Ph.D. Proposal: Xu Jin

Mon Jun 11 2018 02:00 PM to 03:00 PM
MK 317
“Adaptive Control Architectures for Cyber-Physical System Security in the Face of Actuator and Sensor Attacks”

You're invited to hear

Ph.D. Thesis Proposal

by

Xu Jin

(Advisor: Prof. W. M. Haddad)

“Adaptive Control Architectures for Cyber-Physical System
Security in the Face of Actuator and Sensor Attacks”

2 p.m., Monday, June 11
MK 317

Abstract:
In this work, we develop control architectures for systems with sensor and actuator attacks and with exogenous disturbances. In particular, first we develop an adaptive controller that guarantees uniform ultimate boundedness of the closed-loop dynamical system in the face of adversarial sensor and actuator attacks that are time-varying and partial asymptotic stability when the sensor and actuator attacks are time-invariant. Then, we develop an adaptive control algorithm for addressing security for a class of networked vehicles that comprise n human-driven vehicles sharing kinematic data and an autonomous vehicle in the aft of the vehicle formation receiving data from the preceding vehicles by wireless vehicle-to-vehicle communication devices. Moreover, we propose a novel adaptive control architecture for addressing security and safety in cyber-physical systems subject to exogenous disturbances. Next, we develop a novel distributed adaptive control architecture for addressing networked multiagent systems subject to stochastic exogenous disturbances with compromised sensor and actuators. Specifically, for a class of linear leader-follower multiagent systems, we develop a new structure of the neighborhood synchronization error for the control design protocol of each follower. Finally, we develop an energy-based static and dynamic control framework for stochastic port-controlled Hamiltonian systems. In particular, we obtain constructive sufficient conditions for stochastic feedback stabilization that provide a shaped energy function for the closed-loop system while preserving a Hamiltonian structure at the closed-loop level. In the dynamic control case, energy shaping is achieved by combining the physical energy of the plant and the emulated energy of the controller.

Committee Members:

  • Prof. John-Paul Clarke, AE, Georgia Institute of Technology
  • Prof. Eric M. Feron, AE, Georgia Institute of Technology

Location

MK 317