CN110161882A - A kind of fault detection method of the networked system based on event trigger mechanism - Google Patents
A kind of fault detection method of the networked system based on event trigger mechanism Download PDFInfo
- Publication number
- CN110161882A CN110161882A CN201910504797.1A CN201910504797A CN110161882A CN 110161882 A CN110161882 A CN 110161882A CN 201910504797 A CN201910504797 A CN 201910504797A CN 110161882 A CN110161882 A CN 110161882A
- Authority
- CN
- China
- Prior art keywords
- fault detection
- matrix
- formula
- detection filter
- filter
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The present invention discloses a kind of fault detection method of networked system based on event trigger mechanism, belongs to networked system field；Initially set up there are sensor saturation, disturbance and fault condition under Continuous Network system model, solve the problems, such as that real network bandwidth is limited by introducing effective event triggering communication transfer strategy, fault Detection Filter is redesigned, introduces residual error evaluation mechanism to judge whether system breaks down；With Lyapunov Theory of Stability and linear matrix inequality analysis method, adequate condition existing for filtering error system Asymptotic Stability and fault Detection Filter is obtained；Optimization problem is solved using the tool box Matlab LMI, obtaining Optimal Fault Detection Filter parameter isThe method of the present invention considers under actual conditions that there are network bandwidths in system limited, sensor is suitable for general fault detection, has preferable universality by constraint of saturation and failure.
Description
Technical field
The invention belongs to networked system fields, are related to a kind of failure inspection of networked system based on event trigger mechanism
Survey method.
Background technique
Network control system is to be formed between controlled device and other component by shared communication network connection
Closed-loop control system.Compared to traditional control system, network control system have simple connection, strong flexibility, be easy extension,
The advantages that convenient for safeguarding.But due to the introducing of network, a series of new problems are also inevitably brought, when such as information transmission
Prolong, data-bag lost, quantization error and Bandwidth-Constrained etc., declines so as to cause the performance of system, system unstability can be made when serious.
Fault detection is to judge whether system breaks down, it is the important evidence that system safety operation early warning mechanism is established.Due to logical
The introducing for interrogating network causes traditional fault detection method to be difficult to directly apply to network control system, therefore is directed to unreasonably
Think network factors, the fault detection method for studying networked system has important theory significance and application value.
Fault detection is to establish a threshold value relevant to that can survey signal (such as state, output) and valuation functions, is passed through
Whether comparative assessment functional value and threshold value, detection failure occur, and when valuation functions value is greater than threshold value, system detection is out of order simultaneously
Issue alarm signal.However the most of scholar research object selected when study networking system failure detection problem for from
Dissipate system, for the transmission mode in communication network mostly use be constant duration traditional period trigger mechanism, in reality
Network congestion is inevitably generated in the limited situation of network bandwidth, increases unnecessary calculating, is wasted a large amount of
The energy and Internet resources.
Summary of the invention
For above-mentioned problems of the prior art, the present invention provides a kind of networkings based on event trigger mechanism
The fault detection method of system.Consider that networked system has that sensor is limited by constraint of saturation and real network bandwidth
Under, fault Detection Filter is devised, so that networked system can not only keep Asymptotic Stability under above-mentioned condition constraint, and
And satisfiable H∞Performance indicator is effectively detected by residual error evaluation mechanism and is out of order.
Technical solution of the present invention:
A kind of fault detection method of the networked system based on event trigger mechanism, comprising the following steps:
1) there are the limited mathematical models with the networked system of sensor constraint of saturation of communication bandwidth for foundation:
Wherein:For state vector,For the derivative of state vector；For the survey of belt sensor saturation
Measure output vector；WithIt is measurement noise and unknown failure signal respectively, and meets L2[0,∞)。A,Bw,
Bf, C and DwFor the constant matrices of known appropriate dimension；It is the non-linear partial under sensor saturation, belongs to [L1,
L2],WithIt is diagonal matrix, and L=L2-L1It is symmetric positive definite matrix.For the limited net of communication bandwidth
Network environment, trigger mechanism and network detection are as follows:
Wherein: σ ∈ [0,1),It is positive definite weighting matrix, sampler acquires output signal, τ with fixed cycle h
It (t) is the time-vary delay system of network transmission, ekIt (t) is error vector,For filter input, the trigger transmission data moment is
i0h,i1h,…,ikH ...,It is i-thkThe time delay of secondary triggering.
