Technological progress leads to an on-going improvement of products in view of functionality, energy consumption or safety at the cost of increased complexity of tasks to be performed. The aim to achieve optimal performance of a process is getting more and more difficult to achieve as the number of parameters that influence the performance of the process is constantly increasing. The high complexity typically prohibits an optimization by hand and instead requires automatic optimization procedures and efficient optimization software, such as the ESA NLP solver WORHP (We Optimize Really Huge Problems). It is specifically designed to solve large-scale nonlinear optimization problems with several hundred thousand or even millions of optimization parameters and already satisfies many of the Clean Sky requirements. The purpose of this project is to adapt WORHP to aviation objectives and constraints with the aim to obtain an even more robust and efficient European NLP solver.
The project is divided into three parts.
- Part 1 addresses theoretical foundations and structural definitions of the optimization problems to be considered. This includes a study of problems that are typical for aeronautics applications.
- Part 2 is concerned with the implementation of extensions towards trajectory optimization (optimal control) in the existing solver WORHP and its companion transcriptor TransWORHP.
- A detailed test campaign on commonly used test sets like CUTEr and on testcases from aviation industry is performed in part 3.
The implemented algorithms will be tested in a systematic way on the previously defined test-sets in order to assess the robustness and efficiency of the algorithm. The results of the test campaign will be used to refine the algorithm. The developed software will be documented, validated and tested. Suitable interfaces to existing software packages will be provided.
Final Report Summary - AWACS (Adaption of WORHP to Avionics Constraints)
Achieving optimal performance of technical processes is increasingly difficult, as the number of parameters that influence their performance continues to grow, driven by overall technological progress. The high complexity typically prohibits manual optimisation and instead requires automatic optimisation procedures by mathematical software, such as the European NLP solver WORHP (We Optimize Really Huge Problems). It is specifically designed to solve large-scale nonlinear optimisation problems with several hundred thousand or even millions of optimisation parameters.
The purpose of the EU CleanSky project “AWACs” was to adapt WORHP to aviation objectives and constraints with the aim to increase its robustness and thus to enable new technologies in the overall field of aerospace engineering. Among others, the project tackled the following particular issues:
- Improve performance, i.e. have the solver produce optimal solutions in less computational time. This is relevant when the solver is run on resource-constrained hardware, such as the so-called Electronic Flight Bags (EFBs), which are essentially laptops or tablet computers used by pilots to plan their flight.
- Improve robustness, i.e. prevent breakdowns of the optimisation process, e.g. if the computer model of the aircraft suffers from technical problems in certain states that are evaluated by the solver.
- Ensure the solver is interruptible, so an application can stop it to work with a suboptimal solution, rather than waiting for an optimal one; this is of interest if time budgets are limited.
- Handle multiple objectives, so-called cost functions, which describe how “good” a particular solution is. Aircraft operation (like virtually every application) has various, partially competing objectives, such as fuel consumption, noise generation, overall flight time or generation of contrails. Being able to handle them in a comprehensive way can help aircraft operators achieve better solutions.
- Validate that the solver is able to solve realistic aviation problems, and document its performance.
The project achieved its core objectives: WORHP satisfies all functional and technical requirements and is able to solve 11 of the 12 evaluated aircraft trajectory optimisation problems more than the other considered solvers Ipopt (9 of 12) and SNOPT (7 of 12). Performance testing demonstrated a reduction in required CPU time of 60%, and an overall success rate close to 96% for the standard optimisation test set “CUTEst”.
The work in this project was shared between a consortium of four partners: Steinbeis Innovationszentrum für Optimierung, Steuerung und Regelung at Universität Bremen, the Operations Research group at the University of Southampton, Steinbeis Innovationszentrum für Optimierung, Steuerung und Regelung at Universität der Bundeswehr München and the Institute of Flight System Dynamics at the Technische Universität München. The Topic Managers role with respect to this project covers statement of the problem, feedback on deliverables and integration of the results into CleanSky SGO activities.