activity
20122023
most citedAnalysis and Design of Optimization Algorithms via Integral Quadratic Constraints

383 citations · 773 across the 39 of their papers we have counts for

collaborators

47 papers

math.OC2023

A Tutorial on the Structure of Distributed Optimization Algorithms

Bryan Van Scoy, Laurent Lessard

We consider the distributed optimization problem for a multi-agent system. Here, multiple agents cooperatively optimize an objective by sharing information through a communication…

math.OC2023

A Tutorial on a Lyapunov-Based Approach to the Analysis of Iterative Optimization Algorithms

Bryan Van Scoy, Laurent Lessard

Iterative gradient-based optimization algorithms are widely used to solve difficult or large-scale optimization problems. There are many algorithms to choose from, such as gradient…

math.OC2023

Automated Lyapunov Analysis of Primal-Dual Optimization Algorithms: An Interpolation Approach

Bryan Van Scoy, John W. Simpson-Porco, Laurent Lessard

Primal-dual algorithms are frequently used for iteratively solving large-scale convex optimization problems. The analysis of such algorithms is usually done on a case-by-case basis…

eess.SY2023

Guaranteed Stability Margins for Decentralized Linear Quadratic Regulators

Mruganka Kashyap, Laurent Lessard

It is well-known that linear quadratic regulators (LQR) enjoy guaranteed stability margins, whereas linear quadratic Gaussian regulators (LQG) do not. In this letter, we consider s…

math.OC2022

Absolute Stability via Lifting and Interpolation

Bryan Van Scoy, Laurent Lessard

We revisit the classical problem of absolute stability; assessing the robust stability of a given linear time-invariant (LTI) plant in feedback with a nonlinearity belonging to som…

math.OC2022

Optimal Control of Multi-Agent Systems with Processing Delays

Mruganka Kashyap, Laurent Lessard

In this article, we consider a cooperative control problem involving a heterogeneous network of dynamically decoupled continuous-time linear plants. The (output-feedback) controlle…