CN114866284B - Unmanned ship cluster distributed safety control method - Google Patents
Unmanned ship cluster distributed safety control method Download PDFInfo
- Publication number
- CN114866284B CN114866284B CN202210338174.3A CN202210338174A CN114866284B CN 114866284 B CN114866284 B CN 114866284B CN 202210338174 A CN202210338174 A CN 202210338174A CN 114866284 B CN114866284 B CN 114866284B
- Authority
- CN
- China
- Prior art keywords
- dos
- aperiodic
- dos attack
- attack
- unmanned ship
- 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.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/14—Network architectures or network communication protocols for network security for detecting or protecting against malicious traffic
- H04L63/1441—Countermeasures against malicious traffic
- H04L63/1458—Denial of Service
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
- H04W12/12—Detection or prevention of fraud
- H04W12/126—Anti-theft arrangements, e.g. protection against subscriber identity module [SIM] cloning
Landscapes
- Engineering & Computer Science (AREA)
- Computer Security & Cryptography (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Computer Hardware Design (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Feedback Control In General (AREA)
Abstract
The invention provides an unmanned ship cluster distributed safety control method, which comprises the following steps: performing association modeling on a wave disturbance model, a composite fault model and a DoS attack model of the unmanned ship cluster system to form a comprehensive model; establishing an aperiodic DoS attack model of the unmanned ship cluster according to the comprehensive model; and the DoS attack activation and dormancy stage is divided according to the aperiodic DoS attack model, so that the unmanned ship cluster implements the switching between the baseline control and the distributed security control, and the unmanned ship cluster is updated and controlled based on event triggering in the DoS attack dormancy stage.
Description
Technical Field
The invention relates to the technical field of unmanned boats, in particular to a cluster distributed safety control method for unmanned boats.
Background
In recent years, with the exhaustion of land fuel resources, the strategic position of the ocean occupying about 71% of the earth's area is increasing. To fully explore and exploit marine resources, development of marine equipment technology is indispensable. The ocean intelligent equipment represented by unmanned ships (including underwater vehicles, underwater robots, unmanned ships on water surfaces and the like) is a main carrier for offshore operation at present.
The working range of the unmanned ship is often in a water area with complex and changeable environment, and the unmanned ship is often influenced in an unpredictable way. With the improvement of unmanned ship operation capability, the complexity of unmanned ship operation capability is improved, and the safety guarantee of unmanned ship operation capability is also deeply focused. The unmanned ship can discover possible faults as soon as possible, and adopts proper and reasonable fault tolerance means to reduce the potential risk of the unmanned ship, so that the realization of autonomous fault diagnosis and error tolerant control is the core of the unmanned ship for safe sailing and operation.
Unmanned vessels typically communicate and interconnect through a network, and networked unmanned vessels are likely to fail due to DOS attacks. DoS is a short term for Denial of Service, i.e., denial of service, and the act of attack that causes DoS is called DoS attack, the purpose of which is to disable a computer or network from providing normal services. The most common DoS attacks are computer network broadband attacks and connectivity attacks. Where the service resources include network bandwidth, file system space capacity, open processes, or allowed connections. Such attacks can result in starvation of communication resources, and the consequences of such attacks cannot be avoided no matter how fast the computer is processing, the memory capacity is large, and the network bandwidth is fast.
The networked unmanned ship cluster can bring serious consequences if being attacked by physical layer composite faults and network layer aperiodic DoS.
Disclosure of Invention
The invention aims to provide a distributed safety control method for an unmanned ship cluster, which aims to solve the problems that the existing networked unmanned ship cluster is subject to physical layer composite faults and network layer aperiodic DoS attacks can not maintain reliability and safety.
In order to solve the technical problems, the invention provides a distributed safety control method for unmanned ships, which comprises the following steps:
performing association modeling on a wave disturbance model, a composite fault model and a DoS attack model of the unmanned ship cluster system to form a comprehensive model;
establishing an aperiodic DoS attack model of the unmanned ship cluster according to the comprehensive model; and
and switching between baseline control and distributed security control of the unmanned ship cluster according to DoS attack activation and dormancy stages divided by the aperiodic DoS attack model, and performing event trigger-based unmanned ship cluster updatable control in the DoS attack dormancy stage.
Optionally, in the unmanned ship cluster distributed security control method, forming the comprehensive model and the aperiodic DoS attack model includes:
Constructing a correlation model of wave disturbance and/or mutation and/or slow-change actuator composite faults and/or aperiodic DoS attacks under unmanned ship opening and/or dynamic ocean scenes;
establishing an unmanned ship aperiodic DoS attack model according to the totally-interrupted communication topological link or the different activation and dormancy results which are kept communicated by the aperiodic DoS attack; and
and introducing the DoS attack frequency and the average residence time index, and constructing index constraint conditions of the unmanned ship cluster on aperiodic DoS attack under the attack resistance target.
Optionally, in the unmanned aerial vehicle cluster distributed security control method, the DoS attack activation and dormancy stages divided according to the aperiodic DoS attack model enable the unmanned aerial vehicle cluster to implement the switching between the baseline control and the distributed security control, and the unmanned aerial vehicle cluster updatable control based on event triggering in the DoS attack dormancy stage includes:
switching from a baseline security controller of the unmanned aerial vehicle under the influence of the aperiodic DoS activation attack to a distributed security controller of the unmanned aerial vehicle under the influence of the aperiodic DoS sleep attack.
Optionally, in the unmanned ship cluster distributed security control method, the baseline security controller includes estimated compensation information, and negative feedback of the estimated compensation information provides additional and positive information for compensating negative effects of faults in fault-tolerant control, implements a fault-tolerant target for effectively counteracting composite faults of the physical layer executor, and an anti-attack target in a non-periodic DoS attack activation stage of the network layer; and
The distributed safety controller comprises estimation compensation information and distributed state information for completing information interaction based on the latest successful trigger time;
the distributed state information only needs to complete interaction at the latest successful triggering moment, and implements a fault tolerance target for effectively counteracting the composite fault of the physical layer executor and an anti-attack target of the network layer aperiodic DoS attack dormancy stage.
Optionally, in the unmanned aerial vehicle cluster distributed security control method, the DoS attack activation and dormancy stages divided according to the aperiodic DoS attack model enable the unmanned aerial vehicle cluster to implement the switching between the baseline control and the distributed security control, and the unmanned aerial vehicle cluster updatable control based on event triggering in the DoS attack dormancy stage further includes:
the unmanned ship cluster based on event triggering can be updated and controlled, and a low-complexity distributed security control mechanism based on events is performed, so that the bandwidth occupation of communication topology in the unmanned ship cluster system is reduced, the influence of network physical threat is lightened, and the upper limit of an event triggering threshold is set to eliminate the cyclic repeated triggering behavior.
