Sökning: "sampled-data control"
Visar resultat 11 - 15 av 26 avhandlingar innehållade orden sampled-data control.
11. Learning in the Loop : On Neural Network-based Model Predictive Control and Cooperative System Identification
Sammanfattning : Inom reglerteknik har integrationen av maskininlärningsmetoder framträtt som en central strategi för att förbättra prestanda och adaptivitet hos styrsystem. Betydande framsteg har gjorts inom flera viktiga aspekter av reglerkretsen, såsom inlärningsbaserade metoder för systemidentifiering och parameterskattning, filtrering och brusreducering samt reglersyntes. LÄS MER
12. Fixed structure LQ design with applications
Sammanfattning : This thesis deals mainly with the problem of designing structure constrained controllers (or fixed structure control design) which is a problem that occurs in many industrial control applications. In process industry for example, almost all control loops are closed with commercial PI controllers (which have specified structures). LÄS MER
13. Frequency Domain Identification of Continuous-Time Systems : Reconstruction and Robustness
Sammanfattning : Approaching parameter estimation from the discrete-time domain is the dominating paradigm in system identification. Identification of continuous-time models on the other hand is motivated by the fact that modelling of physical systems often take place in continuous-time. LÄS MER
14. Non-Uniform Sampling in Statistical Signal Processing
Sammanfattning : Non-uniform sampling comes natural in many applications, due to for example imperfect sensors, mismatched clocks or event-triggered phenomena. Examples can be found in automotive industry and data communication as well as medicine and astronomy. LÄS MER
15. Initialization Methods for System Identification
Sammanfattning : In the system identification community a popular framework for the problem of estimating a parametrized model structure given a sequence of input and output pairs is given by the prediction-error method. This method tries to find the parameters which maximize the prediction capability of the corresponding model via the minimization of some chosen cost function that depends on the prediction error. LÄS MER