2) design error failure Fault detection filter:
Wherein: xFIt (t) is filter status,For filter input, rFIt (t) is residual signals；AF,BF,CFAnd DFFor to
The filter parameter of design.
Whether occurred using residual error evaluation mechanism detection failure, and residual error valuation functions J (t) and threshold value JthIt respectively indicates
It is as follows:
Wherein: TdIndicate limited assessment time span.
Whether system breaks down, and is judged by the rule of formula (6):
3) adequate condition existing for system Asymptotic Stability and fault Detection Filter is as follows:
Wherein * indicates symmetrical matrix block, and
Θ11=-X-XT, Θ12=-Y-ZT,Θ22=-Z-ZT, Θ77=-2I+ σ Ω,
It is intermediate variable,
It is intermediate variable,
Ω is positive definite weighting matrix, Q, R,It is unknown positive definite matrix, X, Y, Z,It is appropriate
The unknown matrix and performance indicator γ of dimension, dependent variable be all it is known, I is unit matrix, and 0 is null matrix.
The given < σ of scalar lambda > 0 and 0 < 1 solves linear matrix inequality (7) using the tool box Matlab LMI, when not
When equation (7) has feasible solution, there are positive definite matrix Ω, Q, R,With matrix X, Y,And
Performance indicator γ then system is asymptotically stable, and meets H∞Performance indicator, and thus, it is possible to obtain fault Detection Filter
Parameter can continue to carry out step 4)；When inequality (7) is without feasible solution, fault Detection Filter parameter can not be obtained, no longer
Step 4) is carried out, is terminated.
4) Optimal Fault Detection Filter parameter is calculated
According toPerformance indicator γ is found out, and is asked using the tool box Matlab LMI
Solve convex optimization problem (8):
Wherein, e (t)=rF(t)-f (t) is residual error error signal,
When formula (8) has solution, optimal H is obtained∞Performance indicator is γmin, and acquire Optimal Fault Detection Filter parameter
It is as follows:
Wherein:It is nonsingular matrix.
5) whether logical decision determines that failure occurs
Based on event trigger mechanism, the input of filter is obtained by network transmissionBy fault Detection Filter formula
(3) residual signals r is obtainedF(t), the current of residual error assessment t moment then by residual error evaluation mechanism formula (4) and formula (5) is calculated
Value J (t) and threshold value Jth, whether occur finally by formula (6) logic judgment failure.
Compared with prior art, beneficial effects of the present invention: for the limited net with sensor constraint of saturation of communication bandwidth
Network environment, the present invention are given under the network environment by introducing a kind of effectively transmission strategy based on event trigger mechanism
The design method of fault Detection Filter, compared to traditional period trigger mechanism using constant duration triggering, this method is more
With practical application value, data traffic volume can be effectively reduced, saves Internet resources.
Detailed description of the invention
Fig. 1 is the flow chart of the networked system fault detection method based on event trigger mechanism.
Fig. 2 is the structural block diagram of the networked system fault detection method based on event trigger mechanism.
Fig. 3 is w (t) ≠ 0, the residual signals figure in the presence of the failure of σ=0.1, λ=0.15.
Fig. 4 is w (t) ≠ 0, residual error valuation functions figure when σ=0.1, λ=0.15.
Fig. 5 is w (t) ≠ 0, event triggering moment and trigger interval figure when σ=0.1, λ=0.15.
Specific embodiment
The following further describes the specific embodiments of the present invention with reference to the drawings.
Referring to attached drawing 1, a kind of fault detection method of the networked system based on event trigger mechanism, including following step
It is rapid:
Step 1: there are the limited mathematical models with the networked system of sensor constraint of saturation of communication bandwidth for foundation
The state-space expression of networked system based on event trigger mechanism is as follows:
The case where considering sensor constraint of saturation, and saturation function sat ():Belong to [L1, L2], L1And L2
It is diagonal matrix, and L=L2-L1It is symmetric positive definite matrix.
