Les fibres multimodales ont longtemps été délaissées en raison des distorsions temporelles et spatiales subies par la lumière au cours de sa propagation dans la fibre. Ces distorsions sont les conséquences des couplages modaux et de la disparité des temps de propagation des modes de fibre. Bien que complexe, la propagation dans un guide multimodal reste déterministe et peut être maitrisée par une structuration cohérente de l’excitation. La manipulation d’ondes en présence de gain dans la fibre optique, au coeur de ces travaux de thèse, constitue une problématique plus complexe encore puisque la carte de saturation des modes hétérogène rend la propagation non linéaire. Deux types d’amplificateurs multimodaux à fibre dopée ytterbium ont été étudiés : une fibre à saut d’indice à large coeur et une fibre à coeurs multiples couplés. Le contrôle spatial du faisceau transmis est obtenu en structurant le front d’onde incident à l’aide d’un miroir déformable couplé à un algorithme itératif. En régime d’excitation continue, cette technique de contrôle adaptatif, robuste et rapide a permis de focaliser le rayonnement en extrémité de fibre sur des spots uniphases, malgré les couplages modaux, l’hétérogénéité de gain modal et la saturation du gain. Il a aussi été démontré que la mise en forme du front d’onde incident ne réduisait pas le gain d’amplification. Une puissance de 2,8 W a été confinée dans un unique spot avec un gain de12 dB. Des structures intensimétriques plus complexes de type « multispots » ont également été obtenues. Enfin, la focalisation à travers la fibre amplificatrice a été réalisée avec succès en régime femtoseconde pour lequel la propagation s’accompagne de couplages spatio-temporels. Une première démonstration de principe a permis d’obtenir 120 kW de puissance crête avec un gain de 14 dB dans une impulsion uniquement limitée par la dispersion chromatique (350 fs), le profilage spatial permettant aussi de contrôler l’impulsion amplifiée par la sélection de modes dont les vitesses de groupe sont proches. / For a long time, multimode fibers were sparsely investigated because of the spatial and temporal distortions occurring during propagation across the fiber. Those distortions are consequences of mode coupling and modal propagation constant disparity. Although the propagation in a multimode waveguide is complex, it is deterministic and can be controlled by spatial shaping of the excitation. Considering an amplifying medium, the problem, at the heart of this thesis, is more complex because of nonlinear propagation due to heterogeneous gain saturation. Two kinds of Ytterbium doped multimode fiber amplifiers were tested: a step index fiber with a large core diameter and a coupled core multicore fiber. Spatial control of the output of the amplifier was achieved using a deformable mirror in combination with an iterative algorithm. In the case of a continuous wave excitation of the amplifier, we demonstrated that it was possible to confine light in a single-phase spot with a 2,8 W average power and 12 dB gain. We also demonstrated that the spatial shaping of the output has no effect on the amplifier gain. Furthermore, we obtained more complex output fields of multi-spot structure. Finally, focalization through the amplifying fiber was successfully demonstrated in femtosecond regime for which spatio-temporal couplings occur. A 120 kW peak power spot with a gain of 14 dB in a 350 fs pulse was obtained in a first experimental proof of concept. The spatial shaping allows also to control the duration of the amplified pulse by selection of modes with close group velocities.