Optionally, in the unmanned ship cluster distributed safety control method, the method further includes:
Wave disturbance omega is introduced into the motion equation of swinging, yawing and rolling of the ith unmanned ship i (t)＝[ω ψi (t)ω φi (t)] T Exponential abrupt and gradual actuator compound fault
The obtained unmanned ship 'wave disturbance-composite fault' dynamic equation is expressed as follows:
establishing an aperiodic DoS attack model, and modeling the aperiodic DoS attack as an activated and dormant state;
three indexes are given for aperiodic DoS attacks, namely the number of DoS attacks N Γ (t 0 T), doS attack frequency
During the DoS attack total activation time interval Γ a (t 0 Average residence time index τ within t) a > 0, where
Represented as the number of DoS active attacks and DoS sleep attacks, respectively.
Optionally, in the unmanned ship cluster distributed safety control method, the method further includes:
defining aperiodic DoS attack total activation and total dormancyTime interval, define
For a total activation time interval of an aperiodic DoS attack, i.e. in which the information interaction is interrupted, where t 0 For initial time, t is termination time, U is union, U is intersection,/->
Activating time interval for the r-th DoS attack, r being a natural number, wherein +.>
At t for aperiodic DoS attack 0 ,t]A spacer activating sequence, and->
Is a non-periodic time-varying interval; / >
The information of the adjacent unmanned ship cannot be utilized to realize distributed anti-attack safety control within the total activation time interval of the aperiodic DoS attack;
definition Γ d (t 0 ,t)＝[t 0 ,t]\Γ a (t 0 T) is the total dormancy time interval of the aperiodic DoS attack, namely the information interaction is allowed in the time interval, the communication topology structure is not changed, and \is the remainder set;
the information of the adjacent unmanned ships can be utilized to realize distributed anti-attack safety control in the total sleep time interval of the aperiodic DoS attack;
setting the number of DoS attacks, the DoS attack frequency and the average residence time for aperiodic DoS attack modeling, and defining
Is the number of DoS attacks, wherein +.>
The number of DoS active attacks and DoS sleep attacks, respectively; definitions->
Is the DoS attack frequency, wherein->
Expressed as the number of DoS-enabled attacks; during the total activation time interval Γ of DoS attack a (t 0 Defining a presence threshold Γ in t) 0 Gtoreq 0 and average residence time index τ a > 0 satisfies->
Determining DoS attack frequency satisfying the following constraint
Average residence time τ a ，
τ a ＞(α 1 -σ * ) -1 (α 1 +α 2 )
The unmanned aerial vehicle cluster distributed security control is located at an aperiodic DoS sleep attack time interval, and the unmanned aerial vehicle cluster baseline security control is located at an aperiodic DoS activation attack time interval.
Optionally, in the unmanned ship cluster distributed safety control method, the method further includes:
according to the activation interval time Γ in aperiodic DoS attack a (t 0 T) unmanned ship cluster communication is interrupted, using estimated information of a distributed unknown input observer
Under unmanned ship cluster aperiodic DoS activation attack modeling, designing a baseline safety controller of an ith unmanned ship represented as follows:
wherein K is 1 ＝[K x K f ]Expressed as compensation gain, where K x Estimating gain for internal state, K f Expressed as a fault estimation gain, the specific following is:
the designed baseline security controller contains only estimated compensation information
Improving increased status and fault estimation information +.>
Unmanned ship angle and angular velocity state estimation information from distributed unknown input observer
Actuator composite fault estimation information +.>
The negative feedback function of the system provides additional and positive information for compensating negative effects of faults in fault-tolerant control, improves singleness and conservation of the existing independent fault estimation and independent fault-tolerant control technology, fully utilizes organic connection of fault estimation and fault-tolerant control, and finally achieves a fault-tolerant target for effectively counteracting composite faults of a physical layer actuator and an anti-attack target in a network layer aperiodic DoS attack activation stage.
Optionally, in the unmanned ship cluster distributed safety control method, the method further includes:
according to sleep interval time Γ of aperiodic DoS attack d (t 0 T) unmanned ship cluster communication is allowed, and updating of unmanned ship cluster distributed safety controller is carried out in non-periodic DoS attack dormancy interval time period；
According to the baseline safety controller, under the aperiodic DoS sleep attack modeling of the unmanned ship cluster, switching the distributed safety controller based on the event triggering mechanism of the ith unmanned ship, which is designed as follows:
wherein K is 2 Expressed as information interaction gain, a ij Is that
The j-th column element value of the i-th row of (2), wherein +.>
And->
The method comprises the steps of respectively obtaining a communication topology adjacency matrix and a set of nodes adjacent to an ith node in a graph theory; />
Respectively representing the status values of the i-th and j-th unmanned boats for completing information interaction at the latest successful triggering moment;
distributed security controller includes estimated compensation information
Also contains distributed status information for completing information interaction based on latest successful trigger time>
Gain K through information interaction 2 And connecting, wherein the distributed state information completes interaction at the latest successful triggering moment.
Optionally, in the unmanned ship cluster distributed safety control method, the method further includes:
During aperiodic DoS attack sleep interval Γ d (t 0 T) unmanned ship cluster communication is allowed, and updating of the unmanned ship cluster distributed safety controller is carried out in the non-periodic DoS attack dormancy interval time period; sleep interval time Γ during DoS attack d (t 0 Time series within t)
Complete event triggered sampling to update the security controller at each event trigger time +.>
Is activated;
completing the state value of information interaction according to the latest successful trigger moment of the ith unmanned ship
Construction state interaction error signal +.>
Based on state interaction error delta i (t) event trigger threshold upper bound explicit update time sequence expressed below>
Wherein θ is i > 0 is represented as a time-triggered based threshold scalar, and is represented as a two-norm, with the time at which the constraint is satisfied being the time of the event-triggerable sample update time
The upper bound of the event trigger threshold is
The inventor of the invention finds that aiming at the distributed cooperative control problem of the unmanned ship cluster, the prior art is often focused on solving a single constraint problem, for example, considering single wave disturbance of a physical layer, single actuator partial failure, blocking, saturation fault or single network attack influence of a network layer, and the influence on the cooperative consistency target of the unmanned ship cluster under each constraint association modeling is not deeply studied, so that the prior art has limitations in treating multiple constraint problems and association modeling problems;
In addition, due to the existence of the aperiodic DoS network attack, all links of the unmanned ship cluster network layer are respectively kept interrupted and communicated in the activation and dormant states of the aperiodic DoS attack, namely information transmission, interaction interruption and communication among unmanned ships, the existing multi-intelligent system cooperative control method based on graph theory cannot be directly popularized and applied to the unmanned ship cluster system influenced by the DoS attack, and an aperiodic DoS attack model needs to be established and a novel unmanned ship cluster distributed type safety control method for resisting the DoS attack needs to be developed;
in the unmanned aerial vehicle cluster distributed safety control method provided by the invention, aiming at a networked unmanned aerial vehicle cluster system influenced by DoS attack, the unmanned aerial vehicle cluster distributed safety control method is provided, and aims to solve the problems that a physical layer has mutation and a slow-change actuator compound fault and a network layer has aperiodic DoS attack in an open and dynamic ocean scene, and the fault tolerance target for effectively counteracting the physical layer compound fault and the defending target of the network layer DoS attack are realized through the provided distributed safety control method, and meanwhile, the reliability, stability and safety of the unmanned aerial vehicle cluster are ensured.
