Control loop for finding initial translator position of linear synchronous motor

This article presents a simple and reliable method for controlling the relative orientation between the two magnetic fields of a permanent magnet synchronous motor. Finding the initial (at motor powering- up time) value of this relative location is essential for the proper operation of the motor. After showing the system controllability, the utilized feedback control loop finds this initial relative orientation quickly and accurately. Further, using the proposed method allows considerable cost saving, as a transducer that is usually used for this purpose can be eliminated. The cost saving is most obvious in the case of linear motors and angle motors with large diameters. The way the problem is posed is an essential part of this work, and it is the reason behind the apparent simplicity of the solution. The method proposed relies on a single sensor, and it was tested when a relative encoder was used.

Controlling the relative orientation between the two magnetic fields of a synchronous motor

A simple and reliable method for controlling the relative orientation between the two magnetic fields of a permanent magnet synchronous motor is presented. Finding the initial (at motor powering-up time) value of this relative location is essential for the proper operation of the motor. The feedback control loop used finds this initial relative orientation quickly. Further, using the proposed method allows considerable cost saving, as a transducer that is usually used for this purpose can be eliminated. The cost saving is most obvious in the case of linear motors and angle motors with large diameters. The way the problem is posed is an essential part of this work and it is the reason behind the apparent simplicity of the solution. The method relied upon a single sensor, and it has been tested when a relative encoder was used

Towards a cyberspatial pedagogy : exploring synchronous online learning potentials

It has been a quarter of a century since William Gibson (1984) coined the term cyberspace in his seminal science fiction novel Neuromancer. Subsequently, a proliferation of online teaching technologies have emerged supporting Virilio’s (1991) contention that, “time and space have ceased to function as meaningful dimensions to human thought and action.” The aim of this presentation is to discuss and demonstrate the innovative modification of an online, synchronous learning environment, Elluminate Live! (eLive), which allows participants to transcend the spatial dimension. Specifically, we present an example of good practice which aimed to enhance student engagement by implementing a structured online tutorial series which replicated the entire first year psychology on-campus tutorial series in the eLive environment. We discuss Student Evaluation of Teaching and Units (SETU) results which support the utility of this pedagogic strategy. Finally, we outline various challenges for the virtual teacher who wishes to implement a structured learning program in the eLive environment.
Gibson, W 1984, Neuromancer, Ace Books, New York, USA.
Virilio, P 1991, The aesthetics of disappearance, Semiotext(e), New York, USA.

Voltage stability analysis with optimum size and location based synchronous machine DG

Power loss of a distribution system can be reduced significantly by using optimum size and location of distributed generation (DG). Proper allocation of DG with appropriate size maximizes overall system efficiency. Moreover it improves the reliability and voltage profile of the distribution system. In this paper, IEEE 123 node test feeder has been considered to determine the optimum size and location of a synchronous machine based DG for loss reduction of the system. This paper also investigates the steady-state and dynamic voltage profile of that three phase unbalance distribution network in presence of DG with optimum size. This analysis shows that optimum size of DG at proper location minimizes the power loss as well as improves the dynamic voltage profile of the distribution system.

A high performance position sensorless surface permanent magnet synchronous motor drive based on flux angle

A position sensorless Surface Permanent Magnet Synchronous Motor (SPMSM) drive based on flux angle is presented in this paper. The motor equations are written in rotor fixed d-q reference frame. A PID controller is used to process the speed error to generate the reference torque current keeping the magnetizing current fixed. The estimated stator flux using Recurrent Neural Network (RNN) is used to find out the rotor position. The flux angle and the reference current phasor angle are used in vector rotator to generate the reference phase currents. Hysteresis current controller block controls the switching of the 3-phase inverter to apply voltage to the motor stator. Simulation studies on different operating conditions indicate the acceptability of the drive system. The drive system only requires a speed transducer and is free from position sensor requirement. The proposed control scheme is robust under load torque disturbances and motor parameter variations. It is also simple and low cost to implement in a practical environment.

Synchronous Objects for One Flat Thing, reproduced

Synchronous Objects is a website where a visitor/ reader can investigate the interlocking systems of organisation in the choreography of William Forsythe's dance One Flat Thing, reproduced (2000). These systems were quantified through the collection of data and transformed into a series of objects - synchronous objects - that work in harmony to explore these choreographic structures, reveal their patterns and re-imagine what they might look like. The goal of the project was to create a learning platform to engage a broad public in this exploration of choreography, to explore cross-disciplinary research and to stimulate creative discovery for specialists and non-specialists alike.

