Fuzzy logic controller and cascade inverter for direct torque control of IM

In this paper, a five-level cascaded H-bridge multilevel inverters topology is applied on induction motor control known as direct torque control (DTC) strategy. More inverter states can be generated by a five-level inverter which improves voltage selection capability. This paper also introduces two different control methods to select the appropriate output voltage vector for reducing the torque and flux error to zero. The first is based on the conventional DTC scheme using a pair of hysteresis comparators and look up table to select the output voltage vector for controlling the torque and flux. The second is based on a new fuzzy logic controller using Sugeno as the inference method to select the output voltage vector by replacing the hysteresis comparators and lookup table in the conventional DTC, to which the results show more reduction in torque ripple and feasibility of smooth stator current. By using Matlab/Simulink, it is verified that using five-level inverter in DTC drive can reduce the torque ripple in comparison with conventional DTC, and further torque ripple reduction is obtained by applying fuzzy logic controller. The simulation results have also verified that using a fuzzy controller instead of a hysteresis controller has resulted in reduction in the flux ripples significantly as well as reduces the total harmonic distortion of the stator current to below 4 %.     

Preparation and characterization of poly(vinyl alcohol)/gum tragacanth/cellulose nanocomposite film

The effects of gum tragacanth obtained from two species of Astragalus Gossypinus (GT-G) and A. Parrowianus (GT-P) at two levels of 10% and 30% combined with cellulose nanofibers (CNF; 5%) on the physico-mechanical and structural properties of polyvinyl alcohol (PVA) nanocomposite film were investigated in this study. The water solubility and water vapor permeability of the films decreased with increasing the content of both gums, especially in the film containing 30% GT-P. The highest values of the tensile strength (39.3 MPa) and elongation at break (445%) belonged to the treatment containing 10% GT-P (90/10P/0). The FTIR and DSC analyses confirmed good interactions between GT and PVA in the 90/10P/0 treatment. SEM images indicated the dense structure of this film as the optimum treatment. Although the presence of CNF in the films containing GT-G improved some properties, especially the Young modulus, it impaired all the functional properties of nanocomposite GT-P film.     

Analysis and forecasting of IPO underpricing

Probability of withdrawal is a feature of initial public offering (IPOs), which can be an important parameter in decisions of investors and issuers. Considering the probability of offering withdrawal facilitates more precise estimation of underpricing. In this paper, the effective factors on probability of IPO withdrawal and underpricing in Tehran Stock Exchange have been characterized using regression, and then neural network is applied to estimate the probability of IPO withdrawal and underpricing. To evaluate the performance of our applied method, fuzzy regression is employed and compared with neural network. According to the obtained empirical results, neural network demonstrates better accuracy than fuzzy regression. The results indicate that there is a meaningful relationship between underpricing and probability of withdrawal, and the probability of IPO withdrawal plays an important role in precise evaluation of underpricing.     

Integrated Inspection Scheduling and Maintenance Planning for Infrastructure Systems

Operation and maintenance of an infrastructure system rely on information collected on its components, which can provide the decision maker with an accurate assessment of their condition states. However, resources to be invested in data gathering are usually limited and observations should be collected based on their Value of Information (VoI). Assessing the VoI is computationally intractable for most applications involving sequential decisions, such as long‐term infrastructure maintenance. In this article, we propose an approach for integrating adaptive maintenance planning based on Partially Observable Markov Decision Process (POMDP) and inspection scheduling based on a tractable approximation of VoI. Two alternative myopic approaches, namely pessimistic and optimistic, are introduced, and compared theoretically and by numerical examples.     

Adaptive neural dynamic surface control of MIMO stochastic nonlinear systems with unknown control directions

In this paper, an adaptive neural output‐feedback control approach is considered for a class of uncertain multi‐input and multi‐output (MIMO) stochastic nonlinear systems with unknown control directions. Neural networks (NNs) are applied to approximate unknown nonlinearities, and K‐filter observer is designed to estimate unavailable system's states. Due to utilization of Nussbaum gain function technique in the proposed approach, the singularity problem and requirement to prior knowledge about signs of high‐frequency gains are removed, simultaneously. Razumikhin functional method is employed to deal with unknown state time‐varying delays, so that the offered control approach is free of common assumptions on derivative of time‐varying delays. Also, an adaptive neural dynamic surface control is developed; hence, explosion of complexity in conventional backstepping method is eliminated, effectively. The boundedness of all the resulting closed‐loop signals is guaranteed in probability; meanwhile, convergence of the tracking errors to adjustable compact set in the sense of mean quartic value is also proved. Finally, simulation results are shown to verify and clarify efficiency of the offered approach. Copyright © 2016 John Wiley & Sons, Ltd.     

Hybrid solar parabolic dish power plant and high‐temperature phase change material energy storage system

In this study, a conventional steam power plant with two regenerative boilers is considered, and one of its boilers is replaced with parabolic solar dish collectors and storing the produced thermal energy by the phase change material (PCM) in a storage tank. The results show the necessity of the existence of an auxiliary fired‐gas boiler to provide constant load during the whole 24 hours. The performance of the proposed hybridized system is evaluated through energy and exergy analyses. It was demonstrated that substituting solar collectors with one of the boilers marginally lowers the energy efficiency but increases the exergy efficiency of the whole power plant up to 41.76%. Moreover, it is found out that this hybridization decreases the total irreversibility of the power plant in comparison with the base case, from 51.1 to 47.2 MW. The parametric analysis states that raising the mass flow rate of the heat transfer fluid in the solar collectors not only enhances the system performance but also increases the volume of the PCM tank.     

Parallel‐series connected rectenna array using frequency selective surface (FSS) for power harvesting applications at 5.8 GHz

This article presents a frequency selective surface (FSS) and rectenna array in parallel‐series connection to harvest power of wireless power systems. To improve the basic antenna parameters, a frequency selective surface was mounted on the reverse side of the substrate. According to the results, the proposed method showed significant improvement in comparison to other methods in both single and rectenna array. Moreover, the conversion efficiency of the presented technique was increased to 76%. The output voltage of 4.5 and 9 V and the current of 60 and 120 mA were resulted for 5 and 10 rectenna units, respectively. The proposed arrays can be expanded to large scale integrated array without any significant degradation in conversion efficiency.     

A multiobjective integrated multiproject scheduling and multiskilled workforce assignment model considering learning effect under uncertainty

Today, organizations try to decline academically expenses using humans and resources in addition to rising managers and operators' satisfaction. Meantime, a very important step in the process of decision is the assignment of human resources, particularly in connection with research and development (R&D) projects in which the system is highly dependent on the capabilities of human resources. In this study, we tried all the assumptions that come true in the real world, considered a model for applied R&D projects to reduce costs and increase the efficiency of projects. Therefore, an integrated multiproject scheduling and multiskill human resource assignment model under uncertainty has developed for R&D projects. Furthermore, it is assumed that the activity processing time is related to human resources assignment that means the learning effect is considered. To demonstrate the proposed model efficiency, the various dimensions instance problem was solved accurately and efficiently in GAMS software, and the results have been reported. In addition, the proposed model is validated through the input parameter sensitivity analysis. The results indicate a suitable performance of the proposed fuzzy mathematical programming model is due to the complexity of the problem.