Bounded‐Input Control of the Quadrotor Unmanned Aerial Vehicle: A Vision‐Based Approach

In this paper, a bounded‐input controller is designed for the quadrotor vertical take‐off and landing unmanned aerial vehicle (UAV). Visual information is used to localize the aircraft with respect to its environment and an image‐based visual servo scheme is developed to navigate the motion of it. The visual features are selected from perspective image moments and projected on a rotated image plane, which simplifies the controller design. The flow of the features is used as the linear velocity information, and the controller assumes angular velocity and attitude information available for feedback. To design the controller, the dynamics of the quadrotor are decoupled into two parts: translational dynamics and rotational dynamics. First visual data are used to design a bounded‐input controller for the translational dynamics, and then a saturated controller is designed for the rotational dynamics. The boundedness of the controller increases the chance of keeping the visual features in the field of view of the camera. Furthermore, the controllers also cope with the unknown depth of the image, and the external disturbances. The complete stability analysis of the overall system is presented to show that all states are bounded and the error signals converge to zero asymptotically. Simulation examples are provided in both nominal and perturbed conditions which show the effectiveness of the proposed theoretical results.     

Critical rotational speed,critical velocity of fluid flow and free vibration analysis of a spinning SWCNT conveying viscous fluid

In this article, the influences of rotational speed and velocity of viscous fluid flow on free vibration behavior of spinning single-walled carbon nanotubes (SWCNTs) are investigated using the modified couple stress theory (MCST). Taking attention to the first-order shear deformation theory, the modeled rotating SWCNT and its equations of motion are derived using Hamilton’s principle. The formulations include Coriolis, centrifugal and initial hoop tension effects due to rotation of the SWCNT. This system is conveying viscous fluid, and the related force is calculated by modified Navier–Stokes relation considering slip boundary condition and Knudsen number. The accuracy of the presented model is validated with some cases in the literatures. Novelty of this study is considering the effects of spinning, conveying viscous flow and MCST in addition to considering the various boundary conditions of the SWCNT. Generalized differential quadrature method is used to approximately discretize the model and to approximate the equations of motion. Then, influence of material length scale parameter, velocity of viscous fluid flow, angular velocity, length, length-to-radius ratio, radius-to-thickness ratio and boundary conditions on critical speed, critical velocity and natural frequency of the rotating SWCNT conveying viscous fluid flow are investigated.     

Classifying the Geometric Dilution of Precision of GPS satellites utilizing Bayesian decision theory

The errors resulting from satellite configuration geometry can be determined by Geometric Dilution of Precision (GDOP). Considering optimal satellite subset selection, lower GDOP value usually causes better accuracy in GPS positioning. However, GDOP computation based on complicated transformation and inversion of measurement matrices is a time consuming procedure. This paper deals with classification of GPS GDOP utilizing Parzen estimation based Bayesian decision theory. The conditional probability of each class is estimated by Parzen algorithm. Then based on Bayesian decision theory, the class with maximum posterior probability is selected. The experiments on measured dataset demonstrate that the proposed algorithm lead, in mean classification improvement, to 4.08% in comparison with Support Vector Machine (SVM) and 9.83% in comparison with K-Nearest Neighbour (KNN) classifier. Extra work on feature extraction has been performed based on Principle Component Analysis (PCA). The results demonstrate that the feature extraction approach has best performance respect to all classifiers.     

A numerical framework for load identification and regularization with application to rolling disc problem

Indirect identification methods are applied when direct measurement is unfeasible. One example is the measurement of the contact force between wheel and rail in railway traffic. This paper focuses on optimization-based methods for the identification of contact forces with the aim of developing a reliable and robust load identification scheme. A particular issue discussed here is the choice of discretization in space–time, enabling the sampling instances of the measurements, the parameterization of the sought input and the discretization of the pertinent state equations to be decoupled, in contrast to traditional methods such as, e.g. dynamic programming.In the present preliminary study where a 2-D disc is considered as a representative of a train wheel, a radial concentrated force rotates around the disc’s perimeter, representing the contact force acting on the rim of the wheel, while radial strains are measured on a set of points corresponding to the strain gauges position. The strain history data is then used in the identification procedure where the applied force is sought to minimize the discrepancy between the predicted and measured strain history. In particular the convergence of the results with respect to the temporal discretization of the model and the time parameterization of the sought loading history are investigated under the influence of noise. It is seen that choosing a discretization of the sought load that is coarser than that of the state variable gives a more robust scheme. The traditional Tikhonov regularization can also be added within the current framework. Furthermore, with the aid of a sensitivity analysis, the influence of measurement noise can be quantified.     

