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Grant: Discovery Grants Program - Individual

University of Windsor

$46,000.00

Towards resiliency through health monitoring, diagnosis, prognosis, and fault tolerance in complex and cyber-physical systems with applications to electrified and connected vehicles.

FY 2018-19

Summary
Many complex engineering systems, including safety critical and cyber-physical systems (CPS), need to perform reliably, efficiently, safely and securely for extended periods of time without any interruption or degradation in their performance. This requirement often stems from safety, security, economics, or environmental reasons. Aerospace, automotive, manufacturing, autonomous space and underwater vehicles and structures, (nuclear) power and communication systems; chemical process control and allied industries; water resources; energy storage and smart grids are some examples. However, events (e.g. aging) leading to performance degradation, incipient or complete failure of instruments or components; and in recent years, cyber and terrorist attacks on critical infrastructures are inevitable. Therefore, failure/attack resiliency offered by intelligent ability to continuously monitor the health of systems; detect and rank the severity of any possible faults or attacks; and isolate, prognose, and accommodate for them through self healing, would be highly desirable functions for all aforementioned systems. *The proposed research, which resides at the intersection of control, communications, machine learning, data mining, computational intelligence, big data, and cyber-physical systems, will tackle some missing core of fundamental knowledge that would pave the way towards monitoring the health and normal functioning of complex systems/CPS, and will guard them against undesirable effects such as aging of components, failures or malicious attacks and intrusions by adversaries. The research focus is on providing the system/CPS with sophisticated capabilities including Fault (or Attack) Detection, and Isolation (FDI or ADI) in the first instance, and, Estimation, Prognosis, and Accommodation (EPA) afterwards. This is achieved without costly hardware and through analytical redundancy based approaches. *Electronics and artificial intelligence is taking the automotive industry through a revolutionary transformation, however, recent attacks on cars through tire pressure monitor sensor, anti-lock braking, or GPS system, have alerted the industry regarding some emerging challenges and they are looking to universities for help. Given the needs of the industry in Ontario and Michigan, the application focus area is on battery diagnosis & prognosis in electrified vehicles, as well as security issues, FDI/ADI, and EPA in connected autonomous vehicle (CAV) systems.*The applicant has a solid track record of over thirty five years of research and collaboration with industry, government, and other university organizations. Many highly qualified students and research personnel have been trained in his lab and are successfully employed in Canada and all over the world. The research is of value to many Canadian industries and has a high chance for commercialization.*
Program
Discovery Grants Program - Individual
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data

As published

Application id
RGPIN-2018-04002
Name nom
Saif, Mehrdad
Department département
Electrical and Computer Engineering
Organization id
37
Institution établissement
University of Windsor
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2018
Competition year année de concours
2018
Award amount
46000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
513
Area of application group en
Manufacturing processes and products
Area of application group fr
Procédés et produits industriels
Area of application en
Electrical and electronic machinery and equipment (including computer hardware)
Area of application fr
Machinerie et équipement électriques et électroniques (y compris matériel informatique)
Research subject code
2509
Research subject group en
Electrical and electronic engineering
Research subject group fr
Génie électrique et électronique
Research subject en
Control systems
Research subject fr
Asservissements
Partie
1
Nb partie
5
Application title
Towards resiliency through health monitoring, diagnosis, prognosis, and fault tolerance in complex and cyber-physical systems with applications to electrified and connected vehicles.
Keyword
NSERC
Application summary
Many complex engineering systems, including safety critical and cyber-physical systems (CPS), need to perform reliably, efficiently, safely and securely for extended periods of time without any interruption or degradation in their performance. This requirement often stems from safety, security, economics, or environmental reasons. Aerospace, automotive, manufacturing, autonomous space and underwater vehicles and structures, (nuclear) power and communication systems; chemical process control and allied industries; water resources; energy storage and smart grids are some examples. However, events (e.g. aging) leading to performance degradation, incipient or complete failure of instruments or components; and in recent years, cyber and terrorist attacks on critical infrastructures are inevitable. Therefore, failure/attack resiliency offered by intelligent ability to continuously monitor the health of systems; detect and rank the severity of any possible faults or attacks; and isolate, prognose, and accommodate for them through self healing, would be highly desirable functions for all aforementioned systems. *The proposed research, which resides at the intersection of control, communications, machine learning, data mining, computational intelligence, big data, and cyber-physical systems, will tackle some missing core of fundamental knowledge that would pave the way towards monitoring the health and normal functioning of complex systems/CPS, and will guard them against undesirable effects such as aging of components, failures or malicious attacks and intrusions by adversaries. The research focus is on providing the system/CPS with sophisticated capabilities including Fault (or Attack) Detection, and Isolation (FDI or ADI) in the first instance, and, Estimation, Prognosis, and Accommodation (EPA) afterwards. This is achieved without costly hardware and through analytical redundancy based approaches. *Electronics and artificial intelligence is taking the automotive industry through a revolutionary transformation, however, recent attacks on cars through tire pressure monitor sensor, anti-lock braking, or GPS system, have alerted the industry regarding some emerging challenges and they are looking to universities for help. Given the needs of the industry in Ontario and Michigan, the application focus area is on battery diagnosis & prognosis in electrified vehicles, as well as security issues, FDI/ADI, and EPA in connected autonomous vehicle (CAV) systems.*The applicant has a solid track record of over thirty five years of research and collaboration with industry, government, and other university organizations. Many highly qualified students and research personnel have been trained in his lab and are successfully employed in Canada and all over the world. The research is of value to many Canadian industries and has a high chance for commercialization.*