A identificação de sistemas em malha fechada assume papel importante no contexto atual, já que reduz o custo operacional do processo de identificação no estágio de testes, evitando, por exemplo, a geração de produtos fora de especificação. Entretanto, requer uma série de cuidados especiais no tratamento dos dados a serem analisados para a obtenção dos modelos. Nesta dissertação um estudo acerca da identificação de sistemas monovariáveis lineares a partir de dados de operação em malha fechada, avaliando diferentes métodos e técnicas de identificação em malha fechada já consolidados é apresentado. Um novo método, recentemente proposto por Agüero (2005), o Virtual Closed Loop ouMétodo da Malha Virtual, que consiste na adição e remoção virtual de um controlador à malha analisada, de forma a filtrar a ação de controle real em um procedimento totalmente offline, é estudado em detalhes e uma adaptação é realizada na metodologia, com a simplificação do filtro virtual e forma de obtenção do modelo da malha aberta. O desenvolvimento e estudo da metodologia estão baseados em uma série de sistemas SISO distintos, com dinâmicas variáveis. Além disso, diferentes cenários com características peculiares são aplicados ao estudo, como distúrbios não medidos e ruído de medição, ilustrando de forma simples possíveis comportamentos dinâmicos encontrados em plantas industriais. / The identification of closed loop systems has taken on an important role in the current context, since it reduces the operational costs of the identification process in the testing stage, thus avoiding, for instance, the creation of non-specified products. However, it requires special care in the treatment of data to be analyzed for the obtainment of models. In this work, we present a study on the identification of linear models from closed loops operational data, evaluating different consolidated methods and techniques of closed loop identification. A new method is studied in detail in this work: the Virtual Closed Loop, which was proposed by Agüero (2005). It consists of the virtual addition and removal of a controller to the analyzed loop, so as to filter the input of the system in a completely offline procedure. It is also presented modifications on this methodology resulting in an simplification of the virtual filter and in the ways to obtain the open loop model. The development and study of this methodology are both based on different SISO systems, with variable dynamics. Other interesting characteristics, peculiar to the study, are considered in this work, as noise and dither signals. It illustrates, in a simple way, possible dynamic behavior patterns found in industrial plants.

A identificação de sistemas em malha fechada assume papel importante no contexto atual, já que reduz o custo operacional do processo de identificação no estágio de testes, evitando, por exemplo, a geração de produtos fora de especificação. Entretanto, requer uma série de cuidados especiais no tratamento dos dados a serem analisados para a obtenção dos modelos. Nesta dissertação um estudo acerca da identificação de sistemas monovariáveis lineares a partir de dados de operação em malha fechada, avaliando diferentes métodos e técnicas de identificação em malha fechada já consolidados é apresentado. Um novo método, recentemente proposto por Agüero (2005), o Virtual Closed Loop ouMétodo da Malha Virtual, que consiste na adição e remoção virtual de um controlador à malha analisada, de forma a filtrar a ação de controle real em um procedimento totalmente offline, é estudado em detalhes e uma adaptação é realizada na metodologia, com a simplificação do filtro virtual e forma de obtenção do modelo da malha aberta. O desenvolvimento e estudo da metodologia estão baseados em uma série de sistemas SISO distintos, com dinâmicas variáveis. Além disso, diferentes cenários com características peculiares são aplicados ao estudo, como distúrbios não medidos e ruído de medição, ilustrando de forma simples possíveis comportamentos dinâmicos encontrados em plantas industriais. / The identification of closed loop systems has taken on an important role in the current context, since it reduces the operational costs of the identification process in the testing stage, thus avoiding, for instance, the creation of non-specified products. However, it requires special care in the treatment of data to be analyzed for the obtainment of models. In this work, we present a study on the identification of linear models from closed loops operational data, evaluating different consolidated methods and techniques of closed loop identification. A new method is studied in detail in this work: the Virtual Closed Loop, which was proposed by Agüero (2005). It consists of the virtual addition and removal of a controller to the analyzed loop, so as to filter the input of the system in a completely offline procedure. It is also presented modifications on this methodology resulting in an simplification of the virtual filter and in the ways to obtain the open loop model. The development and study of this methodology are both based on different SISO systems, with variable dynamics. Other interesting characteristics, peculiar to the study, are considered in this work, as noise and dither signals. It illustrates, in a simple way, possible dynamic behavior patterns found in industrial plants.

We study linear descriptor systems with rectangular variable coefficient matrices. Using local and global equivalence transformations we introduce normal and condensed forms and get sets of characteristic quantities. These quantities allow us to decide whether a linear descriptor system with variable coefficients is regularizable by derivative and/or proportional state feedback or not. Regularizable by feedback means for us that their exist a feedback which makes the closed loop system uniquely solvable for every consistent initial vector.

