CN116187801A - System interval availability determination method for indicating task sustainability in unmanned system - Google Patents
System interval availability determination method for indicating task sustainability in unmanned system Download PDFInfo
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Abstract
The invention provides a system interval availability determination method for characterizing task sustainability in an unmanned system, which comprises the following steps: judging the state of a single unmanned system; defining a state transition rule of a single unmanned system into a calculation module thereof, and providing input for calculating the availability of each unmanned system; calculating the availability of a single unmanned system based on the state transition matrix; reporting the self available state to the unmanned system cluster head by the single unmanned system; the unmanned system cluster head obtains the availability of the system interval according to the system task success criterion, and decides whether the system continues to execute the task. The invention can provide support for the demonstration of key parameter indexes such as average fault time, function average recovery time and the like of a single unmanned system, and can provide a system availability evaluation result more closely to the demand aiming at a core focus of sustainable tasks concerned in application scenes such as swarm combat, manned/unmanned cooperative combat and the like.
Description
Technical Field
The invention relates to the field of equipment system availability evaluation, in particular to a system interval availability evaluation or determination method for representing task sustainability in a bee colony combat unmanned system.
Background
With the occurrence of the battle scene of the bee colony battle and the system battle of the manned/unmanned cooperative peer, the traditional usability measuring parameter, namely the usability A o Has become unsuitable for use anymore, mainly for two reasons. First because of using availability A o Essentially characterized is an average probability value that the system can complete a task under the condition of long-period use, and the evaluation method is as follows: the method comprises the steps of dividing a system into a plurality of state levels, wherein part of states identify that the system is available, the other states represent that the system is unavailable, counting the time interval of the transition of the system between different states, obtaining the probability A (t) that the system is in the available state at the moment t by using a Markov model, and finally enabling t & gtto & gtinfinity to obtain the utilization availability A o Is the evaluation value of (a), i.e
From this, it can be seen that A o The method is suitable for system objects with long-period use characteristics, such as high-value fighter plane and other equipment. In the scenes of swarm combat, manned/unmanned cooperative combat and the like, the main role of the combat function is to provide low-cost or consumable unmanned aerial vehicles which are generated for completing specific functions at the beginning of design and do not meet the premise assumption of long-period use. Second, because the battle mode of the swarm battle, the manned/unmanned cooperative peer is more concerned with the success of a single task, i.e. the system should be continuously available in a certain task period, and the availability A is used o Derived from a (t), a (t) can only characterize that the system is in an available state at time t, that is, the system may have experienced an unavailable state before that time, but the system is subsequently adjusted back to an available state due to some recovery mechanism (e.g., a function restart). As can be seen, A (t) is unable to characterize the level of continuous availability of the system, and if this parameter is used to evaluate system availability, this will cause the evaluation to be doneThe fruit deficiency is high, so that the formulation of a combat scheme is misled, and the combat effect is influenced. In summary, in the background of systematic combat, it is highly desirable to define new system availability evaluation parameters, in particular availability parameters that can characterize the sustainability of a system task, and provide a method for evaluating the parameters.
Disclosure of Invention
The invention aims to solve the technical problem of providing a system interval availability evaluation index for characterizing task sustainability in an unmanned system, and providing a specific calculation evaluation method thereof, which is used for evaluating the system interval availability for characterizing task sustainability and improving the accuracy of continuous availability level evaluation of the unmanned system.