Firstly, the association modeling of the wave disturbance-composite fault-DoS attack of an unmanned ship cluster system under an open and dynamic ocean scene is not limited to single disturbance modeling, physical fault modeling or network attack modeling, and a real and accurate association model of the wave disturbance, abrupt change and slow change actuator composite fault and aperiodic DoS attack under the open and dynamic ocean scene of the unmanned ship is constructed;
secondly, the aperiodic DoS attack modeling of the unmanned aerial vehicle cluster realizes creatively establishing an aperiodic DoS attack model of the unmanned aerial vehicle according to the totally-interrupted communication topological link or the different activation and dormancy results which are kept communicated by the aperiodic DoS attack, introduces DoS attack frequency and average residence time index, improves the safety control that the collaborative control method of the multiple intelligent systems based on graph theory under fixed topology, switching topology and random topology cannot be directly popularized and applied to the unmanned aerial vehicle cluster system influenced by the DoS attack, and constructs index constraint conditions of the unmanned aerial vehicle cluster for realizing the aperiodic DoS attack under the anti-attack target;
the unmanned ship cluster switching baseline control and the distributed safety control comprise unmanned ship cluster switching control ideas, namely, the unmanned ship cluster switching control ideas are switched from the unmanned ship baseline safety controller under the influence of aperiodic DoS activation attack to the unmanned ship distributed safety controller under the influence of aperiodic DoS dormancy attack. The designed baseline safety controller only comprises estimation compensation information, and negative feedback of the baseline safety controller provides additional and positive information for compensating negative influences of faults in fault-tolerant control, so that singleness and conservation of the existing independent fault estimation and independent fault-tolerant control technology are improved, organic connection of fault estimation and fault-tolerant control is fully utilized, and finally, a fault-tolerant target for effectively counteracting composite faults of a physical layer actuator and an anti-attack target in a non-periodic DoS attack activation stage of a network layer are realized. The designed distributed safety controller comprises estimated compensation information and distributed state information for completing information interaction based on the latest successful trigger time, the distributed state information only needs to complete interaction at the latest successful trigger time, the limitations of huge and redundant data volume caused by uniform sampling trigger and uncertainty of data volume caused by random sampling trigger and large network transmission bandwidth resource burden in the prior art are improved, and the limitations of complete information acquisition under the condition that the prior sensor sensing technology needs to be more complete and more realistic ocean unmanned ship task scene are overcome, so that a fault tolerance target for effectively counteracting composite faults of a physical layer actuator and an anti-attack target in a network layer aperiodic DoS attack dormancy stage are realized.
Finally, the unmanned ship cluster based on event triggering can update the control strategy: the improved event-triggering-based unmanned ship cluster updatable control strategy realizes a low-complexity event-based distributed security control mechanism to reduce bandwidth occupation of communication topology in an unmanned ship cluster system and reduce the influence of network physical threat, and meanwhile, the designed upper limit of an event triggering threshold can eliminate the cyclic repeated triggering behavior. Further, the improved event triggering mechanism also overcomes the redundancy of the prior art that uniform time sampling triggers result in data volume and the uncertainty of random time sampling triggers result in data volume.
In summary, the distributed security control of the unmanned ship cluster (effective fault tolerance of physical faults and effective countermeasures of network attacks) under the influence of the aperiodic DoS attack of the network layer and the composite faults of the physical layer executor realizes the cooperative consistency of the unmanned ships, thereby playing an important role in the aspects of material supply, topographic mapping, sea rescue, unmanned search and the like in civil fields such as military combat enclosure, driving away, sweeping, anti-diving and the like.
Drawings
Fig. 1 is a schematic diagram of a distributed security control method for unmanned boats cluster according to an embodiment of the present invention.
Detailed Description
The invention is further elucidated below in connection with the embodiments with reference to the drawings.
It should be noted that the components in the figures may be shown exaggerated for illustrative purposes and are not necessarily to scale. In the drawings, identical or functionally identical components are provided with the same reference numerals.
In the present invention, unless specifically indicated otherwise, "disposed on …", "disposed over …" and "disposed over …" do not preclude the presence of an intermediate therebetween. Furthermore, "disposed on or above" … merely indicates the relative positional relationship between the two components, but may also be converted to "disposed under or below" …, and vice versa, under certain circumstances, such as after reversing the product direction.
In the present invention, the embodiments are merely intended to illustrate the scheme of the present invention, and should not be construed as limiting.
In the present invention, the adjectives "a" and "an" do not exclude a scenario of a plurality of elements, unless specifically indicated.
It should also be noted herein that in embodiments of the present invention, only a portion of the components or assemblies may be shown for clarity and simplicity, but those of ordinary skill in the art will appreciate that the components or assemblies may be added as needed for a particular scenario under the teachings of the present invention. In addition, features of different embodiments of the invention may be combined with each other, unless otherwise specified. For example, a feature of the second embodiment may be substituted for a corresponding feature of the first embodiment, or may have the same or similar function, and the resulting embodiment would fall within the disclosure or description of the application.
It should also be noted herein that, within the scope of the present invention, the terms "identical", "equal" and the like do not mean that the two values are absolutely equal, but rather allow for some reasonable error, i.e., the terms also encompass "substantially identical", "substantially equal". By analogy, in the present invention, the term "perpendicular", "parallel" and the like in the table direction also covers the meaning of "substantially perpendicular", "substantially parallel".
The numbers of the steps of the methods of the present invention are not limited to the order of execution of the steps of the methods. The method steps may be performed in a different order unless otherwise indicated.
The unmanned ship cluster distributed safety control method provided by the invention is further described in detail below with reference to the accompanying drawings and specific embodiments. The advantages and features of the present invention will become more apparent from the following description. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for convenience and clarity in aiding in the description of embodiments of the invention.
The invention aims to provide a distributed safety control method for unmanned ship clusters, which aims to solve the problem that the existing networked unmanned ship clusters can bring serious consequences when being attacked by aperiodic DoS.
In order to achieve the above purpose, the present invention provides a distributed safety control method for unmanned ships, comprising: performing association modeling on a wave disturbance model, a composite fault model and a DoS attack model of the unmanned ship cluster system to form a comprehensive model; establishing an aperiodic DoS attack model of the unmanned ship cluster according to the comprehensive model; and according to the aperiodic DoS attack model, enabling the unmanned aerial vehicle cluster to implement switching between the base line control and the distributed security control, and performing event trigger-based unmanned aerial vehicle cluster updatable control.
