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

许多复杂的工程系统，包括安全关键系统和网络物理系统（CPS），需要在不中断或性能下降的情况下长时间可靠、高效、安全和可靠地运行。这一要求通常源于安全、经济或环境方面的原因。航空航天、汽车、制造业、自主空间和水下航行器及结构、（核）动力和通信系统；化工过程控制及相关行业；水资源;能源储存和智能电网就是一些例子。然而，导致仪器或部件性能下降、初步失效或完全失效的事件（如老化）；近年来，针对关键基础设施的网络和恐怖袭击不可避免。因此，故障/攻击弹性提供了智能能力，可以持续监控系统的健康状况；检测任何可能的故障或攻击的严重程度并对其进行排序；通过自我修复来隔离、预测和适应它们，将是所有上述系统非常理想的功能。

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.