Sökning: "parameterestimering"
Visar resultat 1 - 5 av 10 uppsatser innehållade ordet parameterestimering.
1. Rotor temperature estimation in Induction Motors with Supervised Machine Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The electrification of the automotive industry and artificial intelligence are both growing rapidly and can be greatly beneficial for a more sustainable future when combined. Induction machines exhibit many complex relationships between physical and electromagnetic properties that must be calculated in order to produce the correct quantities of torque and speed commanded by the driver. LÄS MER
2. Short-horizon Prediction of Indoor Temperature using Low-Order Thermal Networks : A case study of thermal models for heat-system control applications
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Optimizing and controlling the heating systems in buildings is one way to decrease their load on the power grid, as well as introduce load flexibility to be used in Demand Response (DR) applications. A requirement in occupied buildings is that the thermal comfort of the residents is guaranteed, making the optimization of heating systems a constrained problem with respect to indoor temperature. LÄS MER
3. Dynamic Modelling of the Patient Circuit for High Frequency Ventilation
Master-uppsats, KTH/Maskinkonstruktion (Inst.)Sammanfattning : Artificial breathing is vital when it comes to treatment of critically ill patients where the natural breathing mechanism is insufficient. With the help of mechanical ventilators, the natural breathing mechanism of the patient can be assisted or even exchanged with the artificial breathing from the machine. LÄS MER
4. Parameter Estimation of LPI Radar in Noisy Environments using Convolutional Neural Networks
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Low-probability-of-intercept (LPI) radars are notoriously difficult for electronic support receivers to detect and identify due to their changing radar parameters and low power. Previous work has been done to create autonomous methods that can estimate the parameters of some LPI radar signals, utilizing methods outside of Deep Learning. LÄS MER
5. Optimal Control Model for an Autonomous Underwater Vehicle
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : The main goal with this thesis was to develop an optimal control model for anautonomous underwater vehicle (AUV) and evaluate whether reference trackingusing Model Predictive Control (MPC) based on a linear dynamics modeldescribing all six degrees of freedom (DOF) is a suitable method for waypointnavigation. MPC is an advanced receding horizon optimal control method capableof including constraints in the optimization. LÄS MER