FIG. 1 provides a first embodiment of the present invention, which shows a schematic flow diagram of a distributed security control method for unmanned aerial vehicle clusters; as shown in fig. 1, the unmanned ship cluster distributed safety control method in this embodiment includes:
step one: according to the conventional unmanned ship swinging, yawing and rolling motion equation, setting N unmanned ships to form a networked unmanned ship cluster system, and considering that the compound faults of the abrupt and gradual change actuators occur in rudder deflection channels in the ith unmanned ship (i=1, …, N), namely:
wherein v is i (t),r i (t),ψ i (t),p i (t),φ i (t),δ i (t) the yaw rate, yaw angle, roll rate, roll angle, rudder deflection angle, and ω of the ith unmanned boat, respectively ψi (t),ω φi (t) wave disturbances denoted as yaw path and roll path of the ith unmanned boat ζ, ω n Expressed as damping ratio and natural frequency, T v ,T r Expressed as a time constant, K dv ,K dr ,K vr ,K dp ,K vp Represented as an unmanned boat system gain matrix.
Superimposed in rudder deflection angle channel
Expressed as abrupt and gradual actuator compound failure. Order the
And->
Respectively expressed as->
The specific mutation and mild actuator composite fault index model is as follows:
wherein the method comprises the steps of
Expressed as a constant fault upper bound, fault occurrence time, and fault decay rate. The characteristics of unobvious early characteristics and unobvious behaviors of the slowly-varying faults are introduced by exponential modeling, and when the fault attenuation rate meets +.>
When the actuator fails, the actuator becomes slowly changedA fault; when the failure attenuation rate is satisfied->
The actuator failure is a sudden failure, wherein +.>
Is a known constant value of the setting.
Step two: defining a system state x of a dynamic equation of the unmanned ship according to the swinging, yawing and rolling motion equation of the ith unmanned ship in the step one i (t), measurable output y of angle sensor i (t) wave induced external disturbance ω i (t) is x respectively i (t)＝[v i (t)r i (t)ψ i (t)p i (t)φ i (t)] T ,y i (t)＝[ψ i (t)φ i (t)] T ,ω i (t)＝[ω ψi (t)ω φi (t)] T The unmanned boat dynamic equation is expressed as follows:
wherein the method comprises the steps of
The gain matrix A, B, F, E and C expressed as the composite fault of the exponential abrupt and gradual executor and the unmanned ship dynamic equation are expressed as follows:
Step three: the networked unmanned ship clusters are connected with each other through a communication network, and the network layer of the networked unmanned ship clusters can be influenced by aperiodic DoS attacks of adversary attackers. And under the activation and dormant states of the aperiodic DoS attack, each link of the unmanned ship cluster network layer is respectively maintained to be interrupted and communicated, namely, the interruption and the communication of information transmission among the unmanned ships are realized.
Definition of the definition
For a total activation time interval of an aperiodic DoS attack, i.e. during which the information interaction is interrupted, where t 0 For initial time, t is termination time, U is union, U is intersection,/->
Activating a time interval (r is a natural number) for the r-th DoS attack, wherein +.>
At t for aperiodic DoS attack 0 ,t]Spaced activation sequences, an
Is an aperiodic time varying interval. The information of the adjacent unmanned ship cannot be utilized to realize distributed anti-attack safety control within the total activation time interval of the aperiodic DoS attack.
Definition Γ d (t 0 ,t)＝[t 0 ,t]\Γ a (t 0 T) is the total sleep time interval of the aperiodic DoS attack, namely, the information interaction is allowed in the time interval, the communication topology structure is not changed, and \is the remainder set. The information of the adjacent unmanned ships can be utilized to realize distributed anti-attack safety control in the total sleep time interval of the aperiodic DoS attack.
For aperiodic DoS attack modeling, three classes of indexes are given, as follows:
DoS attack number N Γ (t 0 T): definition of the definition
Wherein->
Represented as the number of DoS active attacks and DoS sleep attacks, respectively.
DoS attack frequency
Definitions->
Wherein->
Expressed as the number of DoS-enabled attacks.
DoS attack total activation time interval Γ a (t 0 T): presence of a boundary value Γ 0 Gtoreq 0 and average residence time index τ a > 0, satisfy
Step four: according to the dynamic equation of the ith unmanned aerial vehicle in the second step, defining the augmentation state of the ith unmanned aerial vehicle augmentation model as
Augmentation uncertainty is +.>
An augmented model of the ith unmanned boat may be obtained as follows:
wherein the system augmentation matrix of the ith unmanned ship augmentation model is represented as follows:
where 0 is represented as a matrix of elements 0.
According to the augmentation model of the unmanned ship, a distributed unknown input observer is designed to realize effective estimation of the composite faults of the internal state, the unknown mutation and the slow-change actuator;
wherein z is i (t) is represented as the state of an unknown input observer,
expressed as an augmented state->
Wherein>
Represented as system state x i Estimated state of (t)>
Denoted as actuator composite fault f δi The estimated faults of (t), M, G, J, H are denoted as unknown input observer gain matrices.
Step five: at aperiodic DoS attack activation interval Γ a (t 0 T) unmanned ship cluster communication is interrupted, and only the estimation information of the distributed unknown input observer obtained in the fourth step can be used
(including unmanned ship angle, angular velocity state estimation information->
And actuator composite fault estimation information>
) Under the DoS attack modeling of the unmanned ship cluster, designing a base line safety controller of an ith unmanned ship expressed as follows to realize a fault tolerance target for the composite fault of the physical layer executor and an anti-attack target in the non-periodic DoS attack activation stage of the network layer;
wherein K is 1 ＝[K x K f ]Expressed as compensation gain, where K x Estimating gain for internal state, K f Expressed as a fault estimation gain, the specific following is:
wherein the damping ratio and the natural frequency ζ, ω n Time constant T v ,T r Gain K of unmanned ship system dv ,K dr ,K vr ,K dp ,K vp See step one for definition of (a).
