Towards the Next-Generation of Fault-Tolerant Control Systems

点击翻译按钮获取中文摘要

Small faults when left undetected can result in catastrophic failure with significant property, personnel, and environmental damages. There are countless such examples in every type of complex system. Even when a fault does not cause a catastrophic failure, it can lead to severe performance degradation and premature failure. Hence there is a need for advanced control systems to detect the inception of faults in a broad class of systems and ultimately mitigate its progression. Control systems need to be able to identify or classify faults, while still maintaining controllability. Fault detection is made extremely difficult in practice, owing to system nonlinearity, sensor noise, and limited sensor data. While fault detection is needed by all systems, owing to my recent progress the results from this proposal will initially drive innovations in clean energy through the diagnosis of fuel cells and vertical axis wind turbines. Ultimate Program Vision: I aim to sufficiently advance the study of fault detection and fault-tolerant control so that faults do not trigger catastrophes. Within the overall research program of this Discovery grant, I aim to train 2 PhD and 2 MASc students and have the following objectives: 1.Advancing observer design in fully nonlinear systems. 2.Enhancing machine learning systems through observers. 3.Developing observers for utilizing intermittent low-power sensors. 4.Designing observers to detect and tolerate large changes in systems. The grant is also anticipated to drive several future collaboration on the control and diagnostics of fuel cell stacks. There is an anticipated explosion in the need for resilient automation and I aims to expand this program to systems outside clean energy. Thus, in the longer-term, this program aims to 1.Extend fault detection and fault tolerance control to driver-less automobiles, warehouse robots, and automatic deliver-drones. 2.Extend fault detection and fault tolerance control to micro-chip manufacturing systems through planned collaboration with Applied Materials and Photon control. 3.Provide unparalleled HQP training on the next generation of sensing and control strategies. The advances in control systems from this research are expected to reduce performance degradations in fuel cell and wind systems, consequently reducing their lifetime system costs and therefore hasten the transition to clean energy. As this research is also applicable to autonomous systems, there are long-lasting impacts through the improvement of safety and reliability in autonomous vehicles. The potential of this research is broad and will help to both raise the level of Canadian expertise in control systems and position SFU and Canada as a leader in system reliability.