Search Results for author: Andrea Bisoffi

Found 10 papers, 1 papers with code

Setpoint control of bilinear systems from noisy data

no code implementations4 Apr 2024 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.

Controller synthesis for input-state data with measurement errors

no code implementations6 Feb 2024 Andrea Bisoffi, Lidong Li, Claudio De Persis, Nima Monshizadeh

We consider the problem of designing a state-feedback controller for a linear system, based only on noisy input-state data.

Controller Synthesis from Noisy-Input Noisy-Output Data

1 code implementation4 Feb 2024 Lidong Li, Andrea Bisoffi, Claudio De Persis, Nima Monshizadeh

We consider the problem of synthesizing a dynamic output-feedback controller for a linear system, using solely input-output data corrupted by measurement noise.

Data-driven input-to-state stabilization with respect to measurement errors

no code implementations16 Sep 2023 Hailong Chen, Andrea Bisoffi, Claudio De Persis

We consider noisy input/state data collected from an experiment on a polynomial input-affine nonlinear system.

Data-driven design of safe control for polynomial systems

no code implementations23 Dec 2021 Alessandro Luppi, Andrea Bisoffi, Claudio De Persis, Pietro Tesi

We consider the problem of designing an invariant set using only a finite set of input-state data collected from an unknown polynomial system in continuous time.

Learning controllers for performance through LMI regions

no code implementations20 Oct 2021 Andrea Bisoffi, Claudio De Persis, Pietro Tesi

For this control design problem, we provide here convex programs to enforce the performance specification from data in the form of linear matrix inequalities (LMI).

Data-driven control via Petersen's lemma

no code implementations24 Sep 2021 Andrea Bisoffi, Claudio De Persis, Pietro Tesi

In the cases of data generated by linear and polynomial systems, we conveniently express the uncertainty captured in the set of data-consistent dynamics through a matrix ellipsoid, and we show that a specific form of this matrix ellipsoid makes it possible to apply Petersen's lemma to all of the mentioned cases.

LEMMA

Trade-offs in learning controllers from noisy data

no code implementations15 Mar 2021 Andrea Bisoffi, Claudio De Persis, Pietro Tesi

Specifically, the feasible set of the latter design problem is always larger, and the set of system matrices consistent with data is always smaller and decreases significantly with the number of data points.

A hybrid barrier certificate approach to satisfy linear temporal logic specifications

no code implementations23 Nov 2020 Andrea Bisoffi, Dimos V. Dimarogonas

In order to solve this problem, we introduce an extension to such a hybrid system framework of the so-called eventuality property, which matches suitably the condition for the satisfaction of such a temporal logic specification.

Satisfaction of linear temporal logic specifications through recurrence tools for hybrid systems

no code implementations13 Nov 2020 Andrea Bisoffi, Dimos V. Dimarogonas

In this work we formulate the problem of satisfying a linear temporal logic formula on a linear plant with output feedback, through a recent hybrid systems formalism.

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