22 citations · 79 across the 13 of their papers we have counts for
13 papers
Data-Driven Robust Control Using Prediction Error Bounds Based on Perturbation Analysis
Baiwei Guo, Yuning Jiang, Colin N. Jones +1
For linear systems, many data-driven control methods rely on the behavioral framework, using historical data of the system to predict the future trajectories. However, measurement…
Safe Zeroth-Order Optimization Using Linear Programs
Baiwei Guo, Yang Wang, Yuning Jiang +2
To solve unmodeled optimization problems with hard constraints, this paper proposes a novel zeroth-order approach called Safe Zeroth-order Optimization using Linear Programs (SZO-L…
Safe Zeroth-Order Optimization Using Quadratic Local Approximations
Baiwei Guo, Yuning Jiang, Giancarlo Ferrari-Trecate +1
This paper addresses black-box smooth optimization problems, where the objective and constraint functions are not explicitly known but can be queried. The main goal of this work is…
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…
Near-Optimal Design of Safe Output Feedback Controllers from Noisy Data
Luca Furieri, Baiwei Guo, Andrea Martin +1
As we transition towards the deployment of data-driven controllers for black-box cyberphysical systems, complying with hard safety constraints becomes a primary concern. Two key as…
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…
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…
Finite-sample-based Spectral Radius Estimation and Stabilizability Test for Networked Control Systems
Liang Xu, Baiwei Guo, Giancarlo Ferrari-Trecate
In the analysis and control of discrete-time linear time-invariant systems, the spectral radius of the system state matrix plays an essential role. Usually, it is assumed that syst…
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…
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…
A comment on "Performance guarantees of a greedy algorithm for minimizing a supermodular set function on comatroid"
Orcun Karaca, Baiwei Guo, Maryam Kamgarpour
We provide a counterexample to the performance guarantee obtained in the paper "Performance guarantees of a greedy algorithm for minimizing a supermodular set function on comatroid…
Actuator Placement under Structural Controllability using Forward and Reverse Greedy Algorithms
Baiwei Guo, Orcun Karaca, Tyler Summers +1
Actuator placement is an active field of research which has received significant attention for its applications in complex dynamical networks. In this paper, we study the problem o…
Actuator Placement for Optimizing Network Performance under Controllability Constraints
Baiwei Guo, Orcun Karaca, Tyler Summers +1
With the rising importance of large-scale network control, the problem of actuator placement has received increasing attention. Our goal in this paper is to find a set of actuators…