Dynamic optimisation problems are problems where the search space does not remain constant over time. Evolutionary algorithms aimed at static optimisation problems often fail to effectively optimise dynamic problems. The main reason for this is that the algorithms converge to a single optimum in the search space, and then lack the necessary diversity to locate new optima once the environment changes. Many approaches to adapting traditional evolutionary algorithms to dynamic environments are available in the literature, but differential evolution (DE) has been investigated as a base algorithm by only a few researchers. This thesis reports on adaptations of existing DE-based optimisation algorithms for dynamic environments. A novel approach, which evolves DE sub-populations based on performance in order to discover optima in an dynamic environment earlier, is proposed. It is shown that this approach reduces the average error in a wide range of benchmark instances. A second approach, which is shown to improve the location of individual optima in the search space, is combined with the first approach to form a new DE-based algorithm for dynamic optimisation problems. The algorithm is further adapted to dynamically spawn and remove sub-populations, which is shown to be an effective strategy on benchmark problems where the number of optima is unknown or fluctuates over time. Finally, approaches to self-adapting DE control parameters are incorporated into the newly created algorithms. Experimental evidence is presented to show that, apart from reducing the number of parameters to fine-tune, a benefit in terms of lower error values is found when employing self-adaptive control parameters. / Thesis (PhD)--University of Pretoria, 2012. / Computer Science / unrestricted

Battery storage devices have been widely utilized for different applications. However, for high power applications, battery storage systems come with several challenges, such as the thermal issue, low power density, low life span and high cost. Compared with batteries, supercapacitors have a lower energy density but their power density is very high, and they offer higher cyclic life and efficiency even during fast charge and discharge processes. In this dissertation, new techniques for the control and energy management of the hybrid battery-supercapacitor storage system are developed to improve the performance of the system in terms of efficiency, power quality and reliability. To evaluate the findings of this dissertation, a laboratory-scale DC microgrid system is designed and implemented. The developed microgrid utilizes a hybrid lead-acid battery and supercapacitor energy storage system and is loaded under various grid conditions. The developed microgrid has also real-time monitoring, control and energy management capabilities. A new control scheme and real-time energy management algorithm for an actively controlled hybrid DC microgrid is developed to reduce the adverse impacts of pulsed power loads. The developed control scheme is an adaptive current-voltage controller that is based on the moving average measurement technique and an adaptive proportional compensator. Unlike conventional energy control methods, the developed controller has the advantages of controlling both current and voltage of the system. This development is experimentally tested and verified. The results show significant improvements achieved in terms of enhancing the system efficiency, reducing the AC grid voltage drop and mitigating frequency fluctuation. Moreover, a novel event-based protection scheme for a multi-terminal DC power system has been developed and evaluated. In this technique, fault identification and classifications are performed based on the current derivative method and employing an artificial inductive line impedance. The developed scheme does not require high speed communication and synchronization and it transfers much less data when compared with the traditional method such as the differential protection approach. Moreover, this scheme utilizes less measurement equipment since only the DC bus data is required.

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During this master thesis an adaptive control system for angular velocity was developed. The approach focuses on radio controlled quadrotors and thereby targets a computational efficient solution. The adaptation is divided into two steps. First, an Integral Squared Plus Time Delay (I2PD) model estimation is done through the Recursive Least Squares (RLS) algorithm. Second, control parameters for the quadrotors Proportional Integral Derivative (PID) controller are found by using empirically modified Tuning Rules (TRs) which are based on the I2PD model. Simulation results show the benefits of an adaptive tuning algorithm in regards of the time consuming process of manually tuning a PID controller as well as robustness against both predictable and unpredictable system changes. This includes actuator degradation, battery consumption, changes in weight or inertia etc. However, it is apparent that the tuning algorithm demands an arbitrary initial approximation to be stable at initialization.

In addition to serving as a brief overview of aspects relevant to reduced-order modeling (in particular balanced-state and modal techniques) as applied to structural finite element models, this work produced tools for visualizing the relationship between the modes of a model and the states of its balanced representation. Specifically, error contour and mean error plots were developed that provide a designer with frequency response information absent from a typical analysis of a balanced model via its Hankel singular values. The plots were then used to analyze the controllability and observability aspects of finite element models of an illustrative system from a modal perspective -- this aided in the identification of computational artifacts in the models and helped predict points at which to halt the truncation of balanced states. Balanced reduced-order reference models of the illustrative system were implemented as part of a direct adaptive control algorithm to observe the effectiveness of the models. It was learned that the truncation point selected by observing the mean error plot produced the most satisfactory results overall -- the model closely approximated the dominant modes of the system and eliminated the computational artifacts. The problem of improving the performance of the system was also considered. The truncated balanced model was recast in modal form so that its damping could be increased, and the settling time decreased by about eighty percent.

