A Fault Detection Method Based on Feedforward Compensation in Mechatronic Control System

2014 ◽  
Vol 664 ◽  
pp. 360-364
Author(s):  
Zhang Lei ◽  
Chang Tian Qing ◽  
Su Kui Feng
Keyword(s):  
Control System ◽  
Fault Detection ◽  
Detection Method ◽  
External Disturbance ◽  
Disturbance Compensation ◽  
Band Filter ◽  
Simulation Results ◽  
Compensation Approach ◽  
The Relationship ◽  
Shaft Friction

For the fault detection of mechatronic control system, based on observer a feedforward compensation approach was presented. The model of a mechatronic control system was investigated and divided into two loops for disturbance compensation and fault detection. The external disturbance of the vehicle was analyzed, and the relationship between the support shaft friction moment as main disturbance element and the attitude effect of the vehicle was built by the way of data curve fitting. The adjustment coefficients were proposed respectively in nine kinds of running section of the vehicle, because disturbance was very complicated and time-variant in different section. Fault detection observer was designed to generate residuals in the inner loop, and the whole residual was calculated. The compensation was deduced in accordance with responses produced by the disturbance, so the disturbance could be compensated. Band filter was proposed for other noises. Finally, an example was presented to illustrate the proposed approach. The simulation results showed that the disturbance elements can be compensated rapidly.

scholarly journals Over/Undervoltage and Undervoltage Shift of Hybrid Islanding Detection Method of Distributed Generation

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Manop Yingram ◽  
Suttichai Premrudeepreechacharn
Keyword(s):  
Control System ◽  
Distributed Generation ◽  
Hybrid Method ◽  
Detection Method ◽  
System Simulation ◽  
Detection Methods ◽  
Islanding Detection ◽  
Active Method ◽  
Passive Method ◽  
Simulation Results

The mainly used local islanding detection methods may be classified as active and passive methods. Passive methods do not perturb the system but they have larger nondetection zones, whereas active methods have smaller nondetection zones but they perturb the system. In this paper, a new hybrid method is proposed to solve this problem. An over/undervoltage (passive method) has been used to initiate an undervoltage shift (active method), which changes the undervoltage shift of inverter, when the passive method cannot have a clear discrimination between islanding and other events in the system. Simulation results on MATLAB/SIMULINK show that over/undervoltage and undervoltage shifts of hybrid islanding detection method are very effective because they can determine anti-islanding condition very fast.ΔP/P>38.41% could determine anti-islanding condition within 0.04 s;ΔP/P<-24.39% could determine anti-islanding condition within 0.04 s;-24.39%≤ΔP/P≤ 38.41% could determine anti-islanding condition within 0.08 s. This method perturbed the system, only in the case of-24.39% ≤ΔP/P ≤38.41% at which the control system of inverter injected a signal of undervoltage shift as necessary to check if the occurrence condition was an islanding condition or not.

Study on Disturbance Compensation for Ship-Borne Servo Control System

2014 ◽  
Vol 687-691 ◽  
pp. 367-370
Author(s):  
Dong Xu Zhu ◽  
Hui Jun Xie ◽  
Xin Rong Wang
Keyword(s):  
Control System ◽  
Disturbance Rejection ◽  
Servo Control ◽  
Disturbance Compensation ◽  
Servo Control System ◽  
Simulation Results

Aimed at rejecting the disturbance for Ship-borne Servo Control System, using the ADRC method to improve the disturbance rejection ability of system. And the model is validated by PID, the simulation results show that the anti-interference ability could be improved by of ADRC method, and the controller has engineering function and prospect.

