Fault detection method for self-triggering transmission system based on convex polytope theory

Abstract

The invention discloses a fault detection method for solving a system with a self-triggering transmission mechanism based on a convex polytope theory. The fault detection method comprises the following steps: S1, establishing a continuous system model containing interference input and faults and discretizing the continuous system model; S2, designing a fault detection filter, and deriving a stateestimation error system; S3, processing the error system by using a convex polytope theory, and defining random stability and H_ / H infinity performance constraints; S4, solving a linear matrix inequality to obtain the parameters of the fault detection filter; S5, designing a self-triggering transmission mechanism; and S6, substituting the parameters obtained in the above step into the fault detection filter to carry out fault detection.

Description

Technical field [0001] The invention relates to the fault diagnosis field of known system mathematical models, such as three-capacity water tank systems, power systems, and the like. Specifically, it relates to a fault detection method for solving systems with self-triggered transmission mechanisms based on convex polytope theory. Background technique [0002] With the continuous development of modern technology, modern industrial systems are becoming more and more complex and costly. Once the system fails, it will not only cause huge economic losses, but even endanger the lives of workers. This requires the system to have higher security, stability and reliability. Fault diagnosis technology is playing an increasingly important role in industrial production, and many research and production practices show that fault diagnosis technology has very important practical significance. [0003] In a networked control system, due to bandwidth limitations, data transmission will be subjec...

AI Technical Summary

Problems solved by technology

However, existing methods do not perform well in fault detection for systems with disturbing inputs and faults based on self-triggering transfer mechanisms

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