Danylo Malyuta
Education
- B.Sc in Mechanical Engineering, EPFL, Switzerland (2012-2015)
- M.Sc in Robotics, Systems and Control, ETH Zürich, Switzerland (2015-2018)
- Ph.D candidate in Aeronautics and Astronautics, University of Washington, Seattle (2018-present)
Research Statement
His research explores optimization-based control of dynamical systems. The work is fundamental in that his algorithms work for any system. Current applications have been found for rocket landing, spacecraft control and quadrotor control. There are two central themes to his work.
The first theme asks the question: can we reformulate difficult control problems as simple-to-solve convex optimization problems? In this domain, he is advancing the state of the art of lossless convexification to be able to, for example, convexify a class of mixed-integer problems. This turns intractable problems into ones that can be solved in real-time and with little computational power.
The second theme asks the question: if an optimization problem is hopelessly non-convex, can we deploy computational power to presolve the entire problem before putting it on a computationally constrained vehicle? In this domain, he is developing massively parallel algorithms for explicit model predictive control with mixed-integer convex problems and for dynamic programming.
Research Interests
- Convex optimization
- Mixed-integer programming
- Optimal control theory
- Massive parallelism on CPU and/or GPU
Publications
Journals:
- Approximate multiparametric mixed-integer convex programming
D. Malyuta and B. Açıkmeşe. - Dual quaternion based powered descent guidance with state-triggered constraints
T. Reynolds, M. Szmuk, D. Malyuta, M. Mesbahi, B. Açıkmeşe, and J. M. Carson III - Lossless convexification of a class of optimal control problems with a mixed-integer input exclusivity constraint
D. Malyuta, M. Szmuk, and B. Açıkmeşe - Long-duration fully autonomous operation of rotorcraft UAS for remote-sensing data acquisition
D. Malyuta, C. Brommer, D. Hentzen, T. Stastny, R. Siegwart, and R. Brockers
Conferences:
- Approximate semi-explicit and explicit hybrid model predictive control via simplicial partitioning
D. Malyuta and B. Açıkmeşe - Real-time quad-rotor path planning using convex optimization and compound state-triggered constraints
M. Szmuk, D. Malyuta, T. P. Reynolds, M. S. Mceowen, and B. Açıkmeşe - Partition-based feasible integer solution pre-computation for hybrid model predictive control
D. Malyuta, B. Açıkmeşe, M. Cacan, and D. S. Bayard - Robust model predictive control for linear systems with state and input dependent uncertainties
D. Malyuta, B. Açıkmeşe, and M. Cacan - Discretization performance and accuracy analysis for the rocket powered descent guidance problem
D. Malyuta, T. Reynolds, M. Szmuk, M. Mesbahi, B. Açıkmeşe, and J. M. Carson III - A state-triggered line of sight constraint for 6-DoF powered descent guidance problems
T. Reynolds, M. Szmuk, D. Malyuta, M. Mesbahi, B. Açıkmeşe, and J. M. Carson III - Long-duration autonomy for small rotorcraft UAS including recharging
C. Brommer, D. Malyuta, D. Hentzen, and R. Brockers - Active model rocket stabilization via cold gas thrusters
D. Malyuta, X. Collaud, M. M. Gaspar, G. M. P. Rouaze, R. Pictet, A. Ivanov, and N. Mullin
Theses:
Reviewer for:
- IEEE Control Systems Letters
- AIAA Science and Technology Forum and Exposition (SciTech)
Awards
- UW College of Engineering Dean’s Fellowship (2018-present)
- ETH Zürich Willi Studer Prize (2018)
- Swiss-American Society Scholarship (2017)
- Fondation Zdenek et Michaela Bakala Scholarship (2016)
- Jaguar Land Rover Award for the Best Use of Virtual Methods to Achieve Vehicle Targets (2016)
- Second-best EPFL Bachelor Cumulative GPA (2015)
- Best Academic Achievement Award (IB Diploma 45/45 points, top 0.25% worldwide) (2012)