基于Smith预测器的马尔可夫方法缓解远程外科手术延迟

Pub Date : 2022-07-01 DOI:10.4018/ijban.292057
Ratish Kumar
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引用次数: 0

摘要

通过网络控制系统(NCS)进行远程机器人和远程操作的接受程度日益提高。NCS涉及反馈控制回路系统,其中控制组件(如执行器和传感器)被控制,并允许通过实时网络与分布在地理位置上的分布式用户共享其反馈。系统的性能和手术并发症主要取决于系统的延时、丢包和抖动。数据包到达接收端的延迟不仅会造成系统的不稳定,还会影响系统的性能。本文设计并仿真了基于模型的Smith预测控制器的功能。通过马尔可夫方法和卡尔曼技术对模型和随机误差进行估计。仿真结果表明,从主控制器到从控制器的延迟为49.926ms,从传感器到控制器的延迟为79.497ms,总延迟为129.423ms。这减少了延迟,提高了手术的准确性,消除了危及患者健康的危险因素。
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Alleviation of Delay in Tele-Surgical Operations using Markov Approach based Smith Predictor
The acceptance of tele-robotics and teleoperations through networked control system (NCS) is increasing day-by-day. NCS involves the feedback control loop system wherein the control components such as actuators and sensors are controlled and allowed to share their feedback over real time network with distributed users spread geographically. The performance and surgical complications majorly depend upon time delay, packet dropout and jitter induced in the system. The delay of data packet to the receiving side not only causes instability but also affect the performance of the system. In this article, author designed and simulate the functionality of a model-based Smith predictive controller. The model and randomized error estimations are employed through Markov approach and Kalman techniques. The simulation results show a delay of 49.926ms from master controller to slave controller and 79.497ms of delay from sensor to controller results to a total delay of 129.423ms. This reduced delay improve the surgical accuracy and eliminate the risk factors to criticality of patients’ health.
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