Step six: during aperiodic DoS attack sleep interval Γ d (t 0 T) unmanned ship cluster communication is allowed, and updating of the unmanned ship cluster distributed safety controller can be realized only in the non-periodic DoS attack dormancy interval period. Sleep interval time Γ during DoS attack d (t 0 Definition of t)
For time series based on event trigger control, i.e. the i-th updatable security controller is +_ at each event trigger moment >
Is activated. In each triggerable period +.>
According to the baseline safety controller in the fifth step, under the DoS attack modeling of the unmanned aerial vehicle cluster, the distributed safety controller based on the event triggering mechanism of the ith unmanned aerial vehicle is designed to realize the fault tolerance target of the composite fault of the physical layer executor and the attack resistance target of the aperiodic DoS attack dormancy stage of the network layer,
wherein K is 2 Expressed as information interaction gain, a ij Is that
The j-th column element value of the i-th row of (2), wherein +.>
And->
The communication topology adjacency matrix and the set of the nodes adjacent to the ith node in the graph theory are respectively. />
The status values respectively indicated as the status values of the i-th and j-th unmanned boats for completing information interaction at the latest successful trigger moment comprise the following definitions:
wherein the method comprises the steps of
Represented as the latest successful trigger time value, and scalar k i (t) is expressed as
Step seven: completing the state value of information interaction according to the latest successful trigger moment of the ith unmanned aerial vehicle obtained in the step six
Construction state interaction error signal +.>
According to state exchangeMutual error delta i (t) and the event trigger mechanism expressed below can explicitly update the time sequence +.>
Wherein θ is i The expression of > 0 is expressed as a threshold scalar based on time triggering, the expression of I is expressed as a two-norm, namely, sampling update time which can be triggered by events is only the time when the constraint condition is met without uniformly sampling at a specified frequency 
Step eight: firstly, solving the following algebraic Riccati equation to obtain a symmetrical positive definite matrix P and a positive definite matrix Q 1 And a normal number k 1 ：
PA+A T P-k 1 PBB T P+Q 1 ＝0
The gain matrix A and the gain matrix B of the unmanned ship dynamic equation are shown in the step two. From the solved matrix P, Q 1 Constant k 1 Solving the following linear matrix inequality to obtain a positive definite matrix Q 2 And step five, the internal state estimation gain K to be solved x ：
Next, set up
Wherein 1 is N N x 1 column matrix of element 1, I N For the n×n unit matrix, the gain matrix E is shown in step two. Solving the inequality constraint as follows, the scalar +.>
Wherein ε is 1 ,ρ 3 To set a positive constant lambda max ,λ min Expressed as maximum and minimum eigenvalues, max { } expressed as maximum,
expressed as a Laplacian matrix of the communication topology in graph theory>
Is the largest feature root of (1). Simultaneously step seven time-triggered threshold scalar θ i Satisfy->
Again, a positive constant ε is set 2 ,∈ inc Solving the inequality constraint to obtain a scalar alpha with positive value 1 ,α 2 ：
Where min { } is expressed as taking the minimum value.
Finally, set k 3 ＝||PBK 1 I and compensating the gain K according to the step five 1 ＝[K x K f ]Can be further provided with the following expression scalar
Step nine: according to the scalar solved in step eight
Solving the matrix inequality to obtain matrix H, J 1 :
Wherein the method comprises the steps of 
And->
See step four. The remaining unknown input observer gain matrices G, J in step four may be set to
Wherein the system is augmented with a matrix
See step four. Further, setting an information interaction gain K 2 For K 2 ＝τk 1 B T P, wherein the positive constant τ satisfies +.>
And->
Is Laplace matrix->
Is the minimum non-zero feature root of (2).
Step ten: giving a normal number sigma according to the matrix and the constant parameters set and solved in the step eight and the step nine * ∈(0,α 1 ) According to the index definition modeled for aperiodic DoS attack in step three (DoS attack frequency
Average residence time τ a > 0), in time interval [ t ] 0 T) when the following DoS attack frequency is satisfied>
Average residence time τ a Constraint ensures that the proposed unmanned ship cluster distributed safety control method can finally achieve the index consistency target of unmanned ship clusters,
τ a ＞(α 1 -σ * ) -1 (α 1 +α 2 )
wherein the method comprises the steps of
α 1 ,α 2 And (8) taking the value in the step eight.
Further, the state consistency error signal is set to
The i-th unmanned ship index consistency performance is represented by an index type index of state consistency error:
wherein the exponential decay rate is
Amplitude is +.>
Wherein eta Γ ,Γ 0 Is a preset positive constant, and +.>
Denoted as initial t 0 Time of day state consistency error signal.
In summary, the invention provides a plurality of innovation points, and in particular the invention provides a 'wave disturbance-composite fault-DoS attack' associated modeling of an unmanned ship cluster system, wherein wave disturbance omega is introduced into the swinging, yaw and roll motion equation of the ith unmanned ship in the second step i (t)＝[ω ψi (t)ω φi (t)] T Exponential abrupt and gradual actuator compound fault
The dynamic equation of the unmanned ship wave disturbance-composite fault is expressed as follows:
and in the third step, an aperiodic DoS attack model is established, and the aperiodic DoS attack is modeled as an active and dormant state. Defining a total activation time interval of the aperiodic DoS attack (the distributed anti-attack safety control cannot be realized by using the information of the adjacent unmanned ship) and a total dormancy time interval of the aperiodic DoS attack (the distributed anti-attack safety control can be realized by using the information of the adjacent unmanned ship). Further, given three classes of metrics for aperiodic DoS attacks,number of DoS attacks N, respectively Γ (t 0 ,t) (
Respectively expressed as the number of DoS active attacks and DoS sleep attacks); doS attack frequency
During the DoS attack total activation time interval Γ a (t 0 Average residence time index τ within t) a ＞0。
The multi-element association mechanism analysis of wave disturbance-composite fault-DoS attack improves the prior art to solve the problem of single constraint (single wave disturbance of a physical layer, partial failure of a single actuator, seizing, saturation fault or attack influence of a network layer), constructs a real and accurate association model of the wave disturbance, sudden change and slow change actuator composite fault and aperiodic DoS attack under the open and dynamic ocean scene of a relatively perfect unmanned ship, and provides reference and support for researching the multi-constraint problem and association modeling problem under the cluster safety control target of the unmanned ship.
The invention also provides aperiodic DoS attack modeling of the unmanned ship cluster, and due to the existence of aperiodic DoS network attack, each link of the unmanned ship cluster network layer is respectively maintained to be interrupted and communicated in the activation and dormant states of the aperiodic DoS attack, namely, the information transmission, interaction interruption and communication among the unmanned ships. According to the method, an aperiodic DoS attack model of the unmanned ship is creatively built according to the totally-interrupted communication topology link or the dissimilar activation and dormancy results of the communication maintenance caused by the aperiodic DoS attack, doS attack frequency and average residence time indexes are introduced, the safety control of the unmanned ship cluster system influenced by the DoS attack, which cannot be directly promoted and applied by a multi-agent system cooperative control method based on graph theory under fixed topology, switching topology and random topology, is improved, and the index constraint condition of the unmanned ship cluster for the aperiodic DoS attack under the anti-attack target is built.
In step three, two classes of aperiodic DoS attack total activation and total sleep time interval are givenAnd (5) defining. Specifically, the method comprises the following steps: definition of the definition
For a total activation time interval of an aperiodic DoS attack, i.e. during which the information interaction is interrupted, where t 0 For initial time, t is termination time, U is union, U is intersection,/->
Activating a time interval (r is a natural number) for the r-th DoS attack, wherein +.>
At t for aperiodic DoS attack 0 ,t]Spaced activation sequences, an
Is an aperiodic time varying interval. The information of the adjacent unmanned ship cannot be utilized to realize distributed anti-attack safety control in the total activation time interval of the aperiodic DoS attack. Definition Γ d (t 0 ,t)＝[t 0 ,t]\Γ a (t 0 T) is the total sleep time interval of the aperiodic DoS attack, namely, the information interaction is allowed in the time interval, the communication topology structure is not changed, and \is the remainder set. The information of the adjacent unmanned ships can be utilized to realize distributed anti-attack safety control in the total sleep time interval of the aperiodic DoS attack.
