Geometric integrators for higher-order variational systems and their application to optimal control

TL;DR

This paper develops symplectic-momentum integrators for higher-order Lagrangian systems that preserve geometric invariants, with applications to optimal control problems formulated as second-order variational problems.

Contribution

It introduces a method to construct variational integrators for higher-order systems that preserve invariants and applies these techniques to optimal control.

Findings

Constructed implicit symplectic-momentum integrators for higher-order systems.

Preserved geometric invariants like energy and momentum in numerical simulations.

Applied integrators to optimal control problems modeled as second-order variational systems.

Abstract

Numerical methods that preserve geometric invariants of the system, such as energy, momentum or the symplectic form, are called geometric integrators. In this paper we present a method to construct symplectic-momentum integrators for higher-order Lagrangian systems. Given a regular higher-order Lagrangian $L\colon T^{(k)}Q\to\mathbb{R}$ with $k\geq 1$, the resulting discrete equations define a generally implicit numerical integrator algorithm on $T^{(k-1)}Q\times T^{(k-1)}Q$ that approximates the flow of the higher-order Euler--Lagrange equations for $L$. The algorithm equations are called higher-order discrete Euler--Lagrange equations and constitute a variational integrator for higher-order mechanical systems. The general idea for those variational integrators is to directly discretize Hamilton's principle rather than the equations of motion in a way that preserves the invariants of the original system, notably the symplectic form and, via a discrete version of Noether's theorem, the momentum map. We construct an exact discrete Lagrangian $L_d^e$ using the locally unique solution of the higher-order Euler--Lagrange equations for $L$ with boundary conditions. By taking the discrete Lagrangian as an approximation of $L_d^e$, we obtain variational integrators for higher-order mechanical systems. We apply our techniques to optimal control problems since, given a cost function, the optimal control problem is understood as a second-order variational problem.