +1
Recently, several direct Data-Driven Predictive Control (DDPC) methods have been proposed, advocating the possibility of designing predictive controllers from historical input-outp…
Structured state-space models are deep Wiener models
Fabio Bonassi, Carl Andersson, Per Mattsson +1
The goal of this paper is to provide a system identification-friendly introduction to the Structured State-space Models (SSMs). These models have become recently popular in the mac…