Feral swine (Sus scrofa) are an invasive species in the Mississippi Alluvial Valley (MAV). They cause millions in damage annually to agriculture, and likely negatively affect native wildlife species. Using camera traps, I monitored 36 forest patches within the MAV to assess the effects of swine invasions on native wildlife species richness. I also modified the double-observer point count technique into a new method for estimating swine abundance with camera traps. Feral swine suppressed native vertebrate richness by 26% when compared to uninvaded patches. I validated the new double-observer technique by determining if it could detect an abundance-area relationship in wildlife populations and estimate a known decrease in abundance following swine removal. This technique was sensitive enough to detect the increase and decrease in abundance and estimated the number of individuals removed from the population relatively accurately. This technique may be useful in the future to manage feral swine populations.

To monitor and control the combustion in a diesel engine one can study the speed signal from the flywheel. The idea is that if individual cylinders give different amount of torque this will lead to variations in the flywheel speed. A model which describes the cylinder torque based on flywheel speed can be used to estimate the torque from individual cylinders. With this new knowledge of the individual performance of each cylinder the engine can be balanced. The balancing aim at making the speed of the flywheel more even but also required a model with estimated cylinder torque as input. This model may also be used for testing new control algorithms easily and gaining understanding of the dynamics. In this thesis a time dissolved model is constructed to describe the cylinder pressure-, crankshaft-, flywheel and damper dynamics. The model is based on a physical point of view by approximating the system into nodes containing mass, stiffness and friction. The inputs into the model are injection data from the engine management system (EMS) and a torque from a drive line. Ways to reduce the complexity of the model are investigated in order to invert the model to estimate the injection data based on flywheel speed measurements. Measurementsare done in a test bed to receive data required for model simulation and validation. The result is that the main behavior of the dynamics is caught. The self oscillation behaviors in some operating points are however not caught which indicates that the model can not explain all behaviors. A reduced model works almost as well but of course looses more of the non stiffness behavior. As expected, the model equations can not be solved in real time. The result of the inverted reduced model depends on the flywheel signal. When the signal contains little non stiffness behavior the result is good. An observer model based on the reduced model is suggested and tested in order to estimate the indicated torque from flywheel data. The observer manages to detect errors in the injection.

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<p>The NOx conversion efficiency of a combined Selective Catalytic Reduction and</p> <p>Ammonia Slip Catalyst (SCR-ASC) in a Diesel Aftertreatment (AT) system degrades with</p> <p>time. A novel model-informed data-driven On-Board Diagnostic (OBD) binary classification</p> <p>strategy is proposed in this paper to distinguish an End of Useful Life (EUL) SCR-ASC catalyst</p> <p>from Degreened (DG) ones. An optimized supervised machine learning model was used for the</p> <p>classification with a calibrated single-cell 3-state Continuous Stirred Tank Reactor (CSTR)</p> <p>observer used for state estimation. The method resulted in 87.5% classification accuracy when</p> <p>tested on 8 day-files from 4 trucks (2 day-files per truck; 1 DG and 1 EUL) operating in realworld on-road conditions.</p>

Heat flux and heat conductance at the metal mold interface plays a key role in controlling the final metal casting strength. It is difficult to obtain these parameters through direct measurement because of the required placement of sensors, however they can be obtained through inverse heat conduction calculations. Existing inverse heat conduction methods are analyzed and classified into three categories, i.e., direct inverse methods, observer-based methods and optimization methods. The solution of the direct inverse methods is based on the linear relationship between heat flux and temperature (either in the time domain or in the frequency domain) and is calculated in batch mode. The observer-based method consists on the application of observer theory to the inverse heat conduction problem. The prominent characteristic in this category is online estimation, but the methods in this category show weak robustness. Transforming estimation problems into optimization problems forms the methods in the third category. The methods in third category show very good robustness property and can be easily extended to multidimensional and nonlinear problems. The unknown parameters in some inverse heat conduction methods can be obtained by a proposed calibration procedure. A two-index property evaluation (accuracy and robustness) is also proposed to evaluate inverse heat conduction methods and thus determine which method is suitable for a given situation. The thermocouple dynamics effect on inverse calculation is also analyzed. If the thermocouple dynamics is omitted in the inverse calculation, the time constant of thermocouple should be as small as possible. Finally, a simple model is provided simulating the temperature measurement using a thermocouple. FEA (Finite Element Analysis) is employed to simulate temperature measurement.

