Many real-time systems such as smart grids, network enabled manufacturing, robot swarms and flocks, and automotive control systems are implemented as distributed, event-triggered control systems where the control loops are closed through a real-time communication network with limited resources. Such systems are referred to as network control systems (NCS) or cyber-physical systems. The interest for NCS is motivated by the many benefits they offer, such as the ease of maintenance and installation, large flexibility and the low cost. Adding resource-constrained communication network in the feedback control loop, however, brings challenging issues that have to be investigated before the above benefits can be realized.
The network imperfections, such as time-varying delays, packet losses, quantization and limited network resources can degrade the performance of control systems, and they can even destabilize the system. Attacks on the communication network, sensors and actuators degrade the performance of the control systems. Therefore, secure network control system design is a priority. These NCS are expected to generate large quantities of data.
The research team intends to develop novel sensors, advanced learning and intelligent control schemes, human-machine interaction methods, big data analytics, and security assurance schemes for NCS.
Interested in learning more about the research or interested in joining the research group? Visit http://web.mst.edu/~sarangap/, or please contact:
Curators’ Distinguished Professor and William A. Rutledge - Emerson Electric Co. Chair
Learning, adaptation and control, neural networks, secure cyber-physical-human systems, big data prognostics, robotics/autonomous systems.
Wireless sensor networks; wireless ad-hoc networks; passive FRID systems; energy-efficient protocols; RF-based localization.