For the ease of processing, sat (Cx (t)) is divided into linear segment and non-linear partial:
Wherein non-thread partIt is as follows to meet condition:
Step 2: design error failure Fault detection filter
Consider network transmission by actual bandwidth limit with sensor constraint of saturation, in order to reduce the number of Trig control signal
With the burden of shared network, event trigger mechanism is selected, it is assumed that trigger condition is as follows:
Design error failure Fault detection filter formula (3), and binding events trigger mechanism and sensor constraint of saturation, are passed by network
Defeated fault Detection Filter input are as follows:
Comprehensively consider formula (10), (3) and (14), pass through the available filtering error system (15) of the method for state augmentation:
Wherein: e (t)=rF(t)-f (t), H=[I 0],
It can be seen that filtering error system (15) have merged network transfer delay, sensor constraint of saturation parameter, event touching
Parameter is sent out, noise and unknown failure signal are measured.The fault detection problem of original system is translated into unknown parameter error system
The H of system∞Filtering problem.Specific problem becomes to find filter parameter A belowF,BF,CFAnd DFSo that filtering error system is full
The following condition of foot:
(i) whenWhen, filtering error system (15) is asymptotically stable.
(ii) under zero initial condition, to any non-vanishing vectorFiltering error vector e (t) is fullWherein γ is H∞Performance indicator, suppression level of the reflection residual signals to external disturbing signal.
Construct residual error valuation functions J (t) and threshold value JthRespectively formula (4) and formula (5), whether system, which breaks down, is used formula
(6) judged.It when residual error valuation functions value is greater than threshold value, then breaks down and alarms, otherwise indicate that there is no events
Barrier.
Step 3: adequate condition existing for system Asymptotic Stability and fault Detection Filter
Construct Lyapunov function are as follows:
It is theoretical using Lyapunov Theory of Stability and free-form curve and surface, obtain filtering error system (15) meet (i) and
(ii) adequate condition (17):
Wherein * indicates symmetrical matrix block, and
θ44=-2I+ σ Ω, θ46=σ Ω κ, θ66=-γ I+ σ κTΩ κ, κ=[0 0Dw], Σ12(1)=λ M, Σ12
(2)=λ N, Γ
=[- MH M-N N 00 0].
The positive < σ of scalar lambda > 0 and 0 < 1 is given, when there are scalar γ > 0 and matrix Ω > 0, Q > 0, R > 0, P > 0, with
And appropriate dimension matrix M, N make formula (17), then filtering error system (15) meets (i) and (ii).
Although formula (17) gives the condition that filtering error system (15) meet (i) and (ii), regrettably in formula (17)
There are the nonlinear terms of coupling, can not directly be solved using the tool box LMI of MATLAB.Below by introducing added martix
G releases coupling, obtains the adequate condition (18) that new filtering error system (15) meets (i) and (ii):
Wherein * indicates symmetrical matrix block, and
Λ1=diag
{0,Γ+ΓT, 0 },
According to expression formula (18), adequate condition existing for system stabilization and fault Detection Filter is established below.
For convenience, matrix G is first resolved into following form:
In order to carry out contragradient transformation, it is assumed here that matrix G21And G22It is reversible, and defines invertible matrix
In order to be further simplified, it is given below expression formula:
To formula (18) both sides respectively multiplied byAnd J2Contragradient transformation is carried out, system Asymptotic Stability and fault detection filtering can be obtained
Adequate condition existing for device (7).
The given < σ of scalar lambda > 0 and 0 < 1 solves linear matrix inequality (7) using the tool box Matlab LMI, works as formula
(7) when having feasible solution, there are positive definite matrix Ω, Q, R,With matrix X, Y, Z,And performance
Index γ then system is asymptotically stable, and meets H∞Performance indicator, and it is hereby achieved that fault Detection Filter is joined
Number can continue to carry out step 4；When formula (7) is without feasible solution, fault Detection Filter parameter can not be obtained, is no longer walked
Rapid 4, terminate.
