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Ph.D. Proposal Oral Exam - Suvadeep Banerjee

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Title:  Response Signature Driven Error Detection and Recovery in Control Systems and Circuits

Committee: 

Dr. Chatterjee, Advisor

Dr. Raychowdhury, Chair

Dr. Ferri

Abstract:

The objective of the proposed research 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 objective 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. Both off-line as well as on-line detection and diagnosis techniques are investigated and rely on analysis of system-under-test response signatures to relevant test stimulus and real-time stimulus, respectively. For on-line error detection and diagnosis, linear and nonlinear state space encodings of the system under test are used and specific properties of the codes used are analyzed in real-time. Recovery is initiated using supervised as well as unsupervised learning algorithms that determine how best the system should be controlled in the presence of the diagnosed performance impairments. Future challenges that need to be addressed include viability studies of the proposed techniques on a variety of pilot autonomous systems as well as application to systems with soft as well as hard real-time performance constraints.

Status

  • Workflow Status:Published
  • Created By:Daniela Staiculescu
  • Created:01/09/2017
  • Modified By:Daniela Staiculescu
  • Modified:01/12/2017

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