A small fault detection method for a closed-loop control system of a sampling manipulator

A fault detection and closed-loop control technology, applied in general control systems, control/regulation systems, testing/monitoring control systems, etc., can solve problems such as difficulty in detecting small faults, frequent changes in fault diagnosis speed, etc., and achieve the release of symbol constraints. , the effect of increasing the detectable fault information and improving the rapidity

Active Publication Date: 2022-03-15
SOUTH CHINA UNIV OF TECH +1
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  • Abstract
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Problems solved by technology

[0004] In order to overcome the defects and deficiencies in the prior art, the present invention provides a small fault detection method for the closed-loop control system of the sampling manipulator. Aiming at the problem that it is difficult to detect small faults in nonlinear uncertain systems, a method based on determination is proposed. The learning dynamic estimation method can effectively and accurately model the uncertain dynamics of the system, and realize the estimation of fault information; for the problem that the closed-loop system is difficult to detect faults due to the compensation of the controller, a control-based The total measurable fault residual detection scheme compensated by the controller can eliminate the compensation effect of the controller on the fault information, realize the enhancement of the detectable fault information, and ensure the rapid detection of faults; at the same time, on this basis, by designing a The weighted and recursive absolute residual accumulation mechanism solves the problems of frequent fault changes and slow fault diagnosis speed, and ensures the safety and rapidity of the fault detection system

Method used

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  • A small fault detection method for a closed-loop control system of a sampling manipulator
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  • A small fault detection method for a closed-loop control system of a sampling manipulator

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Embodiment 1

[0088] Such as figure 1 As shown, the present embodiment provides a small fault detection method of the closed-loop control system of the sampling manipulator, comprising the following steps:

[0089] S1: Establish a discrete-time single-link rigid manipulator dynamics model based on sampling data, specifically expressed as:

[0090]

[0091] Among them, k represents the running time of the sampling discrete manipulator system, T s Indicates the sampling time interval, and the sampling time point is kT s , X(k)=[x 1 (k),x 2 (k)] T ; x 1 (k) and x 2 (k) are the joint angular displacement and joint angular velocity of the manipulator respectively. u(k) is the control torque, f 0 (X(k)) and g 0 (X(k)) is the unknown nonlinear function of the system, g 0 (X(k))=T s M(x 1 (k)) -1 , f 0 (X(k))=x 2 (k)+T s M(x 1 (k)) -1 [-V m (x 1 (k),x 2 (k))x 2 (k)-G(x 1 (k))], M(x 1 (k)) is the inertia matrix of the manipulator, V m (x 1 (k),x 2 (k)) is the centripetal...

Embodiment 2

[0134] A small fault detection system for a closed-loop control system of a sampling manipulator, including: a model building block, an adaptive neural network controller building block, a dynamic estimator building block, a total measurable fault residual calculation module, and an absolute fault residual cumulative value Calculation module, fault detection decision building block;

[0135] In this embodiment, the model building module is used to establish a data sampling-based mechanical arm dynamics model and an expected regression trajectory model;

[0136] In this embodiment, the adaptive neural network controller building block is used to construct an adaptive neural network controller;

[0137] In this embodiment, the dynamic estimator building block is used to construct a dynamic estimator to approximate the unknown dynamics of the system;

[0138] In this embodiment, the total measurable fault residual calculation module is used to calculate the total measurable faul...

Embodiment 3

[0152] This embodiment provides a storage medium, the storage medium may be a storage medium such as ROM, RAM, magnetic disk, optical disk, etc., and the storage medium stores one or more programs. A glitch detection method for a closed-loop control system of a robotic arm.

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Abstract

The invention discloses a small fault detection method of a closed-loop control system of a sampling manipulator. The method comprises the following steps: designing an adaptive neural network controller of a discrete time manipulator; constructing a dynamic estimator to approximate the unknown dynamics of the system; The system dynamic residual and the residual compensated by the controller can further obtain the enhanced total measurable fault residual; calculate the weighted and recursive absolute fault residual cumulative value; The cumulative value is compared with the self-adaptive threshold, if there is a certain moment when the cumulative value of the fault residual is greater than the self-adaptive threshold, it is determined that the manipulator breaks down at this moment; the failure detection scheme of the present invention ensures that after the manipulator system breaks down, Realize rapid detection of faults, through the weighted recursive absolute residual accumulation mechanism, solve the problems of frequent fault changes and slow fault diagnosis speed, and ensure the safety and rapidity of the fault detection system.

Description

technical field [0001] The invention relates to the technical field of robot fault detection, in particular to a small fault detection method for a closed-loop control system of a sampling manipulator. Background technique [0002] Fault detection is an important issue in modern engineering systems and has received extensive attention so far. Modern engineering systems have increasingly high requirements for safety and reliability. The main goal of fault detection is to identify the occurrence of system faults during real-time operation. Timely and accurate fault diagnosis is crucial to the reliable and efficient operation of many engineering systems, especially those safety-critical, such as aero-engines, chemical processes, industrial robots, power networks, etc. [0003] Small faults are usually those that are smaller than the system uncertainty (e.g., unmodeled dynamics or disturbances / noise), and these faults usually appear at an early stage before larger faults occur. ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B23/02
CPCG05B23/0262G05B2219/24065
Inventor 王敏刘雅梅曾宇鹏戴诗陆
Owner SOUTH CHINA UNIV OF TECH
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