Studying the dynamic behavior of electric power systems is important part of a power engineer’s work. Transient phenomena in electric power systems can be naturally and conveniently modelled as hybrid or event-continuous systems, which are a generalization of classical dynamical systems. The approach is illustrated by a model of a large electric power system with controllers and protective devices. An original event detection algorithm for explicit numerical methods with error and stability control is presented and used to simulate the model. The simulation results show that the approach can be successfully applied to modeling and simulation of electric power systems. The model was composed and simulated in the modeling and simulation environment ISMA.
It is well known that the process of controlling a rotorcraft with a drive referred to as a rotor aircraft,\r\nin the event of adverse weather conditions, e.g. under the influence of strong wind, is the most difficult phase of\r\nthe flight, requiring a lot of commitment and skill from the pilot/operator. This situation is confirmed by a\r\nrelatively large number of aviation accidents that occur during the implementation of the process of controlling\r\na multi-rotor in difficult weather conditions. In view of the above, it should be noted that the degree of\r\ndifficulty of piloting an unmanned aircraft increases significantly when this operation is performed remotely by\r\nmeans of radio signals. As a consequence, the process of safely bringing an unmanned aircraft to the ground is\r\nextremely difficult even for an experienced operator who receives limited information about the flight condition\r\nof a multi-rotor. In view of the above, it is necessary to implement on-board control systems that enable\r\nautomatic implementation of the flight stabilization process, e.g. during a storm. The key goal of this work is to\r\ndesign a multi-rotor control system based on the proposed algorithms for controlling unmanned aerial vehicles\r\nduring high-wind flight, supported by a mathematical apparatus and selected simulation tests in the\r\nMatlab/Simulink environment. Based on the above, in the final part of this work, practical conclusions were\r\nformulated, reflecting the desirability of the tests carried out and confirmation of the results obtained.
Fiber Bragg Gratings (FBG) are widely used in different areas of the state-of–the -art fiber optics. Every task imposes specified requirements to the FBG spectral characteristics, which are scheduled at the gratings manufacturing stage. Manufacturing and using the Bragg fiber-optic gratings is impossible without measuring their characteristics at every stage of manufacturing the gratings themselves and devices on their basis. To select FBG’s optimal parameter we will compare the parameter SGW with several different the most widely used apodization functions. Upon manufacturing the FBG there applied strict requirements to their parameters. Recording or manufacturing the fiber Bragg gratings might be classified according to the type of the laser being used, radiation wave length, recording techniques, irradiation material and grating type. The article is dedicated to the techniques of computing and measuring the FBG’s principal parameters; it is necessary to define optimal parameters of the characteristics for the grating quality operation.
The relationships of the individuals in social networks give rise to interesting and important features in various fields, such as graph mining and communication networks. Among those useful features are clique structures which represent fully connected relations between members, and the maximum cliques which identify the highest-connected subgroups. In this work, we propose the modified differential evolution algorithm (moDE) for finding a maximum clique in social networks. The moDE solves the constrained continuous optimization problem which is transformed from the discrete maximum clique problem. It uses a new mutation strategy to generate and adjust mutant vectors, mixes two important crossover rates in crossover, and incorporates the extracting and extending clique procedure to increase the performance of clique finding. The algorithm is tested on several social network problems and compared with the previously developed method. The results show that moDE is effective for finding a maximum clique and outperforms the compared method. Key-Words: Maximum clique problem, social network, differential evolution algorithm, constrained continuous optimization problem
The European Energy Road Map 2050 and the Spanish Renewable Energies Plan for 2011-2020 are promoting the use of renewable energies as a necessary path to achieve the greenhouse gas reduction target necessary to avoid the rising global warming, and in particular, the use of Ocean Energy. Within the different types of on-shore wave-based energy devices, Oscillating Water Column (OWC) converters are one of the more widely used ones. An OWC plant is basically composed by a capture chamber coupled to a turbo-generator module. This paper deals with the model development for on-shore OWC wave energy power devices.