A nonlinear adaptive backstepping approach for coordinated excitation and steam-valving control of synchronous generators

Steam-valving and excitation systems play an important role to maintain the transient stability of power systems with synchronous generators when power systems are subjected to large disturbances and sudden load changes. This paper presents a nonlinear adaptive backstepping approach for controlling excitation and steam-valving systems of synchronous generators. In this paper, the proposed excitation and steam-valving controllers are designed in a coordinated manner so that they can work under several and most severe operating conditions. Both excitation and steam-valving controllers are designed by considering some critical parameters as unknown. The effectiveness of the proposed coordinated control scheme is evaluated on a single machine infinite bus system under different operating conditions such as load changes and three-phase short circuit faults at the generator terminal. Finally, performance of the proposed scheme is compared to that of a similar nonlinear adaptive backstepping excitation controller without any coordination and simulation results demonstrate the superiority of the proposed one.

Nonlinear excitation control of synchronous generators based on adaptive backstepping method

n this paper, the design of a nonlinear excitation control of a synchronous generator is presented where the generator is connected to a single machine infinite bus (SMIB) system. An adaptive backstepping method is used to design the excitation controller with an objective of enhancing the overall dynamic stability of the SMIB system under different contingencies. In this paper, two types of contingencies are considered- i) unknown parameters and physical quantities during the controller design process and ii) controller performance evaluation under different system configurations such as three-phase short circuit faults. The adaption law, which is mainly based on the formulation of Lyapunov function, is used to estimate the unknown parameters which guarantee the convergence of different physical quantities of synchronous generators, e.g., the relative speed, terminal voltage, etc. The effectiveness of the proposed scheme is evaluated under different system configurations as mentioned in the second contingency and compared to that of an existing adaptive backstepping controller and a conventional power system stabilizer (PSS). Simulation results demonstrate the superiority of the proposed control scheme over the existing controllers.

Statistical modelling of artificial neural network for sorting temporally synchronous spikes

Artificial neural network (ANN) models are able to predict future events based on current data. The usefulness of an ANN lies in the capacity of the model to learn and adjust the weights following previous errors during training. In this study, we carefully analyse the existing methods in neuronal spike sorting algorithms. The current methods use clustering as a basis to establish the ground truths, which requires tedious procedures pertaining to feature selection and evaluation of the selected features. Even so, the accuracy of clusters is still questionable. Here, we develop an ANN model to specially address the present drawbacks and major challenges in neuronal spike sorting. New enhancements are introduced into the conventional backpropagation ANN for determining the network weights, input nodes, target node, and error calculation. Coiflet modelling of noise is employed to enhance the spike shape features and overshadow noise. The ANN is used in conjunction with a special spiking event detection technique to prioritize the targets. The proposed enhancements are able to bolster the training concept, and on the whole, contributing to sorting neuronal spikes with close approximations.

Modeling, parameter measurement and sensorless speed estimation of IPM synchronous generator for direct drive variable speed wind turbine application

This paper presents simple methods of determining parameters of interior permanent magnet (IPM) synchronous generator such as magnet flux (λM), d-axis inductance (Ld) and q-axis inductance (Lq) of IPM synchronous generator, which are used to control the wind turbine generator. These methods are simple and do not require any complex theory, signal injection or special equipment. Moreover, a sensorless speed estimator is proposed to estimate the speed of the generator without using speed sensor. The measured parameters are used in this speed estimator. The elimination of speed sensor will enhance the system robustness and reduce the design complexity and system cost for a small-scale wind turbine considered in this paper. The effectiveness of parameter measurement methods and sensorless speed estimator is demonstrated by experimental results. Experimental results show that the proposed speed estimator that uses the measured parameters can estimate the generator speed with a small error.

Building virtual learning communities

This chapter introduces the concept of virtual learning communities and discusses and further enhances the theory and definitions presented in related literature. A model comprising four criteria essential to virtual learning communities is presented and discussed in detail. Theory and case studies relating to the impact of virtual learning communities on distance education and students from diverse cultural groups are also examined. In addition, this chapter investigates the enabling technologies and facilitation that is required to build virtual learning communities. Other case studies are used to illustrate the process of building virtual learning communities. Emerging technologies such as wikis and video lectures are also analysed to determine the effects they have on building and sustaining effective virtual learning communities.

The role of trading partner relationships in determining innovation performance: an empirical examination

This paper examines the respective roles of trading partner relationships and innovation management practices in predicting product and process related innovation performance. The empirical data were drawn from 194 Australian managers. Data analysis using structural equation modelling indicates that supplier relationships and customer relationships have less impact on product and process innovation performance than do knowledge and creativity management. However, the results also indicate that trading partner relationships have a strong and positive association with innovation management practices, meaning that organisations commonly implement both in a synchronous manner.