157 citations · 589 across the 64 of their papers we have counts for
8 papers · 1 filter
Data-driven harmonic output regulation of a class of nonlinear systems
Zhongjie Hu, Claudio De Persis, John W. Simpson-Porco +1
The paper deals with the data-based design of state-feedback controllers that solve the output regulation problem for a class of nonlinear systems. Inspired by recent developments…
Data-driven input-to-state stabilization
Hailong Chen, Andrea Bisoffi, Claudio De Persis
For the class of nonlinear input-affine systems with polynomial dynamics, we consider the problem of designing an input-to-state stabilizing controller with respect to typical exog…
A Versatile Framework for Data-Driven Control of Nonlinear Systems
Nima Monshizadeh, Claudio De Persis, Pietro Tesi
This note aims to provide a systematic investigation of direct data-driven control, enriching the existing literature not by adding another isolated result, but rather by offering…
Setpoint control of bilinear systems from noisy data
Andrea Bisoffi, Dominiek M. Steeman, Claudio De Persis
We consider the problem of designing a controller for an unknown bilinear system using only noisy input-states data points generated by it. The controller should achieve regulation…
Convex Co-Design of Control Barrier Function and Safe Feedback Controller Under Input Constraints
Han Wang, Kostas Margellos, Antonis Papachristodoulou +1
We study the problem of co-designing control barrier functions (CBF) and linear state feedback controllers for continuous-time linear systems. We achieve this by means of a single…
Controller Synthesis from Noisy-Input Noisy-Output Data
Lidong Li, Andrea Bisoffi, Claudio De Persis +1
We consider the problem of synthesizing a dynamic output-feedback controller for a linear system, using solely input-output data corrupted by measurement noise. To handle input-out…
Controller synthesis for input-state data with measurement errors
Andrea Bisoffi, Lidong Li, Claudio De Persis +1
We consider the problem of designing a state-feedback controller for a linear system, based only on noisy input-state data. We focus on input-state data corrupted by measurement er…
Enforcing contraction via data
Zhongjie Hu, Claudio De Persis, Pietro Tesi
We present data-based conditions for enforcing contractivity via feedback control and obtain desired asymptotic properties of the closed-loop system. We focus on unknown nonlinear…