Cyber-physical systems: Analysis and Design
Prof. Peng Shi
School of Electrical and Electronic Engineering
University of Adelaide, Australia
Abstract:
Cyber-physical systems (CPS), such as smart grids and intelligent transportation systems, are complex
systems where software and hardware components are seamlessly integrated toward performing well-defined
tasks. However, this integration increases the vulnerability of CPS with higher possibility of
cyber-attack that could cause severe consequences to economics, society, and human beings. Hence,
cyber-security is critical and important in CPS. In this talk, the security of CPS is discussed from the
perspectives of attackers. We will introduce the background of CPS and security issues, and some
existing work on cyber-attacks. We then present our recent work on the design of stealthy hybrid attacks
to CPS, which enables attackers to launch hybrid cyber-attacks more effectively to maximize system
performance degradation with less chance to be detected.
Biography:
Peng Shi received the PhD degree in Electrical Engineering from the University of Newcastle, Australia,
the PhD degree in Mathematics from the University of South Australia, the Doctor of Science degree from
the University of Glamorgan, UK, and the Doctor of Engineering degree from the University of Adelaide,
Australia. He is now a Professor at the School of Electrical and Electronic Engineering, and the
Director of Advanced Unmanned Systems Laboratory, at the University of Adelaide, Australia. His research
interests include systems and control theory and applications to autonomous and robotic systems,
cyber-physical systems, and multi-agent systems. He received the MA Sargent Medal Award from Engineers
Australia in 2022 to recognize his longstanding eminence in science and practice of electrical
engineering, the Life-time achiever Leader-Board acknowledgement from THE AUSTRALIAN from 2019-2022, and
the Highly Cited Researcher recognition from Thomson Reuters from 2014-2022. Currently he serves as the
Editor-in-Chief of IEEE Transactions on Cybernetics, a Senior Editor of IEEE Access, and an editorial
member for a number of journals, including Automatica and IEEE Transactions on (Artificial Intelligence,
and Circuits and Systems). His professional services also include as the President of the International
Academy for Systems and Cybernetic Sciences, the Vice President of IEEE SMC Society, and IEEE SMC
Distinguished Lecturer. He is a Fellow of IEEE, IET, IEAust and CAA, a Member of the Academy of Europe,
and an Honorary Member of the Romanian Academy of Scientists.
Combining Performance and Stability: The Art of Robust Optimization
Prof. Seyedali Mirjalili
Torrens University, Australia
Abstract:
In today's complex and uncertain world, finding reliable solutions to optimization problems is essential
for success. This talk covers robust optimization techniques that can help us achieve this by combining
good performance with low sensitivity to possible perturbations. The use of evolutionary optimization
algorithms has become increasingly popular due to their simplicity, flexibility, and ability to handle
difficult search spaces. However, there is still room for improvement, especially when it comes to
robust optimization combined with multi-objective approaches. To achieve optimal results that are less
sensitive to perturbations, a highly systematic robust optimization algorithm design process is
necessary. This process includes designing challenging robust test problems, developing performance
metrics to measure algorithm success, and creating computationally efficient algorithms to find robust
solutions. While progress has been made in developing robust optimization techniques, this talk shows
that there are still gaps in the literature that need to be addressed. These include the need for more
standard and challenging test functions for both single- and multi-objective algorithms, as well as more
standard performance metrics for quantifying their performance. Additionally, there is a need for more
investigation and analysis of current robustness metrics, as well as for reducing the computational cost
and improving the reliability of robust optimization techniques. There will be discussions on how to
establish a more systematic robust algorithm design process that will enable us to find reliable
solutions to optimization problems in even the most uncertain and complex of environments by addressing
these gaps.
Biography:
Seyedali Mirjalili is a Professor at the Center for Artificial Intelligence Research and Optimization at
Torrens University. He has gained international recognition for his contributions to nature-inspired
artificial intelligence techniques, with over 500 published works that have garnered more than 80,000
citations and an H-index of 85. He was included on the list of the top 1% of highly-cited researchers in
2019, and Web of Science named him one of the most influential researchers in the world. In 2022 and
2023, The Australian newspaper recognized him as a global leader in Artificial Intelligence and a
national leader in the Evolutionary Computation and Fuzzy Systems fields. Additionally, he serves as a
senior member of IEEE and holds editorial positions at several top AI journals, including but not
limited to, Engineering Applications of Artificial Intelligence, Applied Soft Computing, Neurocomputing,
Advances in Engineering Software, and Computers in Biology.