23 citations · 39 across the 7 of their papers we have counts for
5 papers · 1 filter
A Data-Driven Sparse-Learning Approach to Model Reduction in Chemical Reaction Networks
Farshad Harirchi, Omar A. Khalil, Sijia Liu +3
In this paper, we propose an optimization-based sparse learning approach to identify the set of most influential reactions in a chemical reaction network. This reduced set of react…
Conflict-driven Hybrid Observer-based Anomaly Detection
Zheng Wang, Farshad Harirchi, Dhananjay Anand +3
This paper presents an anomaly detection method using a hybrid observer -- which consists of a discrete state observer and a continuous state observer. We focus our attention on an…
A New Data-Driven Sparse-Learning Approach to Study Chemical Reaction Networks
Farshad Harirchi, Doohyun Kim, Omar A. Khalil +4
Chemical kinetic mechanisms can be represented by sets of elementary reactions that are easily translated into mathematical terms using physicochemical relationships. The schematic…
Guaranteed Fault Detection and Isolation for Switched Affine Models
Farshad Harirchi, Sze Zheng Yong, Necmiye Ozay
This paper considers the problem of fault detection and isolation (FDI) for switched affine models. We first study the model invalidation problem and its application to guaranteed…
Optimal Input Design for Affine Model Discrimination with Applications in Intention-Aware Vehicles
Yuhao Ding, Farshad Harirchi, Sze Zheng Yong +2
This paper considers the optimal design of input signals for the purpose of discriminating among a finite number of affine models with uncontrolled inputs and noise. Each affine mo…