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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.