Step 4: calculating Optimal Fault Detection Filter parameter
For formula (15), convex optimization problem formula (8) is solved using the tool box Matlab LMI.When formula (8) has solution, obtain most
Excellent H∞Performance indicator is γminWith Optimal Fault Detection Filter parameter expression (9).When formula (8) is without solution, then can not obtain
Optimal Fault Detection Filter.
Step 5: whether logical decision determines that failure occurs
Based on event trigger mechanism, the input of filter is obtained by network transmissionBy fault Detection Filter formula
(3) residual signals r is obtainedF(t), the current of residual error assessment t moment then by residual error evaluation mechanism formula (4) and formula (5) is calculated
Value J (t) and threshold value Jth, whether occur finally by formula (6) logic judgment failure.
Embodiment:
Using the fault detection method of the networked system proposed by the present invention based on event trigger mechanism, in no external world
In the case where disturbance and failure, system is asymptotically stable.WhenWhen, the failure in system is carried out by the above method
Detection.Concrete methods of realizing is as follows:
The mathematical model of certain networking motor stirring system is formula (10), wherein system parameter are as follows:
Assuming that sensor saturation function sat (Cx (t)) can be expressed as follows:
Wherein saturation value is
Based on event trigger mechanism and consider sensor constraint of saturation, it is assumed that h=0.1, λ=0.15, σ=0.1,By solving convex optimization problem (8), optimal H can be obtained∞Performance indicator is
γmin=1.2105 and corresponding trigger parameter matrixAnd obtain Optimal Fault Detection Filter
Parameter
CF=[0.0627 0.0144-0.0464], DF=[0.0050 0.0257].
Notice H∞Performance indicator is extremely important, reflect residual signals to the suppression level of external disturbing signal, it
Value will receive trigger condition, the influence of network delay and sensor constraint of saturation.As can be seen from Table 1 and Table 2, with parameter σ
With the increase of λ, γminValue also increasing accordingly.In addition, table 3 gives optimal performance index γminBy sensor constraint of saturation
The influence of condition variation.
The optimal performance index γ that table 1 changes with parameter σmin
The optimal performance index γ that table 2 changes with parameter lambdamin
Table 3 is with parameter L1, L2The optimal performance index γ of variationmin
The failure detection time that table 4 changes with parameter σ
In order to further verify the validity of above-mentioned fault Detection Filter, it is assumed that interfering noise signal w (t) is [0,1]
Upper obedience uniformly distributed random signal, and assume that fault-signal has following form
Under zero initial condition, changed over time as shown in Fig. 3 using the available residual signals of MATLAB, also,
Attached drawing 4 shows that the residual error valuation functions J (t) for having fault-free that two kinds of situations occur under event trigger mechanism in system becomes at any time
The curve of change.According to the threshold expression (5) of residual error evaluation mechanism, assessment time span T is chosend=200s, can be in the hope of threshold
Value Jth=0.2586.Again by the expression formula (4) of residual error valuation functions, J (t) can be obtained by comparing by calculating |T=55.4=0.2615 >
It detects and is out of order within 0.2586, i.e. 5.4s.Using the time span of the available fault detection of same method with parameter σ's
Situation of change is as shown in table 4.In addition, event triggering moment and trigger interval figure when attached drawing 5 gives parameter σ=0.1.It is commenting
Estimate time 200s, the number of sampling is 2001 times, and the number that sensor is sent is 853 times, it is meant that event trigger mechanism number
Only have 42.63% according to transmission rate, this greatly reduces network burden, reduces network congestion.
It can be seen that designed fault Detection Filter can be judged quickly after the failure occurred detects event
Barrier；Also, the transmission strategy based on event trigger mechanism can reduce data traffic volume, save Internet resources, illustrate to be mentioned
Method is significantly out.
