5 papers · 1 filter
Sparse Linear Regression with Constraints: A Flexible Entropy-based Framework
Amber Srivastava, Alisina Bayati, Srinivasa Salapaka
This work presents a new approach to solve the sparse linear regression problem, i.e., to determine a k-sparse vector w in R^d that minimizes the cost ||y - Aw||^2_2. In contrast t…
Closed-Loop Identification of Stabilized Models Using Dual Input-Output Parameterization
Ran Chen, Amber Srivastava, Mingzhou Yin +1
This paper introduces a dual input-output parameterization (dual IOP) for the identification of linear time-invariant systems from closed-loop data. It draws inspiration from the r…
On Fulfilling the Exigent Need for Automating and Modernizing Logistics Infrastructure in India: Enabling AI-based Integration, Digitalization, and Smart Automation of Industrial Parks and Robotic Warehouses
Shaurya Shriyam, Prashant Palkar, Amber Srivastava
To stay competitive, the Low- or Middle-Income Countries (LMICs) need to embrace Industry 4.0 and Logistics 4.0. This requires government-level interventions and policy-making to i…
A Dual System-Level Parameterization for Identification from Closed-Loop Data
Amber Srivastava, Mingzhou Yin, Andrea Iannelli +1
This work presents a dual system-level parameterization (D-SLP) method for closed-loop system identification. The recent system-level synthesis framework parameterizes all stabiliz…
Once upon a time step: A closed-loop approach to robust MPC design
Anilkumar Parsi, Marcell Bartos, Amber Srivastava +2
A novel perspective on the design of robust model predictive control (MPC) methods is presented, whereby closed-loop constraint satisfaction is ensured using recursive feasibility…