Using real time control (RTC) techniques to improve urban drainage system performance is proven to be an effective solution for alleviating urban flooding. Many modeling methods of urban drainage systems have been introduced in existing literatures to accommodate different situations and scenarios. Nonlinear hydrologic models are useful for detailed simulations in pipes and sewers. However, to utilize RTC requires users to establish suitable models that both reflect physical characteristics of the system while not over complicating with unnecessary details. A mixed integer system was proposed where hybrid Model Predictive Control can be used to compute control actions in previous literature. However, the complexity of solving associated optimization problem grows exponentially with the size of the system and therefore, the computation time renders direct application of such method infeasible. This paper investigates the possibility of partitioning the system into several subsystems with communications and instead of computing solutions in centralized framework, the control actions are obtained distributedly by individual subsystems. The performance of decentralized schemes is demonstrated with numerical simulations on a fictional sewage system composed of 13 tanks and 12 control follows under 4 rain scenarios corresponding to different rain intensities. Decentralized Model Predictive Control is shown to have comparable performance compared with the centralized framework while having significantly improved computation time. Two methods are also presented to reduce pumping energy costs by harvesting rainfall energy
As a result of the recent rapid increase in smart technologies, many people now enjoy movies and music content through their smart devices while using public transportation. However, because their concentration is aimed at content on their smart devices, passengers sometimes forget to disembark and miss their destination stations. In this paper, we therefore propose a destination notification system for disembarking public transport using high frequencies based on the smart devices themselves. The proposed application could support automatic debarkation notifications when the smart device approaches the destination station. We tested destination notification with the proposed system and ten smart devices to evaluate its performance. According to the test results, the proposed system showed 99.4% accuracy and was therefore confirmed as potentially very useful. As such, the proposed system could be a useful technology for notifying smart device users when to get off public transport, capable of global commercialization.
A sensor tier design and its setting within the multi-tiered architectural structure of EMULSION, the new horizontal-type IoT platform paradigm, is presented in this paper ♠, along with typical examples of hardware and deployment schemas.♠This publication has emanated from joint research conducted with the financial support of the Bulgarian National Science Fund (BNSF) under the Grant No. KP-06-IP-CHINA/1 (КП-06-ИП-КИТАЙ/1) and the S&T Major Project of the Science and Technology Ministry of China, Grant No. 2017YFE0135700.
The subject of this article is to analyze and select simulation tests in the field of issues related to flight control systems for micro-class aircraft. The main purpose of the work is to develop an algorithm for the flight control system, taking into account both the speed and direction of the wind acting on the UAV, which are the key attributes that play a decisive impact on the disturbance of flight parameters and its correct performance. What is more, atmospheric conditions determined by the influence of wind can produce phenomena dangerous to aviation in the form of wind shear or blast from the back during the landing process of the aircraft. The occurrence of the above situation may be the cause of stall phenomenon, which in turn may be the cause of a dangerous aviation phenomenon (accident, incident, etc.). For the purposes of solving the research problem, the article uses a mathematical apparatus in the form of equations describing the movement of the aircraft and the forces and moments acting on it. Based on the mathematical analysis of the UAV object, in the further part of the article, an algorithm was developed to estimate the impact of wind and an analysis of measurement errors occurring during flights and their impact on the measured values, as well as the values calculated on their basis. On this basis, charts have been developed defining clearly the various relationships. In the final part of the thesis, based on the mathematical analysis, simulation tests and analysis of the results obtained, the final conclusions and observations were formulated, which are reflected in practical applications. Key-Words: Control model, micro class UAV object, equations of motion, strong wind influence
In this paper, a novel control structure combing the adaptive backstepping (BS) and sliding mode\r\n(SM) control techniques to improve the performance and enhance the robustness of the vector control of six\r\nphase induction motor (SPIM) drives is proposed. The outer speed closed loop control uses the BS controller\r\nwith the integral error tracking component added to improve its sustainability. Second order sliding mode\r\ncontroller is proposed for the inner current closed loop control to can effectively compensate for load\r\ndisturbance in the system so the proposed method is more robust, stability and faster dynamics response,\r\nchattering free performance. The proposed speed control scheme is validated through Matlab-Simulink. The\r\nsimulation results confirm the good dynamics and robustness of the proposed control algorithm based on\r\n(BS_SOSM) technique
The needs of the modern world often require automatization of certain aspects of mankind activities. Science is no exception to this. In this paper we pay attention to vague functional dependencies as generalized functional dependencies. These dependencies are considered as fuzzy formulas. We give strict proof of the equivalence: any two-element vague relation instance on given scheme (which satisfies some set of vague functional dependencies) satisfies given vague functional dependency if and only if the attached fuzzy formula is a logical consequence of the corresponding set of fuzzy formulas. Thanks to this result, we put ourselves into position to automatically verify if some vague functional dependency follows from some set of vague functional dependencies. An appropriate example which supports this claim is also provided.