Claims (1)
1. a kind of fault detection method of the networked system based on event trigger mechanism, which comprises the following steps:
1) there are the limited mathematical models with the networked system of sensor constraint of saturation of communication bandwidth for foundation:
Wherein:For state vector,For the derivative of state vector；Measurement for belt sensor saturation is defeated
Outgoing vector；WithIt is measurement noise and unknown failure signal respectively, and meets L2[0,∞)；A,Bw,Bf, C and
DwFor the constant matrices of known appropriate dimension；It is the non-linear partial under sensor saturation, belongs to [L1, L2],WithIt is diagonal matrix, and L=L2-L1It is symmetric positive definite matrix；For the limited network rings of communication bandwidth
Border, trigger mechanism and network detection are as follows:
Wherein: σ ∈ [0,1),It is positive definite weighting matrix, sampler acquires output signal with fixed cycle h, and τ (t) is net
The time-vary delay system of network transmission, ekIt (t) is error vector,For filter input, trigger sends the data moment as i0h,
i1h,…,ikH ...,It is i-thkThe time delay of secondary triggering；
2) design error failure Fault detection filter:
Wherein: xFIt (t) is filter status,For filter input, rFIt (t) is residual signals；AF,BF,CFAnd DFIt is to be designed
Filter parameter；
Whether occurred using residual error evaluation mechanism detection failure, and residual error valuation functions J (t) and threshold value JthRespectively indicate as
Under:
Wherein: TdIndicate limited assessment time span；
Whether system breaks down, and is judged by the rule of formula (6):
3) adequate condition existing for system Asymptotic Stability and fault Detection Filter is as follows:
Wherein * indicates symmetrical matrix block, and
Θ11=-X-XT, Θ12=-Y-ZT,Θ22=-Z-ZT, Θ77=-2I+ σ Ω, It is intermediate variable, It is intermediate variable,
Ω is positive definite weighting matrix, Q, R,It is unknown positive definite matrix, X, Y, Z,It is appropriate dimension
Unknown matrix and performance indicator γ, dependent variable be all it is known, I is unit matrix, and 0 is null matrix；
The given < σ of scalar lambda > 0 and 0 < 1 solves linear matrix inequality (7) using the tool box Matlab LMI, works as inequality
(7) when having feasible solution, there are positive definite matrix Ω, Q, R,With matrix X, Y, Z,And property
Energy index γ, then system is asymptotically stable, and meets H∞Performance indicator, and thus, it is possible to obtain fault Detection Filter ginseng
Number can continue to carry out step 4)；When inequality (7) is without feasible solution, fault Detection Filter parameter can not be obtained, no longer into
Row step 4) terminates；
4) Optimal Fault Detection Filter parameter is calculated
According toPerformance indicator γ is found out, and the solution of the application tool box Matlab LMI is convex
Optimization problem (8):
Wherein, e (t)=rF(t)-f (t) is residual error error signal,
When formula (8) has solution, optimal H is obtained∞Performance indicator is γmin, and acquire Optimal Fault Detection Filter parameter such as
Under:
Wherein:It is nonsingular matrix；
5) whether logical decision determines that failure occurs
Based on event trigger mechanism, the input of filter is obtained by network transmissionIt is obtained by fault Detection Filter formula (3)
To residual signals rF(t), the current value J (t) of residual error assessment t moment then by residual error evaluation mechanism formula (4) and formula (5) is calculated
With threshold value Jth, whether occur finally by formula (6) logic judgment failure.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910504797.1A CN110161882B (en) | 2019-06-12 | 2019-06-12 | Fault detection method of networked system based on event trigger mechanism |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910504797.1A CN110161882B (en) | 2019-06-12 | 2019-06-12 | Fault detection method of networked system based on event trigger mechanism |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110161882A true CN110161882A (en) | 2019-08-23 |
| CN110161882B CN110161882B (en) | 2020-09-18 |
Family
ID=67628499
