3 citations · 9 across the 7 of their papers we have counts for
6 papers · 1 filter
Wasserstein distributionally robust risk-constrained iterative MPC for motion planning: computationally efficient approximations
Alireza Zolanvari, Ashish Cherukuri
This paper considers a risk-constrained motion planning problem and aims to find the solution combining the concepts of iterative model predictive control (MPC) and data-driven dis…
Iterative risk-constrained model predictive control: A data-driven distributionally robust approach
Alireza Zolanvari, Ashish Cherukuri
This paper proposes an iterative distributionally robust model predictive control (MPC) scheme to solve a risk-constrained infinite-horizon optimal control problem. In each iterati…
Sample Average Approximation of Conditional Value-at-risk based Variational Inequalities
Ashish Cherukuri
This paper focuses on a class of variational inequalities (VIs), where the map defining the VI is given by the component-wise conditional value-at-risk (CVaR) of a random function.…
Data-driven distributionally robust optimization over a network via distributed semi-infinite programming
Ashish Cherukuri, Alireza Zolanvari, Goran Banjac +1
This paper focuses on solving a data-driven distributionally robust optimization problem over a network of agents. The agents aim to minimize the worst-case expected cost computed…
A two-step approach to Wasserstein distributionally robust chance- and security-constrained dispatch
Amin Maghami, Evrim Ursavas, Ashish Cherukuri
This paper considers a security constrained dispatch problem involving generation and line contingencies in the presence of the renewable generation. The uncertainty due to renewab…
Initialization-free distributed coordination for economic dispatch under varying loads and generator commitment
Ashish Cherukuri, Jorge Cortes
This paper considers the economic dispatch problem for a network of power generating units communicating over a strongly connected, weight-balanced digraph. The collective aim is t…