39 citations · 157 across the 35 of their papers we have counts for
20 papers · 1 filter
Data-Driven Superstabilizing Control under Quadratically-Bounded Errors-in-Variables Noise
Jared Miller, Tianyu Dai, Mario Sznaier
The Error-in-Variables model of system identification/control involves nontrivial input and measurement corruption of observed data, resulting in generically nonconvex optimization…
Unsafe Probabilities and Risk Contours for Stochastic Processes using Convex Optimization
Jared Miller, Matteo Tacchi, Didier Henrion +1
This paper proposes an algorithm to calculate the maximal probability of unsafety with respect to trajectories of a stochastic process and a hazard set. The unsafe probability esti…
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…
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…
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…
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…
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,…
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…
Quantifying the Safety of Trajectories using Peak-Minimizing Control
Jared Miller, Mario Sznaier
This work quantifies the safety of trajectories of a dynamical system by the perturbation intensity required to render a system unsafe (crash into the unsafe set). Computation of t…
Superstabilizing Control of Discrete-Time ARX Models under Error in Variables
Jared Miller, Tianyu Dai, Mario Sznaier
This paper applies a polynomial optimization based framework towards the superstabilizing control of an Autoregressive with Exogenous Input (ARX) model given noisy data observation…
Data-Driven Stabilizing and Robust Control of Discrete-Time Linear Systems with Error in Variables
Jared Miller, Tianyu Dai, Mario Sznaier
This work presents a sum-of-squares (SOS) based framework to perform data-driven stabilization and robust control tasks on discrete-time linear systems where the full-state observa…
Data-Driven Gain Scheduling Control of Linear Parameter-Varying Systems using Quadratic Matrix Inequalities
Jared Miller, Mario Sznaier
This paper synthesizes a gain-scheduled controller to stabilize all possible Linear Parameter-Varying (LPV) plants that are consistent with measured input/state data records. Inspi…
A Globally Convergent LP and SOCP-based algorithm for Semidefinite Programming
Biel Roig-Solvas, Mario Sznaier
Semidefinite programs (SDP) are one of the most versatile frameworks in numerical optimization, serving as generalizations of many conic programs and as relaxations of NP-hard comb…
Analysis and Control of Input-Affine Dynamical Systems using Infinite-Dimensional Robust Counterparts
Jared Miller, Mario Sznaier
Input-affine dynamical systems often arise in control and modeling scenarios, such as the data-driven case when state-derivative observations are recorded under bounded noise. Comm…
Bounding the Distance to Unsafe Sets with Convex Optimization
Jared Miller, Mario Sznaier
This work proposes an algorithm to bound the minimum distance between points on trajectories of a dynamical system and points on an unsafe set. Prior work on certifying safety of t…
Peak Estimation for Uncertain and Switched Systems
Jared Miller, Didier Henrion, Mario Sznaier +1
Peak estimation bounds extreme values of a function of state along trajectories of a dynamical system. This paper focuses on extending peak estimation to continuous and discrete se…
Euclidean Distance Bounds for LMI Analytic Centers using a Novel Bound on the Lambert Function
Biel Roig-Solvas, Mario Sznaier
Linear matrix inequalities (LMIs) are ubiquitous in modern control theory, as well as in a variety of other fields in science and engineering. Their analytic centers, i.e. the maxi…
Decomposed Structured Subsets for Semidefinite and Sum-of-Squares Optimization
Jared Miller, Yang Zheng, Mario Sznaier +1
Semidefinite programs (SDPs) are standard convex problems that are frequently found in control and optimization applications. Interior-point methods can solve SDPs in polynomial ti…
Chordal Decomposition in Rank Minimized Semidefinite Programs with Applications to Subspace Clustering
Jared Miller, Yang Zheng, Biel Roig-Solvas +2
Semidefinite programs (SDPs) often arise in relaxations of some NP-hard problems, and if the solution of the SDP obeys certain rank constraints, the relaxation will be tight. Decom…
Robust Anomaly Detection Using Semidefinite Programming
Jose A. Lopez, Octavia Camps, Mario Sznaier
This paper presents a new approach, based on polynomial optimization and the method of moments, to the problem of anomaly detection. The proposed technique only requires informatio…