1 citations · 2 across the 5 of their papers we have counts for
5 papers
Learning neural controllers for nonlinear systems from data
Zhongjie Hu, Zhi-Wei Liu, Chen Wang
This article addresses the problem of designing neural feedback controllers for unknown nonlinear systems. We propose an indirect data-driven framework that uses offline data to id…
Output regulation via input-output data
Andrea Bisoffi, Wenjie Liu, Zhongjie Hu +1
From a multi-input-multi-output (MIMO) discrete-time linear system, we collect input-output data affected by noise in the form of an unknown exosignal and, from these data points (…
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…
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…
Learning controllers from data via kernel-based interpolation
Zhongjie Hu, Claudio De Persis, Pietro Tesi
We propose a data-driven control design method for nonlinear systems that builds on kernel-based interpolation. Under some assumptions on the system dynamics, kernel-based function…