Adaptive Fault Detection and Isolation Methods for Uncertain Nonlinear Control Systems

A nonlinear control and fault detection technology, applied in general control systems, control/regulation systems, test/monitoring control systems, etc., can solve the problem of adaptive fault detection and isolation methods for uncertain nonlinear control systems, without considering system parameters Uncertainty, single fault type, etc.

Active Publication Date: 2021-06-11
HARBIN INST OF TECH
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention is to solve the problem that the fault types that can be judged by the fault diagnosis method in the prior art are relatively single, and the uncertainty of system parameters is not considered. Now, an adaptive fault detection and isolation method for an uncertain nonlinear control system is proposed.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Adaptive Fault Detection and Isolation Methods for Uncertain Nonlinear Control Systems
  • Adaptive Fault Detection and Isolation Methods for Uncertain Nonlinear Control Systems
  • Adaptive Fault Detection and Isolation Methods for Uncertain Nonlinear Control Systems

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach 1

[0054] Specific implementation mode one: combine figure 1 To illustrate this embodiment, the adaptive fault detection and isolation method for an uncertain nonlinear control system includes:

[0055] Step 1: Design an uncertain parameter estimation scheme for the control system model, update the estimated values ​​of uncertain parameters in real time, reduce the influence of parameter uncertainty on fault diagnosis, and improve the sensitivity of the fault detection scheme;

[0056] The control system model is a nonlinear control system containing parameter uncertainty, and its state space expression is:

[0057]

[0058] Among them, x is the n-dimensional state vector of the system; is the first derivative of x, that is, the state space model of the system; θ is an uncertain parameter, f(x,u) and is a known nonlinear function matrix, Δ(x, u, t) represents the nonlinear uncertainty; assuming that the system only has one specific fault in N types of faults (this method ...

specific Embodiment approach 2

[0095] Specific implementation mode two: this implementation mode is different from the specific implementation mode in that the steps described in step one upper bound of for:

[0096] upper bound of for:

[0097]

[0098] Among them, λ m is the largest eigenvalue of matrix A, δ m is the upper bound of the system disturbance, ie |Δ(x,u,t)|≤δ m ;

[0099] The initial value of the parameter adaptive estimation error upper bound is:

[0100]

[0101] Among them, θ max ,θ min are the upper and lower bounds of the uncertain parameter vector modulus, namely θ min ≤|θ|≤θ max .

[0102] Other steps and parameters are the same as those in the first embodiment.

specific Embodiment approach 3

[0103] Specific implementation mode three: the difference between this implementation mode and specific implementation modes one or two is that the steps described in step two Corresponding fault detection adaptive threshold μ i (t), specifically:

[0104]

[0105] Among them, Ψ i (x,u) is a known function row vector the upper bound of L i Represents the state estimator gain of the state estimator (12), t represents the running time of the system, δ im is the upper bound of the disturbance component of the system, ie |Δ i (x,u,t)|≤δ im .

[0106] Other steps and parameters are the same as those in Embodiment 1 or 2.

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

An adaptive fault detection and isolation method for an uncertain nonlinear control system relates to a fault detection and isolation method for a nonlinear control system. The purpose of the invention is to solve the problem that the existing fault diagnosis method can judge relatively single fault types and does not consider the uncertainty of system parameters. The method of the present invention includes: designing an estimation scheme for uncertain parameters for the control system model, and updating the estimated value of the uncertain parameter in real time; based on the obtained estimated value of the uncertain parameter, designing a fault detection state estimator to estimate the state of the system , to get the residual of the system state estimation; when a fault is detected in the system at a certain moment, it is judged which type the fault belongs to, that is, the isolation scheme is started. The invention belongs to the field of fault detection and isolation of nonlinear control systems.

Description

technical field [0001] The invention relates to a fault detection and isolation method for a nonlinear control system, in particular to an adaptive fault detection and isolation method for an uncertain nonlinear control system. Background technique [0002] In order to improve the reliability and security of the control system, it is very important to design a fault diagnosis scheme for the system. When the system fails, such as actuator failures, sensor failures, and structural failures caused by aging or damage of system components, effective fault diagnosis methods can detect the occurrence of faults in a timely and accurate manner, determine the type of fault, and provide fault-tolerant or Deactivation and replacement of faulty components provide a prerequisite to prevent further spread of faults and reduce the impact of faults on system operation to ensure system stability, reliability, and security. [0003] Most of the existing fault diagnosis schemes only diagnose a...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Patents(China)
IPC IPC(8): G05B23/02
CPCG05B23/0213G05B23/0243G05B23/0275
Inventor 孙维超闫帅高会军
Owner HARBIN INST OF TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products