In order to solve the above problems, the present invention provides a system interval availability determination method for indicating task sustainability in an unmanned system, which includes the following steps:
s1, a single unmanned system judges whether the single unmanned system is in an available state or not through sensing the state of a functional module; dividing a single unmanned system into m states s= { S 1 ,s 2 ,…,s m -wherein the status of availability of the unmanned system is denoted w= { s 1 ,s 2 ,…,s l ' state indicating unavailability of unmanned system is denoted as f= { s l+1 ,s l+2 ,…,s m -S = W & -F;
s2, defining a state transition rule of a single unmanned system into a calculation module thereof, so as to calculate interval availability R of each unmanned system i [t 1 ,t 2 ]Providing an input;
s21, obtaining the average time of the unmanned system from the state c to the state j through the statistical test data and the simulation data
And use +.>
To characterize the state transition law of the single unmanned system; />
S22, obtaining a state transition rate matrix Q= [ Q ] of the single unmanned system cj ] n×n And defined in the computing modules of each unmanned system, wherein: when c is not equal to j, let
When c=j, let q cc ＝-∑ c≠j q cj ；
S3, calculating the interval availability R of the single unmanned system i based on the internally defined state transition rate matrix i [t 1 ,t 2 ]I.e. a single unmanned system i is within a time range t 1 ,t 2 ]Probability of continuously maintaining the available state;
s31, when t 1 When=0, the section availability R of the unmanned system i i [0,t 2 ]Calculated by the following formula:
wherein, gamma i ＝[p 1 ,p 2 ,…,p n ]Represents the initial state probability of the unmanned system i and satisfies sigma c p c =1; if the system is in state s at the initial time r Then there is
Wherein I is |w|×|w| Representing a unit array of dimensions |w|×|w| and 0 |F|×|w| Then a zero matrix of dimension |f|×|w| is represented, with |w| and |f| representing the number of available and unavailable states, respectively, of unmanned system i; q (Q) WW Is a matrix formed by elements determined by the intersection of the rows and columns of the available state coordinates in the transfer rate matrix Q; 1 |W|×1 Representing that none of the elements is "1" and the dimension is |W|×1 column vector;
s32, when t 1 When not equal to 0, the interval availability R of the unmanned system i i [t 1 ,t 2 ]Calculated by the following formula:
s33, solving the formulas (1) and (2) in the step S31 and the step S32 by using a matrix index algorithm by using a single unmanned system
And +.>
The numerical result of the item is further obtained to obtain the interval availability R of each unmanned system i [t 1 ,t 2 ]；
S4, the single unmanned system calculates the availability R of the system interval i [t 1 ,t 2 ]Reporting to the unmanned system cluster head to obtain the number u of the available unmanned systems and the corresponding numbers thereof, wherein u is epsilon { k, k+1, …, n };
s5, the unmanned system cluster head utilizes the system interval availability parameter R reported by each unmanned system according to the system task success criterion i [t 1 ,t 2 ]Obtaining the availability A t of system interval 1 ,t 2 ]；
S51, defining a systematic task success criterion; over a period of time t 1 ,t 2 ]In the system formed by n unmanned systems, if the number of the systems in the available state in the system is always at least k, the system task is considered to be successful;
s52, a calculation module of the system cluster head utilizes the system interval availability parameter R reported by each unmanned system i [t 1 ,t 2 ]Generating u state transition probability matrixes P i Evaluating the availability of the system interval by using a finite Markov chain embedding method; by defining a finite state Markov chain { M (j), j=1, 2, …, u }, the state space of which is denoted as B= {0,1, …, k }, after characterizing the addition of the unmanned system to the system, the whole unmanned system is at [ t ] 1 ,t 2 ]The number of systems in available state owned internally;
the remaining entries are all 0, indicating that no such state transition exists;
s53, u state transition probability matrixes P obtained by system cluster heads i The availability of the system interval is obtained according to the formula (5):
wherein: pi= [1,0, …,0] 1×(k+1) Representing the state of the markov chain { M (j), j=1, 2, …, u } in the initial condition as b= {0};
the method is used for summing the probabilities that the number of the available systems in the system is greater than or equal to k, and converting the interval availability into a digital form through pi and U;
s6, the cluster head of the unmanned system obtains the availability A t of the system interval of the system according to the obtained body 1 ,t 2 ]And the number u of available systems remaining in the system to decide whether the system is to continue executing/canceling tasks;
s61, when the availability of system interval A [ t ] 1 ,t 2 ]When σ is not less than and the number of available systems remaining in the system u is not less than k, the system continues to perform tasks, where σ represents a given threshold.
