Spatial processing that exploits the diversity provided by smart antenna arrays, in which the adaptive beamformer is employed, is another alternative to increase the efficiency of wireless system capacity and performance without allocating additional frequency spectrum. An array beamformer is a processor used in conjunction with an array of sensors to provide a versatile form of spatial filtering; it can be designed to form main lobe in direction corresponding to the desired source and nulling the interferences from others direction. They are two types of adaptive array beamformer structures, viz., broadband and narrowband array structures. To deal with the wideband desired signal or interferences the broadband array beamformer is preferred. For broadband interferences suppression, many adaptive array beamforming algorithms, based on the linearly constrained have been extensively used. In this thesis, the beamspace approach for designing the broadband antenna array beamformer, with frequency invariant character, is devised and implemented with the sliding window linearly constrained RLS (SW-LC-RLS) algorithm, to deal with the broadband moving jammers (or interferences) suppression. Also, to combat the pointing error effect of desired user¡¦s look direction, the derivative constraint is adopted for devising the derivative SW-LC-RLS beamforming algorithm for broadband moving jammers suppression. Computer simulation results confirmed that the proposed scheme is more robust against the moving jammers over the conventional algorithms. It can be applied to the existing wideband wireless communications systems to achieve desired performance for supporting high data rate communication services.

The technique of direct sequence code division multiple access (DS-CDMA) cellular system has been the focus of increased attention. In this thesis, we will consider the environment of DS-CDMA systems, where the asynchronous narrow band interference due to other systems is joined suddenly to the CDMA system. The suddenly joined narrow band interference will make the system crush down. The main concern of this thesis is to deal with suddenly joined narrow band interference cancellation. An adaptive filtering algorithm based on sliding window criterion and variable forgetting factor is known to be very attractive for violent changing environment. In this thesis, a new sliding window linearly constrained recursive least squares (SW LC-RLS) algorithm and variable forgetting factor linearly constrained recursive least squares (VFF LC-RLS) algorithm on the modified minimum mean squared error (MMSE) structure [9] is devised for RAKE receiver in direct sequence code-division multiple access (DS-CDMA) system over multipath fading channels. Where the channel estimation scheme is accomplished at the output of adaptive filter. The proposed SW LC-RLS algorithm and VFF LC-RLS has the advantage of having faster convergence property and tracking ability, and can be applied to the environment, where the narrow band interference is suddenly joined to the system, to achieve desired performance. Via computer simulation, we show that the performance, in terms of mean square errors (MSE) and signal to interference plus noise ratio (SINR), is superior to the conventional LC-RLS and orthogonal decomposition-based LMS algorithms based on the MMSE structure [9].

Modern power networks are being driven ever closer to both their physical and operational limits. As a result, control systems are being increasingly relied on to assure satisfactory system performance. Power system stabilizers (PSSs) are one example of such controllers. Their purpose is to increase system damping and they are typically designed using a model of the network that is valid during nominal operating conditions. The limitation of this design approach is that during off-nominal operating conditions, such as those triggered by daily load fluctuations, performance of the controller can degrade. The research presented in this report attempts to evaluate the possibility of employing an adaptive PSS as a means of avoiding the performance degradation precipitated by off-nominal operation. Conceptually, an adaptive PSS would be capable of identifying changes in the network and then adjusting its parameters to ensure suitable damping of the identified network. This work begins with a detailed look at the identification algorithm employed followed by a similarly detailed examination of the control algorithm that was used. The results of these two investigations are then combined to allow for a preliminary assessment of the performance that could be expected from an adaptive PSS. The results of this research suggest that an adaptive PSS is a possibility but further work is needed to confirm this finding. Testing using more complex network models must be carried out, details pertaining to control parameter tuning must be resolved and closed-loop time domain simulations using the adaptive PSS design remain to be performed.

Modern power networks are being driven ever closer to both their physical and operational limits. As a result, control systems are being increasingly relied on to assure satisfactory system performance. Power system stabilizers (PSSs) are one example of such controllers. Their purpose is to increase system damping and they are typically designed using a model of the network that is valid during nominal operating conditions. The limitation of this design approach is that during off-nominal operating conditions, such as those triggered by daily load fluctuations, performance of the controller can degrade. The research presented in this report attempts to evaluate the possibility of employing an adaptive PSS as a means of avoiding the performance degradation precipitated by off-nominal operation. Conceptually, an adaptive PSS would be capable of identifying changes in the network and then adjusting its parameters to ensure suitable damping of the identified network. This work begins with a detailed look at the identification algorithm employed followed by a similarly detailed examination of the control algorithm that was used. The results of these two investigations are then combined to allow for a preliminary assessment of the performance that could be expected from an adaptive PSS. The results of this research suggest that an adaptive PSS is a possibility but further work is needed to confirm this finding. Testing using more complex network models must be carried out, details pertaining to control parameter tuning must be resolved and closed-loop time domain simulations using the adaptive PSS design remain to be performed.

