Online Real-Time Estimation of Response Time for Periodic Messages in Controller Area Networks

Abstract

The Controller Area Networks (CAN) are widely used in industrial Networked Control Systems (NCSs), such as construction machineries, hybrid vehicles, robotics, and other applications. The message response time (MRT) or communication delay is the main issue to degrade the performance of CAN-based NCSs since its exact value is time-varying and unpredictable. The online acquisition of exact MRT can be quite helpful for the delay compensation of NCSs. However, since the clocks on different nodes are asynchronous, the MRT acquisition in CAN is a challenging work. The current delay acquisition methods for asynchronous systems are not suitable for the delay compensation in CAN-based NCSs because they either increase the bus load of CAN or cannot acquire the exact MRT in real time. In this paper, we propose a novel online real-time MRT estimation method for periodic CAN messages based on the analysis of message traces on CAN bus. The proposed method can estimate the exact MRT of the received message instance in real time without increasing the bus load and can be conveniently embedded into the CAN nodes without requiring additional equipment. In order to validate the proposed method, practical experiments are carried out and the experimental results show that the proposed method can effectively estimate the exact MRT of periodic CAN messages.

A New Compensation Method for DRR of a Roll-Pitch Seeker Based on ESO

“…To solve the problem of the roll-pitch seeker's suppression of interference torque and compensation for DRR, many researchers have proposed some quantitative methods [15,[20][21][22][23][24][25][26]. Li et al [20,21] take the platform seeker as the research object and propose the DRR compensation strategy based on ESO, which cannot be applied to a roll-pitch seeker without improvement.…”

“…However, this method involves the filtering process, which means that the compensation effect will be affected by the filtering accuracy. Gao et al [25] propose an estimation and compensation method for engineering application, but it lacks theoretical derivation. Lin et al [26] proposed an estimation method combining Kalman filtering and ESO, but it was not used in the rollpitch seeker.…”

“…Lin et al [26] proposed an estimation method combining Kalman filtering and ESO, but it was not used in the rollpitch seeker. The above-mentioned methods [15,[20][21][22][23][24][25][26] cannot completely solve the DRR compensation problem of the roll-pitch seeker under different simulation environments. The compensation effect will change with the change of the environment, and the influence of model loop parameters on the compensation effect is not considered in these existing methods either.…”