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910504797.1A Active CN110161882B (en) | 2019-06-12 | 2019-06-12 | Fault detection method of networked system based on event trigger mechanism |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110161882B (en) |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110580035A (en) * | 2019-09-02 | 2019-12-17 | 浙江工业大学 | motion control system fault identification method under sensor saturation constraint |
| CN110673474A (en) * | 2019-09-17 | 2020-01-10 | 浙江工业大学 | Intrusion-tolerant control method of networked motion control system based on event triggering |
| CN110703742A (en) * | 2019-11-08 | 2020-01-17 | 哈尔滨工业大学 | Event-driven and output quantization-based fault detection method for unmanned surface vehicle system |
| CN110989347A (en) * | 2019-12-07 | 2020-04-10 | 天津大学 | Networked control system and control method based on event trigger mechanism |
| CN113311811A (en) * | 2021-07-14 | 2021-08-27 | 江苏东源电器集团股份有限公司 | Event-triggered multi-agent system and distributed cooperative fault detection method thereof |
| CN113325822A (en) * | 2021-05-25 | 2021-08-31 | 四川大学 | Network control system fault detection method based on dynamic event trigger mechanism and sensor nonlinearity |
| CN113641104A (en) * | 2021-08-23 | 2021-11-12 | 江南大学 | Limited frequency domain fault detection method for tank reactor under dynamic event triggering |
| CN113746698A (en) * | 2021-08-31 | 2021-12-03 | 云境商务智能研究院南京有限公司 | Method for designing fault detection filter of networked system under random network attack |
| CN113997317A (en) * | 2021-12-29 | 2022-02-01 | 南京邮电大学 | Three-link manipulator actuator fault detection method based on event trigger mechanism |
| CN114545907A (en) * | 2022-03-15 | 2022-05-27 | 中南大学 | Fault detection method of flight control system based on filter |
| CN114740826A (en) * | 2022-04-20 | 2022-07-12 | 南通大学 | Multi-vehicle tracking system fault detection method based on optimal variable-order observer |
| CN115225381A (en) * | 2022-07-19 | 2022-10-21 | 海南大学 | Asynchronous fault detection filter design method |
| CN116527060A (en) * | 2023-05-29 | 2023-08-01 | 北京理工大学 | Information compression and anomaly detection method based on event trigger sampling |
| CN117221075A (en) * | 2023-10-16 | 2023-12-12 | 哈尔滨理工大学 | Discrete networking system fault detection method based on self-adaptive event trigger mechanism |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108415402A (en) * | 2018-01-29 | 2018-08-17 | 山东科技大学 | Consider the EMU robust filtering fault detection method of event-driven and output saturation |
| US20180255383A1 (en) * | 2016-05-09 | 2018-09-06 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for the industrial internet of things |
| CN108629132A (en) * | 2018-05-10 | 2018-10-09 | 南京邮电大学 | The collaborative design method of fault Detection Filter and controller under DoS attack |
| CN108667673A (en) * | 2018-06-22 | 2018-10-16 | 东北大学 | Nonlinear networked control systems fault detection method based on event trigger mechanism |
| US20180364691A1 (en) * | 2017-06-15 | 2018-12-20 | International Business Machines Corporation | Enhanced service procedures using force measurement |
| CN109309593A (en) * | 2018-11-22 | 2019-02-05 | 江南大学 | A kind of fault detection method of the networked system based on Round-Robin agreement |
| CN109343513A (en) * | 2018-11-20 | 2019-02-15 | 哈尔滨工业大学 | Based on the synchronous fault detection of event driven unmanned surface vehicle and control method |
| CN109495313A (en) * | 2018-12-07 | 2019-03-19 | 天津津航计算技术研究所 | Wireless sensor network fault detection method based on Poisson distribution fault model |
| CN109696669A (en) * | 2018-12-24 | 2019-04-30 | 北京理工大学 | The Multi-sensor Fusion estimation method that event triggers under a kind of correlated noise environment |
-
2019
- 2019-06-12 CN CN201910504797.1A patent/CN110161882B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180255383A1 (en) * | 2016-05-09 | 2018-09-06 | Strong Force Iot Portfolio 2016, Llc | Methods and systems for the industrial internet of things |
| US20180364691A1 (en) * | 2017-06-15 | 2018-12-20 | International Business Machines Corporation | Enhanced service procedures using force measurement |
| CN108415402A (en) * | 2018-01-29 | 2018-08-17 | 山东科技大学 | Consider the EMU robust filtering fault detection method of event-driven and output saturation |
