Searched for: mods_note_programme_s:"Mechanical%5C+Engineering%5C+%7C%5C+Systems%5C+and%5C+Control"
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Bartels, Emiel (author)
A future rise in electrical energy demand is expected due to the electrification of the thermal energy supply and the rise in popularity of the Electric Vehicle (EV). This rise in the electrical energy demand results in needed investments in the electrical energy infrastructure to prevent congestion at the transformer due to the higher peak of...
master thesis 2020
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An, Jerry (author)
This work presents a decentralized optimization conflict resolution method based on a novel Alternating Directions Method of Multipliers (ADMM) variant and model predictive control (MPC). The variant, titled Online Adaptive Alternating Direction Method of Multipliers (OA-ADMM) aims to unify the application of ADMM to online systems, i.e. systems...
master thesis 2020
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Khalik, Alan (author)
With data-driven control it is possible to design a controller for systems with non-parametric models. The intermediate step of modelling or identification of the system is not necessary, because a non-parametric model of the system can be obtained by means of experimental data. In the linear time-invariant (LTI) framework, these non-parametric...
master thesis 2020
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Palande, Shreyash (author)
Substantial efforts are being made to make robots more reliable and safe to work around humans. Robots often perform flawless demos in a controlled environment under the supervision of an operator but tend to fail in the real world when deployed for a long period of time due to faults and environmental disturbances. A robotic system is composed...
master thesis 2020
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Mestre, Francisca (author)
The rising number of electricity consumers poses a challenge to power generators and grid operators in maintaining a balanced grid. Peak shaving is a technique that consists of shifting electricity consumption from hours of high demand to times of low demand, and has been gaining popularity in recent years. It allows to reduce peak loads which...
master thesis 2020
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Luijkx, Jelle (author)
There are many stages that involve humans handling food objects in the processing chains from farms to stores. For some of these tasks it is desirable to look for a robotic solution to either assist the human or even take over that task, e.g. if it is physically demanding, imposes contamination risks or because of economical considerations....
master thesis 2020
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de Haan, Taeke (author)
In this thesis, a geometry-based grasping method for vine-tomato is proposed. The method utilizes a geometric model of the robotic hand and truss to determine an optimal grasping location on the truss stem. This allows grasping a truss without requiring delicate contact sensors or complex mechanical models. A computer vision pipeline is...
master thesis 2020
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Dieben, Bas (author)
Drinking Water Distribution Network (DWDN) vulnerability to disasters yields ever threatening consequences to society. Earthquakes are shown to have devastating effects on these networks, causing multiple pipe breaks and leaks to occur simultaneously. This results in a lack of pressure and unavailability of water for extended time periods....
master thesis 2020
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Edridge, Thomas (author)
Higher-grade Inertial Measurement Units (IMUs) provide a better estimation of the orientation but are more expensive than lower-grade IMUs. The increase in availability and affordability of lower-grade IMUs over the last few years has provided an alternate solution: combine multiple lower-grade IMUs to increase sensor accuracy at low cost....
master thesis 2020
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Tombakaitė, Gabriele (author)
Sensors are used all around us in various industries, for instance: agricultural, medical,aerospace and automotive. It is important for these industries to have reliable sensor data because the functionality of technologies depends on it. In this work, the industry of inter-est is automotive, specifically in the field of Cooperative Adaptive...
master thesis 2020
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Jeschke, Joost (author)
Model Predictive Control (MPC) has shown promising results in the control of urban traffic networks, but has one major drawback. The, often nonlinear, optimization that has to be performed at every control time step is computationally too complex to use MPC controllers for real-time implementations (i.e. when the online optimization is performed...
master thesis 2020
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de Pont, Mike (author)
The human sensorimotor system can be seen as a complex network in which the brain plays an important role, resulting in a difficult-to-understand relation between proprioceptive stimuli and cortical responses. However, understanding this relationship is of added value for understanding various diseases which cause dysfunctionality. In recent...
master thesis 2020
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van der Geest, Xander (author)
The use of distributed multi-agent formation control for non-holonomic mobile robots shows great promise in practical environments. In this thesis, a Robot Operating System (ROS) package is developed in which various formation control algorithms are implemented for use on a group of skid-steer drive mobile robots. These formation control...
master thesis 2020
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Dekker, Quinten (author)
Dense 3D modeling based on monocular visual data is a powerful process of gaining spatial 3D understanding from 2D observations. The use of visual data to reconstruct such 3D models is still a challenging topic. To obtain the accurate dimensions, additional metadata is required such as a GPS which is not always available. Besides this, dealing...
master thesis 2020
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Khalid, Omer (author)
Traffic congestion on highways is a multi-sectoral phenomenon affecting society, the economy and the environment. It often takes place at specific locations such as on and off-ramps, weaving segments and intersections. The on-ramp merging procedure is considered as one of the main factors that causes traffic congestion on highways. The studies...
master thesis 2020
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Martinez Claramunt, F. (author)
Multi-robot motion planning without a central coordinator usually relies on the sharing of planned trajectories among the robots via wireless communication in order to achieve predictive collision avoidance. Path planners found in the literature that feature this scheme usually boast levels of performance comparable with their centralized...
master thesis 2020
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Hajee, B. (author)
The built environment is becoming healthier, smarter and more energy efficient during the transition to green building activity. Multi-sensor networks are a promising component of this transition, provided that their measurements are reliable. The reliability of the data is a real concern for DWA, as they use it for control purposes as well as...
master thesis 2020
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Kalisvaart, Dylan (author)
Super-resolution microscopy methods are able to image samples with improved resolution over the diffraction limit. Single-molecule localization microscopy (SMLM) methods break the diffraction limit by sparsely activating fluorescent emitters. The resulting sparsity in the emission signal can be exploited by estimation algorithms, which enables...
master thesis 2020
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Pietrak, Jakub (author)
Graph Neural Networks are a unique type of Deep Learning models that have a capability to exploit an explicitly stated structure of data representation. By design they carry a strong relational inductive bias, which is a set of assumptions that makes the algorithm prioritize some solutions over another, independent of observed data. This makes...
master thesis 2020
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Zattoni Scroccaro, Pedro (author)
In this thesis, we study Online Convex Optimization algorithms that exploit predictive and/or dynamical information about a problem instance. These features are inspired by recent developments in the Online Mirror Decent literature. When the Player's performance is compared with the best fixed decision in hindsight, we show that it is possible...
master thesis 2020
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