Output feedback controller for polytopic systems exploiting the direct searching of the design space

This paper deals with the problem of designing a robust static output feedback controller for polytopic systems. The current research that tackled this problem is mainly based on LMI method, which is conservative by nature. In this paper, a novel approach is proposed, which considers the design space of the controller parameters and iteratively partitions the space to small simplexes. Then, by assessing the stability in each simplex, the solution space for design parameters is directly determined. It has been theoretically proved that, if there exists a feasible solution in the design space, the algorithm can find it. To validate the result of the proposed approach, comparative simulation examples are given to illustrate the performance of the design methodology as compared to those of previous approaches.     

Morphological evolution on the surface of hydrothermally synthesized hydroxyapatite microspheres in the presence of EDTMP

Well-ordered and surface engineered hierarchical hydroxyapatite microspheres (HAM) were prepared via a template free hydrothermal process. Ethylene diamine tetra (methylene phosphonic acid) (EDTMP) was used as chelating or regulating agent for the first time in this study. The results indicated the formation of sheet-like particles in the absence of EDTMP. On the other hand, microspheres with radially grown nanorods (HAMNR) or nanosheets (HAMNS) on the surface were obtained (with average diameter of 5?µm) in the presence of EDTMP. X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy were used to characterize the crystalline phases in the synthesized samples. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that EDTMP concentration played an important part in regulating the morphology to form well organized microspheres with nanosheets or nanorods on the surface. Brunauer-Emmett-Teller (BET) revealed an increase in the specific surface area with the change in morphology from the HAMNS to HAMNR. Possible mechanisms are proposed to account for the formation of different morphologies based upon thermodynamic and kinetic theories.     

A Simple Quasi-2D Numerical Model of a Thermogage Furnace

A simple quasi-2D model for the temperature distribution in a graphite tube furnace is presented. The model is used to estimate the temperature gradients in the furnace at temperatures above which contact sensors can be used, and to assist in the redesign of the furnace heater element to improve the temperature gradients. The Thermogage graphite tube furnace is commonly used in many NMIs as a blackbody source for radiation thermometer calibration and as a spectral irradiance standard. Although the design is robust, easy to operate and can change temperature rapidly, it is limited by its effective emissivity of typically 99.5–99.8%. At NMIA, the temperature gradient along the tube is assessed using thermocouples up to about 1,500°C, and the blackbody emissivity is calculated from this. However, at higher operating temperatures (up to 2,900°C), it is impractical to measure the gradient, and we propose to numerically model the temperature distributions used to calculate emissivity. In another paper at this conference, the model is used to design an optimized heater tube with improved temperature gradients. In the model presented here, the 2-D temperature distribution is simplified to separate the axial and radial temperature distributions within the heater tube and the surrounding insulation. Literature data for the temperature dependence of the electrical and thermal conductivities of the graphite tube were coupled to models for the thermal conductivity of the felt insulation, particularly including the effects of allowing for a gas mixture in the insulation. Experimental measurements of the temperature profile up to 1,500°C and radial heat fluxes up to 2,200°C were compared to the theoretical predictions of the model and good agreement was obtained.     

A robust critical path in an environment with hybrid uncertainty

In this article, we consider the project critical path problem in an environment with hybrid uncertainty. In this environment, the duration of activities are considered as random fuzzy variables that have probability and fuzzy natures, simultaneously. To obtain a robust critical path with this kind of uncertainty a chance constraints programming model is used. This model is converted to a deterministic model in two stages. In the first stage, the uncertain model is converted to a model with interval parameters by alpha-cut method and distribution function concepts. In the second stage, the interval model is converted to a deterministic model by robust optimization and min-max regret criterion and ultimately a genetic algorithm with a proposed exact algorithm are applied to solve the final model. Finally, some numerical examples are given to show the efficiency of the solution procedure.     

A potential trackable bone filler: Preparation and characterization

This study reported the synthesis of fluorescent hydroxyapatite/alginate/carbon quantum dots (HA/Alg/CQDs) nanocomposites via the co-precipitation technique. The N-doped CQDs as a new class of fluorescent materials were prepared by the citric acid pyrolysis method, with an average size around 4 nm. Physical, chemical, and optical properties of the synthesized nanocomposites were investigated by X-ray diffraction (XRD), Fourier-transformed infrared spectroscopy (FTIR), atomic force microscopy (AFM), field-emission scanning electron microscopy (FESEM), UV–visible spectroscopy, and photoluminescence (PL) spectroscopy, respectively. The PL spectroscopy data verified the favorable in vitro luminescent emission of the HA/Alg/CQDs nanocomposites in comparison with HA/Alg and HA samples. The XRD patterns of the prepared samples confirmed the formation of crystalline HA in all composites, possessing a Ca/P ratio around 1.5 as obtained by EDX elemental analysis. The FESEM analysis exhibited HA nanoplates that homogeneously distributed throughout the alginate matrix. Therefore, the synthesized nanocomposites could be regarded as potential trackable drug carriers for hard tissue engineering applications.     

