Control and Automation Architectures for Adaptive and Safe Manufacturing Systems

Abstract 

Driven by rising product variety, shorter product life cycles, and increasingly volatile supply chains, the current manufacturing paradigm is shifting toward production systems that demand significantly greater flexibility and adaptability. Meeting these demands requires moving beyond classical fixed-logic controllers toward model-based, adaptive, and distributed control strategies capable of managing dynamic system-level behavior. At the same time, the growing volume of data and information available on the factory floor opens the door to AI-driven automation, provided it can be integrated without compromising safe and predictable operation. In this talk, I will describe how my group has approached these challenges at three levels. At the field level, I will introduce how we are leveraging existing AI tools to improve human-robot collaboration for repetitive assembly processes. At the system level, I will describe how we design control and automation methods to coordinate multiple subsystems (e.g., mobile robots, flexible machine tools), improving system-level flexibility and adaptability. At the enterprise level, I will broaden the scope to examine how external factors, including power grid variability and fluctuating customer demand, impose additional constraints on system operation, and discuss how control strategies can be designed to maintain flexibility and performance in the presence of external disturbances. Case studies from both simulated environments and operational testbeds will highlight how these methods can be applied to realize the next generation of intelligent, interconnected, and responsive factories of the future.

 About the Speaker 

Ilya Kovalenko is currently an Assistant Professor in the Department of Mechanical Engineering and the Department of Industrial & Manufacturing Engineering at Penn State University. He received both his PhD in Mechanical Engineering (2020) and his MS degree in Mechanical Engineering from the University of Michigan (2018), and his BS degree in Mechanical Engineering from the Georgia Institute of Technology (2015). He was awarded the NSF CAREER award in 2025. His current research interests lie in the areas of control theory, artificial intelligence, and smart manufacturing, with a focus on cooperative control, cyber-physical systems, and robotics.

Host: Professor Justin Yim