可主动回中的参数时变洗出算法研究OA

Current motion cueing algorithms struggle to achieve both high motion sensation fidelity and strong real-time performance.To address the issue,this paper proposes a parametric time-varying washout algorithm with active return-to-center.The algorithm incorporates an active return-to-center controller which employs rotational degrees of freedom to quickly compensate for translational acceleration loss,thus reducing the displacement of translational degrees of freedom.On this basis,a parametric time-varying and approximately optimal washout algorithm is developed.It builds a parameter optimization model for the washout algorithm,as well as a coupling evaluation model between the motion system and human perception,establishing the mathematical relationship between algorithm parameters and motion perception fidelity.Through optimization,a mapping table linking influencing factors to optimal washout algorithm parameter combinations is obtained.The inverse distance weighting interpolation method is then employed to achieve real-time online calculation of the approximately optimal parameter combinations,avoiding extensive computations required for online parameter optimization and enhancing the adaptability of the motion simulation algorithm to changes in influencing factors.Simulation results demonstrate the method exhibits strong real-time performance and noise resistance.In terms of motion simulation fidelity,it reduces motion perception error by 43.63%compared to the classical washout algorithm and also cuts the usage of the motion platform's longitudinal travel,thereby improving the efficiency of the platform's translational travel in motion perception simulation.