Simulation and control of a stepping motor

Open-loop operatlon of the stepping motor exploits the inherent advantages of the machine. For near optimum operation: in this mode, however, an accurate system model is required to facilitate controller design. Such a model must be comprehensive and take account of the non-linearities inherent in the system. The result is a complex formulation which can be made manageable with a computational aid. A digital simulation of a hybrid type stepping motor and its associated drive circuit is proposed. The simulation is based upon a block diagram model which includes reasonable approximations to the major non-linearities. The simulation is shown to yield accurate performance predictions. The determination of the transfer functions is based upon the consideration of the physical processes involved rather than upon direct input-outout measurements. The effects of eddy currents, saturation, hysteresis, drive circuit characteristics and non-linear torque displacement characteristics are considered and methods of determining transfer functions, which take account of these effects, are offered. The static torque displacement characteristic is considered in detail and a model is proposed which predicts static torque for any combination of phase currents and shaft position. Methods of predicting the characteristic directly from machine geometry are investigated. Drive circuit design for high efficiency operation is considered and a model of a bipolar, bilevel circuit is proposed. The transfers between stator voltage and stator current and between stator current and air gap flux are complicated by the effects of eddy currents, saturation and hysteresis. Frequency response methods, combined with average inductance measurements, are shown to yield reasonable transfer functions. The modelling procedure and subsequent digital simulation is concluded to be a powerful method of non-linear analysis.

Public R&D policies and private R&D investment:a survey of the empirical evidence

The importance of R&D investment in explaining economic growth is well documented in the literature. Policies by modern governments increasingly recognise the benefits of supporting R&D investment. Government funding has, however, become an increasingly scarce resource in times of financial crisis and economic austerity. Hence, it is important that available funds are used and targeted effectively. This paper offers the first systematic review and critical discussion of what the R&D literature has to say currently about the effectiveness of major public R&D policies in increasing private R&D investment. Public policies are considered within three categories, R&D tax credits and direct subsidies, support of the university research system and the formation of high-skilled human capital, and support of formal R&D cooperations across a variety of institutions. Crucially, the large body of more recent literature observes a shift away from the earlier findings that public subsidies often crowd-out private R&D to finding that subsidies typically stimulate private R&D. Tax credits are also much more unanimously than previously found to have positive effects. University research, high-skilled human capital, and R&D cooperation also typically increase private R&D. Recent work indicates that accounting for non-linearities is one area of research that may refine existing results. © 2014 John Wiley & Sons Ltd.

On a Class of Elliptic Equations for the N-Laplacian in R^n with One-Sided Exponential Growth

2000 Mathematics Subject Classification: 35J40, 49J52, 49J40, 46E30

Fibre impairment compensation using artificial neural network equalizer for high-capacity coherent optical OFDM signals

We propose an artificial neural network (ANN) equalizer for transmission performance enhancement of coherent optical OFDM (C-OOFDM) signals. The ANN equalizer showed more efficiency in combating both chromatic dispersion (CD) and single-mode fibre (SMF)-induced non-linearities compared to the least mean square (LMS). The equalizer can offer a 1.5 dB improvement in optical signal-to-noise ratio (OSNR) compared to LMS algorithm for 40 Gbit/s C-OOFDM signals when considering only CD. It is also revealed that ANN can double the transmission distance up to 320 km of SMF compared to the case of LMS, providing a nonlinearity tolerance improvement of ∼0.7 dB OSNR.

The determinants of R&D investment: A survey of the empirical research

This paper offers an extensive survey and a critical discussion of the empirical literature on the driving factors of R&D. These factors are subsumed under five broad types. The paper first summarises the key predictions from theory regarding each type's R&D effect. It then examines for which factors differences in the theoretical predictions can also be found in empirical studies, and for which factors the empirical evidence is more unanimous. As the focus is on the empirical literature, methodological issues are also highlighted. The major factor types identified in the literature are, individual firm or industry characteristics, particularly internal finance and sales; competition in product markets; R&D tax credits and subsidies; location and resource related factors, such as spillovers from university research within close geographic proximity, membership of a research joint venture and cooperation with research centres, and the human capital embodied in knowledge workers; and spillovers from foreign R&D. Although on balance there is a consensus regarding the R&D effects of most factors, there is also variation in results. Recent work suggests that accounting for non-linearities is one area of research that may explain and encompass contradictory findings.

Ordering induced by chemical, thermal and mechanical constraints at solid interfaces

We know that classical thermodynamics even out of equilibrium always leads to stable situation which means degradation and consequently d sorder. Many experimental evidences in different fields show that gradation and order (symmetry breaking) during time and space evolution may appear when maintaining the system far from equilibrium. Order through fluctuations, stochastic processes which occur around critical points and dissipative structures are the fundamental background of the Prigogine-Glansdorff and Nicolis theory. The thermodynamics of macroscopic fluctuations to stochastic approach as well as the kinetic deterministic laws allow a better understanding of the peculiar fascinating behavior of organized matter. The reason for the occurence of this situation is directly related to intrinsic non linearities of the different mechanisms responsible for the evolution of the system. Moreover, when dealing with interfaces separating two immiscible phases (liquid - gas, liquid -liquid, liquid - solid, solid - solid), the situation is rather more complicated. Indeed coupling terms playing the major role in the conditions of instability arise from the peculiar singular static and dynamic properties of the surface and of its vicinity. In other words, the non linearities are not only intrinsic to classical steps involving feedbacks, but they may be imbedded with the non-autonomous character of the surface properties. In order to illustrate our goal we discuss three examples of ordering in far from equilibrium conditions: i) formation of chemical structures during the oxidation of metals and alloys; ii) formation of mechanical structures during the oxidation of metals iii) formation of patterns at a solid-liquid moving interface due to supercooling condition in a melt of alloy. © 1984, Walter de Gruyter. All rights reserved.

Correcting for bias when estimating the cost of hospital-acquired infection : an analysis of lower respiratory tract infections in non-surgical patients

Hospital acquired infections (HAI) are costly but many are avoidable. Evaluating prevention programmes requires data on their costs and benefits. Estimating the actual costs of HAI (a measure of the cost savings due to prevention) is difficult as HAI changes cost by extending patient length of stay, yet, length of stay is a major risk factor for HAI. This endogeneity bias can confound attempts to measure accurately the cost of HAI. We propose a two-stage instrumental variables estimation strategy that explicitly controls for the endogeneity between risk of HAI and length of stay. We find that a 10% reduction in ex ante risk of HAI results in an expected savings of £693 ($US 984).

A Petrov-Galerkin method for a singularly perturbed ordinary differential equation with non-smooth data

In this paper, a singularly perturbed ordinary differential equation with non-smooth data is considered. The numerical method is generated by means of a Petrov-Galerkin finite element method with the piecewise-exponential test function and the piecewise-linear trial function. At the discontinuous point of the coefficient, a special technique is used. The method is shown to be first-order accurate and singular perturbation parameter uniform convergence. Finally, numerical results are presented, which are in agreement with theoretical results.