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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.

Aiming to increase the convergence speed of perturbation based extremum seeking control, this paper proposed a novel gradient-based perturbation extremum seeking control (GPESC) scheme by combining sine perturbation signal and input-output gradient. In this scheme, the demodulated output signal in classic extremum seeking control (CESC) is replaced with filtered input-output gradient signal to decrease the fluctuation of convergence, which can speed up the movement toward extremum dramatically. Strict stability analysis of GPESC is presented by using averaging method, and parameter selection principles are discussed. Moreover the effectiveness and superiority of the proposed scheme are verified with simulations.