This paper investigates the application of a novel Model Predictive Control structure for the drive system with an induction motor. The proposed controller has a cascade-free structure that consists of a vector of electromagnetics (torque, flux) and mechanical (speed) states of the system. The long-horizon version of the MPC is investigated in the paper. In order to reduce the computational complexity of the algorithm, an explicit version is applied. The influence of different factors (length of the control and predictive horizon, values of weights) on the performance of the drive system is investigated. The effectiveness of the proposed approach is validated by some experimental tests.
The article discusses changes in Polish regulations concerning assessment of the climate hazard in underground mines. Currently, the main empirical index representing the heat strain, used in qualification of the workplace to one of the climate hazard levels in Poland is the equivalent climate temperature. This simple heat index allows easy and quick assessment of the climate hazard. To a major extent, simple heat indices have simplifications and are developed for a specific working environments. Currently, the best methods used in evaluation of microclimate conditions in the workplace are those based on the theory of human thermal balance, where the physiological parameters characterising heat strain are body water loss and internal core temperature of the human body. The article describes the results of research on usage of equivalent climate temperature to heat strain evaluation in underground mining excavations. For this purpose, the numerical model of heat exchange between man and his environment was used, taken from PN-EN ISO 7933:2005. The research discussed in this paper has been carried out considering working conditions and clothing insulation in use in underground mines. The analyses performed in the study allowed formulation of conclusions concerning application of the equivalent climate temperature as a criterion of assessment of climate hazards in underground mines.
For building applications, woven fabrics have been widely used as finishing elements of room interior but not in particular aimed for sound absorbers. Considering the micro perforation of the woven fabrics, they should have potential to be used as micro-perforated panel (MPP) absorbers; some measurement results indicated such absorption ability. Hence, it is of importance to have a sound absorption model of the woven fabrics to enable us predicting their sound absorption characteristic that is beneficial in engineering design phase. Treating the woven fabric as a rigid frame, a fluid equivalent model is employed based on the formulation of Johnson-Champoux-Allard (JCA). The model obtained is then validated by measurement results where three kinds of commercially available woven fabrics are evaluated by considering their perforation properties. It is found that the model can reasonably predict their sound absorption coefficients. However, the presence of perturbations in pores give rise to inaccuracy of resistive component of the predicted surface impedance. The use of measured static flow resistive and corrected viscous length in the calculations are useful to cope with such a situation. Otherwise, the use of an optimized simple model as a function of flow resistivity is also applicable for this case.
A strip yield model implementation by the present authors is applied to predict fatigue crack growth observed in structural steel specimens under various constant and variable amplitude loading conditions. Attention is paid to the model calibration using the constraint factors in view of the dependence of both the crack closure mechanism and the material stress-strain response on the load history. Prediction capabilities of the model are considered in the context of the incompatibility between the crack growth resistance for constant and variable amplitude loading.
A novel VC (voice conversion) method based on hybrid SVR (support vector regression) and GMM (Gaussian mixture model) is presented in the paper, the mapping abilities of SVR and GMM are exploited to map the spectral features of the source speaker to those of target ones. A new strategy of F0 transformation is also presented, the F0s are modeled with spectral features in a joint GMM and predicted from the converted spectral features using the SVR method. Subjective and objective tests are carried out to evaluate the VC performance; experimental results show that the converted speech using the proposed method can obtain a better quality than that using the state-of-the-art GMM method. Meanwhile, a VC method based on non-parallel data is also proposed, the speaker-specific information is investigated using the SVR method and preliminary subjective experiments demonstrate that the proposed method is feasible when a parallel corpus is not available.
At the early stage of information system analysis and design one of the challenge is to estimate total work effort needed, when only small number of analysis artifacts is available. As a solution we propose new method called SAMEE – Simple Adaptive Method for Effort Estimation. It is based on the idea of polynomial regression and uses selected UML artifacts like use cases, actors, domain classes and references between them. In this paper we describe implementation of this method in Enterprise Architect CASE tool and show simple example how to use it in real information system analysis.