Publication

laOPT: A Native C++ Optimal Control Toolbox for High-Performance Implementations, and Application to Racing

2026

Abstract

We present laOPT, a native C++ toolbox for highperformance optimal control applications. The optimal control problem formulated by the user through an intuitive highlevel interface is transcribed into a nonlinear program (NLP). laOPT offers solver interfaces to interior point and sequential quadratic programming (SQP) methods. In particular, the laOPT SQP solver can interface with various established QP solvers. Thanks to template programming, C++ compilers can optimize the solver executable for maximum runtime performance. We demonstrate the capabilities of laOPT on a highspeed mini race car experiment and benchmark against stateof-the-art optimization packages.

Official source

https://infoscience.epfl.ch/entities/publication/3da2cc1c-2af0-4904-8313-48fb578c1851

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

2026

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/3da2cc1c-2af0-4904-8313-48fb578c1851

About this result

Related concepts (20)

Nonlinear programming

In mathematics, nonlinear programming (NLP) is the process of solving an optimization problem where some of the constraints or the objective function are nonlinear. An optimization problem is one of calculation of the extrema (maxima, minima or stationary points) of an objective function over a set of unknown real variables and conditional to the satisfaction of a system of equalities and inequalities, collectively termed constraints. It is the sub-field of mathematical optimization that deals with problems that are not linear.

Sequential quadratic programming

Sequential quadratic programming (SQP) is an iterative method for constrained nonlinear optimization which may be considered a quasi-Newton method. SQP methods are used on mathematical problems for which the objective function and the constraints are twice continuously differentiable. SQP methods solve a sequence of optimization subproblems, each of which optimizes a quadratic model of the objective subject to a linearization of the constraints.

Template metaprogramming

Template metaprogramming (TMP) is a metaprogramming technique in which templates are used by a compiler to generate temporary source code, which is merged by the compiler with the rest of the source code and then compiled. The output of these templates can include compile-time constants, data structures, and complete functions. The use of templates can be thought of as compile-time polymorphism. The technique is used by a number of languages, the best-known being C++, but also Curl, D, Nim, and XL.

Related publications (13)

laOPT: A Native C++ Optimal Control Toolbox for High-Performance Implementations, and Application to Racing

Chat with Graph Search

Learning stabilising policies for constrained nonlinear systems

Parameterized algorithms for block-structured integer programs with large entries

AC-OPF-based Joint Optimal Sizing and Siting of Electric Vehicle Charging Stations and Photovoltaic Plants in Coupled Traffic-Power Networks