10 citations · 14 across the 17 of their papers we have counts for
19 papers
Communication-efficient ADMM over Hierarchical Networks
Binh Nguyen, Shuangqing Wei, Truong X. Nghiem
This paper develops a novel distributed optimization algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve hierarchical optimization problems over tree…
Learning-enabled Acceleration of Scenario-based Model Predictive Control
Trinh Tran, Binh Nguyen, Truong X. Nghiem
Scenario-based model predictive control (SBMPC) is a variant of model predictive control (MPC) that explicitly accounts for uncertainty by optimizing control actions over multiple…
AD-MPCC: Adaptive Differentiable Model Predictive Contouring Control for Autonomous Racing
Nam T. Nguyen, Binh Nguyen, Ahmad Amine +3
This paper presents Adaptive Differentiable Model Predictive Contouring Control (AD-MPCC), a framework for autonomous racing that integrates differentiable MPCC with online paramet…
Active Learning for Optimal Experimental Design in Machine Learning-Based Building Energy System Identification
Nam T. Nguyen, Truong X. Nghiem
Machine learning (ML) techniques have been commonly adopted to identify the dynamics of building energy systems (BESs), owing to their flexibility relative to first-principles, phy…
LEAF: A Learning-Enabled ADMM Framework for Accelerated Convex Optimization
Binh Nguyen, Trinh Tran, Truong X. Nghiem
We propose LEAF, a learning-enabled ADMM framework for accelerated convex optimization. The key idea is to approximate the Moreau envelope of the objective function using an Input…
Structure- and Stability-Preserving Learning of Port-Hamiltonian Systems
Binh Nguyen, Nam T. Nguyen, Truong X. Nghiem
This paper investigates the problem of data-driven modeling of port-Hamiltonian systems while preserving their intrinsic Hamiltonian structure and stability properties. We propose…