On this page you will find different software tools created at the Institute of Flight System Dynamics at Technische Universität München. The tools have been created as a result of the research conducted at the Institute. To promote the scientific progress in their research fields the tools are made available to the scientific community under specific licensing conditions. Please find more information about our software and the terms and conditions in the list below and don’t hesitate to contact their developers for questions, comments or suggestions.
FALCON.m is a free optimal control tool developed at the Institute of Flight System Dynamics at TUM. It provides a MATLAB class library in order to set-up, solve and analyze optimal control problems using numerical optimization methods. The tool is optimized for usability and performance and enables the solution of high fidelity real-life optimal control problems with ease. Learn more about FALCON.m.
SimPol is a free MATLAB® toolbox to create, maintain, and verify bi-directional traceability between Polarion® ALM products and MATLAB® Simulink®, Stateflow®, as well as Simulink® Test™. It is specifically designed to support model-based software development workflows, which must be compliant to common standards like DO-178C/DO-331 or ISO 26262. The tool supports generation of requirement allocation files and different linking modes like direct linking or the creation of a shadow model in Polarion®. Trace analysis helps to detect and repair broken links, identify missing coverage, and review the implementation or test cases of supspected requirements. Learn more and download SimPol here.
osgVisual is a C++ OpenGL toolkit which is based on OpenSceneGraph. It provides high level visualization functions for scientific visualization and vehicle simulators like flight simulators. It is primarily developed to act as visual system on the research flight simulator at the Institute of Flight System Dynamics, TU München, but can be used with minimal adaption in other visualization purposes. Learn more about osgVisual here.
Subset Simulation Toolbox for MATLAB®
This modular toolbox implements an algorithm for Subset Simulation (SuS) using Markov-chain Monte Carlo (MCMC) sampling. This is a more efficient way to estimate rare failure events than traditional Monte Carlo (MC) simulations, where you would need to simulate an exponential number of samples for diminishing event probabilities.
Simulation Accelerator Toolbox for MATLAB®
This toolbox presents an abstraction layer that can be put in front of our Subset Simulation Toolbox to simplify and speed up subset simulations with Simulink models. In short, it contains a custom code generation and compilation process that produces a binary simulation target that is optimised for speed in the context of subset simulation.
The details of the inner workings and architecture are captured in the user manual and publication linked above. In short summary, it might give you 5–15⨉ faster simulation results when you iterate Monte Carlo samples than what you are able to achieve using the standard simulation tools.