Tutorial Proposal

Tutorial 1
Monitoring, Fault-Tolerant and Cyber-Resilient Control of Renewable Microgrids

Brief description

Renewable Energy Systems (RESs) such as wind turbines and Solar Photovoltaic (PV) arrays together with battery storage, all integrated in microgrids, constitute the key elements of the next-generation electricity grid, known as the “smart grid”. To meet the crucial reliability and cybersecurity requirements of both the cyber and physical components of RESs in microgrids, innovative approaches for physical-faults and cyber-attacks monitoring and fault-tolerant and cyber-resilient control are needed. Although cyber-attacks originate from different sources than faults, both may have similar signatures that can result in increased operating costs, physical damages or even cascading failures. The origin and severity of attacks and faults must be carefully identified for corrective actions to be taken without delay and to limit the damage induced to the system. Therefore, early detection, diagnosis, and accommodation (mitigation) of physical-faults and cyber-attacks are critical for the safe and secure operation of RESs and microgrids. In this regard, recent advancements in digitalization and the Industrial Internet of Things (IIoT) safeguarded by advanced intrusion detection and cyber-attack mitigation countermeasures offer significant advantages as never before. Besides, empowered by the increasing computational power broadly available in modern computers, recent theoretical developments on Artificial Intelligence (AI) and advanced machine learning capabilities have broken new ground. Indeed, they enable the conversion of massive and multidimensional sensor data into useful information and provide new perspectives for intelligent monitoring and reliable and secure control of energy and power systems. Given the above premises, this tutorial aims at highlighting the challenges, recent developments, applications, solutions, and future trends of physical-fault/cyber-attack diagnosis and fault-tolerant and cyber-resilient control in renewable microgrids. Specifically, the main goals of this tutorial are detailed as follows:

  • Discuss the critical problem of the occurrence of physical-faults and cyber-attacks in RESs (wind turbines and solar PV systems) in microgrids and smart grids;
  • Introduce the currently available techniques and tools for condition monitoring, control and health management of wind turbines and solar PV systems in microgrids;
  • Present a review of new and emerging state-of-the-art techniques in condition monitoring, fault-tolerant control and cyber-resilient control of wind turbines and solar PV systems in microgrids;
  • Illustrate some step-by-step design approaches through several case studies;
  • Discuss important challenges and remaining problems, as well as future directions of this emerging and active research and development field.


Youmin Zhang

Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, Canada

Youmin Zhang is a Professor with the Department of Mechanical, Industrial & Aerospace Engineering at Concordia University in Montreal, Canada. He is also a licensed Professional Engineer (P.Eng.) registered in Ontario. He received his Ph.D. degree from Northwestern Polytechnical University, China, in 1995. He has authored 8 books and more than 550 journal and conference papers. His research interests include condition monitoring, fault detection and diagnosis (FDD) and fault-tolerant control (FTC), cooperative guidance, navigation, and control (GNC) of single and multiple unmanned vehicles, and advanced diagnosis, prognosis, and health management of safety-critical systems, wind turbines, smart grids and smart cities under the framework of cyber-physical systems (CPS). Dr. Zhang’s research has drawn considerable attention in the field. His publications have received 19,889 citations at Google Scholar with an h-index of 66 and i10-index of 302, and 9,861 citations with 562 items and an h-index of 49 at Web of Science (WOS).More detailed information can be found at http://users.encs.concordia.ca/~ymzhang/.

Hamed Badihi

College of Automation Engineering, Nanjing University of Aeronautics and Astronautics Nanjing, Jiangsu, China

Hamed Badihi is an Associate Professor with the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics (NUAA), Nanjing, China since 2019. Prior to this position, he was a Horizon Postdoctoral Fellow with the Department of Mechanical, Industrial & Aerospace Engineering at Concordia University in Montreal, Canada where he also received his Ph.D. degree in Mechanical Engineering in 2016. His research interests include all aspects of condition monitoring, fault diagnosis and prognosis, and fault-tolerant and cyber-resilient control of cyber-physical energy systems. Specific research areas include wind turbines and wind farms, solar photovoltaic systems, renewable microgrids and smart grids. Dr. Badihi is a member of the Technical Committees of various international conferences, and serving as Guest Editor and Reviewer of several SCI journals and conferences.

