PhD Proposal by Xu Jin

Event Details
  • Date/Time:
    • Monday June 11, 2018 - Tuesday June 12, 2018
      2:00 pm - 3:59 pm
  • Location: Montgomery Knight Building: Rm 317
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Summary Sentence: Adaptive Control Architectures for Cyber-Physical System Security in the Face of Actuator and Sensor Attacks

Full Summary: No summary paragraph submitted.

Ph.D. Thesis Proposal


Xu Jin

Advisor: Prof. W. M. Haddad

Committee members: Profs John-Paul Clarke and Eric M. Feron


Adaptive Control Architectures for Cyber-Physical System Security in the Face of

Actuator and Sensor Attacks



2 PM, Monday, June 11, 2018

Montgomery Knight Building

Room 317





     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.

Additional Information

In Campus Calendar

Graduate Studies

Invited Audience
Public, Graduate students, Undergraduate students
Phd proposal
  • Created By: Tatianna Richardson
  • Workflow Status: Published
  • Created On: May 14, 2018 - 9:34am
  • Last Updated: May 14, 2018 - 9:34am