Abstract Reverse link feedback power control in subject to a feedback delay and in conjuction with diversity is considered over a frequency-nonselective slow Rayleigh fading channel. The transmission power of a mobile station is adjusted as a function of fed back estimated channel state information, so that the average error probability is minimized when the average transmission power is fixed. The channel state is estimated by using known, constant-power pilot symbols. In each frame, a time multiplexed pilot symbol is transmitted in addition to the antipodal data symbols. In the literature, feedback MMSE (minimum mean-square error) power control has been analyzed in the case of a random time-invariant channel. Therein the frame size was two, i.e. one data and one pilot symbol were transmitted in each frame. Also, the fading gain was estimated by a one-shot MMSE estimator. This author's main contribution is that the aforementioned analysis has been extended to a more general system model in which the frame size is arbitrary, and in which the time-variant fading gain is estimated by an optimal MMSE estimator. For power control purposes, the estimator has to be a predictor since feedback requires causality. First, in order to avoid a delay in detection, the predictor is used in both power control and detection. In the case of a frame size of two, the performance of feedback MMSE power control employing the predictor is compared to that of a system using the one-shot estimator. Then, the performance of feedback MMSE power control with an optimal frame size is evaluated. Finally, the system performance is derived when a smoother is employed in detection, and the additional effects of a feedback delay and diversity on the performance are investigated. The performance difference between optimal (channel states are assumed to be known) and MMSE power control using a one-shot estimator is found to be significant at large signal-to-noise ratios (SNR's). This is in contradiction with the result presented earlier in the literature. The reason for the large performance difference is that the SNR of the channel estimate is small, since each estimate is computed using only one pilot symbol. The performance difference between optimal and MMSE power control with the predictor is smaller than said difference in the case of the one-shot estimator because the estimate is averaged over many pilot symbols. It is also observed that the lag error of the estimator considerably reduces the benefit of MMSE power control, even when the channel changes very slowly. To diminish the lag error, and to achieve good performance, a large number of estimator coefficients is required. It is well known that fixed-step adjustment closed loop power control attempts to compensate for all changes caused by the channel. In contrast, according to Monte Carlo simulations, MMSE power control did not attempt to compensate for the deepest fades. At other time instants, it strives to set the received SNR to an approximately constant level, which depends on the bit-error rate (BER) target. Increasing the frame size from the value of two not only improves the spectrum utilization, but was also shown to yield better performance for the pilot symbol system with MMSE power control over a slowly fading channel. Also, a clear performance improvement was achieved by using the smoother in detection. The performance loss resulting from a feedback delay of 10-20 % from the channel coherence time was shown to be small with reasonable BER values. Estimation errors were shown to diminish the benefit of power control when the diversity order was two, compared to the case of no diversity.

In this study a closed-loop cruise controller to minimise the running costs of the heavy-haul train is proposed. The running costs of a heavy-haul train are dependent on its travelling time, maintenance costs and energy consumption during the trip. The Coallink train with the new train technologies, Distributed Power (DP) traction and Electronically Controlled Pneumatic (ECP) brake system, is the centre of the study. A literature study on existing train control, both passenger and heavy-haul trains, is carried out to build up a knowledge base. Many different techniques for train handling were observed, their features in relation to heavy-haul ECP trains are discussed. From these backgrounds, a comprehensive longitudinal train model is proposed and successfully validated with real-life data from Spoornet. In the model, both static and dynamic in-train forces are studied, as well as energy consumption. This is possible by modelling each locomotive and wagon as an individual unit. The equations of motion for the train with coupled units and additional non-linearities, such as traction power limits, are considered. An open-loop controller for maintaining equilibrium velocity is designed. During transient velocity changes, a transient controller for calculating the required additional acceleration and deceleration is designed and validated. Because locomotive traction settings are only available in discrete notches, quantisation conversion from force into notches results in input chattering. In addition, during brake to traction transitions, the locomotives receive a sudden traction demand which results in spikes in in-train forces. To avoid these problems, input filtering is performed for these inputs. Closed-loop controllers based on LQR method, optimised for in-train forces, energy consumption and velocity regulation respectively, are designed and compared. To overcome the communication constraints, a fencing concept is introduced whereby the controller is reconfigured adaptively to the current track topology. Different train configurations in terms of availability of additional control channels for both traction and braking are compared, as well as their effects on dynamic and static in-train force. These configurations are unified, distributed and individual traction and brake controls. The results from these different configurations are compared to recorded train data and given in this study. From the results, it is found that the closed-loop controller optimised for in-train force is able to provide the best overall improvement out of the three controllers. / Dissertation (MEng)--University of Pretoria, 2007. / Electrical, Electronic and Computer Engineering / Unrestricted

The growing global population and climate change threaten the availability of many critical resources, and have been directly impacting the food and agriculture sector. Therefore, new cultivation technologies must be rapidly developed and implemented to secure the world's future food needs. Closed-loop greenhouse agriculture systems provide an opportunity to decrease resource reliance and increase crop yield. Greenhouses provide versatility in what can be grown and the resources required to function. Greenhouses can become highly efficient and resilient through the application of a closed-loop systems approach that prioritizes repurposing, reusing, and recirculating resources. Here, we employ a text mining approach to research the available research (meta-research) and publications within the area of closed-loop systems in greenhouses. This meta-research provides a clearer definition of the term “closed-loop system” within the context of greenhouses, as the term was previously vaguely defined. Using this meta-research approach, we identify six major existing research topic areas in closed-loop agriculture systems, which include: models and controls; food waste; nutrient systems; growing media; heating; and energy. Furthermore, we identify four areas that require further urgent work, which include the establishment of better connection between academic research to industry applications; clearer criteria surrounding growing media selection; critical operational requirements of a closed-loop system; and the functionality and synergy between the many modules that comprise a closed-loop greenhouse systems. / Thesis / Master of Applied Science (MASc)

No / In this work we have studied the performance of MIMO-DWT based multicarrier system using the feedback circuit from the receiver to the transmitter to understand the channel state information (CSI) and to create a steering matrix in order to constructively combine the received signal at the receiver which provides the advantage of keeping the burden of processing at the transmitter which has more power and less constraints.

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