This thesis presents different state estimation techniques for speed sensorlees
field oriented control of induction motors. The theoretical basis of each algorithm is
explained in detail and its performance is tested with simulations and experiments
individually.
First, a stochastical nonlinear state estimator, Extended Kalman Filter (EKF)
is presented. The motor model designed for EKF application involves rotor speed,
dq-axis rotor fluxes and dq-axis stator currents. Thus, using this observer the rotor
speed and rotor fluxes are estimated simultaneously. Different from the widely
accepted use of EKF, in which it is optimized for either steady-state or transient
operations, here using adjustable noise level process algorithm the optimization of
EKF has been done for both states / the steady-state and the transient-state of
operations. Additionally, the measurement noise immunity of EKF is also
investigated.
Second, Unscented Kalman Filter (UKF), which is an updated version of
EKF, is proposed as a state estimator for speed sensorless field oriented control of
induction motors. UKF state update computations, different from EKF, are derivative
free and they do not involve costly calculation of Jacobian matrices. Moreover,
variance of each state is not assumed Gaussian, therefore a more realistic approach is
provided by UKF. In this work, the superiority of UKF is shown in the state
estimation of induction motor.
Third, Model Reference Adaptive System is studied as a state estimator. Two
different methods, back emf scheme and reactive power scheme, are applied to
MRAS algorithm to estimate rotor speed.
Finally, a flux estimator and an open-loop speed estimator combination is
employed to observe stator-rotor fluxes, rotor-flux angle and rotor speed. In flux
estimator, voltage model is assisted by current model via a closed-loop to
compensate voltage model&rsquo / s disadvantages.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/1055953/index.pdf |
| Date | 01 August 2003 |
| Creators | Akin, Bilal |
| Contributors | Ersak, Aydin |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | To liberate the content for public access |
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