Dissertations / Theses on the topic 'Observer'

Feedback control of Chest Acceleration or Chest Deflection is believed to be a good way of minimizing the risk of injury. In order to implement such a controller in a car, an observer estimating these responses is needed. The objective of the study was to develop a model of the dummy’s chest capable of estimating the Chest Acceleration and the Chest Deflection during frontal crashes in real time. The used sensor data come from car accelerometer and spindle rotation sensor of the belt, the data has been collected from dummies during crash tests. This study has accomplished the aims using a simple linear model of the chest using masses, springs and dampers. The parameters of the model have been estimated through system identification. Two types of black-box models have also been studied, one ARX model and one state-space model. The models have been tested and validated against data coming from different crash setups. The results show that all of the studied models can be used to estimate the dummy responses, the physical grey-box model and the black-box state-space model in particular.

Genom att använda återkoppling av storheterna bröstacceleration och bröstintryck antas man kunna minska risken för skador vid krockar i personbilar. För att kunna implementera detta behövs en observatör för dessa storheter. Målet med denna studie är att ta fram en modell för att kunna skatta accelerationen i bröstkorgen samt bröstintrycket i realtid i frontala krockar. Sensordata som använts kom från en accelerometer och en givare för att mäta rotationen i bältessnurran. Detta har gjorts genom att modellera bröstkorgen med linjära fjädrar och dämpare. Dess parametrar har skattats från data från krocktester från krockdockor. Två s.k. black-box-modeller har också tagits fram, en ARX-modell och en på tillståndsform. Modellerna har testats och validerats mha data från olika sorters krocktester. Resultaten visar att alla studerade modeller kan användas för att skatta de ovan nämnda storheterna, den fysikaliska modellen och black-box-modellen på tillståndsform fungerade bäst.

The longitudinal controller at DaimlerChrysler AG consists of two cascade controllers. The outer control loop contains the driver assistance functions such as speed limiter, cruise control, etc. The inner control loop consists of a PID-controller and an observer. The task of the observer is to estimate the part of the vehicle's acceleration caused by large disturbances, for example by a changed vehicle mass or the slope of the road.

As observer the Kalman filter is selected. It is the optimal filter when the process model is linear and the process noise and measurement noise can be modeled as Gaussian noise. In this Master's thesis the theory for the Kalman filter is presented and it is shown how to choose the filter parameters. Simulated annealing is a global optimization technique which can be used when autotuning, i.e., automatically find the optimal parameter settings. To be able to perform autotuning for the longitudinal controller one has to model the environment and driving situations.

In this Master's thesis it is verified that the parameter choice is a compromise between a fast but jerky, or a slow but smooth estimate. As the output from the Kalman filter is directly added to the control value for the engine and brakes, it is important that the output is smooth. It is shown that the Kalman filter implemented in the test vehicles today can be exchanged with a first-order lag function, without loss in performance. This makes the filter tuning easier, as there is only one parameter to choose.

Change detection is a method that can be used to detect large changes in the signal, and react accordingly - for example by making the filter faster. A filter using change detection is implemented and simulations show that it is possible to improve the estimate using this method. It is suggested to implement the change detection algorithm in a test vehicle and evaluate it further.

The Automated Manual Transmission system Opticruise is dependent on signals from sensors located in different parts of the Scania trucks. These signals are of different qualities and have different update frequencies. Some signals and quantities that are hard or impossible to measure are also of importance to this system.

In this thesis a driveline observer for the purpose of signal improvement is developed and estimations of unknown quantities such as road incline and mass of the vehicle are performed. The outputs of the observer are produced at a rate of 100 Hz, and include in addition to the mass and road incline also the speed of the engine, output shaft of the gearbox, wheel and the torsion in the driveline. Further the use of an accelerometer and the advantages gained from using it in the observer are investigated.

The outputs show an increased quality and much of the measurement noise is successfully removed without introducing any time delays. A simulation frequency of 100 Hz is possible, but some dependency toward the stiffness of the driveline is found. The observer manages to estimate the road slope accurately. With the use of an accelerometer the road slope estimation is further improved and a quickly converging mass estimation is obtained.

To satisfy the increasing petroleum consumption on a world wide basis there is a need to find new resources. As mature fields are drained, reservoir pressure falls, which again leads to tight pressure margins. To reduce down time due to hole stability problems (e.g. kicks) there is a demand for accurate control of the pressure profile in the well. As the pressure profile is not known and depends on unknown factors such as friction loss there is a need to estimate the pressure. In this thesis an observer that adapts to unknown factors, such as friction and density changes, and estimates the bottomhole pressure is presented. Furthermore, a parameter estimator for the bulk modulus in the annulus is developed as an extension to the observer to facilitate for future control design. Both designs are based on a third order model and provide rigid proofs of stability and convergence of the estimated pressure and parameters. The pressure estimate from the observer is shown to converge to the true pressure under reasonable conditions. For parameter estimates to converge to their true values conditions on excitation are presented. The observer and parameter estimator are tested in simulations and also on log data from a well drilled at the Grane field in the North Sea. Simulation results show that the observer performs very well during typical drilling procedures affecting choke valve opening, pump flows and drill string movements. The observer shows promising behavior when tested on log data from the Grane field.

Due to stricter emission legislation, there is a need for more efficient control of diesel engines with exhaust gas recirculation(EGR). In particular, it is important to estimate the air/fuel ratio accurately in transients. Therefore a new engine gas flow model has been developed. This model divides the gas into one part for oxygen and one part for inert gases. Based on this model an observer has been designed to estimate the oxygen concentration in the gas going into the engine, which can be used to calculate the air/fuel ratio. This observer can also be used to estimate the intake manifold pressure. The advantage of estimating the pressure, instead of low pass filtering the noisy signal, is that the observer does not cause time delay.

This dissertation includes two essays exploring the effects of observers' interpretation of signaling behavior by others on the inferences and decision making of the observers. The first essay investigates how observers make inferences about other people's brand attachment. We propose that observers use the proximity of branded objects to the physical being of the user and the costs incurred to acquire the object to determine the degree of self-extension of the object—that is, to what extent it represents a part of the person's self-concept. Through two studies, we show that to the extent that an object is seen as self-extensive, the user would be inferred to be engaging in self-expression, attempting to convey aspects of their personality to others by using the object. These beliefs about self-expression then lead observers to infer that the individual is attached to the brand.

In the second essay, we consider how a brand's advertising appeals should be affected by its market position. Building on an experimental study, we present a duopoly model of brand advertising copy decisions, where consumer motives are influenced by Quality-based and Image-based advertising appeals. We show that each brand's decision to select one type of advertising appeal over the other is a function of its market position. We find that larger brands will use Quality-based appeals while smaller brand will use Image-based appeals. We empirically test these findings by examining advertising decisions for major brands found in a popular newsmagazine. Consistent with the model, we find that larger market share brands use Quality-based advertising appeals to a greater extent, while smaller brands use more Image-based appeals. Further, we find that brands that deviate from the predictions of the model are less profitable. Our results suggest that marketing managers should consider their position in the market when crafting advertising appeals, with larger brands emphasizing product quality in their appeals and smaller brands emphasizing the fit of their products with consumers' self-image.