This algorithm introduces an adaptive observation model under the particle filtering framework,and adaptively chooses the noise variance and the particle quantity according to the errors of tracking and the athletes\' act change margin.

An adaptive sliding-mode observer for induction motor sensorless speed control was studied,which was composed of two sliding-mode current observers,a sliding-mode rotor flux observer and speed observer.

Aiming at a kind of nonlinear closed-loop stable systems,a robust fault diagnosis method based on adaptive-fuzzy state observer and neural network learning structure is presented under external disturbance and internal system parameter error,the adaptive-fuzzy systems is adopted to repair nonlin- ear parts and RBF neural network is designed to track and diagnose faults.

This paper studies an enhanced adaptive observer to estimates speed and position of the rotor to satisfy the needs of full-speed implement for SPMSM drives.