Meanwhile, in the third step, aiming at aperiodic DoS attack modeling, three indexes of DoS attack number, doS attack frequency and average residence time are provided, and the method specifically refers to the following steps: definition of the definition
Is the number of DoS attacks, wherein +.>
The number of DoS active attacks and DoS sleep attacks, respectively; definitions->
Is the DoS attack frequency, wherein->
Expressed as the number of DoS-enabled attacks; during the total activation time interval Γ of DoS attack a (t 0 Defining a presence threshold Γ in t) 0 Gtoreq 0 and average residence time index τ a > 0 satisfies->
/>
Further in step ten, the DoS attack frequency satisfying the following constraint is proposed
Average residence time τ a ；
τ a ＞(α 1 -σ * ) -1 (α 1 +α 2 )
Therefore, the distributed security control of the unmanned ship cluster is only located at the aperiodic DoS sleep attack time interval (information interaction), meanwhile, the baseline security control of the unmanned ship cluster is located at the aperiodic DoS activation attack time interval (information non-interaction), and then the index consistency target of the unmanned ship cluster is finally achieved.
The invention also provides a unmanned ship cluster switching type baseline control and a distributed safety control method, and the innovation point comprises an unmanned ship cluster switching control idea, namely, the unmanned ship cluster switching control idea is that the unmanned ship cluster switching control method is switched from a baseline safety controller under the influence of aperiodic DoS activation attack to a distributed safety controller under the influence of aperiodic DoS dormancy attack.
In one aspect, in step five, consider the activation interval time Γ during an aperiodic DoS attack a (t 0 T) unmanned ship cluster communication is interrupted and only a distributed unknown input view is availableEstimation information of a tester
Under unmanned ship cluster aperiodic DoS activation attack modeling, designing a baseline safety controller of an ith unmanned ship represented as follows:
wherein K is 1 ＝[K x K f ]Expressed as compensation gain, where K x Estimating gain for internal state, K f Expressed as a fault estimation gain, the specific following is:
the designed baseline security controller contains only estimated compensation information
Improving increased status and fault estimation information +.>
Unmanned ship angle and angular velocity state estimation information from distributed unknown input observer
Actuator composite fault estimation information +.>
The negative feedback function of the system provides additional and positive information for compensating negative effects of faults in fault-tolerant control, improves the singleness and conservation of the existing independent fault estimation and independent fault-tolerant control technology, fully utilizes the organic connection of fault estimation and fault-tolerant control, and finally realizes the fault-tolerant target for effectively counteracting composite faults of a physical layer actuator and the anti-attack aim of a network layer aperiodic DoS attack activation stageAnd (5) marking.
On the other hand, in step six, consider that in aperiodic DoS attack sleep interval time Γ d (t 0 T) unmanned ship cluster communication is allowed, and besides the baseline safety controller can be utilized, the unmanned ship cluster distributed safety controller can be updated in the aperiodic DoS attack sleep interval period. According to the baseline safety controller in the fifth step, under the aperiodic DoS sleep attack modeling of the unmanned aerial vehicle cluster, switching and designing the distributed safety controller of the ith unmanned aerial vehicle based on the event triggering mechanism, wherein the distributed safety controller is represented as follows:
Wherein K is 2 Expressed as information interaction gain, a ij Is that
The j-th column element value of the i-th row of (2), wherein +.>
And->
The communication topology adjacency matrix and the set of the nodes adjacent to the ith node in the graph theory are respectively. />
The status values are respectively expressed as the status values of the i-th unmanned aerial vehicle and the j-th unmanned aerial vehicle for completing information interaction at the latest successful triggering moment.
The designed distributed safety controller comprises estimated compensation information
Further comprising distributed status information completing the information interaction based on the latest successful trigger moment>
Gain K through information interaction 2 The distributed state information is connected only by completing interaction at the latest successful trigger moment, so that the defects of huge and redundant data volume caused by uniform sampling trigger, uncertainty of data volume caused by random sampling trigger and large network transmission bandwidth resource burden in the prior art are overcome, and the defect that the existing sensor sensing technology needs to be more complete and more real in acquisition of complete information under the marine unmanned ship task scene is overcome, thereby realizing a fault tolerance target for effectively counteracting composite faults of a physical layer actuator and an anti-attack target in a network layer aperiodic DoS attack dormancy stage.
The invention also provides an event-triggered unmanned ship cluster updatable control strategy, which is used for controlling the sleep interval time gamma of the non-periodic DoS attack d (t 0 T) unmanned ship cluster communication is allowed, and updating of the unmanned ship cluster distributed safety controller can be realized only in the non-periodic DoS attack sleep interval period. Compared with the existing update control strategy (uniformly sampled and randomly sampled time trigger strategy), the unmanned ship cluster based on the event trigger mechanism is improved by the distributed safety controller, namely the unmanned ship cluster based on the event trigger mechanism can update the control strategy in the DoS attack sleep interval time gamma d (t 0 Time series within t)
The sampling of event triggering is completed, namely the security controller can be updated at the moment of each event triggering>
Is activated.
In the seventh step, completing the information interaction according to the acquired status value of the ith unmanned aerial vehicle at the latest successful trigger time
Construction state interaction error signal +.>
Based on state interaction error delta i (t) the followingThe indicated event trigger threshold upper bound can explicitly update the time sequence +.>
Wherein θ is i The expression of > 0 is expressed as a threshold scalar based on time triggering, the expression of I is expressed as a two-norm, namely, sampling update time which can be triggered by events is only the time when the constraint condition is met without uniformly sampling at a specified frequency
The improved event-triggering-based unmanned ship cluster updatable control strategy realizes a low-complexity event-based distributed safety control mechanism so as to reduce bandwidth occupation of communication topology in an unmanned ship cluster system and reduce the influence of network physical threat, and meanwhile, the designed event triggering threshold upper bound 
The cycle repeat trigger behavior can be eliminated. Further, the improved event trigger mechanism also overcomes the redundancy of the prior art that uniform time sampling triggers result in data volume and the uncertainty of random time sampling triggers result in data volume.
In summary, the above embodiments describe in detail different configurations of the unmanned aerial vehicle cluster distributed security control method, and of course, the present invention includes, but is not limited to, the configurations listed in the above implementation, and any contents transformed based on the configurations provided in the above embodiments fall within the scope of protection of the present invention. One skilled in the art can recognize that the above embodiments are illustrative.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that identical and similar parts between the embodiments are all enough to be referred to each other. For the system disclosed in the embodiment, the description is relatively simple because of corresponding to the method disclosed in the embodiment, and the relevant points refer to the description of the method section.
