Dual EKF-based model parameters identification for flight simulation turntable

The load change of flight simulation turntable often leads to the deviation of its control performance due to the poor adaptability of the traditional fixed-parameter controller for the varying model parameters. Aiming to identify the model parameters of flight simulation turntable precisely and rapidly and lay a solid foundation for the realization of adaptive controller with constantly high dynamic performance regardless of load alternation, this paper proposes an effective method based on dual extended Kalman filter (DEKF) to identify model parameters of turntable, in which, two low-order EKFs instead of one high-order EKF are used to reduce the computational complexity and improve the identification accuracy. And a parameter weighing approach is designed to overcome the enlarged error caused by differences in magnitude order among the parameters. Furthermore, simulations and experiments are conducted to verify the effectiveness and superiority of this method.