Area of research
Control and Systems Engineering · Artificial Intelligence
Research interest
Research interests include Fault Detection and Control Systems, Advanced Control Systems Optimization, Control Systems and Identification, and Target Tracking and Data Fusion in Sensor Networks.
A novel automated soft sensor design tool for industrial applications based on machine learning
Comprehensive Analysis on Machine Learning Approaches for Interpretable and Stable Soft Sensors
A multi-feature-based fault diagnosis method based on the weighted timeliness broad learning system
Anomaly detection for drilling tools based on operating mode recognition and interval-augmented Mahalanobis distance
False alarm reduction in drilling process monitoring using virtual sample generation and qualitative trend analysis
Data-driven capacity estimation of commercial lithium-ion batteries from voltage relaxation
A Novel Approach to Alarm Causality Analysis Using Active Dynamic Transfer Entropy
LIONSIMBA: A Matlab Framework Based on a Finite Volume Model Suitable for Li-Ion Battery Design, Simulation, and Control
State-of-charge estimation in lithium-ion batteries: A particle filter approach
On simultaneous on-line state and parameter estimation in non-linear state-space models
Optimal control and state estimation of lithium-ion batteries using reformulated models