Compensation of Torque Ripple in High Performance BLDC Motor Drives

Brushless DC motor drives (BLDC) are finding expanded use in high performance applications where torque smoothness is essential. The nature of the square-wave current excitation waveforms in BLDC motor drives permits some important system simplifications compared to sinusoidal permanent magnet AC (PMAC) machines. However, it is the simplicity of the BLDC motor drive that is responsible for causing an additional source of ripple torque commonly known as commutation torque to develop. In this paper, a compensation technique for reducing the commutation torque ripple is proposed. With the experimental results, the proposed method demonstrates the effectiveness for a control system using the BLDC motors that requires high speed and accuracy

Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS

Background: Finding relevant articles from PubMed is challenging because it is hard to express the user's specific intention in the given query interface, and a keyword query typically retrieves a large number of results. Researchers have applied machine learning techniques to find relevant articles by ranking the articles according to the learned relevance function. However, the process of learning and ranking is usually done offline without integrated with the keyword queries, and the users have to provide a large amount of training documents to get a reasonable learning accuracy. This paper proposes a novel multi-level relevance feedback system for PubMed, called RefMed, which supports both ad-hoc keyword queries and a multi-level relevance feedback in real time on PubMed. Results: RefMed supports a multi-level relevance feedback by using the RankSVM as the learning method, and thus it achieves higher accuracy with less feedback. RefMed "tightly" integrates the RankSVM into RDBMS to support both keyword queries and the multi-level relevance feedback in real time; the tight coupling of the RankSVM and DBMS substantially improves the processing time. An efficient parameter selection method for the RankSVM is also proposed, which tunes the RankSVM parameter without performing validation. Thereby, RefMed achieves a high learning accuracy in real time without performing a validation process. RefMed is accessible at http://dm.postech.ac.kr/refmed. Conclusions: RefMed is the first multi-level relevance feedback system for PubMed, which achieves a high accuracy with less feedback. It effectively learns an accurate relevance function from the user's feedback and efficiently processes the function to return relevant articles in real time.1114Nsciescopu

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

Quality of service support for wireless networks

This dissertation addresses the issue of Quality of Service (QoS) support for wireless networks, especially IEEE802.11 wireless LANs, having time-varying capacity which makes the QoS support problem difficult. To provide guarantees of QoS parameters such as delay violation probability, packet loss probability due to buffer overflow, etc., for the wireless networks, we need to take into account not only input traffic characteristics, but also time-varying wireless channel characteristics. Considering the wireless channel characteristics, with the theoretical tool of large deviation theory we analyze the wireless Generalized Processor Sharing (GPS) scheme to provide stochastic performance guarantees for wireless LANs through the PCF mode which is based on a polling scheme, and propose connection admission schemes to admit as many connections as possible while satisfying QoS requirements of each connection. To increase the throughput and delay performance of the best-effort traffics such as the TCP traffics flowing through the wireless LANs we propose the H∞ AQM scheme for the congested queue which resides in the AP station, facing the wireless networks with time-varying channel capacity. We show superior performance of the proposed scheme in comparison with the ABED scheme through ns simulation results. For the cases where traffic or channel models are not available, we propose the adaptive bandwidth allocation scheme and the relative differentiated service architecture for wireless LANs, and show the experimental results obtained from the testbed in which the proposed schemes were implemented