collaborators

5 papers

eess.SY2025

Filtering in Multivariate Systems with Quantized Measurements using a Gaussian Mixture-Based Indicator Approximation

Angel L. Cedeño, Rodrigo A. González, Boris I. Godoy +1

This work addresses the problem of state estimation in multivariable dynamic systems with quantized outputs, a common scenario in applications involving low-resolution sensors or c…

eess.SY2025

Truncated Gaussian Noise Estimation in State-Space Models

Rodrigo A. González, Angel L. Cedeño, Koen Tiels +1

Within Bayesian state estimation, considerable effort has been devoted to incorporating constraints into state estimation for process optimization, state monitoring, fault detectio…

eess.SY2025

Simultaneous Input and State Estimation under Output Quantization: A Gaussian Mixture approach

Rodrigo A. González, Angel L. Cedeño

Simultaneous Input and State Estimation (SISE) enables the reconstruction of unknown inputs and internal states in dynamical systems, with applications in fault detection, robotics…

eess.SY2025

Observer Switching Strategy for Enhanced State Estimation in CSTR Networks

Lisbel Bárzaga-Martell, Francisco Ibáñez, Angel L. Cedeño +4

Accurate state estimation is essential for monitoring and controlling nonlinear chemical reactors, such as continuous stirred-tank reactors (CSTRs), where limited sensor coverage a…

eess.SY2025

The Quadrature Gaussian Sum Filter and Smoother for Wiener Systems

Angel L. Cedeño, Rodrigo A. González, Juan C. Agüero

Block-Oriented Nonlinear (BONL) models, particularly Wiener models, are widely used for their computational efficiency and practicality in modeling nonlinear behaviors in physical…