Abstract
To improve the state estimation accuracy of nonlinear induction motor
with uncertain parameters, a robust desensitized rank Kalman filtering
(DRKF) is proposed to reduce state estimation error sensitivities to
uncertain parameters. A new sensitivity function is defined, and a novel
desensitized cost function for the deterministic sampling methods is
designed to obtain an optimal gain matrix. The sensitivity propagation
is summarized for deterministic sampling methods. Based on the rank
sample rule, the sensitivity propagation method is given, and the DRKF
algorithm is derived. Two dynamic behaviors of the induction motor with
two uncertain stator and rotor resistances are simulated to demonstrate
that the proposed DRKF has an excellent performance.