Automated Model Generation and Observer Design for Interconnected Systems : A Port-Hamiltonian Approach

This work addresses the automated generation of physical-based models and model-based observers. We develop port-Hamiltonian methods, which for the first time allow a complete and consistent automation of these two processes for a large class of interconnected systems

Leverage ratio and its impact on the resilience of the banking sector and efficiency of macroprudential policy

Basel III responded to the financial crisis by redefining and expanding the capital requirements for risk-weighted assets and by proposing the introduction of a leverage ratio which sets a minimum level of capital for banks in relation to total exposures. The capital requirement is being increased primarily through the active use of macroprudential capital buffers. As a result, it was proposed that the leverage ratio requirement should also take into account the level of capital buffers and thus become a macroprudential policy tool. This article examines the relationship between capital and leverage ratios and discusses the options for, and effects of, introducing a macroprudential leverage ratio. We find that the capital and leverage ratios complement each other and that the introduction of a macroprudential leverage ratio could, under certain circumstances, enhance the effectiveness of a macroprudential policy.Web of Science67429927

Automated archiving of archaeological aerial images

The main purpose of any aerial photo archive is to allow quick access to images based on content and location. Therefore, next to a description of technical parameters and depicted content, georeferencing of every image is of vital importance. This can be done either by identifying the main photographed object (georeferencing of the image content) or by mapping the center point and/or the outline of the image footprint. The paper proposes a new image archiving workflow. The new pipeline is based on the parameters that are logged by a commercial, but cost-effective GNSS/IMU solution and processed with in-house-developed software. Together, these components allow one to automatically geolocate and rectify the (oblique) aerial images (by a simple planar rectification using the exterior orientation parameters) and to retrieve their footprints with reasonable accuracy, which is automatically stored as a vector file. The data of three test flights were used to determine the accuracy of the device, which turned out to be better than 1° for roll and pitch (mean between 0.0 and 0.21 with a standard deviation of 0.17–0.46) and better than 2.5° for yaw angles (mean between 0.0 and −0.14 with a standard deviation of 0.58–0.94). This turned out to be sufficient to enable a fast and almost automatic GIS-based archiving of all of the imagery

Accuracy analysis of direct georeferenced UAV images utilising low-cost navigation sensors

Unmanned aerial vehicles (UAVs), also known as unmanned airborne systems (UAS) or remotely piloted airborne systems (RPAS), are an established platform for close range airborne photogrammetry. Compared to manned platforms, the acquisition of local remote sensing data by UAVs is a convenient and very flexible option. For the application in photogrammetry UAVs are typically equipped with an autopilot and a lightweight digital camera. The autopilot includes several navigation sensors, which might allow an automated waypoint flight and offer a systematic data acquisition of the object resp. scene of interest. Assuming a sufficient overlap between the captured images, the position (3 coordinates: x, y, z) and the orientation (3 angles: roll, pitch, yaw) of the images can be estimated within a bundle block adjustment. Subsequently, coordinates of observed points that appear in at least two images, can be determined by measuring their image coordinates or a dense surface model can be generated from all acquired images by automated image matching. For the bundle block adjustment approximate values of the position and the orientation of the images are needed. To gather this information, several methods exist. We introduce in this contribution one of them: the direct georeferencing of images by using the navigation sensors (mainly GNSS and INS) of a low-cost on-board autopilot. Beside automated flights, the autopilot offers the possibility to record the position and the orientation of the platform during the flight. These values don’t correspond directly to those of the images. To compute the position and the orientation of the images two requirements must be fulfilled. First the misalignment angles and the positional differences between the camera and the autopilot must be determined (mounting calibration). Second the synchronization between the camera and the autopilot has to be established. Due to the limited accuracy of the navigation sensors, a small number of ground control points should be used to improve the estimated values, especially to decrease the amount of systematic errors. For the bundle block adjustment the calibration of the camera and their temporal stability must be determined additionally. This contribution presents next to the theory a practical study on the accuracy analysis of direct georeferenced UAV imagery by low-cost navigation sensors. The analysis was carried out within the research project ARAP (automated (ortho)rectification of archaeological aerial photographs). The utilized UAS consists of the airplane “MAJA”, manufactured by “Bormatec” (length: 1.2 m, wingspan: 2.2 m) equipped with the autopilot “ArduPilot Mega 2.5”. For image acquisition the camera “Ricoh GR Digital IV” is utilised. The autopilot includes a GNSS receiver capable of DGPS (EGNOS), an inertial measurement system (INS), a barometer, and a magnetometer. In the study the achieved accuracies for the estimated position and orientation of the images are presented. The paper concludes with a summary of the remaining error sources and their possible corrections by applying further improvements on the utilised equipment and the direct georeferencing process

Full- & Reduced-Order State-Space Modeling of Wind Turbine Systems with Permanent-Magnet Synchronous Generator

Wind energy is an integral part of nowadays energy supply and one of the fastest growing sources of electricity in the world today. Accurate models for wind energy conversion systems (WECSs) are of key interest for the analysis and control design of present and future energy systems. Existing control-oriented WECSs models are subject to unstructured simplifications, which have not been discussed in literature so far. Thus, this technical note presents are thorough derivation of a physical state-space model for permanent magnet synchronous generator WECSs. The physical model considers all dynamic effects that significantly influence the system's power output, including the switching of the power electronics. Alternatively, the model is formulated in the $(a,b,c)$- and $(d,q)$-reference frame. Secondly, a complete control and operation management system for the wind regimes II and III and the transition between the regimes is presented. The control takes practical effects such as input saturation and integral windup into account. Thirdly, by a structured model reduction procedure, two state-space models of WECS with reduced complexity are derived: a non-switching model and a non-switching reduced-order model. The validity of the models is illustrated and compared through a numerical simulation study.Comment: 23 pages, 11 figure