Abstract not available

Wireless sensor networks (WSN) increasingly permeate modern societies nowadays. But in spite of their plethora of successful applications, WSN are often unable to surmount many operational challenges that unexpectedly arise during their lifetime. Fortunately, robotic agents can now assist a WSN in various ways. This thesis illustrates how mobile robots which are able to carry a limited number of sensors can help the network react to sensor faults, either during or after its deployment in the monitoring region. Two scenarios are envisioned. In the first one, carrier robots surround a point of interest with multiple sensor layers (focused coverage formation). We put forward the first known algorithm of its kind in literature. It is energy-efficient, fault-reactive and aware of the bounded robot cargo capacity. The second one is that of replacing damaged sensing units with spare, functional ones (coverage repair), which gives rise to the formulation of two novel combinatorial optimization problems. Three nature-inspired metaheuristic approaches that run at a centralized location are proposed. They are able to find good-quality solutions in a short time. Two frameworks for the identification of the damaged nodes are considered. The first one leans upon diagnosable systems, i.e. existing distributed detection models in which individual units perform tests upon each other. Two swarm intelligence algorithms are designed to quickly and reliably spot faulty sensors in this context. The second one is an evolving risk management framework for WSNs that is entirely formulated in this thesis.

With rapid growth of information on the Web, Web search engines have gained great momentum for exploiting valuable Web resources. Although keywords-based Web search engines provide relevant search results in response to users’ queries, future enhancement is still needed. Three important issues include (1) search results can be diverse because ambiguous keywords in queries can be interpreted to different meanings; (2) indentifying keywords in long queries is difficult for search engines; and (3) generating query-specific Web page summaries is desirable for Web search results’ previews. Based on clickthrough data, this thesis proposes a query-concept bipartite graph for representing queries’ relations, and applies the queries’ relations to applications such as (1) personalized query suggestions, (2) long queries Web searches and (3) query-specific Web page summarization. Experimental results show that query-concept bipartite graphs are useful for performance improvement for the three applications.

Wireless sensor networks (WSN) increasingly permeate modern societies nowadays. But in spite of their plethora of successful applications, WSN are often unable to surmount many operational challenges that unexpectedly arise during their lifetime. Fortunately, robotic agents can now assist a WSN in various ways. This thesis illustrates how mobile robots which are able to carry a limited number of sensors can help the network react to sensor faults, either during or after its deployment in the monitoring region. Two scenarios are envisioned. In the first one, carrier robots surround a point of interest with multiple sensor layers (focused coverage formation). We put forward the first known algorithm of its kind in literature. It is energy-efficient, fault-reactive and aware of the bounded robot cargo capacity. The second one is that of replacing damaged sensing units with spare, functional ones (coverage repair), which gives rise to the formulation of two novel combinatorial optimization problems. Three nature-inspired metaheuristic approaches that run at a centralized location are proposed. They are able to find good-quality solutions in a short time. Two frameworks for the identification of the damaged nodes are considered. The first one leans upon diagnosable systems, i.e. existing distributed detection models in which individual units perform tests upon each other. Two swarm intelligence algorithms are designed to quickly and reliably spot faulty sensors in this context. The second one is an evolving risk management framework for WSNs that is entirely formulated in this thesis.

Thesis (Ph. D.)--Missouri University of Science and Technology, 2009. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed January 5, 2010) Includes bibliographical references (p. 152-159).