Este trabalho avaliou o potencial da aplicação da técnica recursiva dos mínimos quadrados (MQR) para o ajuste em tempo atual dos parâmetros de modelos autorregressivos com variáveis exógenas (ARX), as quais são constituídas pelos níveis de montante para melhorar o desempenho das previsões de níveis fluviais em tempo atual. Três aspectos foram estudados em conjunto: variação do alcance escolhido para a previsão, variação da proporção da área controlada em bacias a montante e variação da área da bacia da seção de previsão. A pesquisa foi realizada em três dimensões principais: a) metodológica (sem recursividade; com recursividade; com recursividade e fator de esquecimento); b) temporal (6 alcances diferentes: 10, 24, 34, 48, 58 e 72 horas); e c) espacial (variação da área controlada da bacia e da área da bacia definida pela seção de previsão). A área de estudo escolhida para essa pesquisa foi a bacia do rio Uruguai com exutório no posto fluviométrico de Uruguaiana (190.000 km²) e as suas sub-bacias embutidas de Itaqui (131.000 km²), Passo São Borja (125.000km²), Garruchos (116.000 km²), Porto Lucena (95.200 km²), Alto Uruguai (82.300 km²) e Iraí (61.900 km²). Os dados de níveis fluviométricos, com leituras diárias às 07:00 e às 17:00 horas, foram fornecidos pela Companhia de Pesquisa de Recursos Minerais (CPRM), sendo utilizados os dados de 1/1/1991 a 30/6/2015. Para a análise de desempenho dos modelos, foi aplicado como estatística de qualidade o coeficiente de Nash-Sutcliffe (NS) e o quantil 0,95 dos erros absolutos (EA(0,95): erro que não foi ultrapassado com a frequência de 0,95). Observou-se que os erros EA(0,95) dos melhores modelos obtidos para cada bacia sempre aumentam com a redução da área controlada, ou seja, a qualidade das previsões diminui com o deslocamento da seção de controle de jusante para montante. O ganho na qualidade das previsões com a utilização dos recursos adaptativos torna-se mais evidente, especialmente quando observam-se os valores de EA(0,95), pois esta estatística é mais sensível, com diferenças maiores em relação ao coeficiente NS. Além disso, este é mais representativo para os erros maiores, que ocorrem justamente durante os eventos de inundações. De modo geral, foi observado que, à medida que diminui a área da bacia, é possível obter previsões com alcances cada vez menores. Porém a influência do tamanho da área controlada de bacias a montante melhora o desempenho de bacias menores quando se observam principalmente os erros EA(0,95). Por outro lado, se a proporção da bacia controlada de montante já é bastante grande, como é o caso das alternativas 1 e 2 utilizadas para previsão em Itaqui (entre 88,5% e 95,4 %, respectivamente), os recursos adaptativos não fazem muita diferença na obtenção de melhores resultados. Todavia, quando se observam bacias com menores áreas de montante controladas, como é o caso de Porto Lucena para a alternativa 2 (65% de área controlada), o ganho no desempenho dos modelos com a utilização dos recursos adaptativos completos (MQR+f.e: mínimos quadrados recursivos com fator de esquecimento) torna-se relevante. / This study evaluated the potential of the application of the recursive least squares technique (RLS) to adjust in real time the model parameters of the autoregressive models with exogenous variables (ARX), which consists of the upstream levels, to improve the performance of the forecasts of river levels in real time. Three aspects were studied jointly: the variation of the lead time chosen for the forecast, the variation in the proportion of controlled area in upstream basins and variation in the area of forecasting section of the basin. The research was conducted in three main dimensions: a) methodological (without recursion; with recursion; with recursion and forgetting factor); b) temporal (6 different lead times: 10, 24, 34, 48, 58 and 72 hours); and c) spatial (variation in the controlled area of the basin and the area of the basin defined by the forecast section). The study area chosen for this research was the Uruguay River basin with its outflow at the river gage station of Uruguaiana (190,000 km²) and its entrenched sub-basins in Itaqui (131,000 km²), Passo São Borja (125,000 km²), Garruchos (116,000 km²), Porto Lucena (95,200 km²), Alto Uruguai (82,300 km²), and Iraí (61,900 km²). The river levels data, with daily readings at 7am and 5pm, were provided by the Company of Mineral Resources Research (CPRM), with the data used from January 1, 1991 to June 30, 2015. We applied the Nash-Sutcliffe coefficient (NS) and the quantile 0.95 of absolute errors (EA(0,95): error has not been exceeded at the rate of 0.95) for the analysis of models performances. We observed that the errors EA(0.95) of the best models obtained for each basin always increase with the reduction of the controlled area then the quality of the forecasts decreases with displacement of the downstream control section upstream. The gain in quality of the forecasts with the use of adaptive resources becomes more evident especially when the observed values of EA(0.95) as this statistic is more sensitive with greater differences in relation to the Nash-Sutcliffe Coefficient (NS). Moreover, this is most representative for larger errors which occur precisely during flooding events. In general, we observed that, as much as the area of the basin decreases, it is possible to obtain forecasts with smaller lead times, but the influence of the size of the area controlled upstream basins improves the performance of smaller basins when observing, especially the errors EA (0.95). However, if the proportion of the upstream of controlled basin is already quite large - as in the case of the alternatives 1 and 2 used for forecast in Itaqui (between 88.5% and 95.4%, respectively) - the adaptive resources do not differ too much in getting better results. However, when observing basins with smaller areas controlled upstream - as is the case of Porto Lucena to alternative 2 (65% controlled area) - the performance gain of the models with the use of the complete adaptive resources (MQR+f.e.) becomes relevant.

