Kiri Fr. von Matthisson'ile

Lichtenberg, Georg Christoph, 1742-1799, saksa filosoof ja loodusteadlane, Peterburi TA liigeMatthisson, Friedrich von, 1761-1831, saksa kirjanikSelgitab eksitust, mis tekkis adressaadiga kohtumise

An Approach to State Signal Shaping by Limit Cycle Model Predictive Control

A novel nonlinear model predictive control approach for state signal shaping is proposed. The control strategy introduces a residual shape cost kernel based on the dynamics of circular limit cycles from a supercritical Neimark-Sacker bifurcation normal form. This allows the controller to impose a fundamental harmonic state signal shape with a specific frequency and amplitude. An application example for harmonic compensation in distribution grids integrated with renewable energies is presented. The controller is tasked with the calculation of the reference current for an active power filter used for load compensation. The results achieved are successful, reducing the harmonic distortion to satisfactory levels while ensuring the correct frequency and amplitude.Comment: \copyright 2020 Carlos Cateriano Y\'a\~nez, Gerwald Lichtenberg, Georg Pangalos and Javier Sanchis S\'aez. This work has been accepted to IFAC for publication under a Creative Commons Licence CC-BY-NC-N

Classical and quantum dynamics of the n-dimensional kicked rotator

The classical and quantum dynamics for an n-dimensional generalization of the kicked planar (n=1) rotator in an additional effective centrifugal potential. Therefore, typical phenomena like the diffusion in classical phase space are similar to that of the one-dimensional model. For the quantum dynamics such a result is not expected as in this case the evolution does depend in a very complicated way on the number n of degrees of freedom. In the limit n --> infinity we find the free undistrubed quantum motion. For finite values of n (1<=n<=26) we study numerically the quantum dynamics. Here, we always find localization independent of the actual number of degrees of freedom.Comment: uuencoded gzipped postscript file, Problem in postscript file resolved. For uncompressed postscript file see http://faupt101.physik.uni-erlangen.de/junker/papers95.ht

Active Power Filter Shape Class Model Predictive Controller tuning by Multiobjective Optimization

[EN] In order to compensate the power quality issues that arise in distribution grids with high penetration of renewable energy sources, an active power filter device controlled by a novel model-based predictive controller, i.e. the linear state signal shaping model predictive controller, is implemented. This paper proposes the use of a Multiobjective Optimization evolutionary algorithm, i.e. the Multiobjective Differential Evolution with Spherical Pruning X, for the tuning of this novel controller. An application example for power quality compensation of a grid modeled as a switched system with four modes is given. The model includes nonlinear loads that introduce harmonic distortion and multiple consumer loads that enable the existence of conflicting objectives, typical of multiobjective optimization problems. A decision making strategy is developed in order to find the best controller parameters in a reasonable amount of time that enable the provision of optimal power quality services by balancing multiple objectives that can conflict with each other.This contribution was partly developed within the project NEW 4.0 (North German Energy Transition 4.0) which is funded by the German Federal Ministry for Economic Affairs and Energy (BMWI). This paper was also partly funded by the Free and Hanseatic City of Hamburg (Hamburg City Parliament publication 20/11568).Cateriano Yáñez, C.; Richter, J.; Pangalos, G.; Lichtenberg, G.; Sanchís Saez, J. (2019). Active Power Filter Shape Class Model Predictive Controller tuning by Multiobjective Optimization. En Proceedings 5th CARPE Conference: Horizon Europe and beyond. Editorial Universitat Politècnica de València. 79-86. https://doi.org/10.4995/CARPE2019.2019.10166OCS798

Improving comparability between microarray probe signals by thermodynamic intensity correction

Signals from different oligonucleotide probes against the same target show great variation in intensities. However, detection of differences along a sequence e.g. to reveal intron/exon architecture, transcription boundary as well as simple absent/present calls depends on comparisons between different probes. It is therefore of great interest to correct for the variation between probes. Much of this variation is sequence dependent. We demonstrate that a thermodynamic model for hybridization of either DNA or RNA to a DNA microarray, which takes the sequence-dependent probe affinities into account significantly reduces the signal fluctuation between probes targeting the same gene transcript. For a test set of tightly tiled yeast genes, the model reduces the variance by up to a factor ∼1/3. As a consequence of this reduction, the model is shown to yield a more accurate determination of transcription start sites for a subset of yeast genes. In another application, we identify present/absent calls for probes hybridized to the sequenced Escherichia coli strain O157:H7 EDL933. The model improves the correct calls from 85 to 95% relative to raw intensity measures. The model thus makes applications which depend on comparisons between probes aimed at different sections of the same target more reliable