Koopman Based Trajectory Optimization with Mixed Boundaries

Fuente: arXiv
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Autori principali: Abou-Taleb, Mohamed, Raff, Maximilian, Flaßkamp, Kathrin, Remy, C. David
Natura: Preprint
Pubblicazione: 2024
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author Abou-Taleb, Mohamed
Raff, Maximilian
Flaßkamp, Kathrin
Remy, C. David
author_facet Abou-Taleb, Mohamed
Raff, Maximilian
Flaßkamp, Kathrin
Remy, C. David
contents Trajectory optimization is a widely used tool in the design and control of dynamical systems. Typically, not only nonlinear dynamics, but also couplings of the initial and final condition through implicit boundary constraints render the optimization problem non-convex. This paper investigates how the Koopman operator framework can be utilized to solve trajectory optimization problems in a (partially) convex fashion. While the Koopman operator has already been successfully employed in model predictive control, the challenge of addressing mixed boundary constraints within the Koopman framework has remained an open question. We first address this issue by explaining why a complete convexification of the problem is not possible. Secondly, we propose a method where we transform the trajectory optimization problem into a bilevel problem in which we are then able to convexify the high-dimensional lower-level problem. This separation yields a low-dimensional upper-level problem, which could be exploited in global optimization algorithms. Lastly, we demonstrate the effectiveness of the method on two example systems: the mathematical pendulum and the compass-gait walker.
format Preprint
id arxiv_https___arxiv_org_abs_2412_03195
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Koopman Based Trajectory Optimization with Mixed Boundaries
Abou-Taleb, Mohamed
Raff, Maximilian
Flaßkamp, Kathrin
Remy, C. David
Optimization and Control
Systems and Control
Trajectory optimization is a widely used tool in the design and control of dynamical systems. Typically, not only nonlinear dynamics, but also couplings of the initial and final condition through implicit boundary constraints render the optimization problem non-convex. This paper investigates how the Koopman operator framework can be utilized to solve trajectory optimization problems in a (partially) convex fashion. While the Koopman operator has already been successfully employed in model predictive control, the challenge of addressing mixed boundary constraints within the Koopman framework has remained an open question. We first address this issue by explaining why a complete convexification of the problem is not possible. Secondly, we propose a method where we transform the trajectory optimization problem into a bilevel problem in which we are then able to convexify the high-dimensional lower-level problem. This separation yields a low-dimensional upper-level problem, which could be exploited in global optimization algorithms. Lastly, we demonstrate the effectiveness of the method on two example systems: the mathematical pendulum and the compass-gait walker.
title Koopman Based Trajectory Optimization with Mixed Boundaries
topic Optimization and Control
Systems and Control
url https://arxiv.org/abs/2412.03195