| CN108629132A (en) * | 2018-05-10 | 2018-10-09 | 南京邮电大学 | The collaborative design method of fault Detection Filter and controller under DoS attack |
| CN108667673A (en) * | 2018-06-22 | 2018-10-16 | 东北大学 | Nonlinear networked control systems fault detection method based on event trigger mechanism |
| CN109343513A (en) * | 2018-11-20 | 2019-02-15 | 哈尔滨工业大学 | Based on the synchronous fault detection of event driven unmanned surface vehicle and control method |
| CN109309593A (en) * | 2018-11-22 | 2019-02-05 | 江南大学 | A kind of fault detection method of the networked system based on Round-Robin agreement |
| CN109495313A (en) * | 2018-12-07 | 2019-03-19 | 天津津航计算技术研究所 | Wireless sensor network fault detection method based on Poisson distribution fault model |
| CN109696669A (en) * | 2018-12-24 | 2019-04-30 | 北京理工大学 | The Multi-sensor Fusion estimation method that event triggers under a kind of correlated noise environment |
Non-Patent Citations (3)
| Title |
|---|
| LIU TING: "Analysis and design of the time-delay compensation for networked control systems with random communication delay", 《2016 35TH CHINESE CONTROL CONFERENCE (CCC)》 * |
| SHANGLIN LI: "Event-Triggered Fault Detection for Networked LPV Systems", 《CIRCUITS SYSTEMS AND SIGNAL PROCESSING》 * |
| 高敏等: "带丢包的网络化控制系统的随机故障检测", 《南京理工大学学报》 * |
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110580035A (en) * | 2019-09-02 | 2019-12-17 | 浙江工业大学 | motion control system fault identification method under sensor saturation constraint |
| CN110673474A (en) * | 2019-09-17 | 2020-01-10 | 浙江工业大学 | Intrusion-tolerant control method of networked motion control system based on event triggering |
| CN110703742A (en) * | 2019-11-08 | 2020-01-17 | 哈尔滨工业大学 | Event-driven and output quantization-based fault detection method for unmanned surface vehicle system |
| CN110989347A (en) * | 2019-12-07 | 2020-04-10 | 天津大学 | Networked control system and control method based on event trigger mechanism |
| CN110989347B (en) * | 2019-12-07 | 2022-04-08 | 天津大学 | Networked control system and control method based on event trigger mechanism |
| CN113325822B (en) * | 2021-05-25 | 2022-02-01 | 四川大学 | Network control system fault detection method based on dynamic event trigger mechanism and sensor nonlinearity |
| CN113325822A (en) * | 2021-05-25 | 2021-08-31 | 四川大学 | Network control system fault detection method based on dynamic event trigger mechanism and sensor nonlinearity |
| CN113311811B (en) * | 2021-07-14 | 2021-12-24 | 江苏东源电器集团股份有限公司 | Event-triggered multi-agent system and distributed cooperative fault detection method thereof |
| CN113311811A (en) * | 2021-07-14 | 2021-08-27 | 江苏东源电器集团股份有限公司 | Event-triggered multi-agent system and distributed cooperative fault detection method thereof |
| CN113641104A (en) * | 2021-08-23 | 2021-11-12 | 江南大学 | Limited frequency domain fault detection method for tank reactor under dynamic event triggering |
| CN113746698A (en) * | 2021-08-31 | 2021-12-03 | 云境商务智能研究院南京有限公司 | Method for designing fault detection filter of networked system under random network attack |
| CN113997317B (en) * | 2021-12-29 | 2023-10-13 | 南京邮电大学 | Three-link manipulator actuator fault detection method based on event triggering mechanism |
| CN113997317A (en) * | 2021-12-29 | 2022-02-01 | 南京邮电大学 | Three-link manipulator actuator fault detection method based on event trigger mechanism |
| CN114545907A (en) * | 2022-03-15 | 2022-05-27 | 中南大学 | Fault detection method of flight control system based on filter |
| CN114545907B (en) * | 2022-03-15 | 2023-12-19 | 中南大学 | Fault detection method of flight control system based on filter |
| CN114740826A (en) * | 2022-04-20 | 2022-07-12 | 南通大学 | Multi-vehicle tracking system fault detection method based on optimal variable-order observer |
| CN115225381A (en) * | 2022-07-19 | 2022-10-21 | 海南大学 | Asynchronous fault detection filter design method |
| CN115225381B (en) * | 2022-07-19 | 2023-05-12 | 海南大学 | Asynchronous fault detection filter design method |
| CN116527060A (en) * | 2023-05-29 | 2023-08-01 | 北京理工大学 | Information compression and anomaly detection method based on event trigger sampling |
