6 citations · 7 across the 10 of their papers we have counts for
8 papers · 1 filter
Statistical Learning of Contractive Dynamical Representations for Composite Adaptive Control
Min Kim, José Leonardo Brenes, Fred Hadaegh +1
We present a representation-learning framework for composite adaptive tracking control under dynamically coupled disturbances. The framework connects classical disturbance-accommod…
Schur-Neural KF: Learned Schur-Consistent Corrections to the Extended Kalman Filter
Min Kim, Lianghao Cao, Soon-Jo Chung +1
We present Schur-Neural KF (SN-KF), a learning-based correction to the extended Kalman filter (EKF) that preserves the probabilistic conditioning interpretation of the EKF. The met…
Geometric Fault Identification via Mirror Descent Learning
Mahdi Taheri, Haeyoon Han, Soon-Jo Chung +1
This paper develops a fault detection and identification (FDI) method for nonlinear control-affine systems under simultaneous actuator and sensor faults. We adopt a geometric appro…
Perron-Frobenius Contractive Operator Matching for Data-Driven Reachable Fault Identification and Recovery
Joshua D. Ibrahim, Mahdi Taheri, Soon-Jo Chung +1
This paper focuses on data-driven fault detection, identification, and recovery (FDIR) for nonlinear control-affine systems under actuator faults. We create a unified framework in…
Data-Driven Probabilistic Fault Detection and Identification via Density Flow Matching
Joshua D. Ibrahim, Mahdi Taheri, Soon-Jo Chung +1
Fault detection and identification (FDI) is critical for maintaining the safety and reliability of systems subject to actuator and sensor faults. In this paper, the problem of FDI…
Closing the Loop Inside Neural Networks: Causality-Guided Layer Adaptation for Fault Recovery Control
Mahdi Taheri, Soon-Jo Chung, Fred Y. Hadaegh
This paper studies the problem of real-time fault recovery control for nonlinear control-affine systems subject to actuator loss of effectiveness faults and external disturbances.…
Regret-Optimal Defense Against Stealthy Adversaries: A System Level Approach
Hiroyasu Tsukamoto, Joudi Hajar, Soon-Jo Chung +1
Modern control designs in robotics, aerospace, and cyber-physical systems rely heavily on real-world data obtained through system outputs. However, these outputs can be compromised…
Robust Optimal Network Topology Switching for Zero Dynamics Attacks
Hiroyasu Tsukamoto, Joshua D. Ibrahim, Joudi Hajar +3
The intrinsic, sampling, and enforced zero dynamics attacks (ZDAs) are among the most detrimental stealthy attacks in robotics, aerospace, and cyber-physical systems. They exploit…