Abstract: Constrained control is an enabling technology that can drastically improve the performance of engineering system by allowing them to safely operate at the very edge of their design specifications. This is often achieved by solving a series of constrained optimization problems in real-time. Depending on the time constants of the controlled system, however, it can be challenging to reliably solve the optimization problem at the appropriate sampling rate. This talk will investigate a novel approach to real-time constrained control, which consists in treating the optimizer as a dynamic system that evolves in parallel to the controlled system and studying when the dynamic interconnection between the two systems. We then discuss potential limitations of the method and how these limitations can be overcome by introducing an additional constrained controller that enforces meta-constraints on the interconnected systems. Application examples addressed in the talk will include unmanned aerial vehicles, robotic manipulators, autonomous cars, and quantum systems.

Bio: Marco M. Nicotra is an Assistant Professor in the Department of Electrical, Computer, and Energy Engineering at the University of Colorado Boulder. Previously, he was a postdoctoral fellow in the Aerospace Engineering Department of the University of Michigan, Ann Arbor. He obtained a B.S. degree in Mechanical Engineering from Politecnico di Milano in 2009, a double M.S. degree in Mechatronics Engineering from Politecnico di Milano and Université Libre de Bruxelles in 2012, and a joint Ph.D. Degree in Automation and System Analysis from Universitè Libre de Bruxelles and Università di Bologna in 2016. In 2014 he received an Honorable Mention for the IFAC Young Author Prize, and in 2021 he was an awardee of the NSF CAREER Program. His research interests are in the area of nonlinear systems theory, constrained control, and optimization, as well as their applications to aerospace, energy, robotic, and quantum systems.

Abstract: Constrained control is an enabling technology that can drastically improve the performance of engineering system by allowing them to safely operate at the very edge of their design specifications. This is often achieved by solving a series of constrained optimization problems in real-time. Depending on the time constants of the controlled system, however, it can be challenging to reliably solve the optimization problem at the appropriate sampling rate. This talk will investigate a novel approach to real-time constrained control, which consists in treating the optimizer as a dynamic system that evolves in parallel to the controlled system and studying when the dynamic interconnection between the two systems. We then discuss potential limitations of the method and how these limitations can be overcome by introducing an additional constrained controller that enforces meta-constraints on the interconnected systems. Application examples addressed in the talk will include unmanned aerial vehicles, robotic manipulators, autonomous cars, and quantum systems.

Bio: Marco M. Nicotra is an Assistant Professor in the Department of Electrical, Computer, and Energy Engineering at the University of Colorado Boulder. Previously, he was a postdoctoral fellow in the Aerospace Engineering Department of the University of Michigan, Ann Arbor. He obtained a B.S. degree in Mechanical Engineering from Politecnico di Milano in 2009, a double M.S. degree in Mechatronics Engineering from Politecnico di Milano and Université Libre de Bruxelles in 2012, and a joint Ph.D. Degree in Automation and System Analysis from Universitè Libre de Bruxelles and Università di Bologna in 2016. In 2014 he received an Honorable Mention for the IFAC Young Author Prize, and in 2021 he was an awardee of the NSF CAREER Program. His research interests are in the area of nonlinear systems theory, constrained control, and optimization, as well as their applications to aerospace, energy, robotic, and quantum systems.