Matthias Reiner

Object-oriented modelling of wind turbines and its application for control design based on nonlinear dynamic inversion

ABSTRACT This article presents the object-oriented modelling of wind turbine aero-elastics. The article details the undertaken modelling approach and demonstrates its validity by comparing the results to a domain-specific simulation tool. The resulting object-oriented models can be generically adapted to meet different tasks or combined with models from other domains. Also the combination object-oriented Modelica and functional mock-up interface technology enable a rapid design of nonlinear controllers. As one possible application example, the article presents the model-based design of a corresponding controller. Its goal is to extend the turbine lifetime by reducing the structural loads. To this end, a modern control scheme is proposed that takes full advantage of the underlying object-oriented modelling approach. The controller is based on nonlinear dynamic inversion control methods combined with pseudo control hedging. The controller uses wind speed measurement information to adjust to wind gust load. Simulation-based comparisons to conventional control designs show a large potential reduction of the gust load on the wind turbine using the proposed controller.

Modeling and Feed-Forward Control of Structural Elastic Robots

In this paper an approach for modeling and control of robots with elasticities in power trains and in structural parts is presented and experimentally verified. For this purpose object‐oriented, nonlinear models are developed in the modeling language Modelica. A system theoretical study of the generated models shows that a direct inversion of the models, due to the unstable zero dynamics, is not possible. Therefore an algorithm for the approximate inversion is developed. With this inversion method an approximate inverse model considering structural elasticity for a 6‐axis robot is created and verified for the control of the robot. The new control leads to a considerable improvement of the driving characteristics of the robot in the experiment.

Application of Residual Generators to Detect Material Failure of a GFRP Transversal Leaf Spring

This paper discusses the application of residual generators to detect material failure of a vehicle transversal leaf spring made of glass-fiber reinforced plastic (GFRP). The residual generators are generated by symbolic nullspace computation and optimization based on linear parameter varying (LPV) models of the dynamics of the transversal leaf spring inside the vehicle. The fault detection method is verified using a complex, highly nonlinear vehicle model in combination with a modal transversal leaf spring model based on standard input data (SID), which is generated directly from finite element models (FEM).