S62, except for the case of the step S61, the system cancels the task.
Further, the system refers to a whole consisting of n identical and heterogeneous single systems, the state of each system is divided into a plurality of levels to represent the availability of the single system, and the capability of the system to execute tasks is represented by the capability of the system in a time range [ t ] 1 ,t 2 ]The number of systems in a usable state.
Further, the number of states of the single system, and the division of the available/unavailable states in step S1 include the same case and the different case.
Further, the state transition rule of the single system in step S2 includes the same case and the different case.
Further, when the original state in the system in step S5 is S e B and S is not equal to k, if the single unmanned system i is at [ t ] 1 ,t 2 ]When the internal is continuously in the available state, after the internal is added into the system, the system state becomes s+1, and the state transition probability is R i [t 1 ,t 2 ]The method comprises the steps of carrying out a first treatment on the surface of the If a single unmanned system i is at t 1 ,t 2 ]If the internal state fails to be continuously in the available state, the system state after the addition is still s, and the state transition probability is 1-R i [t 1 ,t 2 ]。
Preferably, when the initial state S e B and s=k in the system described in step S5, then no matter the single unmanned system i is at [ t ] 1 ,t 2 ]Whether the internal is continuously in a usable state or not, the system state is still k after the internal is added, namely the state transition probability is 1.
Compared with the prior art, the invention has the following beneficial effects:
1. aiming at a core focus of sustainable tasks focused in application scenes such as bee colony combat, manned/unmanned cooperative combat and the like, the invention can give a system availability evaluation result more closely to the demand, namely how many unmanned systems are activated to meet the system availability requirement.
2. The invention can provide support for the key parameter index demonstration of the unmanned system, namely, the state transfer rate parameters of the unmanned system can be determined on the premise of meeting the availability of a specific system, and the time values of the system from the advanced state to the secondary state or from the secondary state to the advanced state after the parameters are inverted are represented, and in the operation, the time values can be interpreted as the design requirements of the average fault time, the function reconfiguration/restarting time and the like of the unmanned system.
Drawings
FIG. 1 is a flow chart of a system interval availability determination method for characterizing task sustainability in an unmanned system of the present invention;
FIG. 2 is a numerical solution flow based on matrix index operation in Matlab;
fig. 3 is an analysis of the impact of increasing the number n of unmanned aerial vehicles in the system on the availability of the system according to the present invention.
Detailed Description
The present application is described in further detail below with reference to the drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings. Embodiments and features of embodiments in this application may be combined with each other without conflict.
FIG. 1 illustrates a system interval availability determination method for characterizing task sustainability in an unmanned system, wherein the system refers to a whole composed of n identical and heterogeneous single systems, the state of each system is divided into a plurality of levels to characterize the availability of the single system, and the capability of the system to execute tasks is characterized in a time range [ t ] 1 ,t 2 ]The number of systems in a usable state, the method comprising the steps of:
s1, a single unmanned system judges whether the single unmanned system is in an available state or not through sensing the state of a functional module; dividing a single unmanned system into m states s= { S 1 ,s 2 ,…,s m -wherein the status of availability of the unmanned system is denoted w= { s 1 ,s 2 ,…,s l ' state indicating unavailability of unmanned system is denoted as f= { s l+1 ,s l+2 ,…,s m -S = W & -F; notably, the number of states, the division of available/unavailable states, of a single system includes the same case and the different case.
S2, defining a state transition rule of a single unmanned system into a calculation module thereof, so as to calculate interval availability R of each unmanned system i [t 1 ,t 2 ]Providing an input; it should be noted that the state transition rule of the single system includes the same case and the different case.
S21, obtaining the average time of the unmanned system from the state c to the state j through the statistical test data and the simulation data
And use +.>
To characterize the state transition law of the individual unmanned systems.