Στην παρούσα διδακτορική διατριβή μελετήθηκε η διασύνδεση ενός υπεράκτιου Αιολικού Πάρκου (ΑΠ) επαγωγικών μηχανών ονομαστικής ισχύος 90MW με ένα απομακρυσμένο ασθενές δίκτυο ΕΡ. Η περίπτωση αυτή παρουσιάζει σημαντικές δυσκολίες λόγω του χαμηλού λόγου ισχύων βραχυκύκλωσης ανάμεσα στις δύο πλευρές και των έντονων διακυμάνσεων της ισχύος που απομαστεύεται από τον άνεμο. Με σκοπό να περιορισθούν οι δυσκολίες αυτές και δεδομένου ότι τα διασυνδεδεμένα άκρα είναι απομακρυσμένα (άρα επιβάλλεται η μεταφορά με καλώδιο ΣΡ), επιλέχθηκε η εφαρμογή της διασύνδεσης του ΑΠ στο δίκτυο ΕΡ μέσω της τεχνολογίας Εναλλασσομένου Ρεύματος/ Συνεχούς Ρεύματος/ Εναλλασσομένου Ρεύματος (ΕΡ/ΣΡ/ΕΡ) με Μετατροπείς Πηγής Τάσης (ΜΠΤ). Η τεχνολογία αυτή επιτρέπει τον ανεξάρτητο έλεγχο της πραγματικής από την άεργο ισχύ και έτσι καθιστά δυνατή τη διασύνδεση δικτύων με χαμηλό λόγο ισχύων βραχυκύκλωσης. Ένα επιπλέον πρόβλημα το οποίο επιλύεται μέσω της χρήσης της τεχνολογίας ΕΡ/ΣΡ/ΕΡ με ΜΠΤ είναι αυτό της δυναμικής αντιστάθμισης αέργου ισχύος των επαγωγικών γεννητριών. Ωστόσο, παρόλα τα οφέλη που αποκομίζονται εφαρμόζοντας την τεχνολογία ΕΡ/ΣΡ/ΕΡ με ΜΠΤ, ο έλεγχος της διασύνδεσης παραμένει μια απαιτητική διαδικασία. Ο σχεδιασμός του συστήματος ελέγχου απαιτεί λεπτομερή γνώση της συμπεριφοράς του συστήματος και ακριβή ρύθμιση ώστε να αποκτηθεί η επιθυμητή έξοδος. Η παρουσία έντονα μεταβαλλόμενων και με θόρυβο εισόδων μπορούν να καταστήσουν πολύ δύσκολη την επιλογή των παραμέτρων ελέγχου οι οποίες παρέχουν σωστή συμπεριφορά σε οποιεσδήποτε συνθήκες λειτουργίας. Σύμφωνα με τα παραπάνω κριτήρια ελέγχου, το σύστημα ελέγχου που επιλέχθηκε για την παραπάνω διασύνδεση σχεδιάστηκε σύμφωνα με την υπολογιστική νοημοσύνη, η οποία βασίζεται στην ποιοτική περιγραφή των ελεγχόμενων διαδικασιών και στη μίμηση του συλλογισμού ενός έμπειρου ανθρώπου-χειριστή της διαδικασίας. Οι κλάδοι της υπολογιστικής νοημοσύνης που εφαρμόσθηκαν είναι τα ασαφή συστήματα και τα υβριδικά νευρο-ασαφή συστήματα. Πιο συγκεκριμένα, για τον έλεγχο της διασύνδεσης του ΑΠ με το ασθενές δίκτυο ΕΡ, σχεδιάστηκαν και μελετήθηκαν τρεις διαφορετικές εκδοχές, οι οποίες περιελάμβαναν: 1. ένα ασαφές σύστημα ελέγχου, 2. ένα νευρο-ασαφές σύστημα ελέγχου, 3. ένα προσαρμοζόμενο ασαφές σύστημα ελέγχου, το οποίο ρυθμίζεται σε πραγματικό χρόνο. Προκειμένου να ελεγχθεί η αποτελεσματικότητα του συστήματος ελέγχου, αλλά και να συγκριθούν οι τρεις εκδοχές του ως προς την αποτελεσματικότητά τους σε διαφορετικές διαταραχές, η αξιολόγηση του συστήματος περιέλαβε τρία μέρη. Στο πρώτο μέρος παρουσιάσθηκε η απόκριση του συστήματος σε μια βηματική αύξηση της μέσης τιμής της ταχύτητας του ανέμου. Η μεταβολή που επιλέχθηκε είναι ιδιαίτερα απότομη με σκοπό να ελεγχθεί η απόκριση του συστήματος υπό ακραίες συνθήκες. Στο δεύτερο μέρος παρουσιάσθηκε η απόκριση του συστήματος σε μια βηματική μείωση της μέσης τιμής της ταχύτητας του ανέμου, εξίσου απότομη με την προηγούμενη, ώστε να σχηματισθεί μια ολοκληρωμένη εικόνα για τη δυναμική συμπεριφορά του συστήματος κατά τη μετάβασή του στις διάφορες περιοχές λειτουργίας. Στο τρίτο μέρος έγινε μια αξιολόγηση της αρμονικής παραμόρφωσης, η οποία προκαλείται από τη διακοπτική λειτουργία του αντιστροφέα, στις κυματομορφές του ρεύματος και της τάσης στο ΣΚΣΔ, σύμφωνα με τα προτεινόμενα όρια του κανονισμού ΙΕΕΕ 519. Μέσω εκτενών αποτελεσμάτων εξομοίωσης αποδείχθηκε ότι το προτεινόμενο σύστημα ελέγχου και στις τρεις περιπτώσεις αντιδρά γρήγορα στις μεταβολές ισχύος του ανέμου και η διασύνδεση ΕΡ/ΣΡ/ΕΡ με ΜΠΤ τροφοδοτεί ομαλά το σύστημα ΕΡ με πραγματική ισχύ υπό σχεδόν σταθερή εναλλασσόμενη τάση. Επιπρόσθετα, λόγω του ελέγχου μεταβλητών στροφών, το ΑΠ οδηγείται σε μέγιστη αεροδυναμική απόδοση, χωρίς να απαιτείται μέτρηση της ταχύτητας του ανέμου ή του ρότορα των μηχανών. / In this thesis is studied the connection of an offshore Wind Farm (WF) with induction generators to a weak ac grid. This case presents several difficulties, as a result of the low short circuit ratio between the two interconnected ends and the fluctuating and unstable nature of the wind power. In order to constrain these difficulties and taking into account the long distance between the two interconnected ends (which necessitates the use of a dc cable), it was chosen to use the technology of the High Voltage Direct Current (HVDC) link based on Voltage Sourced Converters(VSCs) for the connection of the WF to the weak ac grid. This technology presents the advantages of dc transmission and due to the high switching capability of the VSCs’ valves, it can instantly regulate the reactive power and consequently the ac voltage, independently of the real power flow. So, the short circuit ratio between the two ends of the link does not have to be high. Furthermore, through this link, the dynamic reactive power compensation of the induction generations can be achieved. However, despite the benefits which are obtained through the technology of the HVDC link based on VSCs, the control of the link is still a demanding procedure. The design of the control system demands a comprehensive knowledge of the system behavior and accurate tuning in order to achieve the desirable output. The presence of highly fluctuating and noisy input signals can make the selection of the control parameters which ensure proper behavior in any operating conditions very difficult. Taking into account the above requirements, the control theory that was implemented to the control system of the above mentioned link is that of computational intelligence. Computational intelligence-based controllers do not require precise mathematical modeling of the system nor complex computations. They rely on the human ability to understand the system behavior and are based on qualitative control rules. In addition, they have inherent abilities to deal with imprecise or noisy data. The categories of computational intelligence that were used in the control system design are fuzzy systems and hybrid neuro-fuzzy systems. More precisely, three alternative versions of the control system of the link between the WF and the weak ac grid were designed: 1. a simple, manually tuned fuzzy control system , 2. a hybrid neuro-fuzzy control System 3. an adaptive, on-line tuned fuzzy control system. In order to test the performance of the control system and compare its three versions, the test of the system includes three parts. In the fist part was studied the performance of the system under a step increase of the wind speed. The step increase was chosen to be very steep, in order to test the system under extreme conditions. In the second part was studied the response of the system under a respective step decrease of the wind speed, in order to test the system performance under any operating condition. In the third part was examined the harmonic content of waveforms of the current and voltage at the point of common coupling, according to the limits of the international standard IEEE 519. Through extended simulation results it was shown that the proposed control system quickly reacts to the step changes of the wind power and the HVDC link based on VSCs manages to feed the weak ac grid with the power from the wind under almost stable ac voltage. In addition, due to the ability of the control system to adjust the stator frequency of the induction generators in relation to the wind velocity, maximum power absorption of the WF is achieved, without monitoring the wind speed or the rotor speed.