| CN116527060B (en) * | 2023-05-29 | 2024-01-05 | 北京理工大学 | Information compression and anomaly detection method based on event trigger sampling |
| CN117221075A (en) * | 2023-10-16 | 2023-12-12 | 哈尔滨理工大学 | Discrete networking system fault detection method based on self-adaptive event trigger mechanism |
| CN117221075B (en) * | 2023-10-16 | 2024-03-19 | 哈尔滨理工大学 | Discrete networking system fault detection method based on self-adaptive event trigger mechanism |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110161882B (en) | 2020-09-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110161882A (en) | A kind of fault detection method of the networked system based on event trigger mechanism | |
| Wang et al. | Event design in event-triggered feedback control systems | |
| Sun et al. | $ L_ {2} $-gain of systems with input delays and controller temporary failure: Zero-order hold model | |
| Du et al. | Multiple event-triggered H2/H∞ filtering for hybrid wired–wireless networked systems with random network-induced delays | |
| Dorfler et al. | Continuous-time distributed observers with discrete communication | |
| CN109309593B (en) | Fault detection method of networked system based on Round-Robin protocol | |
| CN108667673A (en) | Nonlinear networked control systems fault detection method based on event trigger mechanism | |
| Zhu et al. | Resilient distributed control of multi-agent cyber-physical systems | |
| CN110531732B (en) | Random fault detection method for nonlinear networked control system | |
| CN114244605A (en) | Load frequency control method and system considering network attack and time-varying delay | |
| Almeida et al. | Observer based self-triggered control of linear plants with unknown disturbances | |
| He et al. | Robust control for a class of cyber-physical systems with multi-uncertainties | |
| Zhang et al. | On the impact of measurement errors on power system automatic generation control | |
| Shen et al. | A game-theoretic method for resilient control design in industrial multi-agent CPSs with Markovian and coupled dynamics | |
| Xia et al. | Delay-dependent fuzzy static output feedback control for discrete-time fuzzy stochastic systems with distributed time-varying delays | |
| Wigren et al. | Feedback path delay attacks and detection | |
| Golabi et al. | Event‐triggered fault detection for discrete‐time LPV systems with application to a laboratory tank system | |
| Kawano et al. | Revisit input observability: A new approach to attack detection and privacy preservation | |
| Zhu et al. | Passivity analysis and passivation of interconnected event-triggered feedback systems using passivity indices | |
| Nie et al. | Neural-network-based adaptive control of strict-feedback nonlinear systems with actuator faults: Event-triggered communications strategy | |
| Guan et al. | Stabilization of networked control systems with random delays: A new multirate method | |
| Zhu et al. | New H∞ controller design method for networked control systems with quantized state feedback | |
| Li et al. | Robust guaranteed cost fault-tolerant control for uncertain NCS with fast interval time-varying delay | |
| Hosoe et al. | Relationship between noncausal linear periodically time-varying scaling and causal linear time-invariant scaling for discrete-time systems | |
| Hertneck et al. | Event-Triggered Control Based on Integral Quadratic Constraints |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20220725 Address after: 230000 Room 203, building 2, phase I, e-commerce Park, Jinggang Road, Shushan Economic Development Zone, Hefei City, Anhui Province Patentee after: Hefei Jiuzhou Longteng scientific and technological achievement transformation Co.,Ltd. Address before: 1800 No. 214122 Jiangsu city of Wuxi Province Li Lake Avenue Patentee before: Jiangnan University |
|
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20221013 Address after: Room 27A04-2, Building 1, No. 199 Shishan Road, Suzhou Hi tech Zone, Jiangsu Province, 215000 Patentee after: Suzhou hengcan Information Technology Co.,Ltd. Address before: 230000 Room 203, building 2, phase I, e-commerce Park, Jinggang Road, Shushan Economic Development Zone, Hefei City, Anhui Province Patentee before: Hefei Jiuzhou Longteng scientific and technological achievement transformation Co.,Ltd. |