S22, obtaining a state transition rate matrix Q= [ Q ] of the single unmanned system cj ] n×n And defined in the computing modules of each unmanned system, wherein: when c is not equal to j, let
When c=j, let q cc ＝-∑ c≠j q cj 。
S3, calculating the interval availability R of the single unmanned system i based on the internally defined state transition rate matrix i [t 1 ,t 2 ]I.e. a single unmanned system i is within a time range t 1 ,t 2 ]The probability of remaining available continues.
S31, when t 1 When=0, the section availability R of the unmanned system i i [0,t 2 ]Calculated by the following formula:
wherein, gamma i ＝[p 1 ,p 2 ,…,p n ]Represents the initial state probability of the unmanned system i and satisfies sigma c p c =1; if the system is in state s at the initial time r Then there is
Wherein I is |w|×|w| Representing a unit array of dimensions |w|×|w| and 0 |F|×|w| Then a zero matrix of dimension |f|×|w| is represented, with |w| and |f| representing the number of available and unavailable states, respectively, of unmanned system i; q (Q) WW Is a matrix formed by elements determined by the intersection of the rows and columns of the available state coordinates in the transfer rate matrix Q;1 |W|×1 representing that none of the elements is "1" and the dimension is |W|×1 column vector;
s32, when t 1 When not equal to 0, the interval availability R of the unmanned system i i [t 1 ,t 2 ]Calculated by the following formula:
s33, solving the formulas (1) and (2) in the step S31 and the step S32 by using a matrix index algorithm by using a single unmanned system
And +.>
The numerical result of the item is further obtained to obtain the interval availability R of each unmanned system i [t 1 ,t 2 ]。
S4, the single unmanned system calculates the availability R of the system interval i [t 1 ,t 2 ]Reporting to the cluster head of the unmanned system to obtain the number u of the available unmanned systems and the corresponding numbers thereof, wherein u is epsilon { k, k+1, …, n }.
S5, the unmanned system cluster head utilizes the system interval availability parameter R reported by each unmanned system according to the system task success criterion i [t 1 ,t 2 ]Obtaining the availability A t of system interval 1 ,t 2 ]。
S51, defining a systematic task success criterion; over a period of time t 1 ,t 2 ]And if the number of the systems in the available state in the system formed by the n unmanned systems is always at least k, the system task is considered to be successful.
S52, a calculation module of the system cluster head utilizes the system interval availability parameter R reported by each unmanned system i [t 1 ,t 2 ]Raw, give birth toInto u state transition probability matrices P i Evaluating the availability of the system interval by using a finite Markov chain embedding method; by defining a finite state Markov chain { M (j), j=1, 2, …, u }, the state space of which is denoted as B= {0,1, …, k }, after characterizing the addition of the unmanned system to the system, the whole unmanned system is at [ t ] 1 ,t 2 ]The number of systems in possession that are available.
The remaining entries are all 0, indicating that there is no such state transition.
When the original state in the system is s epsilon B and s not equal to k, if the single unmanned system i is in [ t ] 1 ,t 2 ]When the internal is continuously in the available state, after the internal is added into the system, the system state becomes s+1, and the state transition probability is R i [t 1 ,t 2 ]The method comprises the steps of carrying out a first treatment on the surface of the If a single unmanned system i is at t 1 ,t 2 ]If the internal state fails to be continuously in the available state, the system state after the addition is still s, and the state transition probability is 1-R i [t 1 ,t 2 ]。
When the original state s e B in the system is s=k, then no matter the single unmanned system i is at [ t ] 1 ,t 2 ]Whether the internal is continuously in a usable state or not, the system state is still k after the internal is added, namely the state transition probability is 1.
S53, u state transition probability matrixes P obtained by system cluster heads i The availability of the system interval is obtained according to the formula (5):
wherein: pi= [1,0, …,0] 1×(k+1) Representing the state of the markov chain { M (j), j=1, 2, …, u } in the initial condition as b= {0};
is used to limit the number of available systems in the systemThe probabilities of k or more are summed, and the interval availability is converted into digital form by pi and U.
S6, the cluster head of the unmanned system obtains the availability A t of the system interval of the system according to the obtained body 1 ,t 2 ]And the number u of available systems remaining in the hierarchy to decide the hierarchy is to continue executing/canceling tasks.
