Metastable States in Cellular Automata for Traffic Flow

Measurements on real traffic have revealed the existence of metastable states with very high flow. Such states have not been observed in the Nagel-Schreckenberg (NaSch) model which is the basic cellular automaton for the description of traffic. Here we propose a simple generalization of the NaSch model by introducing a velocity-dependent randomization. We investigate a special case which belongs to the so-called slow-to-start rules. It is shown that this model exhibits metastable states, thus sheding some light on the prerequisites for the occurance of hysteresis effects in the flow-density relation.Comment: 15 pages, 8 ps-figures included; accepted for publication in EPJ

Tunable magnetism on the lateral mesoscale by post-processing of Co/Pt heterostructures

Controlling magnetic properties on the nm-scale is essential for basic research in micro-magnetism and spin-dependent transport, as well as for various applications such as magnetic recording, imaging and sensing. This has been accomplished to a very high degree by means of layered heterostructures in the vertical dimension. Here we present a complementary approach that allows for a controlled tuning of the magnetic properties of Co/Pt heterostructures on the lateral mesoscale. By means of in-situ post-processing of Pt- and Co-based nano-stripes prepared by focused electron beam induced deposition (FEBID) we are able to locally tune their coercive field and remanent magnetization. Whereas single Co-FEBID nano-stripes show no hysteresis, we find hard-magnetic behavior for post-processed Co/Pt nano-stripes with coercive fields up to 850 Oe. We attribute the observed effects to the locally controlled formation of the CoPt L1$_{0}$ phase, whose presence has been revealed by transmission electron microscopy.Comment: Accepted for publication in Beilstein J. Nanotechno

Parameter reduction in nonlinear state-space identification of hysteresis

Hysteresis is a highly nonlinear phenomenon, showing up in a wide variety of science and engineering problems. The identification of hysteretic systems from input-output data is a challenging task. Recent work on black-box polynomial nonlinear state-space modeling for hysteresis identification has provided promising results, but struggles with a large number of parameters due to the use of multivariate polynomials. This drawback is tackled in the current paper by applying a decoupling approach that results in a more parsimonious representation involving univariate polynomials. This work is carried out numerically on input-output data generated by a Bouc-Wen hysteretic model and follows up on earlier work of the authors. The current article discusses the polynomial decoupling approach and explores the selection of the number of univariate polynomials with the polynomial degree, as well as the connections with neural network modeling. We have found that the presented decoupling approach is able to reduce the number of parameters of the full nonlinear model up to about 50\%, while maintaining a comparable output error level.Comment: 24 pages, 8 figure

Hysteresis Current Control Operation of Flying Capacitor Multilevel Inverter and Its Application in Shunt Compensation of Distribution Systems

Flying capacitor multilevel inverter (FCMLI) is a multiple voltage level inverter topology intended for high voltage and power operations with low distortion. It uses capacitors, called flying capacitors for clamping the voltage across the power semiconductor devices. In this paper, the implementation of a distribution static compensator (DSTATCOM) using an FCMLI is presented. A hysteresis current control technique for controlling the injected current by the FCMLI-based DSTATCOM is discussed. A new method for controlling the flying capacitor voltages is proposed which ensures that their voltages remain constant and at the same time maintain the desired current profile under the hysteresis current control operation. Simulation studies are performed using PSCAD/EMTDC to validate the efficacy of the control scheme and the FCMLI-based DSTATCOM

Design and Development of Low Torque Ripple Variable-Speed Drive System With Six-Phase Switched Reluctance Motors

Switched reluctance motor (SRM) drives conventionally use current control techniques at low speed and voltage control techniques at high speed. However, these conventional methods usually fail to restrain the torque ripple, which is normally associated with this type of machine. Compared with conventional three-phase SRMs, higher phase SRMs have the advantage of lower torque ripple: To further reduce their torque ripple, this paper presents a control method for torque ripple reduction in six-phase SRM drives. A constant instantaneous torque is obtained by regulating the rotational speed of the stator flux linkage. This torque control method is subsequently developed for a conventional converter and a proposed novel converter with fewer switching devices. Moreover, modeling and simulation of this six-phase SRM drive system has been conducted in detail and validated experimentally using a 4.0-kW six-phase SRM drive system. Test results demonstrate that the proposed torque control method has outstanding performance of restraining the torque ripple with both converters for the six-phase SRM, showing superior performance to the conventional control techniques

Memory-full context-aware predictive mobility management in dual connectivity 5G networks

Network densification with small cell deployment is being considered as one of the dominant themes in the fifth generation (5G) cellular system. Despite the capacity gains, such deployment scenarios raise several challenges from mobility management perspective. The small cell size, which implies a small cell residence time, will increase the handover (HO) rate dramatically. Consequently, the HO latency will become a critical consideration in the 5G era. The latter requires an intelligent, fast and light-weight HO procedure with minimal signalling overhead. In this direction, we propose a memory-full context-aware HO scheme with mobility prediction to achieve the aforementioned objectives. We consider a dual connectivity radio access network architecture with logical separation between control and data planes because it offers relaxed constraints in implementing the predictive approaches. The proposed scheme predicts future HO events along with the expected HO time by combining radio frequency performance to physical proximity along with the user context in terms of speed, direction and HO history. To minimise the processing and the storage requirements whilst improving the prediction performance, a user-specific prediction triggering threshold is proposed. The prediction outcome is utilised to perform advance HO signalling whilst suspending the periodic transmission of measurement reports. Analytical and simulation results show that the proposed scheme provides promising gains over the conventional approach