Saeedreza Jadidi

Department of Mechanical, Industrial and Aerospace Engineering, Concordia University, Montreal, Canada

Saeedreza Jadidi is a PhD Candidate with the Department of Mechanical, Industrial & Aerospace Engineering at Concordia University in Montreal, Canada. He received his B.S. degree in computer engineering and M.S. degree in mechatronics engineering. His current research interests include detection and identification of physical-faults and cyber-attacks, as well as fault-tolerant and cyber-resilient control approaches with application to smart grids and renewable energy systems.

Tutorial 2
Ensuring Safety and Establishing Trust for AI enabled Cyber-Physical Systems through Explainability

Brief description

Artificial intelligence (AI) has been widely adopted in different domains including autonomous vehicles and IoT medical device. In a competitive environment, engineers and researchers are focused on developing innovative applications while minimal attention is provided to safety engineering techniques that cope with the fast pace of technological advances. As a result, recent failures and operational accidents of AI-based system highlight a pressing need for the development of suitable stringent safety monitoring techniques. This tutorial aims at introducing the audience to the arising safety issues of AI-enabled cyber-physical systems (CPSs). We will provide a landscape of informal and formal approaches in ensuring AI-based CPS safety at every phase of the system’s development and defining the gaps. This tutorial also aims at emphasizing the need for operational safety of AI-based CPS and highlight the importance of Explainability in development of safety-critical systems for enhancing trustworthiness. There has been significant research in the domain of model-based engineering that are attempting to solve this design problem. However, in this tutorial we are looking at this problem from a different perspective of a third part observer. Observations from the deployment of a CPS are used to: a) ascertain whether the CPS used in practice actually match the proposed safety assured design, b) explain reasons for a mismatch in CPS operation and the safety assured design, c) generate evidence to establish the trustworthiness of a CPS, d) generate novel practical scenarios where a CPS is likely to fail. The challenge is the uncertainty of the human-in-the-loop behaviour and incompleteness of the environment’s model used in the developed and safety verification of AI-enabled CPS. In this tutorial, we will talk about two aspects: a) theoretical approaches towards validating CPS operation against its design, explanation interfaces for explaining failures, generation of evidence of correct operation to improve trust, and generating novel scenarios for CPS, and b) hands on usage of two software tools HyMN and FaultEx using data from real life examples including closed loop blood glucose control systems (artificial pancreas) and a heavy vehicle braking system.


Sandeep K.S. Gupta, Ayan Banerjee, Imane Lamrani

Arizona State University

Sandeep K. S. Gupta is the Associate Dean for Research in Fulton School of Engineering and a Professor of Computer Science and Engineering in the School for Computing and Augmented Intelligence (SCAI), Arizona State University, Tempe, AZ. Dr. Gupta heads the IMPACT Lab (http://impact.lab.asu.edu) at Arizona State University. IMPACT Lab has significant experience in hosting tutorials. Previously we have hosted tutorials at the Body Sensor Network conference (two times), and at the Food and Drug Administration (FDA) on safety security and sustainability of mobile medical control systems

Ayan Banerjee is an Assistant Research Professor at Arizona State University. His research interest lies in safe, secure and sustainable AI enabled Cyber-Physical systems. His expertise include model based analysis and design of CPS, implementation of CPS with embedded computing, and applications of wearable sensor based control systems in domains such as medical control systems, or gesture recognition. He has continuing collaboration with Food and Drug’s Administration and Mayo Clinic.

Imane Lamrani is a Post Doctoral Fellow in the School for Computing and Augmented Intelligence (SCAI)at Arizona State University. She received a M.S. in Computer Systems and Software Design from Jacksonville State University. Her research goal is to develop rigorous safety verification approaches to evaluate the correct operation of AI-enabled Cyber Physical Systems (CPS) in the field, perform root-cause analysis, and verify the operational safety of AI-enabled CPS