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Feedback optimization problem for master-slave teleoperation tracking in the presence of random noise in dynamics and feedback

机译:动态和反馈中存在随机噪声的情况下,主从遥操作跟踪的反馈优化问题

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In this work, we study the problem of a teleoperation master-slave system with error feedback based on sampled versions of the past and present master and slave positions. The sampling interval is the teleoperation delay, and small random fluctuations in the feedback coefficients are considered apart from small random noise in the dynamics. The overall master-slave dynamical system is abstracted into a stochastic delay differential system with random fluctuations in the parameters. This system is transformed into an ordinary stochastic differential system with an infinite-dimensional state vector, and using perturbation theory, integral expressions for the state correlations are obtained in terms of the noise correlations and feedback coefficient fluctuation correlations. We then partially explain how these computations may be used in minimizing the expected value of a cost functional of the state such as the master-slave tracking error energy. Some details about how the underlying delay differential equations for the master-slave dynamics are simulated using the fourth-order Runge-Kutta algorithm are provided. Finally, the simulation experiments are carried out on hardware, i.e., using the actual PHANToM Omni robot and these demonstrate excellent master-slave tracking when sampled teleoperation feedback is given.
机译:在这项工作中,我们基于过去和现在的主从位置的采样版本,研究带有错误反馈的遥操作主从系统的问题。采样间隔是远程操作延迟,除了动态中的小随机噪声外,还考虑了反馈系数的小随机波动。整个主-从动力系统被抽象为具有随机波动参数的随机时滞微分系统。该系统被转换成具有无限维状态向量的普通随机微分系统,并利用扰动理论,根据噪声相关性和反馈系数波动相关性,获得了状态相关性的积分表达式。然后,我们将部分解释如何在最小化状态成本函数(例如主从跟踪误差能量)的期望值时使用这些计算。提供了一些有关如何使用四阶Runge-Kutta算法模拟主从动力学的基本延迟微分方程的详细信息。最后,仿真实验是在硬件上进行的,即使用实际的PHANToM Omni机器人进行的,当给出采样的遥操作反馈时,这些实验证明了出色的主从跟踪能力。

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