23 citations · 23 across the 3 of their papers we have counts for
7 papers
Event-triggered parameter estimator for sensor fusion
Ariana Méndez-Castillo, Irene Perez-Salesa, Rodrigo Aldana-López +2
This paper studies event-triggered parameter estimation in sensor fusion systems where sensors transmit measurements to a gradient based estimator. We introduce a regressor-driven…
Hierarchical parameter estimation for distributed networked systems: a dynamic consensus approach
Ariana R. Mendez-Castillo, Rodrigo Aldana-Lopez, Antonio Ramirez-Trevino +2
This work introduces a novel two-stage distributed framework to globally estimate constant parameters in a networked system, separating shared information from local estimation. Th…
Autonomous and non-autonomous fixed-time leader-follower consensus for second-order multi-agent systems
Miguel A. Trujillo, Rodrigo Aldana-López, David Gomez Gutierrez +3
This paper addresses the problem of consensus tracking with fixed-time convergence, for leader-follower multi-agent systems with double-integrator dynamics, where only a subset of…
A Note on Optimal Distributed State Estimation for Linear Time-Varying Systems
Irene Perez-Salesa, Rodrigo Aldana-Lopez, Carlos Sagues
In this technical note, we prove that the ODEFTC algorithm constitutes the first optimal distributed state estimator for continuous-time linear time-varying systems subject to stoc…
Distributed Discrete-time Dynamic Outer Approximation of the Intersection of Ellipsoids
Eduardo Sebastián, Rodrigo Aldana-López, Rosario Aragüés +2
This paper presents the first discrete-time distributed algorithm to track the tightest ellipsoids that outer approximates the global dynamic intersection of ellipsoids. Given an u…
NN-ETM: Enabling safe neural network-based event-triggering mechanisms for consensus problems
Irene Perez-Salesa, Rodrigo Aldana-Lopez, Carlos Sagues
Event-triggering mechanisms (ETM) have been developed for consensus problems to reduce communication while ensuring performance guarantees, but their design has grown increasingly…