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Online message delay prediction for model predictive control over controller area network

机译:在线消息时延预测,用于控制器局域网模型预测控制

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Today's Cyber-Physical Systems (CPS) are typically distributed over several computing nodes communicated through buses such as Controller Area Network (CAN). Their control performance gets degraded due to variable delays incurred by messages on the shared CAN bus. This paper presents a novel online delay prediction method that predicts the message delay at runtime based on real-time traffic information on CAN. It leverages the proposed method to improve control quality, by compensating the message delay in the Model Predictive Control (MPC) algorithm design. It demonstrates that the delay prediction is accurate, and the MPC design which takes the message delay into consideration performs considerably better. It also implements the proposed method on an 8-bit 16MHz ATmega328P microcontroller and measures the execution time overhead. The results clearly indicate that the method is computationally feasible for online usage.
机译:当今的网络物理系统(CPS)通常分布在通过总线(如控制器局域网(CAN))进行通信的多个计算节点上。由于共享CAN总线上的消息引起的可变延迟,它们的控制性能会下降。本文提出了一种新颖的在线延迟预测方法,该方法基于CAN上的实时交通信息来预测运行时的消息延迟。它通过补偿模型预测控制(MPC)算法设计中的消息延迟来利用所提出的方法来提高控制质量。它证明了延迟预测是准确的,并且考虑了消息延迟的MPC设计的性能要好得多。它还在8位16MHz ATmega328P微控制器上实现了建议的方法,并测量了执行时间开销。结果清楚地表明该方法对于在线使用是计算上可行的。

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