Systems Engineering

Autonomous Systems

Online Machine Learning and Resilience of Autonomous Systems

Develop online machine learning techniques for enhanced intelligence, anomaly mitigation, and resilience of autonomous systems
Challenges:
- Mining PNT information from images
  (visual-servoing)
- Real-time edge computing (computer
  visualization & control reconfiguration)

Cyber-security of Manufacturing Systems

Develop a unified framework based on the deep learning for real-time health and security monitoring and diagnosis of manufacturing systems
Challenges:
- Limited data of cyber-attack
- Minimal data labelling/annotation
- “Around-the-clock” monitoring

Leader-Follower Formation Control

Develop robust autonomous systems based on
visual-servoing and intelligent control for
leader-follower formation control
Challenges:
- Mining PNT information from images
  (visual-servoing)
- Real-time edge computing
- Obstacle learning, avoidance, path planning
  and control

Publications:

Hong, S. H., Cornelius, J., Wang, Y., & Pant, K. (2019). Fault compensation by online updating of genetic algorithm-selected neural network model for model predictive control. SN Applied Sciences, 1(11), 1488.

Hong, S. H., Cornelius, J., Wang, Y., & Pant, K. (2020). Online Machine Learning Model Compensator for Model Predictive Control and Anomaly Mitigation of Mechanical Systems. In AIAA Scitech 2020 Forum (p. 2251).

S.H. Hong, J. Cornelius, Y. Wang*, K. Pant, "Optimized Artificial Neural Network Model and Compensator in Model Predictive Control for Anomaly Mitigation", Journal of Dynamic Systems, Measurement and Control, https://doi.org/10.1115/1.4049130