A Fast Gradual Fault Detection Method for Underwater Integrated Navigation Systems

2015 ◽  
Vol 69 (1) ◽  
pp. 93-112 ◽  
Author(s):  
Liu Yi-ting ◽  
Xu Xiao-su ◽  
Liu Xi-xiang ◽  
Zhang Tao ◽  
Li Yao ◽  
...  
Keyword(s):  
Fault Detection ◽  
Detection Method ◽  
System Failure ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Detection Program ◽  
Absolute Residual ◽  
Simulation Results ◽  
Short Time

Gradual fault detection is always an important issue in integrated navigation systems, and the gradual fault is the most difficult fault to detect. To detect gradual faults in a timely and precise manner in integrated navigation systems, the statistical concepts of the normalised residual mean and the sum of absolute residuals are introduced according to the characteristics of gradual system failure in this paper. The applicability of the improved residual χ2 detection method is discussed. Then, the gradual fault detection program based on the improved residual χ2 detection method is designed with the criterion of normalised residual mean and the sum of absolute residual. The simulation results and vehicle tests show that: 1) The residual of the failed sub-system can be calculated accurately with the improved residual χ2 detection method, which has strong applicability in gradual fault detection; 2) The gradual fault can be detected in a short time by using the normalised residual mean and the sum of absolute residual.

scholarly journals Research on Fault Detection Method of FADS System

2020 ◽  
Vol 38 (6) ◽  
pp. 1210-1217
Author(s):  
Qianlei Jia ◽  
Weiguo Zhang ◽  
Jingping Shi ◽  
Guangwen Li ◽  
Xiaoxiong Liu
Keyword(s):  
Fault Detection ◽  
High Precision ◽  
Detection Method ◽  
Measurement Noise ◽  
Distribution Characteristics ◽  
Detection Problem ◽  
Chi Square ◽  
Statistical Knowledge ◽  
Noise Simulation ◽  
Simulation Results

In order to solve the fault detection problem of flush air data sensing (FADS), an advanced airborne sensor, a new method is proposed in this paper. First, the high-precision FADS model is established on the basis of the database obtained from the CFD software and aerodynamics knowledge. Then, the distribution characteristics of each group of signals under fault condition are derived through strict formulas. Meanwhile, the threshold of alarm times is designed with statistical knowledge. For verifying the effectiveness of the newly proposed method, a comparison with other two widely adopted methods, including the methods based on parity equation and Chi-square χ2 distribution, is conducted under different measurement noise. Simulation results show that the proposed fault detection method for FADS possess higher accuracy and stronger anti-interference.

scholarly journals Analysis of the Effects of Arc Volt–Ampere Characteristics on Different Loads and Detection Methods of Series Arc Faults

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 323 ◽  
Author(s):  
Qiwei Lu ◽  
Zeyu Ye ◽  
Yilei Zhang ◽  
Tao Wang ◽  
Zhixuan Gao
Keyword(s):  
Fault Detection ◽  
Research And Development ◽  
Hardware Implementation ◽  
Detection Method ◽  
Low Cost ◽  
Experimental Methods ◽  
Experimental Results ◽  
National Standard ◽  
Detection Methods ◽  
The Relationship

Owing to the shortcomings of existing series arc fault detection methods, based on a summary of arc volt–ampere characteristics, the change rule of the line current and the relationship between the voltage and current are deeply analyzed and theoretically explained under different loads when series arc faults occur. A series arc fault detection method is proposed, and the software flowchart and principles of the applied hardware implementation are given. Finally, a prototype of an arc fault detection device (AFDD) with a rated voltage of 220 V and a rated current of 40 A is developed. The prototype was tested according to experimental methods provided by the Chinese national standard, GB/T 31143-2014. The experimental results show that the proposed detection method is simple and practical, and can be implemented using a low-cost microprocessor. The proposed method will provide good theoretical guidance in promoting the research and development of an AFDD.

Simulation of Fault Detection in the Wireless Networked Control System

2013 ◽  
Vol 846-847 ◽  
pp. 778-781
Author(s):  
Hong Liang Guo ◽  
Shao Ying Kong
Keyword(s):  
Control System ◽  
Time Delay ◽  
Fault Detection ◽  
Wireless Network ◽  
Detection Method ◽  
State Space Model ◽  
Failure Detection ◽  
Networked Control System ◽  
Network Control ◽  
Network Control System