The above description is only illustrative of the preferred embodiments of the present invention and is not intended to limit the scope of the present invention, and any alterations and modifications made by those skilled in the art based on the above disclosure shall fall within the scope of the appended claims.
Claims (4)
1. The unmanned ship cluster distributed safety control method is characterized by comprising the following steps of:
performing association modeling on a wave disturbance model, a composite fault model and a DoS attack model of the unmanned ship cluster system to form a comprehensive model;
establishing an aperiodic DoS attack model of the unmanned ship cluster according to the comprehensive model; and
switching between baseline control and distributed security control of the unmanned ship cluster according to DoS attack activation and dormancy stages divided by the aperiodic DoS attack model, and performing event trigger-based renewable control of the unmanned ship cluster in the DoS attack dormancy stage;
forming the integrated model and the aperiodic DoS attack model includes:
constructing a correlation model of wave disturbance and/or wave mutation and/or slow-change actuator composite faults and/or aperiodic DoS attacks under the open and/or dynamic ocean scene of the unmanned ship;
establishing an unmanned ship aperiodic DoS attack model according to different activation and dormancy results of the communication topological link which is completely interrupted or kept communicated by the aperiodic DoS attack; and
introducing DoS attack frequency and average residence time index, and constructing index constraint conditions for aperiodic DoS attack under an attack-resistant target of the unmanned ship cluster;
The method for switching between baseline control and distributed security control of the unmanned boat cluster according to the DoS attack activation and dormancy stage divided by the aperiodic DoS attack model, and the event trigger-based unmanned boat cluster updatable control in the DoS attack dormancy stage comprises the following steps:
switching from a baseline safety controller of the unmanned aerial vehicle under the influence of aperiodic DoS activation attack to a distributed safety controller of the unmanned aerial vehicle under the influence of aperiodic DoS sleep attack;
the baseline safety controller comprises estimated compensation information, wherein negative feedback of the estimated compensation information provides additional and positive information for compensating negative effects of faults in fault-tolerant control, implements a fault-tolerant target for effectively counteracting composite faults of physical layer executors, and an anti-attack target in a network layer aperiodic DoS attack activation stage; and
the distributed safety controller comprises estimation compensation information and distributed state information for completing information interaction based on the latest successful trigger time;
the distributed state information only needs to complete interaction at the latest successful triggering moment, implements a fault tolerance target for effectively counteracting the composite fault of the physical layer executor and an anti-attack target in the network layer aperiodic DoS attack dormancy stage;
The method comprises the steps of enabling the unmanned ship cluster to implement switching between baseline control and distributed security control according to DoS attack activation and dormancy stages divided by the aperiodic DoS attack model, enabling the unmanned ship cluster to update and control based on event triggering in the DoS attack dormancy stage, and further comprising:
the unmanned ship cluster based on event triggering can be updated and controlled, a low-complexity event-based distributed safety control mechanism is carried out, so that the bandwidth occupation of a communication topology in the unmanned ship cluster system is reduced, the influence of network physical threat is lightened, and an event triggering threshold upper bound is set to eliminate the cyclic repeated triggering behavior;
wave disturbance omega is introduced into the motion equation of swinging, yawing and rolling of the ith unmanned ship i (t)＝[ω ψi (t)ω φi (t)] T Exponential abrupt and gradual actuator compound fault
Obtaining the representation of the dynamic equation of the unmanned ship 'wave disturbance-composite fault' such asThe following steps:
establishing an aperiodic DoS attack model, and modeling the aperiodic DoS attack as an activated and dormant state;
three indexes are given for aperiodic DoS attacks, namely the number of DoS attacks N Γ (t 0 T), doS attack frequency
During the DoS attack total activation time interval Γ a (t 0 Average residence time index τ within t) a >0, wherein 
The number of DoS active attacks and DoS sleep attacks, respectively;
defining total activation and total sleep time interval of aperiodic DoS attack, defining
For a total activation time interval of an aperiodic DoS attack, i.e. in which the information interaction is interrupted, where t 0 For initial time, t is termination time, U is union, U is intersection,/->
Activating time interval for the r-th DoS attack, r being a natural number, wherein +.>
For aperiodic DoS attack at [ t0, t]A spacer activating sequence, and->
Is a non-periodic time-varying interval;
the information of the adjacent unmanned ship cannot be utilized to realize distributed anti-attack safety control within the total activation time interval of the aperiodic DoS attack;
definition Γ d (t 0 ,t)＝[t 0 ,t]\Γ a (t 0 T) is the total dormancy time interval of the aperiodic DoS attack, namely the information interaction is allowed in the time interval, the communication topology structure is not changed, and \is the remainder set;
the information of the adjacent unmanned ships can be utilized to realize distributed anti-attack safety control in the total sleep time interval of the aperiodic DoS attack;
setting the number of DoS attacks, the DoS attack frequency and the average residence time for aperiodic DoS attack modeling, and defining
Is the number of DoS attacks, wherein +.>
The number of DoS active attacks and DoS sleep attacks, respectively; definitions- >
Is the DoS attack frequency, wherein->
Expressed as the number of DoS-enabled attacks; during the total activation time interval Γ of DoS attack a (t 0 Defining a presence threshold Γ in t) 0 Gtoreq 0 and average residence time index τ a >0 satisfies the following
Determining DoS attack frequency satisfying the following constraint
Average residence time τ a ，
τ a >(α 1 -σ * ) -1 (α 1 +α 2 )
The unmanned aerial vehicle cluster distributed security control is located at an aperiodic DoS sleep attack time interval, and the unmanned aerial vehicle cluster baseline security control is located at an aperiodic DoS activation attack time interval.
2. The unmanned aerial vehicle cluster distributed security control method of claim 1, further comprising:
according to the activation interval time Γ in aperiodic DoS attack a (t 0 T) unmanned ship cluster communication is interrupted, using estimated information of a distributed unknown input observer
Under unmanned ship cluster aperiodic DoS activation attack modeling, designing a baseline safety controller of an ith unmanned ship represented as follows:
wherein K is 1 ＝[K x K f ]Expressed as compensation gain, where K x Estimating gain for internal state, K f Expressed as a fault estimation gain, the specific following is:
the designed baseline security controller contains only estimated compensation information
Improving incremental state and fault estimation information/>
Unmanned ship angle and angular velocity state estimation information from distributed unknown input observer +. >
Actuator composite fault estimation information +.>
The negative feedback function of the method provides additional and positive information for compensating negative effects of faults in fault-tolerant control, improves singleness and conservation of the existing independent fault estimation and independent fault-tolerant control technology, fully utilizes organic connection of fault estimation and fault-tolerant control, and finally achieves a fault-tolerant target for effectively counteracting composite faults of a physical layer executor and an anti-attack target in a network layer aperiodic DoS attack activation stage.
