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Discrete-Time Neural Network Based State Observer With Neural Network Based Control Formulation For A Class Of Systems With Unmatched Uncertainties, Jason Michael Stumfoll
Discrete-Time Neural Network Based State Observer With Neural Network Based Control Formulation For A Class Of Systems With Unmatched Uncertainties, Jason Michael Stumfoll
Masters Theses
"An observer is a dynamic system that estimates the state variables of another system using noisy measurements, either to estimate unmeasurable states, or to improve the accuracy of the state measurements. The Modified State Observer (MSO) is a technique that uses a standard observer structure modified to include a neural network to estimate system states as well as system uncertainty. It has been used in orbit uncertainty estimation and atmospheric reentry uncertainty estimation problems to correctly estimate unmodeled system dynamics. A form of the MSO has been used to control a nonlinear electrohydraulic system with parameter uncertainty using a simplified …