A Novel Nonlinear Scaling Method for Optimal Motion Cueing Algorithm in Flight Simulator  

作　　者：ZHU Daoyang DUAN Shaoli SHANG Jinqiu GUO Ping 

机构地区：[1]College of Intelligent Manufacturing,Wuhan Technical College of Communications,Wuhan 430070,Hubei,China [2]College of Aeronautical Engineering,Jiangsu Aviation Technical College,Zhenjiang 212134,Jiangsu,China

出　　处：《Wuhan University Journal of Natural Sciences》2020年第5期452-460,共9页武汉大学学报（自然科学英文版）

基　　金：Wuhan Technical College of Communications Fund(Y2019006);Wuhan Technical College of Communications Innovation Team(CX2018A07)。

摘　　要：Motion cueing algorithm plays a key role in simulator motion reproduction and improves the realism of movement sensation by combining with the human vestibular system.It is well established that scaling&limiting should be used to decrease the amplitude of the acceleration and angular velocity signals for making full use of limited workspace of motion platform.A novel nonlinear scaling method based on a third-order polynomial and back propagation(BP)neural networks for the motion cueing algorithm is proposed in this paper.The third-order polynomial method is applied to the low amplitude segment of the input signal to minimize the trigger delay of the sensation acceleration;in the high amplitude segment,the BP neural network is used to adaptively adjust the scaling factor of the input signal,to avoid washout displacement and angular displacement beyond the boundary of the workspace.The simulation experiment is verified in the longitudinal/pitch direction for flight simulator,and the result implies that the proposed method not only can overcome the problem of constant scaling parameter and improve motion platform workspace utilization,but also reduce the false cues during the motion simulation process.

关 键 词：optimal motion cueing algorithm nonlinear scaling human vestibular system dynamic fidelity 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] V211.73[自动化与计算机技术—计算机科学与技术]