3. The unmanned aerial vehicle cluster distributed security control method of claim 2, further comprising:
according to sleep interval time Γ of aperiodic DoS attack d (t 0 T) unmanned ship cluster communication is allowed, and updating of the unmanned ship cluster distributed safety controller is carried out in the non-periodic DoS attack dormancy interval time period;
according to the baseline safety controller, under the aperiodic DoS sleep attack modeling of the unmanned ship cluster, switching the distributed safety controller based on the event triggering mechanism of the ith unmanned ship, which is designed as follows:
wherein K is 2 Expressed as information interaction gain, a ij Is that
The j-th column element value of the i-th row of (2), wherein +.>
And->
Respectively a communication topology adjacent matrix in graph theory and a set of nodes adjacent to the ith node; / >
Respectively representing the status values of the i-th and j-th unmanned boats for completing information interaction at the latest successful triggering moment;
distributed security controller includes estimated compensation information
Further comprising distributed status information completing the information interaction based on the latest successful trigger moment>
Gain K through information interaction 2 And connecting, wherein the distributed state information completes interaction at the latest successful triggering moment.
4. A method of distributed security control of unmanned boats clusters according to claim 3, further comprising:
during aperiodic DoS attack sleep interval Γ d (t 0 T) unmanned ship cluster communication is allowed, and updating of the unmanned ship cluster distributed safety controller is carried out in the non-periodic DoS attack dormancy interval time period; sleep interval time Γ during DoS attack d (t 0 Time series within t)
At which event triggered sampling is completed to update the security controller +/at each event trigger moment>
Is activated;
completing the state value of information interaction according to the latest successful trigger moment of the ith unmanned ship
Construction state interaction error signal +.>
Based on state interaction error delta i (t) event trigger threshold upper bound explicit update time sequence expressed below>
Wherein θ is i >0 is represented as a time trigger-based threshold scalar, and is represented as a two-norm, with the time at which the constraint is satisfied being the time at which the event-triggerable sample is updated 
The upper bound of the event trigger threshold is
/>
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210338174.3A CN114866284B (en) | 2022-04-01 | 2022-04-01 | Unmanned ship cluster distributed safety control method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210338174.3A CN114866284B (en) | 2022-04-01 | 2022-04-01 | Unmanned ship cluster distributed safety control method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114866284A CN114866284A (en) | 2022-08-05 |
| CN114866284B true CN114866284B (en) | 2023-04-25 |
Family
ID=82630288
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210338174.3A Active CN114866284B (en) | 2022-04-01 | 2022-04-01 | Unmanned ship cluster distributed safety control method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114866284B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110096061A (en) * | 2019-06-04 | 2019-08-06 | 兰州大学 | A kind of the disturbance rejection distributed collaboration control method and device of unmanned boat cluster |
| CN112882473A (en) * | 2021-01-25 | 2021-06-01 | 大连海事大学 | Event-triggered unmanned ship cluster distributed cooperative controller, structure and method |
| CN113093733A (en) * | 2021-03-17 | 2021-07-09 | 东南大学 | Sea-hitting method for unmanned boat cluster |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111830976B (en) * | 2020-07-01 | 2021-03-23 | 武汉理工大学 | Unmanned ship control method based on T-S fuzzy system switching under DoS attack |
| CN112995154B (en) * | 2021-02-09 | 2023-05-02 | 南京理工大学 | Synchronous control method for complex network under aperiodic DoS attack |
| CN114035589B (en) * | 2021-12-01 | 2023-07-25 | 上海大学 | Cluster unmanned ship fault tolerance cooperative control method based on anti-attack strategy |
-
2022
- 2022-04-01 CN CN202210338174.3A patent/CN114866284B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110096061A (en) * | 2019-06-04 | 2019-08-06 | 兰州大学 | A kind of the disturbance rejection distributed collaboration control method and device of unmanned boat cluster |
| CN112882473A (en) * | 2021-01-25 | 2021-06-01 | 大连海事大学 | Event-triggered unmanned ship cluster distributed cooperative controller, structure and method |
| CN113093733A (en) * | 2021-03-17 | 2021-07-09 | 东南大学 | Sea-hitting method for unmanned boat cluster |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114866284A (en) | 2022-08-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109557818B (en) | Sliding mode fault-tolerant control method of multi-agent tracking system with multiple faults | |
| CN109116736B (en) | Fault-tolerant control method for actuator fault of linear multi-agent system based on sliding mode | |
| CN111948944B (en) | Four-rotor formation fault-tolerant control method based on adaptive neural network | |
| CN111638726B (en) | Event trigger communication-based multi-unmanned aerial vehicle formation consistency control method | |
| CN107422741B (en) | Learning-based cluster flight distributed attitude tracking control method for preserving preset performance | |
| CN114924588B (en) | Unmanned aerial vehicle cluster elastic safety formation method | |
| CN109884902B (en) | Unmanned aerial vehicle formation system fault detection method based on interval observer | |
| CN110262494B (en) | Collaborative learning and formation control method for isomorphic multi-unmanned ship system | |
| CN112305918A (en) | Multi-agent system sliding mode fault-tolerant consistency control algorithm under supercoiled observer | |
| CN114035589B (en) | Cluster unmanned ship fault tolerance cooperative control method based on anti-attack strategy | |
| CN112947505B (en) | Multi-AUV formation distributed control method based on reinforcement learning algorithm and unknown disturbance observer | |
| CN112859913B (en) | Multi-quad-rotor unmanned helicopter attitude consistency optimal control method considering output constraint | |
| CN113110182B (en) | Fault-tolerant controller design method of leader following multi-agent system | |
| CN111381605A (en) | Underwater multi-target collaborative search method applied to large-range sea area of multiple unmanned aerial vehicles | |
| CN114866284B (en) | Unmanned ship cluster distributed safety control method | |
| CN112198796B (en) | Design method of distributed preposed time state observer | |
| Wang et al. | Distributed finite-time velocity-free robust formation control of multiple underactuated AUVs under switching directed topologies | |
| CN115826417A (en) | Robot formation control method for resisting rejection service attack based on topology reconstruction | |
| CN114035543B (en) | Self-repairing control method under damaged state of airplane | |
| CN114296469B (en) | Unmanned ship reconfigurable fault-tolerant control method based on double-parameter self-adaptive fault identification | |
| Wang et al. | Multi-AUG three-dimensional path planning and secure cooperative path following under DoS attacks | |
| Xi et al. | Multi-missile Distributed Cooperative Guidance Law Based on De Bruijn Network | |
| Niu et al. | Fault diagnosis of carrier rocket actuator based on multiple-model method | |
| Zhang et al. | Distributed cooperative guidance strategy for multi-missile attack the maneuvering target | |
| CN115047892B (en) | Underwater unmanned cluster formation key node identification method based on group intelligence |
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 |