We propose and analyze fast spin initialization for a quantum dot in the Voigt geometry by placing it near a graphene layer. We show that high levels of fidelity, significantly larger than in the case of the quantum dot without the layer, can be quickly obtained due to the anisotropy of the enhanced spontaneous decay rates of the quantum dot near the graphene layer. We initially obtain these results by using a continuous wave optical field with constant control amplitude. We also use state of the art numerical optimal control to find the time-dependent electric field which maximizes the final fidelity for the same short duration as in the previous case. A better fidelity is obtained with this method
This study encompasses a comprehensive analysis of the three-phase transformer - three-phase rectifier assembly, and the establishment of the equivalent circuit of the AC / DC conversion group at the average DC components level. Since the efficiency standards can be expressed in terms of electrical efficiency, in an attempt to improve the transformer efficiency, in this study an enhancement of three-phase power transformer modelling with space phasors is presented. There are established the equations with space phasors of the three-phase transformer with symmetrical compact core. This equations system can be used to analyse the dynamic regimes of threephase transformers. In this study the authors comprehensively analysed aspects of three-phase power transformer with Graetz three-phase bridge assembly operating in AC/DC traction substations.
A basic system with important potential applications in quantum technologies is a quantum dot in the Voigt geometry. The spin states of the quantum dot in the Voigt geometry can act as a prototype qubit which can be manipulated by applied optical fields in order to produce the necessary quantum gates. The basic method for spin initialization in a quantum dot in the Voigt geometry is optical pumping. Here, we propose and analyze a new method for the coherent preparation of the quantum dot spin states based on adiabatic control methods. Specifically, we show that the application of two mutually delayed and partially overlapping optical pulses, similar to those used in stimulated Raman adiabatic passage, can lead to initialization of one of the spin states with high fidelity. We also demonstrate that the fidelity of the method may be increased by integrating the quantum dot with a micropillar cavity. Specifically, we show that a preferential Purcell-enhanced decay rate towards the target spin state, in certain cases, increases the fidelity of spin initialization of the adiabatic method. Our results are based on the numerical solution of the relevant density matrix equations for the quantum dot system, either in an isotropic photonic environment or in a micropillar cavity. The calculations presented in this paper are not limited to quantum dots in micropillar cavities. Similar effects can be obtained by other photonic structures as well, as for example, for quantum dots in photonic crystal cavities.
Controlling unstable behaviour of many nonlinear dynamical systems is one of the recent interesting topics for researchers. Many methods are proposed to stabilize chaotic discrete time systems. In this paper, a comparison between different control methods is performed for distinguishing their efficiency. The used control methods are Ott-Grebogi-Yorke (OGY), Predictive Feedback Control (PFC), Time Delay Auto Synchronization (TDAS) and its extended (ETDAS), control methods based on self-organizing migrating algorithm (SOMA) and differential evolution (DE). They are briefly introduced and then applied to most popular discrete nonlinear systems 100 times. The controlled orbits of period-1 characteristics are evaluated, presenting the robust of each method according to autocorrelation, the number of required iterations, number of successfully controlled orbits, and max absolute value of the control input. TDAS and PFC methods are the most convenient to stabilize the chaotic attractor of the system. Key–Words: Control Methods, Nonlinear Chaotic Discrete Systems, and Autocorrelation.
