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加速度极限的英文

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"加速度极限"怎么读用"加速度极限"造句

英文翻译手机手机版

  • acceleration limit

例句与用法

  • Aiming at the problem of setting in advance for limit of acceleration in " current " statistical model , an improved maneuvering target tracking algorithm based on displacement prediction covariance is presented
    摘要针对“当前”统计模型中加速度极限值的预先设定问题,提出了一种基于位移预测协方差的改进机动目标跟踪算法。
  • This algorithm avoids the adverse influence of setting up the limit of acceleration in advance to state estimation , the simulation result shows the accuracy of the maneuvering target tracking is obviously enhanced by this algorithm
    该算法避免了加速度极限值的预先设定对状态估计的不利影响,仿真结果表明,该算法提高了机动目标的跟踪精度。
  • In the aspect of the time - optimal control algorithm , with the special trajectory , a method for seeking scalar velocity bound curve and scalar acceleration limit has been proposed , which fully considered the dynamics nonlinear
    在机器人时间最优控制算法方面,提出一种在特定轨迹约束下寻求标量速度边界曲线和标量加速度极限分布的方法,其充分考虑了机器人动力学的非线性因素。
  • By analyzing the scalar velocity bound curve and combining distribute of acceleration limit , a time - optimal control algorithm was designed . the results of experiments show it can make full use of the capacity of motor while realizing the stability and positioning accuracy of system , solving the problem of time - optimal control
    通过对标量速度边界曲线的分析,结合加速度极限分布情况,设计了一种在特定轨迹约束下机器人时间最优轨迹规划算法,以在保证系统稳定性和定位精度的前提下,充分发挥电机的性能。
  • Based on above performances the applications of multi - sensor data fusion in state estimation for maneuvering target is studied systemically . the main work includes : based on the analysis that the extreme value of acceleration presupposed causes influence in the “ current ” statistical model , a modified model is given , which utilizes the functional relationship between maneuvering status and estimation of the neighboring intersample position vector to carry out the self - adaptive of the process noise variance . then combining with the recursive characteristic of kalman filter , an improved self - adaptive filtering algorithm is presented
    基于此,本文针对多传感器数据融合技术在机动目标状态估计中的应用进行了系统的研究,其主要工作如下: 1 、基于“当前”统计模型中加速度极限值的预先设定对于滤波效果影响的分析,利用目标机动状况与相邻采样时刻间位置估计量变化之间的函数关系实现噪声方差自适应,进而提出了一种修正的模型,并结合卡尔曼滤波递推算法,提出了一种改进的自适应滤波算法。
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