Este trabalho avaliou o potencial da aplicação da técnica recursiva dos mínimos quadrados (MQR) para o ajuste em tempo atual dos parâmetros de modelos autorregressivos com variáveis exógenas (ARX), as quais são constituídas pelos níveis de montante para melhorar o desempenho das previsões de níveis fluviais em tempo atual. Três aspectos foram estudados em conjunto: variação do alcance escolhido para a previsão, variação da proporção da área controlada em bacias a montante e variação da área da bacia da seção de previsão. A pesquisa foi realizada em três dimensões principais: a) metodológica (sem recursividade; com recursividade; com recursividade e fator de esquecimento); b) temporal (6 alcances diferentes: 10, 24, 34, 48, 58 e 72 horas); e c) espacial (variação da área controlada da bacia e da área da bacia definida pela seção de previsão). A área de estudo escolhida para essa pesquisa foi a bacia do rio Uruguai com exutório no posto fluviométrico de Uruguaiana (190.000 km²) e as suas sub-bacias embutidas de Itaqui (131.000 km²), Passo São Borja (125.000km²), Garruchos (116.000 km²), Porto Lucena (95.200 km²), Alto Uruguai (82.300 km²) e Iraí (61.900 km²). Os dados de níveis fluviométricos, com leituras diárias às 07:00 e às 17:00 horas, foram fornecidos pela Companhia de Pesquisa de Recursos Minerais (CPRM), sendo utilizados os dados de 1/1/1991 a 30/6/2015. Para a análise de desempenho dos modelos, foi aplicado como estatística de qualidade o coeficiente de Nash-Sutcliffe (NS) e o quantil 0,95 dos erros absolutos (EA(0,95): erro que não foi ultrapassado com a frequência de 0,95). Observou-se que os erros EA(0,95) dos melhores modelos obtidos para cada bacia sempre aumentam com a redução da área controlada, ou seja, a qualidade das previsões diminui com o deslocamento da seção de controle de jusante para montante. O ganho na qualidade das previsões com a utilização dos recursos adaptativos torna-se mais evidente, especialmente quando observam-se os valores de EA(0,95), pois esta estatística é mais sensível, com diferenças maiores em relação ao coeficiente NS. Além disso, este é mais representativo para os erros maiores, que ocorrem justamente durante os eventos de inundações. De modo geral, foi observado que, à medida que diminui a área da bacia, é possível obter previsões com alcances cada vez menores. Porém a influência do tamanho da área controlada de bacias a montante melhora o desempenho de bacias menores quando se observam principalmente os erros EA(0,95). Por outro lado, se a proporção da bacia controlada de montante já é bastante grande, como é o caso das alternativas 1 e 2 utilizadas para previsão em Itaqui (entre 88,5% e 95,4 %, respectivamente), os recursos adaptativos não fazem muita diferença na obtenção de melhores resultados. Todavia, quando se observam bacias com menores áreas de montante controladas, como é o caso de Porto Lucena para a alternativa 2 (65% de área controlada), o ganho no desempenho dos modelos com a utilização dos recursos adaptativos completos (MQR+f.e: mínimos quadrados recursivos com fator de esquecimento) torna-se relevante. / This study evaluated the potential of the application of the recursive least squares technique (RLS) to adjust in real time the model parameters of the autoregressive models with exogenous variables (ARX), which consists of the upstream levels, to improve the performance of the forecasts of river levels in real time. Three aspects were studied jointly: the variation of the lead time chosen for the forecast, the variation in the proportion of controlled area in upstream basins and variation in the area of forecasting section of the basin. The research was conducted in three main dimensions: a) methodological (without recursion; with recursion; with recursion and forgetting factor); b) temporal (6 different lead times: 10, 24, 34, 48, 58 and 72 hours); and c) spatial (variation in the controlled area of the basin and the area of the basin defined by the forecast section). The study area chosen for this research was the Uruguay River basin with its outflow at the river gage station of Uruguaiana (190,000 km²) and its entrenched sub-basins in Itaqui (131,000 km²), Passo São Borja (125,000 km²), Garruchos (116,000 km²), Porto Lucena (95,200 km²), Alto Uruguai (82,300 km²), and Iraí (61,900 km²). The river levels data, with daily readings at 7am and 5pm, were provided by the Company of Mineral Resources Research (CPRM), with the data used from January 1, 1991 to June 30, 2015. We applied the Nash-Sutcliffe coefficient (NS) and the quantile 0.95 of absolute errors (EA(0,95): error has not been exceeded at the rate of 0.95) for the analysis of models performances. We observed that the errors EA(0.95) of the best models obtained for each basin always increase with the reduction of the controlled area then the quality of the forecasts decreases with displacement of the downstream control section upstream. The gain in quality of the forecasts with the use of adaptive resources becomes more evident especially when the observed values of EA(0.95) as this statistic is more sensitive with greater differences in relation to the Nash-Sutcliffe Coefficient (NS). Moreover, this is most representative for larger errors which occur precisely during flooding events. In general, we observed that, as much as the area of the basin decreases, it is possible to obtain forecasts with smaller lead times, but the influence of the size of the area controlled upstream basins improves the performance of smaller basins when observing, especially the errors EA (0.95). However, if the proportion of the upstream of controlled basin is already quite large - as in the case of the alternatives 1 and 2 used for forecast in Itaqui (between 88.5% and 95.4%, respectively) - the adaptive resources do not differ too much in getting better results. However, when observing basins with smaller areas controlled upstream - as is the case of Porto Lucena to alternative 2 (65% controlled area) - the performance gain of the models with the use of the complete adaptive resources (MQR+f.e.) becomes relevant.

