most citedA Data-Driven Convex Programming Approach to Worst-Case Robust Tracking Controller Design

13 citations · 14 across the 4 of their papers we have counts for

collaborators

5 papers

math.OC2022

Safe Zeroth-Order Convex Optimization Using Quadratic Local Approximations

Baiwei Guo, Yuning Jiang, Maryam Kamgarpour +1

We address black-box convex optimization problems, where the objective and constraint functions are not explicitly known but can be sampled within the feasible set. The challenge i…

math.OC20211 cited

Actuator Placement for Structural Controllability beyond Strong Connectivity and towards Robustness

Baiwei Guo, Orcun Karaca, Sepide Azhdari +2

Actuator placement is a fundamental problem in control design for large-scale networks. In this paper, we study the problem of finding a set of actuator positions by minimizing a g…

eess.SY2021

A Behavioral Input-Output Parametrization of Control Policies with Suboptimality Guarantees

Luca Furieri, Baiwei Guo, Andrea Martin +1

Recent work in data-driven control has revived behavioral theory to perform a variety of complex control tasks, by directly plugging libraries of past input-output trajectories int…

math.OC202113 cited

A Data-Driven Convex Programming Approach to Worst-Case Robust Tracking Controller Design

Liang Xu, Mustafa Sahin Turan, Baiwei Guo +1

This paper studies finite-horizon robust tracking control for discrete-time linear systems, based on input-output data. We leverage behavioral theory to represent system trajectori…

math.OC2021

Non-conservative Design of Robust Tracking Controllers Based on Input-output Data

Liang Xu, Mustafa Sahin Turan, Baiwei Guo +1

This paper studies worst-case robust optimal tracking using noisy input-output data. We utilize behavioral system theory to represent system trajectories, while avoiding explicit s…