Date of Completion
4-15-2014
Embargo Period
4-14-2014
Advisors
Prof. Robert Gao and Prof. Jiong Tang
Field of Study
Mechanical Engineering
Degree
Master of Science
Open Access
Open Access
Abstract
This the sis present the continuous polynomial adaptive estimator CPAE which estimates a nonlinear parameter in nonlinearly parametrized NLP system. It combines the multiple region law with the companion adaptive system presented in [1] to come up with the CPAE. Stability is discussed and general definition of persistence of excitation PE condition is proposed for parameter convergence using the CPAE. As an application, the CPAE was successfully used to estimate the airspeed in presence of airspeed sensor failure on a developed academic aircraft model. As part of Loss of Control Prevention through adaptive reconfiguration project supported by NASA, the IMU theory method, which estimates airspeed using data from the inertial measurement unit IMU and the global positioning system GPS, is presented and applied on the generic transport model GTM. Conclusions and future work for aforementioned topics were presented at the end of this thesis.
Recommended Citation
Felemban, Haitham B., "Continuous Polynomial Adaptive Estimator for Nonlinearly Parameterized Systems" (2014). Master's Theses. 543.
https://digitalcommons.lib.uconn.edu/gs_theses/543
Major Advisor
Prof. Chengyu Cao