Past Event: Center for Autonomy Seminar

Convex Optimization Based Optimal Control

Behçet Açikmeşe, University of Washington, Seattle

Abstract

Many future aerospace engineering applications will require dramatic increases in our existing autonomous control capabilities. These include robotic sample return missions to planets, comets, and asteroids, formation flying spacecraft, swarms of autonomous spacecraft, unmanned aerial, ground, and underwater vehicles, and autonomous commercial robotic applications. A key control challenge for many autonomous systems is to achieve the performance goals safely with minimal resource use in the presence of mission constraints and uncertainties. In principle these problems can be formulated and solved as optimal control problems. The challenge is solving them reliably in real-time, while assuring: i) full utilization of the performance envelope for the autonomous system; ii) systematic verification of the control algorithms. Our approach to solving these challenging control problems is optimization-based control where we formulate these control problems as optimization problems and then to exploit convex optimization theory and algorithms for their robust and numerically efficient solutions. This seminar introduces several real-world aerospace applications, where optimization-based control has provided dramatic performance improvements over the heritage technologies. For example, recent applications of reusable rockets have benefited from the ability to compute, in real time, numerical solution of the underlying optimal control problems. There are also other applications, which can benefit from advances in real-time optimal control, including autonomous aerial drones, spacecraft proximity operations for rendezvous, docking and servicing, autonomous multi-vehicle systems, hypersonic transportation, proximity operation near asteroids and comets to name few. This talk will point out some of the key control problems that real-time optimal control could address in these applications as well as the challenges we face as researchers in transitioning this enabling technology into practice.

Biography

Behçet Açikmeşe is a Professor of Aerospace Optimization and Control in the William E. Boeing Department of Aeronautics and Astronautics and an adjunct faculty member in the Department of Electrical Engineering at University of Washington, Seattle. He received his Ph.D. in Aerospace Engineering from Purdue University. He was a senior technologist at JPL and a lecturer at Caltech. At JPL, he developed control algorithms for planetary landing, spacecraft formation flying, and asteroid and comet sample return missions. He developed the “flyaway” control algorithms used successfully in NASA’s Mars Science Laboratory and Mars 2020 missions during the landings of Curiosity and Perseverance rovers on Mars in 2012 and 2021. Dr. Açikmeşe invented a real-time convex optimization based planetary landing guidance algorithm (G-FOLD), which is the first demonstration of a real-time optimization algorithm on a reusable rocket. This novel optimization-based control algorithm proved to be a key development in aerospace guidance and control, especially in enabling advanced numerical optimization techniques for autonomous rockets. He is a recipient of the NSF CAREER Award, IEEE Technical Excellence in Aerospace Controls, numerous NASA Achievement awards for his contributions to NASA missions and technology development. He is an associate editor of IEEE Control System Magazine and AIAA Journal of Guidance, Control, and Dynamics. He is a fellow of IEEE and AIAA.