activity
20192025
most citedData-Driven Gain Scheduling Control of Linear Parameter-Varying Systems using Quadratic Matrix Inequalities

39 citations · 110 across the 21 of their papers we have counts for

collaborators
Showing 2023Show all

7 papers · 1 filter

math.OC2023

Data-Driven Superstabilization of Linear Systems under Quantization

Jared Miller, Jian Zheng, Mario Sznaier +1

This paper focuses on the stabilization and regulation of linear systems affected by quantization in state-transition data and actuated input. The observed data are composed of tup…

math.OC2023★ 1 cited

Peak Estimation of Time Delay Systems using Occupation Measures

Jared Miller, Milan Korda, Victor Magron +1

This work proposes a method to compute the maximum value obtained by a state function along trajectories of a Delay Differential Equation (DDE). An example of this task is finding…

math.OC2023

Data-Driven Control of Positive Linear Systems using Linear Programming

Jared Miller, Tianyu Dai, Mario Sznaier +1

This paper presents a linear-programming based algorithm to perform data-driven stabilizing control of linear positive systems. A set of state-input-transition observations is coll…

math.OC2023★ 2 cited

Peak Estimation of Hybrid Systems with Convex Optimization

Jared Miller, Mario Sznaier

Peak estimation of hybrid systems aims to upper bound extreme values of a state function along trajectories, where this state function could be different in each subsystem. This fi…

math.OC2023

Robust Data-Driven Safe Control using Density Functions

Jian Zheng, Tianyu Dai, Jared Miller +1

This paper presents a tractable framework for data-driven synthesis of robustly safe control laws. Given noisy experimental data and some priors about the structure of the system,…

math.OC2023

Peak Value-at-Risk Estimation of Stochastic Processes using Occupation Measures

Jared Miller, Matteo Tacchi, Mario Sznaier +1

This paper formulates algorithms to upper-bound the maximum Value-at-Risk (VaR) of a state function along trajectories of stochastic processes. The VaR is upper bounded by two meth…