Effect of Extraordinary Large Floods on at-site Flood Frequency

The peak flow of extraordinary large floods that occur during a period of systematic record is a controversial problem for flood frequency analysis (FFA) using traditional methods. The present study suggests that such floods be treated as historic flood data even though their historical period is unknown. In this paper, the extraordinary large flood peak was first identified using statistical outlier tests and normal probability plots. FFA was then applied with and without the extraordinary large floods. In this step, two goodness-of-fit tests including mean absolute relative deviation and mean squared relative deviation were used to identify the best-fit probability distributions. Next, the generalized extreme value (GEV), three-parameter lognormal (LN3), log-Pearson type III (LP3), and Wakeby (WAK) probability distributions were used to incorporate and adjust the extraordinary large floods with other systematic data. Finally, procedures with and without historical adjustment were compared for the extraordinary large floods in terms of goodness-of-fit and flood return-period quantiles. The results of this comparison indicate that historical adjustment from an operational perspective was more viable than without adjustment procedure. Furthermore, the results without adjustment were unreasonable (subject to over- and under-estimation) and produced physically unrealistic estimates that were not compatible with the study area. The proposed approach substantially improved the probability estimation of rare floods for efficient design of hydraulic structures, risk analysis, and floodplain management.     

Multicast routing protocols in wireless mesh networks: a survey

Wireless mesh networks (WMNs) introduce a new type of network that has been applied over the last few years. One of the most important developing issues in WMNs is multicast routing, which is a key technology that provides dissemination of data to a group of members in an efficient way. In this article, after an introduction about the structure of a WMN, multicast routing algorithms and protocols in WMNs are surveyed in a detailed and efficient manner. Moreover, effort is made to scale the study into one of the important potential capabilities of multicast routing mechanisms in WMNs, which is taking advantage of using different channels and radios association. While nodes in a single-radio mesh network operating on single-channel have restrictions for capacity, equipping mesh routers with multiple radios using multiple channels can decrease the intention of capacity problem as well as increase the aggregate bandwidth available to the network and improving the throughput. Hence, the purpose of channel assignment is to decrease the interferences while increasing the network capacity and keeping the connectivity of the network. Therefore, this article investigates the multicast protocols considering a definition of three types of WMNs, based on channel-radio association including SRSC, SRMC and MRMC. In its follow, a classification for multicast routing algorithms regarding the achieved optimal solutions will be presented. Finally, a study of MRMC and its relevant problems will be offered, considering the joint channel assignment and the multicast tree construction problem.     

The effect of feedstock and process conditions on the synthesis of high purity CNTs from aromatic hydrocarbons

High purity multi-walled carbon nanotubes were synthesized from aromatic hydrocarbons (benzene, toluene, xylene and trimethyl benzene) using ferrocene as the source of Fe catalyst. Screening studies of aromatic feeds at 675 °C, residence time of 14 s and Fe/C atom ratio of 1.07%, resulted in feedstock carbon conversion of 20-31%, CNT yield of 19.8-30.5%, and catalyst yield of 5.3-8.3 (g CNT/g catalyst). While the quality of the CNTs as determined by TGA, SEM, TEM and Raman spectroscopy, were high and comparable for different feedstocks; their carbon conversion, CNT yield and catalyst yield differed noticeably. A process optimization study for toluene feed showed that carbon conversion of more than 39%, CNT yield of 38.7% and catalyst yield of 18.3 can be achieved at temperature of 800 °C, Fe/C atom ratio of 0.47%, and residence time of 10-20 s.     

Multi-Wavelength vs. Binary Code Pattern Unwrapping in Fringe Projection Method

Phase extraction, phase unwrapping and phase to height conversion are consecutive steps within the fringe projection method for reconstruction of 3D objects. The procedure of determining discontinuities on the wrapped phase, resolving them and achieving the unwrapped phase is called phase unwrapping. A software system was developed that provides the ability to create many kinds of patterns with a verity of desirable properties suitable for different demands in fringe projection systems. In our previous work, an experimental study was reported based on a multi-wavelength unwrapping approach. In the following work, we implemented a new method called binary code pattern unwrapping that is based on time analysis. A comparison of the two unwrapping approaches in terms of resolution, quality, noise, depth accuracy, and computational cost is provided.     

Robust Unknown Input Observer Design for Linear Uncertain Time Delay Systems with Application to Fault Detection

In this paper, a novel approach is proposed to design a robust fault detection observer for uncertain linear time delay systems. The system is composed of both norm‐bounded uncertainties and exogenous signals (noise, disturbance, and fault) which are considered to be unknown. The main contribution of this paper is to present unknown input observer (UIO)‐based fault detection system which shows the maximum sensitivity to fault signals and the minimum sensitivity to other signals. Since the system contains uncertainty terms, an H_∞ model‐matching approach is used in design procedure. The reference residual signal generator system is designed so that the fault signal has maximum sensitivity while the exogenous signals have minimum sensitivity on the residual signal. Then, the fault detection system is designed by minimizing the estimation error between the reference residual signal and the UIO residual signal in the sense of H_∞ norm. A sufficient condition for the existence of such a filter is exploited in terms of certain linear matrix inequalities (LMIs). Application of the proposed method in a numerical example and an engineering process are simulated to demonstrate the effectiveness of the proposed algorithm. Simulation results show the validity of the proposed approach to detect the occurrence of faults in the presence of modeling errors, disturbances, and noise.