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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Title: State-space Encoding Driven Error Resilience in Control Systems and Circuits
Committee:
Dr. Abhijit Chatterjee, ECE, Chair , Advisor
Dr. Arijit Raychowdhury, ECE
Dr. Bonnie Ferri, ECE
Dr. Raheem Beyah, ECE
Dr. Jacob Abraham, UT Austin
Abstract:
The objective of this dissertation is to develop methodologies, support algorithms and software-hardware infrastructure for detection and diagnosis of parametric failures, transient soft errors and security attacks in linear and nonlinear circuits and systems for sensing and control. This research is motivated by the proliferation of autonomous sense-and-control real-time systems, such as intelligent robots and self-driven cars, that must maintain a minimum level of performance in the presence of unavoidable electro-mechanical degradation of system-level components in the field as well as external security attacks. A key focus is on rapid recovery from the effects of such anomalies and impairments with minimal impact on system performance while maintaining low implementation overhead as opposed to traditional schemes for recovery that rely on duplication or triplication. Real-time detection and diagnosis techniques are investigated and rely on analysis of state-space encoding based check signatures. For on-line error detection and diagnosis in control systems, linear and nonlinear state space encodings of the system behavior are analyzed in real-time. Recovery is initiated using guided reinforcement learning algorithms that determine how best the system should be controlled in the presence of the diagnosed performance impairments. For cyber-physical systems, these state-space encodings are used to detect malicious security attacks and to diagnose the affected components swiftly. These checks are utilized for fast recovery from such attacks while avoiding catastrophic system failure. Further research in this area will pave the way for successful deployment of self-healing autonomous systems and resilient cyber-physical systems.