A new fuzzy decision-making procedure applied to emergency electric power distribution scheduling

In this paper a new fuzzy decision-making procedure is developed. Two levels of weightings, called upper and lower weights, are proposed to calculate the fuzzy weightings of different criteria. The preference table is introduced to calculate the upper and lower weights. Also a new method is developed to determine the expected preference values of different alternatives. These values are used for generating the priority list of alternatives. The procedure is applied for providing an emergency electric power distribution, scheduling time table. The IEEE 14-bus standard system and a 14-bus system with four power plants are considered as case studies. Using fuzzy decision-making procedure, the regions with more priorities are more connected to the distribution net, while the maximum consumption criterion is also reasonably respected.     

Finite-element analysis for magnetic resonance image artifact evaluation

The static magnetic field of a magnetic resonance imaging scanner can be distorted by the presence of materials, perturbing the spatial encoding process in magnetic resonance imaging and often resulting in image artifacts. The relationship between the image artifact size and magnetic susceptibility of the material specimen is of interest to engineers for the design of devices that are to be compatible with the imaging volume of the scanner. In this study, a finite-element method was used to simulate the distorted magnetic field of samples with different susceptibilities. With the knowledge of the external- and self- magnetic field interactions, a Lorentz correction was applied to compute the magnetic field deviation. The simulated results were then validated by the corresponding experimental magnetic resonance images.     

Modeling and Management of Firewall Policies

Firewalls are core elements in network security. However, managing firewall rules, especially for enterprise networks, has become complex and error-prone. Firewall filtering rules have to be carefully written and organized in order to correctly implement the security policy. In addition, inserting or modifying a filtering rule requires thorough analysis of the relationship between this rule and other rules in order to determine the proper order of this rule and commit the updates. In this paper we present a set of techniques and algorithms that provide automatic discovery of firewall policy anomalies to reveal rule conflicts and potential problems in legacy firewalls, and anomaly-free policy editing for rule insertion, removal, and modification. This is implemented in a user-friendly tool called ?Firewall Policy Advisor.? The Firewall Policy Advisor significantly simplifies the management of any generic firewall policy written as filtering rules, while minimizing network vulnerability due to firewall rule misconfiguration.     

Microencapsulation of Nigella sativa seeds oil containing thymoquinone by spray‐drying for functional yogurt production

The present work reports on the microencapsulation of Nigella sativa seeds oil containing thymoquinone (TQ) by spray‐drying, using modified starch (MS) and maltodextrin (MD) mixture as wall materials aimed at producing functional yogurt. First, the impact of different ratios of MS/MD on microencapsulation efficiency (ME) and TQ retention was investigated. The highest ME (90.10%) was found in microcapsules prepared from emulsion with 80/20 ratio of MS/MD; however, the microcapsules prepared with 50/50 ratio was selected for considering TQ stability under storage conditions and functional yogurt production due to an acceptable ME (89.48%) and better TQ retention (61.12%). The results showed that the microcapsules stored at refrigerator temperature had the highest content of TQ after 4 weeks. Moreover, the results of chemical and sensory analysis suggest that N. sativa seeds oil microcapsules can be used for producing functional yogurt due to high stability of TQ and proper chemical and sensory properties.     

Introducing a proper hydrogen liquefaction concept for using wasted heat of thermal power plants-case study: Parand gas power plant

A hydrogen liquefaction concept with an innovative configuration and a capacity of 4 kg·s^-1 (345.6 t·d^-1) is developed. The concept involves an ammonia absorption refrigeration system for the pre-cooling of hydrogen and MR streams from 25 ℃ to -30 ℃. The ammonia absorption refrigeration system is fed by exhaust gases of the Parand gas power plant that are normally dissipated to the environment with a temperature of 546 ℃. The simulation is performed by Aspen HYSYS V9.0, using two separate equations of state for simulating hydrogen and MR streams to gain more accurate results especially for ortho-para conversion. Results show that conversion enthalpy estimated by Aspen HYSYS, fits very well to the experimental data. Determining the important independent variables and composition of MRs are done using trial and error procedure, a functional and straightforward method for complicated systems. The minimum temperature limit in the cooling section is lowered, and an ortho-para converter is implemented in this section. The proposed concept performs well from energy aspects and leads to COP and SEC equal to 0.271 and 4.54 kW·h·kg^-1, respectively. The main advantage of this study is in the low SEC, eliminating the losses of the distribution network, and improving the ability of the hydrogen liquefaction for energy storage in off-peak times.