As a solution to mid-air haptic actuation with strong and continuous tactile force, Magnetic Rendering is presented as an intuitive haptic display method applying an electromagnet array to produce a magnetic field in mid-air where the force field can be felt as magnetic repulsive force exerted on the hand through the attached magnet discs. The magnetic field is generated by a specifically designed electromagnet array driven by direct current. By attaching small magnet discs on the hand, the tactile sensation can be perceived by the user. This method can provide a strong tactile force on multiple points covering user’s hand and avoid cumbersome attachments with wires, thus it is suitable for a co-located visual and haptic display. In my work, the detailed design of the electromagnet array for haptic rendering purposes is introduced, which is modelled and tested using Finite Element Method simulations. The model is characterized mathematically, and three methods for controlling the magnetic field are applied accordingly: direct control, system identification and adaptive control. The performance of the simulated model is evaluated in terms of magnetic field distribution, force strength, operation distance and force stiffness. The control algorithms are implemented and tested on a 3-by-3 and a 15-by-15 model, respectively. Simulations are performed on a 15-by-15 model to generate a haptic human face, which results in a smooth force field and accurate force exertion on the control points.

Directors designed for observation and fire control in naval environments consist of a mechanical pedestal moved by two electrical motors. To meet the high demands on director precision, a servo solution based on feedback control is used. The digital servo controller has to be tuned to meet demands on performance and stability. This report presents methods for automatic tuning, intended to replace today’s manual tuning procedures. System identification based on relay feedback and recursive least-squares approximations are combined with the Ziegler-Nichols and AMIGO tuning procedures for PI controllers are evaluated. Evaluations are performed in simulations, for which a SIMULINK model is constructed. Results indicate that the automatic tuning may perform well compared to the manual tuning used today, and that it could bring considerable reduction in the time required for tuning.

No description available.

This research presents an investigation into the development of real time system identification using intelligent algorithms. A simulation platform of a flexible beam vibration using finite difference (FD) method is used to demonstrate the real time capabilities of the identification algorithms. A number of approaches and algorithms for on line system identifications are explored and evaluated to demonstrate the merits of the algorithms for real time implementation. These approaches include identification using (a) traditional recursive least square (RLS) filter, (b) Genetic Algorithms (GAs) and (c) adaptive Neuro_Fuzzy (ANFIS) model. The above algorithms are used to estimate a linear discrete second order model for the flexible beam vibration. The model is implemented, tested and validated to evaluate and demonstrate the merits of the algorithms for real time system identification. Finally, a comparative performance of error convergence and real time computational complexity of the algorithms is presented and discussed through a set of experiments.