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Stability analysis of the linear discrete teleoperation systems with stochastic sampling and data dropout

机译:具有随机采样和数据丢失的线性离散远程操作系统的稳定性分析

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摘要

This paper addresses the stability conditions of the sampled-data teleoperation systems consisting continuous-time master, slave, operator, and environment with discrete-time controllers over general communication networks. The output signals of the slave and master robots are quantized with stochastic sampling periods which are modeled as being from a finite set. By applying an input-delay method, the probabilistic sampling system is converted into a continuous-time system including stochastic parameters in the system matrices. The main contribution of this paper is the derivation of the less conservative stability conditions for linear discrete teleoperation systems taking into account the challenges such as the stochastic sampling rate, constant time delay and the possibility of data packet dropout. The numbers of dropouts are driven by a finite state Markov chain. First, the problem of finding a lower bound on the maximum sampling period that preserves the stability is formulated. This problem is constructed as a convex optimization program in terms of linear matrix inequalities (LMI). Next, Lyapunov-Krasovskii :based approaches are applied to propose sufficient conditions for stochastic and exponential stability of closed-loop sampled-data bilateral teleoperation system. The proposed criterion notifies the effect of sampling time on the stability-transparency trade-off and imposes bounds on the sampling time, control gains and the damping of robots. Neglecting this study undermines both the stability and transparency of teleoperation systems. Numerical simulation results are used to verify the proposed stability criteria and illustrate the effectiveness of the sampling architecture. (C) 2018 European Control Association. Published by Elsevier Ltd. All rights reserved.
机译:本文讨论了采样数据远程操作系统的稳定性条件,该系统由通用通信网络上的连续时间主站,从站,操作员和环境以及带有离散时间控制器的环境组成。从机械手和主机械手的输出信号通过随机采样周期进行量化,该随机采样周期建模为来自有限集。通过应用输入延迟方法,概率采样系统被转换为连续时间系统,该连续时间系统包括系统矩阵中的随机参数。本文的主要贡献是考虑了诸如随机采样率,恒定时间延迟和数据包丢失的可能性等挑战,推导了线性离散远程操作系统的保守性较差的稳定条件。辍学的数量由有限状态马尔可夫链驱动。首先,提出了寻找最大采样周期的下限以保持稳定性的问题。根据线性矩阵不等式(LMI),将此问题构造为凸优化程序。接下来,基于Lyapunov-Krasovskii的方法被用来为闭环采样数据双向遥操作系统的随机和指数稳定性提出充分的条件。提出的准则通知了采样时间对稳定性-透明度折衷的影响,并对采样时间,控制增益和机器人的阻尼施加了限制。忽视这项研究会破坏远程操作系统的稳定性和透明度。数值模拟结果用于验证所提出的稳定性标准并说明采样架构的有效性。 (C)2018欧洲控制协会。由Elsevier Ltd.出版。保留所有权利。

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