This thesis presents a wide spectrum of novel extensions and enhancements to critical components of modern electromagnetic analysis and design systems. These advancements are achieved through the use of computational intelligence, which comprises neural networks, evolutionary algorithms, and fuzzy systems. These tools have been proven in myriad industrial applications ranging from computer network optimization to heavy machinery control. / The analysis module of an electromagnetic analysis and design system typically comprises mesh generation and mesh improvement stages. A novel method for discovering optimal orderings of mesh improvement operators is proposed and leads to a suite of novel mesh improvement techniques. The new techniques outperform existing methods in both mesh quality improvement and computational cost. / The remaining contributions pertain to the design module. Specifically, a novel space mapping method is proposed, which allows for the optimization of response surface models. The method is able to combine the accuracy of fine models with the speed of coarse models. Optimal results are achieved for a fraction of the cost of the standard optimization approach. / Models built from computational data often do not take into consideration the intrinsic characteristics of the data. A novel model building approach is proposed, which customizes the model to the underlying responses and accelerates searching within the model. The novel approach is able to significantly reduce model error and accelerate optimization. / Automatic design schemes for 2D structures typically preconceive the final design or create an intractable search space. A novel non-preconceived approach is presented, which relies on a new genome structure and genetic operators. The new approach is capable of a threefold performance improvement and improved manufacturability. / Automatic design of 3D wire structures is often based on "in-series" architectures, which limit performance. A novel technique for automatic creative design of 3D wire antennas is proposed. The antenna structures are grown from a starting wire and invalid designs are avoided. The high quality antennas that emerge from this bio-inspired approach could not have been obtained by a human designer and are able to outperform standard designs.

