In this paper we present a distributed localized algorithm for the problem, where a group of autonomous mobile robots have to capture a target by forming a circle around it. The robots do not have memory of the past (...
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In this paper we present a distributed localized algorithm for the problem, where a group of autonomous mobile robots have to capture a target by forming a circle around it. The robots do not have memory of the past (oblivious) and only use local sensing. Dedicated communication between the robots is not needed. We introduce the discrete multi-orbit target surrounding problem and present a solution for it. We prove that our solution always guarantees that the robots enclose the target and circulate around it in O(D) time, where D is the sum of distances of the robots from the target in the start configuration. We also evaluate our solution by simulations.
The paper presents a novel control approach for induction generators (IG), that can equally be applied in systems with speeds ranging from normal to ultrahigh levels. As an example of application, an energy system is ...
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The paper presents a novel control approach for induction generators (IG), that can equally be applied in systems with speeds ranging from normal to ultrahigh levels. As an example of application, an energy system is shown developed for utilising waste and renewable energy sources, using ultrahigh speed turbine-generator set for electromechanical energy conversion. The proposed solution combines space vector control (SVC) with hysteresis control (HC) for self-excited induction generators (SEIG). Application of IGs instead of synchronous generators (SG) have significant advantages, such as lower cost, brushless construction (in squirrel cage construction), ruggedness, and that they are practically maintenance free. In high speed and ultrahigh speed applications SEIG systems due to their advantageous properties nowadays get greater attention. The solution presented makes it possible to operate the IG in a wide speed and load range cost effectively, compared to the alternative solution, where a PWM AC/DC converter is used to ensure the magnetizing current for the induction machine. The design and modelling of the system are based on theoretical analyses and computer simulation techniques. The proposed control scheme has shown symmetrical three phase currents and voltages and excellent voltage and current regulation with significantly reduced current ripples and voltage distortions.
Cognitive Infocommunications (CogInfoCom) is a newly emerging research field that investigates the link between infocommunications and the cognitive sciences, with the goal of creating engineering systems in which art...
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Cognitive Infocommunications (CogInfoCom) is a newly emerging research field that investigates the link between infocommunications and the cognitive sciences, with the goal of creating engineering systems in which artificial and natural cognitive systems can work together more effectively. In this paper, we describe the structure of CogInfoCom systems from an interaction perspective. Through the discussions in this paper, our goal is to further clarify the relationship between CogInfoCom and the various research areas that deal with behavioral and structural systems modeling. In order to demonstrate the theoretical aspects of the subject, we describe a pilot application which was developed during the EtoCom project.
In this paper the results of a study on the accuracy of a fuzzy logic-based single-stroke character recognizer are presented by refining various parameter values, such as resolution of the fuzzy grid and the minimum d...
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The measurement of the efficiency of power electronics converters is a special challenge, because it is difficult to perform it accurately using electrical methods (especially in the high efficiency range or in low po...
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ISBN:
(纸本)9781467314534
The measurement of the efficiency of power electronics converters is a special challenge, because it is difficult to perform it accurately using electrical methods (especially in the high efficiency range or in low power applications). Therefore in many applications, where accuracy is crucial, engineers resort to calorimetric approaches. These in turn are extremely slow and special conditions need to be created to obtain good results. In other applications, where the accuracy is not the primary goal, but rather the fast, on-line, comparative estimation governs the demand for realizing the final aim. As a result, a solution to effectively determine the efficiency of the converters while working, is still sought for. The current paper aims at presenting a possible alternative, calculating the efficiency on-line with satisfactory accuracy at a low cost.
The spread of Web 2.0 has caused user-generated content explosion. Users can tag resources in order to describe and organize them. Tag clouds are visually depicted tags in order to facilitate browsing among numerous t...
The spread of Web 2.0 has caused user-generated content explosion. Users can tag resources in order to describe and organize them. Tag clouds are visually depicted tags in order to facilitate browsing among numerous tags and resources. The goal of our paper is to improve tag clouds with vocabulary refinement and enhanced reference counts. Namely, three novel algorithms have been proposed to correct spelling and clerical errors, contract tags, and improve reference counts. The provided algorithms have been validated and verified on real-world tag clouds of a thesis portal.
As a straightforward continuation of our previous work in this paper new memetic (combined evolutionary and gradient based) methods are proposed for constructing hierarchical-interpolative fuzzy rule bases in the fram...
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ISBN:
(纸本)9781467315074
As a straightforward continuation of our previous work in this paper new memetic (combined evolutionary and gradient based) methods are proposed for constructing hierarchical-interpolative fuzzy rule bases in the frame of a supervised machine learning system modeling black box systems defined by input-output pairs. In this work the resulting hierarchical rule bases are constructed by using structure building Genetic and Bacterial Memetic Programming Algorithms, thus stochastic evolutionary optimization methods containing deterministic local search steps. Applying hierarchical-interpolative fuzzy rule bases has proved an efficient way of reducing the complexity of knowledge bases, whereas memetic techniques often ensure a relatively fast convergence in the learning process. The literature has highlighted the advantages of memetic methods against pure evolutionary algorithms, thus the combination of hierarchical-interpolative fuzzy rule bases with memetic techniques may form promising hierarchical-interpolative machine learning systems.
It is well known that beyond the fact that fuzzy systems have favorable modeling capabilities from the viewpoint of accuracy, they also have outstanding inherent interpretability possibilities, which is a rather uniqu...
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