Tools for Design and Simulation of UAV Flight Control

Kurzfassung

High performance and robustness requirements for autonomous UAV flight control systems and stringent requirements for short and cost effective design cycles increase the necessity for an efficient computer aided control law design process using advanced control design methods and tools. This paper describes a model and optimization based flight control law design process, which can be applied to a wide range of vehicle classes. The design process is based on multi-physical, object-oriented flight dynamics modeling using the modeling language Modelica and on a multi-objective parameter optimization environment. A generic Modelica flight dynamics library allows modular composition of new parameterized vehicle models and efficient simulation code generation for specific use cases. Multi-objective optimization is used for tuning the free parameters in linear or nonlinear flight control laws. Thereby, given require-ments for stability, trading structural loads and other physical limitations are formulated as computational design criteria. Robustness to uncertain parameters can be addressed via robustness measures, via a multi-model and multi-case approach, and via statistical Monte-Carlo based criteria. In the assessment step of the design process worst-case optimization w.r.t. uncertain parameters is applied for systematically detecting weaknesses of the control law design. The successful application of the design process to civil transport and high performance military aircraft is demonstrated and the applicability for UAV flight control design is discussed