Swarm Intelligence (SI) is a young field of study from which solutions to complex problems have been proposed based on how some natural organisms (e.g. ants, bees and others) achieve many of their daily tasks through simple sets of interactions. This thesis proposes two models for area exploration and coverage based on SI principles. These two models present a novel approach based on the combination of: ants’ pheromones, in order to keep track of visited places; and bird flocks or fish schooling, so as to move and collaborate. An implementation of both models was done in order to simulate and evaluate both the emergent behavior of the agents as well as their area exploration and coverage performance. Based on the outcome of the simulations it is concluded that both models are able to perform the exploration and coverage task and that one model is better than the other.

No description available.

Wireless sensor networks (WSN) increasingly permeate modern societies nowadays. But in spite of their plethora of successful applications, WSN are often unable to surmount many operational challenges that unexpectedly arise during their lifetime. Fortunately, robotic agents can now assist a WSN in various ways. This thesis illustrates how mobile robots which are able to carry a limited number of sensors can help the network react to sensor faults, either during or after its deployment in the monitoring region. Two scenarios are envisioned. In the first one, carrier robots surround a point of interest with multiple sensor layers (focused coverage formation). We put forward the first known algorithm of its kind in literature. It is energy-efficient, fault-reactive and aware of the bounded robot cargo capacity. The second one is that of replacing damaged sensing units with spare, functional ones (coverage repair), which gives rise to the formulation of two novel combinatorial optimization problems. Three nature-inspired metaheuristic approaches that run at a centralized location are proposed. They are able to find good-quality solutions in a short time. Two frameworks for the identification of the damaged nodes are considered. The first one leans upon diagnosable systems, i.e. existing distributed detection models in which individual units perform tests upon each other. Two swarm intelligence algorithms are designed to quickly and reliably spot faulty sensors in this context. The second one is an evolving risk management framework for WSNs that is entirely formulated in this thesis.