This thesis discusses adaptive control of cooperative robotic manipulator. It deals with gathering and processing of data from six degrees of freedom tensometer and their use in adaptive control.

A study was designed in order to assess the effectiveness of a positive self-modeling strategy in increasing the performance of four University of the Pacific baseball players. A multiple baseline design across participants was used as a means of assessing the effectiveness of the self-modeling technique. Participants viewed edited positive self-modeling videotapes of their own batting performance. Measures were taken on: (a) the number of line drive hits; (b) ground ball hits; (c) the number of times the participant hit a ground ball, but was thrown out; (d) the number of times the participant hit a line drive, but it was caught; (e) swings and misses; (f) not swinging at a strike (called strikes); (g) not swinging at a ball (called balls); (h) the number of foul balls; and (i) the number of pop ups. In addition, batting averages were kept for game performance. It was expected that participants would show an increase in hits, a decrease in hit outs, a decrease in called strikes, an increase in called balls, a decrease in foul balls, and an increase in batting average when each participant began the positive self-modeling. The performance of those participants not yet viewing their positive self-modeling tape was not expected to show such improvement. Improvement was observed in three out of the four participants.

The thesis is focused on aircraft flight level control in case when the location of center of gravity changes during flight. The theoretical part of the thesis describes basics of aerodynamics, which are necessary to understand airplane's behavior and its control theory. Basics of state theory and stability of systems, as it is used for design of linear model. This part also mentions mathematical equations of nonlinear model of business jet and discusses conventional and adaptive methods used to design autopilot parameters. Several autopilots were designed in practical part of the thesis. The most important part is the logic used to determine location of center of gravity of the airplane. The models use nonlinear model of an airplane that better represents the real environment and conditions.

Trust management in mobile networks is challenging due to dynamically changing network environments and the lack of a centralized trusted authority. In this dissertation research, we design and validate a class of dynamic trust management protocols for mobile networks, and demonstrate the utility of dynamic trust management with trust-based applications. Unlike existing work, we consider social trust derived from social networks in addition to traditional quality-of-service (QoS) trust derived from communication networks to obtain a composite trust metric as a basis for evaluating trust of nodes in mobile network applications. Untreated in the literature, we design and validate trust composition, aggregation, propagation, and formation protocols for dynamic trust management that can learn from past experiences and adapt to changing environment conditions to maximize application performance and enhance operation agility. Furthermore, we propose, explore and validate the design concept of application-level trust optimization in response to changing conditions to maximize application performance or best satisfy application requirements. We provide formal proof for the convergence, accuracy, and resiliency properties of our trust management protocols. To achieve the goals of identifying the best trust protocol setting and optimizing the use of trust for trust-based applications, we develop a novel model-based analysis methodology with simulation validation for analyzing and validating our dynamic trust management protocol design. The dissertation research provides new understanding of dynamic trust management for mobile wireless networks. We gain insight on the best trust composition and trust formation out of social and QoS trust components, as well as the best trust aggregation and propagation protocols for optimizing application performance. We gain insight on how a modeling and analysis tool can be built, allowing trust composition, aggregation, propagation, and formation designs to be incorporated, tested and validated. We demonstrate the utility of dynamic trust management protocol for mobile networks including mobile ad-hoc networks, delay tolerant networks, wireless sensor networks, and Internet of things systems with practical applications including misbehaving node detection, trust-based survivability management, trust-based secure routing, and trust-based service composition. Through model-based analysis with simulation validation, we show that our dynamic trust management based protocols outperform non-trust-based and Bayesian trust-based protocols in the presence of malicious, erroneous, partly trusted, uncertain and incomplete information, and are resilient to trust related attacks. / Ph. D.