Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 20 of 109 for “"robust model"”.
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Adaptive robust model predictive control for nonlinear systems
Modeling error and external disturbances can severely degrade the performance of Model Predictive Control (MPC) in real-world scenarios. Robust MPC (RMPC) addresses this limitation by optimizing over control policies but at the expense of computational complexity. An alternative strategy, known as …
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Robust model-based reinforcement learning using L1 adaptive control
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-08-01
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Robust model selection and outlier detection in linear regressions
In this thesis, we study the problems of robust model selection and outlier detection in linear regression. The results of data analysis based on linear regressions are highly sensitive to model choice and the existence of outliers in the data. This thesis aims to help researchers to choose the …
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Robust, model-based fault detection for commercial transport air data probes.
… and cost. This thesis presents an alternative, model-based approach to fault detection for a non-redundant air data system. The model-based fault detection strategy uses robust linear filtering methods to reject exogenous disturbances, e.g. wind, and provide robustness to model errors. The …
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Machine Learning Modeling and Robust Model Predictive Control of a Wind Turbine
… of this research is to develop a comprehensive model-based controller for a wind turbine. To do so, the problem of Robust Model Predictive Control (RMPC) of discrete-time hybrid systems is addressed. A hybrid model of the wind turbine is identified with machine learning techniques and the …
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Robust Model-Based Control of Nonlinear Systems for Bio-Inspired Autonomous Underwater Vehicles
… of this dissertation is to propose a generic robust control framework specific for bio-inspired autonomous underwater vehicles (BIAUV). These vehicles utilize periodic oscillation of a flexible structural component to generate thrust, a propulsion mechanism that can be tuned to operate under …
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Predicting Bitcoin: a robust model for predicting Bitcoin price directions based on network influencers
… of annualized gains. In this thesis, a model for predicting the future daily price of Bitcoin is proposed and evaluated in comparison to that of a purely random model. Bitcoin is a novel digital currency that relies on cryptography instead of a central authority to verify transactions. …
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Applications of stochastic inventory control in market-making and robust supply chains
… extends the classical inventory control model to address stochastic inventory control problems raised in market-making and robust supply chains. In the financial market, market-makers assume the role of a counterpart so that investors can trade any fixed amounts of assets at quoted bid or …
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The development of a harmonised business model for South Africa and the SADC sub-region
… context of her role in the SADC sub-region. A robust model, taking into consideration, the legal, socio-cultural, political and economic diversity of SADC members is proposed. It is believed that the model can serve as a template for other regions in the continent.
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Knowledge Through Making
… The centerpiece of the project is a robust model, which acts as an analogue to the actual construction method.
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Robust Cross-dock Location Model Accounting for Demand Uncertainty
… of this thesis was to develop optimization models to locate cross-docks in supply chain networks. Cross-docks are a type of intermediate facility which aid in the consolidation of shipments, in which the goods spend little or no time in storage. Instead, the goods are quickly and efficiently …
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Optimization of surface dielectric barrier discharge ion sources for electroaerodynamic propulsion
… actuators. Optimizing SDBD actuators requires a robust model for SDBD electrical power draw as a function of geometric, material, and electrical properties.
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Scalable Robust Models Under Adversarial Data Corruption
… the fast-growing amount of data makes the robust models more difficult to handle large-scale data sets. This thesis focuses on the development of methods for scalable robust models under the adversarial data corruption assumptions. Four methods are proposed, including robust regression via …
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Remedies for building reliable cyber-physical systems
… of these systems. Hybrid automata is the main modeling language for cyber-physical systems. However, verifying safety properties is undecidable for all but very restricted known classes of these automata. Our first result introduces a new subclass of hybrid automata for which bounded time …
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Think global, act local when estimating a sparse precision matrix
… Using the framework of probabilistic graphical models, the algorithm performs robust covariance estimation to generate potentials for small cliques and fuses the local structures to form a sparse yet globally robust model of the entire distribution. Identification of appropriate local structures …
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Apply Machine Learning on Cattle Behavior Classification Using Accelerometer Data
… We compared the performance of various models and found a robust model with relatively low computation and high accuracy. For the deep learning approach, we designed an end-to-end trainable Convolutional Neural Networks (CNN) to predict activities for given segments, applied …
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Diameter Estimation of Eucalyptus spp. Plantations in Southern Brazil Using Global Ecosystem Dynamics Investigation Data and Support Vector Regression
… volume, stems per hectare, etc.) and to create a model of plantation diameter using Support Vector Regression (SVR). SVR enabled a robust model of tree diameter even given the heteroskedasticity and spatial auto correlation present in the GEDI data, which deleteriously impacted attempts at linear …
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Beyond Limits: Detecting Anomalies in Sparse, High-dimensional Data
… complicates the training of accurate models. This thesis addresses these issues by proposing a novel approach SparseDetect designed to detect anomalies in high dimensional and low sample situations. SparseDetect combines semi supervised anomaly detection algorithms with advanced …
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The quaternion Bingham Distribution, 3D object detection, and dynamic manipulation
… in the robot's sensory data necessitate a robust model for representing uncertainty on the space of 3-D orientations. This is given by the quaternion Bingham distribution-a maximum entropy probability distribution on the 4-D unit quaternion hypersphere. In this thesis, we apply the …
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Cell Death Mechanisms in Drosophila Differentiated Photoreceptor Neurons
… cell death stimuli. ferritin mutations provide a robust model to study the role of iron and oxidative stress in neurodegeneration. To further investigate the role of Ferritin in photoreceptor survival, we generate genetically-encoded in vivo iron and redox sensors. In summary, by developing novel …
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