2 citations · 3 across the 7 of their papers we have counts for
8 papers
Prescribed-Time and Hyperexponential Concurrent Learning with Partially Corrupted Datasets: A Hybrid Dynamical Systems Approach
Daniel E. Ochoa, Jorge I. Poveda
We introduce a class of concurrent learning (CL) algorithms designed to solve parameter estimation problems with convergence rates ranging from hyperexponential to prescribed-time…
On the Instability of Nesterov's ODE under Non-Conservative Vector Fields
Daniel E. Ochoa, Mahmoud Abdelgalil, Jorge I. Poveda
We study the instability properties of Nesterov's ODE in non-conservative settings, where the driving term is not necessarily the gradient of a potential function. While convergenc…
Decentralized Concurrent Learning with Coordinated Momentum and Restart
Daniel E. Ochoa, Muhammad U. Javed, Xudong Chen +1
This paper studies the stability and convergence properties of a class of multi-agent concurrent learning (CL) algorithms with momentum and restart. Such algorithms can be integrat…
Prescribed-Time Control in Switching Systems with Resets: A Hybrid Dynamical Systems Approach
Daniel E. Ochoa, Nicolas Espitia, Jorge I. Poveda
We consider the problem of achieving prescribed-time stability (PT-S) in a class of hybrid dynamical systems that incorporate switching nonlinear dynamics, exogenous inputs, and re…
Model-Free Optimization on Smooth Compact Manifolds: Overcoming Topological Obstructions using Zeroth-Order Hybrid Dynamics
Daniel E. Ochoa, Jorge I. Poveda
Smooth autonomous dynamical systems modeled by ordinary differential equations (ODEs) cannot robustly and globally stabilize a point in compact, boundaryless manifolds. This obstru…
Accelerated Continuous-Time Approximate Dynamic Programming via Data-Assisted Hybrid Control
Daniel E. Ochoa, Jorge I. Poveda
We introduce a new closed-loop architecture for the online solution of approximate optimal control problems in the context of continuous-time systems. Specifically, we introduce th…
High-Performance Optimal Incentive-Seeking in Transactive Control for Traffic Congestion
Daniel E. Ochoa, Jorge I. Poveda
Traffic congestion has dire economic and social impacts in modern metropolitan areas. To address this problem, in this paper we introduce a novel type of model-free transactive con…
Momentum-Based Nash Set Seeking over Networks via Multi-Time Scale Hybrid Dynamic Inclusions
Daniel E. Ochoa, Jorge I. Poveda
Multi-time scale techniques, such as singular perturbations and averaging theory, have played an essential role in the development of distributed Nash equilibrium-seeking algorithm…