<p> Motivated by the increasing need to monitor safety-critical systems subject to uncer-<br> tainties, a novel set-membership approach is proposed to estimate the state of a dynamical<br> system with unknown-but-bounded exogenous inputs. By fully utilizing the system struc-<br> tural information, the proposed algorithm can address both computational efficiency and<br> estimation accuracy without requiring restrictive conditions on the system. Particularly,<br> the system is first decomposed into the strongly observable subsystem and the weakly un-<br> observable subsystem. To make full use of the subsystem’s properties, a set-membership<br> observer based on the unknown input observer and an ellipsoidal set-membership observer<br> are designed for the two subsystems, respectively. Then, the resulting set estimates from<br> each subsystem are fused and transformed to obtain the set estimate for the original system,<br> which is guaranteed to bound the actual system state. The conditions for the boundedness<br> of the proposed set estimate are discussed, and the proposed set-membership observer is also<br> tested numerically using illustrative examples.</p>

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This thesis deals with the MIMO system analysis, with a comparison of a different frequency charactersitics, and including singular values characteristic. The H2 and H norms are defined for signals and a MIMO systems. A MIMO optimal control using an LQG, an H2 and an H control is defined and described. Their general advantages, disadvantages and similarities are summed up. An H2 and an H state controller and state observer synthesis is implemented in a MATLAB using linear matrix inequalities. Control of an inverted pendulum is designed using the H optimal cascade control, the H2 state control and the H state control. The results are compared with each other. The theoretical possibility of same H2 and H optimal state controller design is presented.

Les travaux de cette thèse portent sur l’estimation et la commande décentralisée des systèmes de grande dimension. L’objectif est de développer des capteurs logiciels pouvant produire une estimation fiable des variables nécessaires pour la stabilisation des systèmes non linéaires interconnectés. Une décomposition d’un tel système de grande dimension en un ensemble de n sous-systèmes interconnectés est primordiale. Ensuite, en tenant compte de la nature du sous-système ainsi que les fonctions d’interconnexions, des lois de commande décentralisées basées observateurs ont été synthétisées. Chaque loi de commande est associée à un sous-système qui permet de le stabiliser localement, ainsi la stabilité du système global est assurée. L’existence d’un observateur et d’un contrôleur stabilisant le système dépend de la faisabilité d’un problème d’optimisation LMI. La formulation LMI, basée sur l’approche de Lyapunov, est élaborée par l’utilisation de principe de DMVT sur la fonction d’interconnexion non linéaire supposée bornée et incertaine. Ainsi des conditions de synthèse non restrictives sont obtenues. Des méthodes de synthèse de loi de commande décentralisée basée observateur ont été proposées pour les systèmes non linéaires interconnectés dans le cas continu et dans le cas discret. Des lois de commande robuste H1 décentralisées sont élaborées pour les systèmes non linéaires interconnectés en présence de perturbations et des incertitudes paramétriques. L’efficacité et la validation des approches présentées sont testées sur un modèle de réseaux électriques composé de trois générateurs interconnectés / This thesis focuses on the decentralized estimation and control for large scale systems. The objective is to develop software sensors that can produce a reliable estimate of the variables necessary for the interconnected nonlinear systems stability analysis. A decomposition of a such large system into a set of n interconnected subsystems is paramount for model simplification. Then, taking into account the nature of the subsystem as well as the interconnected functions, observer-based decentralized control laws have been synthesized. Each control law is associated with a subsystem which allows it to be locally stable, thus the stability of the overall system is ensured. The existence of an observer and a controller gain matrix stabilizing the system depends on the feasibility of an LMI optimization problem. The LMI formulation, based on Lyapunov approach, is elaborated by applying the DMVT technique on the nonlinear interconnection function, assumed to be bounded and uncertain. Thus, non-restrictive synthesis conditions are obtained. Observer-based decentralized control schemes have been proposed for nonlinear interconnected systems in the continuous and discrete time. Robust Hinfini decentralized controllers are provided for interconnected nonlinear systems in the presence of perturbations and parametric uncertainties. Effectiveness of the proposed schemes are verified through simulation results on a power systems with interconnected machines