most citedSparse Robust Optimal Control in Continuous-Time: A Computationally Viable Approach

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math.OC2026

Constrained minmax density transportation for linear parabolic PDEs: a numerical optimal control perspective

Siddhartha Ganguly, Vaibhav Upadhyay, Kenji Kashima +1

This article introduces a numerical optimal control framework for minmax constrained density control for a class of noisy linear parabolic partial differential equations (PDEs), in…

math.OC2026

Exact Solutions to a Class of Constrained Optimal Control Problems via Lossless Convexification for Digital Control

Vaibhav Upadhyay, Siddhartha Ganguly, Debasish Chatterjee

This article establishes a new numerically viable technique for solving a class of constrained, nonconvex, continuous-time optimal control problems (OCPs) for linear systems that c…

math.OC20261 cited

Sparse Robust Optimal Control in Continuous-Time: A Computationally Viable Approach

Siddhartha Ganguly, Ashwin Aravind, Souvik Das +2

This article presents a novel, numerically viable algorithm for solving sparse robust optimal control problems in continuous time. We consider a constrained linear noisy system gov…

math.OC2026

On a Gradient Approach to Chebyshev Center Problems with Applications to Function Learning

Abhinav Raghuvanshi, Mayank Baranwal, Debasish Chatterjee

We introduce , the first gradient-based optimization framework for solving Chebyshev center problems, a fundamental challenge in optimal function learning and geom…

math.OC2025

Data-driven learning of feedback maps for explicit robust predictive control: an approximation theoretic view

Siddhartha Ganguly, Shubham Gupta, Debasish Chatterjee

We establish an algorithm to learn feedback maps from data for a class of robust model predictive control (MPC) problems. The algorithm accounts for the approximation errors due to…

math.OC2024

Data-driven distributionally robust MPC for systems with multiplicative noise: A semi-infinite semi-definite programming approach

Souvik Das, Siddhartha Ganguly, Ashwin Aravind +1

This article introduces a novel distributionally robust model predictive control (DRMPC) algorithm for a specific class of controlled dynamical systems where the disturbance multip…