Mathias Hakenberg

Model Reduction and Control of a Compressible Channel Flow with Combustion

Abstract A model reduction for a compressible flow with combustion is performed using the POD-Galerkin procedure. The model parameters are determined by an optimization. The obtained reduced-order model is incorporated in a model predictive controller and results are shown from a closed-loop CFD-simulation. The controller influences the fuel mass-flow boundary condition to control the temperature at a certain point within the computational domain.

An extended inertia and eigenfrequency emulation for full-scale wind turbine nacelle test benches

The main causes of wind turbines failures are mechanical and electrical drive train components [1]. Since isolated simulation studies seem not to sufficiently reproduce load situations in the fully assembled and operated system, wind industry pays more and more attention to wind turbine System Test Benches. They allow for detailed load analysis within the complete drive train system and also for controller tests. For both investigations drive train dynamics of the wind turbine generator (WTG) are of high relevance. This dynamic behavior is mainly determined by the rotors inertia which, due to its size, has to be dismounted for System Test Bench tests. By that, the dynamics of the remaining drive train change significantly. In order to still operate the WTG controller without modifying it and to allow for representative load analysis a Hardware-in-the-Loop (HiL) Controller needs to reproduce the realistic drive train behavior at the System Test Bench. This paper proposes a control concept which emulates the missing rotor related inertia as well as the drive train and the coupled rotor-drive train related eigenfrequencies which are both crucial for load analysis as well as controller tests. The proposed concept consists of a virtual spring-damper-system combined with a subsidiary state feedback controller. The controller synthesis is conducted using a quadratic norm. The simulation results show that the eigenfrequencies can be reproduced with less than 2% error. When time-discrete operation is considered, the results are slightly downgraded, so that alternative synthesis procedures need to be investigated in the future. The method proposed in this paper is based upon an experimentally verified inertia emulation method [2]. Furthermore the simulation models used throughout this simulation study are experimentally validated models of a 1MW System Test Bench [3] at the Center for Wind Power Drives of RWTH Aachen University.

Use of electronically linked konvoi truck platoons on motorways

In the framework of the Konvoi Project, a consortium amongst of RWTH Aachen University institutes, MAN Nutzfahrzeuge AG and Wabco Development GmbH developed four experimental vehicles in order to investigate the effects of electronically coupled commercial vehicles in real traffic. This article describes the system architecture, the development process and the results of the runs in public traffic.

Einsatz Elektronisch Gekoppelter LKW-Konvois auf Autobahnen

Im Rahmen des Konvoi-Projekts wurden von einem Konsortium aus Instituten der RWTH Aachen University, der MAN Nutzfahrzeuge AG und der Wabco Development GmbH vier Versuchstrager aufgebaut, um die Auswirkungen von elektronisch gekoppelten Nutzfahrzeugen im realen Verkehr zu untersuchen. Der vorliegende Beitrag beschreibt die Architektur des aufgebauten Systems, den Entwicklungsprozess und die Ergebnisse der Fahrten im offentlichen Verkehr.

Lateral guidance of heavy-duty vehicle platoons using model-based predictive control

Abstract Heavy-duty vehicle platoons are a possible future form of organising goods traffic. Only the leading vehicle is manually driven while all the following vehicles are automatically controlled in longitudinal and lateral direction. This paper presents a concept for the generation of reference variables as well as for a model-based predictive control (MPC) scheme to be used for the lateral control within the path tracking. It enables the following vehicles to track the path of the leading vehicle directly by using on-board sensors as well as the existing communication structure of the platoon. It is shown that the presented control concept is feasible and it is evaluated in simulations of tractor-semitrailer platoons using Matlab/Simulink. The results demonstrate the effectiveness of the reference generation as well as of the proposed MPC control scheme. The application to real vehicles will be part of the current project KONVOI at RWTH Aachen.

Frequency-Selective Galerkin Models for Turbulent Boundary Layer Drag Reduction

Abstract Galerkin models for 3D-turbulent boundary layers usually are too complex to be successfully incorporated into model based control strategies. Limiting the frequency spectrum of the ensemble data offers a possibility to reduce the model size and still map the control-relevant dynamics into the reduced-order model. An adaptation of the standard POD-Galerkin procedure is proposed using the example of a turbulent boundary layer, which is actuated by a periodic volume force. A closed-loop simulation shows an exemplary application of such a reduced order model in a model based control setup.

Model Predictive Wind Turbine Control with Move-Blocking Strategy for Load Alleviation and Power Leveling

This contribution presents a Model Predictive Controller (MPC) with moveblocking strategy for combined power leveling and load alleviation in wind turbine operation with a focus on extreme loads. The controller is designed for a 3 MW wind turbine developed by W2E Wind to Energy GmbH and compared to a baseline controller, using a classic control scheme, which currently operates the wind turbine. All simulations are carried out with a detailed multibody simulation turbine model implemented in alaska/Wind. The performance of the two different controllers is compared using a 50-year Extreme Operation Gust event, since it is one of the main design drivers for the wind turbine considered in this work. The implemented MPC is able to level electrical output power and reduce mechanical loads at the same time. Without de-rating the achieved control results, a move-blocking strategy is utilized and allowed to reduce the computational burden of the MPC by more than 50% compared to a baseline MPC implementation. This even allows to run the MPC on a state of the art Programmable Logic Controller.

Model predictive control of Burgers equation based on Galerkin models

A feedback control design for Burgers equation is proposed using a model predictive control approach. A low-order POD Galerkin model derived from a numerical simulation of Burgers equation is used as internal controller model. The reduced-order model accurately predicts the system dynamics as a function of the actuated Dirichlet boundary condition. Closed-loop simulations for reference tracking of a single point inside the computational domain are shown for the ideal case and also in the presence of additional disturbance and measurement noise.

Boundary Actuation in Galerkin-Models of Linear Distributed Parameter Systems

Abstract Proper orthogonal decomposition and subsequent Galerkin-projection is a common technique to obtain low-dimensional models for distributed parameter systems. In this paper a transformation of boundary conditions into equivalent source terms for linear partial differential equations is used to set up such reduced-order models. This approach provides the means to consider boundary actuation in Galerkin-models, which is essential for the design of feedback controllers. Using the example of a one-dimensional convection-diffusion equation, the transient dynamics between the non-actuated and actuated steady state are described with such a reduced-order-model. Dynamic range and model accuracy are investigated in connection with the employed number of POD modes and the dynamics of actuation.