Wireless network control system is characterized by high uncertain delay time, thus the state of the system can not be fully observed. The fault characteristic is interfered by time delay so to be unstable, leading inaccurate fault detection. Traditional fault detection method of wireless network control system is usually based on the characteristics of the stability of the network status data. If the network has time delay fluctuations, it is unable to obtain accurate fault detection results. This paper presents a stochastic delay fault detection method. It builds a state space model of the system, analyzes the delay vector between the sensor end of the system and the controller end, depending on the delay residual signal of the system and the corresponding evaluation function to obtain the system failure detection result. The final simulation result shows that this method has high accuracy in the detection of Stability and randomness of the wireless network fault detection. Thus it is an effective wireless network control system fault detection method.

scholarly journals An Arc Fault Detection Method Based on Multidictionary Learning

2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Na Qu ◽  
Jianhui Wang ◽  
Jinhai Liu ◽  
Zhi Wang
Keyword(s):  
Fault Detection ◽  
Sparse Representation ◽  
Dictionary Learning ◽  
Detection Method ◽  
Amplitude Spectrum ◽  
Learning Method ◽  
Test Results ◽  
Training Samples ◽  
Simulation Results ◽  
Normal Work

This paper uses the dictionary learning of sparse representation algorithm to detect the arc fault. Six kinds of characteristics, that is, the normalized amplitudes of 0Hz, 50Hz, 100Hz, 150Hz, 200Hz, and 250Hz in the current amplitude spectrum, are used as inputs. The output is normal work or arc fault. Increasing the number of training samples can improve the accuracy of the tests. But if the training samples are too many, it is difficult to be expressed by single dictionary. This paper designs a multidictionary learning method to solve the problem. Firstly, n training samples are selected to form s overcomplete dictionaries. Then a dictionary library consisting of s dictionaries is constructed. Secondly, t (t≤s) dictionaries are randomly selected from the dictionary library to judge the test results, respectively. Finally, the final detest result is obtained through the maximum number of votes, that is, the modality with the most votes is the detest result. Simulation results show that the accuracy of detection can be improved.

Fuzzy Adaptive Sliding Mode Control Based on Fuzzy Compensation for Ammunition Auto-Loading Robot

2013 ◽  
Vol 816-817 ◽  
pp. 363-366
Author(s):  
Yu Feng Li ◽  
Kui Wu Li ◽  
Yu Tian Pan ◽  
Bao Quan Guo
Keyword(s):  
Control System ◽  
Fuzzy Systems ◽  
Sliding Mode ◽  
Adaptive Sliding Mode Control ◽  
Sliding Mode Controller ◽  
Disturbance Compensation ◽  
Adaptive Sliding Mode ◽  
Adaptive Sliding Mode Controller ◽  
Simulation Results ◽  
Fuzzy Adaptive

A new fuzzy adaptive sliding mode controller based on fuzzy compensation for robot is proposed. The control architecture employs fuzzy systems to compensate adaptively for plant uncertainties to distinguish different disturbance compensation terms and approximate each of them respectively. By analyzing and comparing the simulation results, it is obviously shown that the control system can lighten the effect on the control system caused by different disturbance factors and eliminate the system chattering than that of traditional SMC.

scholarly journals Design of H∞Control and Simplified Instrument Fault Detection on DC Motor

2020 ◽  
Author(s):  
Lintang Erlangga ◽  
Bagas Budhi Permana ◽  
Ulynnuha Setiyadi ◽  
Samiadji Herdjunanto ◽  
Sujoko Sumaryono
Keyword(s):  
Fault Detection ◽  
Detection Method ◽  
External Disturbance ◽  
Parametric Uncertainty ◽  
Sensor Fault ◽  
Closed Loop System ◽  
Structured Singular Value ◽  
Robust Control Design ◽  
And Performance ◽  
Performance Uncertainty

In the presence of uncertainty, a closed-loop system must be able to maintain its stability and performance. Uncertainty can be categorized into two meanings, disturbance from external systems and perturbation in a dynamical system. In this paper, we will present a robust control design by considering a disturbance from external factors, and analyze its robustness using Structured Singular Value respect to parametric uncertainty and external disturbance. Beside that, every control system has their own region to operate, outside that region a performance degradation will occur, and led into unstability. One factor to that catastrophic is a fault in instrument reading, to anticipate it, this paper also implement Simplified Instrument Fault Detection method to detect a sensor fault in order to give an alarm for further action.

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