Networked motion control system attack estimation method based on gradient descent algorithm

Abstract

The invention discloses a networked motion control system attack estimation method based on a gradient descent algorithm. The method comprises the following steps: firstly determining a state space equation of a system and discretizing the state space equation under the condition that there is a sensor attack in the system; constructing an output equation of tau sensor measurement values; and finally, constructing an observer based on a gradient descent algorithm, and converging the estimation error into a predetermined minimum energy boundary. The event-driven technology is adopted, computingresources can be saved, and the computing performance of the system is improved. According to the observer design based on the gradient descent algorithm, the attack estimation effect precision is higher, and the estimation performance can be improved by adjusting specific parameters.

Description

technical field [0001] The invention belongs to the technical field of network security, and specifically provides an attack estimation method of a networked motion control system based on a gradient descent algorithm, which can identify attacks, evaluate the system security situation, and ensure its safe operation. Background technique [0002] The networked motion control system refers to a kind of networked control system that is closely coupled with the interaction between the information transmission process and the dynamic evolution process of the object. However, it is precisely because of the high coupling between information transmission processing and system dynamics that such systems are vulnerable to information attacks. To ensure that networked motion control systems can operate safely and reliably, they must have the ability to automatically identify attacks. Therefore, whether the attack signal can be accurately identified plays a very important role in the m...

AI Technical Summary

Problems solved by technology

The sliding mode observer requires the system to meet the observer matching conditions, and also needs information such as the upper bound of the attack signal, but in actual engineering, it is impossible to obtain any effective information about the attack

Robust observers are not restricted by observer matching conditions, but the upper bound of the estimation error is unknown, so the accuracy of the estimation cannot be guaranteed

The intermediate observer gives a theoretical upper bound, but the upper bound is relatively large, which only has theoretical significance, and cannot converge the estimation error of the attack signal to a predetermined range, so it is difficult to apply it in practice

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