State estimation with unknown parameters in dynamic models

Yılmaz, Belgin


State estimation in electrical power systems.
Civanlar, Seyhan; Department of Electrical Engineering (1980)
State estimation of transient flow in gas pipelines by a Kalman filter-based estimator
Durgut, İsmail; Leblebicioğlu, Mehmet Kemal (2016-09-01)
In this study, real-time estimation of flow rate and pressure along natural gas pipelines under transient flow condition is aimed. The estimation of the internal states of gas pipelines is based on a recursive discrete data filtering algorithm called the discrete Kalman filter. The state space representation of the transient flow in gas pipelines, which is required for the filtering algorithm, is established by a discrete form of the nonlinear partial differential equations (PDE's) describing the characteri...
State-space identification of switching linear discrete time-periodic systems with known scheduling signals
Uyanik, Ismail; Hamzacebi, Hasan; Ankaralı, Mustafa Mert (The Scientific and Technological Research Council of Turkey, 2019-01-01)
In this paper, we propose a novel frequency domain state-space identification method for switching linear discrete time-periodic (LDTP) systems with known scheduling signals. The state-space identification problem of linear time-invariant (LTI) systems has been widely studied both in the time and frequency domains. Indeed, there have been several studies that also concentrated on state-space identification of both continuous and discrete linear time-periodic (LTP) systems. The focus in this study is the fam...
State estimation techniques for speed sensorless field oriented control of induction motors
Akın, Bilal; Ersak, Aydın; Department of Electrical and Electronics Engineering (2003)
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 spe...
State estimation of induction motor using unscented Kalman filter
Akin, B; Orguner, Umut; Ersak, A (2003-06-25)
In this paper, a new estimation technique, unscented Kalman filter (UKF) is applied to state observation in field oriented control (FOC) of induction motor. UKF, a recent derivative-free nonlinear estimation tool, is used for estimating rotor speed and fluxes using sensed stator current and voltages. In the simulations, UKF, whose several intrinsic properties suggest its use over EKF in highly nonlinear systems, turned out to be very similar to EKF in flux estimates. The simulation results also show that UK...
Citation Formats
B. Yılmaz, “State estimation with unknown parameters in dynamic models,” Middle East Technical University, 1995.