Polyp is the name of a colorectal lesion which is created by cells clumping on the lining of the colon. The colorectal polyps can lead to severe illnesses like colon cancer if they are not treated at the early stage of their development. In current days, there are very many different polyp detection strategies based on biomedical imageries such colon capsule endoscopy (CCE) and optical colonoscopy (OC). The CCE imagery is non-invasive but the quality and resolution of acquired images are low. Moreover, it costs more than OC. So, today OC is the most desired method for detecting colorectal polyps and other lesions besides of its invasiveness. To assist physicians in detecting polyps more accurately and faster, machine learning with biomedical image processing aspect emerges. One of the most the state-of-the-art strategies for polyp detection based on artificial intelligence approach are deep learning (DL) convolutional neural networks (CNNs). As the categorization and grading of polyps need significant information about their specular highlights like their exact shape, size, texture and in general heir morphological features, therefore it is very demanded to employ semantic segmentation strategies for detecting polyps and discriminating them from the background. According to this fact, a novel and innovative method for polyp detection based on their semantic segmentation is proposed in this paper. The proposed segmentation classifier is in fact a modified CNN network named as U-Net. The proposed U-Net provides an advanced and developed semantic segmentation ability for polyp detection from OC images. For evaluating the proposed network, accredited and well-known OC image databases with polyps annotated by professional gastroenterologists known as CVC-ClinicDB, CVC-ColonDB and ETIS-Larib, are employed. The results of implementation demonstrate that the proposed method can outperform the other competitive methods for polyp detection from OC images up to an accuracy of 99% which means that the life lasting hopes could be increased to a considerable ratio.
In this paper, IMC-PID-FOF controllers are implemented on real time water level control of a coupled tank system. The 1DOF-IMC-PID-FOF controller is designed based on the IMC structure, the disturbance rejection is not considered in the controller design and the disturbance response has low performance. In the 2DOF-IMC-PID-FOF controller design, the disturbance rejection is considered, and solved separately from the set-point tracking problem. To do this, a complementary sensitivity function is defined and its time constant τt is a tuning parameter, used to adjust the speed of the disturbance response. In the experiment, set-point tracking and disturbance rejection tests are carried out to evaluate the performance of both 1DOF-IMC-PID-FOF and 2DOFIMC-PID-FOF controllers.
Control strategy for the modulation of the DC power for Modified HVDC Systems is proposed. A microprocessor- based firing scheme is presented which control the firing angles for modified HVDC converter with by-pass valves. Fast and continuous control of the DC voltage is possible with good operational characteristics. Using table-look-up algorithm to speed up the response, it gives a full range control of the firing angle for both rectifier and inverter modes. The algorithm is experimentally verified and is found to give a very-fast, precise and equidistant control of the thyristor triggering. Harmonic generations into the AC system and the converter reactive voltampere absorption have been reduced. The operations of modified bridge, the control algorithm and the microprocessor implementation are described. Experimental results on a laboratory model compare well with the predicted values.
The demands for high-performance microprocessors have recently increased. Accurate branch prediction is one of the most important factors for high-performance processors. In order to predict branch outcomes, instruction program counter bits and the history of recently executed branch outcomes are used. Among the executed branch outcomes, some histories are useful while others are useless. In addition, these useful/useless histories vary among branch instructions. Numerous studies have shown a method that identifies optimal history. However, little research has been done regarding the treatment of useless history. In this paper, a new method called Instruction Address alloyed History Length Modification branch predictor is proposed to handle the useless history bits. When PHT entries are 4,096, IAaHLM has a prediction accuracy of 93.22% and Gshare has a prediction accuracy of 91.84%.
Developing reconfigurable robotic systems may be quite challenging. This contribution aims at proposing a new methodology to ensure the safety of such critical systems. It uses new tools and innovative concepts. To show the relevance of the said methodology, we apply the contribution to a real medical robotic system: BROS. Key–Words: Design, verification, implementation, re-configurable systems, UML, R-TNCES, robotic systems