S61, when the availability of system interval A [ t ] 1 ,t 2 ]When σ is not less than and the number of available systems remaining in the system u is not less than k, the system continues to perform tasks, where σ represents a given threshold.
S62, except for the case of the step S61, the system cancels the task.
For a better understanding of the technical solution of the present invention, the following exemplary embodiments will describe the detailed description of the present invention in further detail. The case is illustrated as follows: a drone swarm system consists of n=33 drones, each carrying the same equivalent of weapon load, assuming that at least k=21 drones successfully release the weapon load to be considered as effectively damaging the target, i.e. the task is successful. The time length of the task of the bee colony fight is t 2 =80 (min), unmanned aerial vehicle is flying about t 1 After=55 (min), the striking distance is entered. Since each device, module of the drone may be put into an unavailable state (or restored to an available state) due to a failure (or restoration) during performance of the task, the solution is: (1) the availability level of the unmanned bee colony battle system in the whole task period is calculated by A0,80]The method comprises the steps of carrying out a first treatment on the surface of the (2) What the level of availability after entering the strike distance is, i.e. A [55,80]]。
Aiming at the above cases, the specific steps for evaluating the availability of the system interval by applying the method provided by the invention are as follows:
s1, defining a system state of a single unmanned aerial vehicle. In the unmanned plane swarm operation, the equipment such as a power device h, a detection module c, a task module w and the like is required to be focused, wherein if the equipment is available, the corresponding symbol is 1; otherwise, it is noted as "0". The unmanned system state can be defined as:
In summary, the set of available states of a single unmanned aerial vehicle is w= { s 1 ,s 3 The unavailable state set is f= { s } 2 ,s 4 ,s 5 }。
S2, analyzing a system state transition rule. Assume that: (1) the power device has no recovery mechanism, and the unmanned aerial vehicle loses the flying ability when the unmanned aerial vehicle fails; (2)
the detection module has no recovery mechanism, and the unmanned aerial vehicle is converted into a following mode when a fault occurs; (3) the task module has a recovery mechanism, and no one is in fault
The machine may restart the task software. Therefore, the state transition rule of the unmanned aerial vehicle is analyzed as follows:
s 1 →s 2 representing power plant failure, if the power plant tie fault interval is
The transfer rate is->
s 1 →s 3 Indicating a fault of the detection module, if the tie fault interval time of the detection module is
The transfer rate is->
s 1 →s 4 Representing the fault of the task module, if the tie fault interval time of the task module is
The transfer rate is->
s 3 →s 2 Indicating a power plant failure, the transfer rate is
s 3 →s 5 Indicating that the task module is faulty, so the transfer rate is
s 4 →s 1 Indicating that the task module resumes working, if the average restart time of the task module is
The transfer rate is->
s 4 →s 2 Indicating a power plant failure, the transfer rate is
s 4 →s 5 Indicating a fault in the detection module, so the transfer rate is
s 5 →s 3 Indicating that the task module resumes operation, the transition rate is
In summary, the state transition matrix of the single unmanned aerial vehicle can be obtained as follows:
and has the following steps:
s3, determining a systematic task success criterion. Assume in this example that two criteria are of interest: (1) throughout the duty cycle [0,80], there is at least k=21
The unmanned aerial vehicle is continuously kept in an available state set W= { s 1 ,s 3 Inner part; (2) after entering the striking range, i.e. duty cycle [55,80]In at least
There are k=21 drones continuously kept in the set of available states w= { s 1 ,s 3 And within. Aiming at the task success criteria, the system interval availability A [0,80] is respectively evaluated]And A [55,80]]. If the two indexes reach the expected value of 95%, determining at least how many unmanned aerial vehicles are put into the unmanned aerial vehicle to execute the task.
S4, modeling the availability of a single system interval. In order to calculate the section availability of the system, the section availability of a single drone needs to be calculated first. In this example, it is assumed that all unmanned aerial vehicles are in state s at the initial time 1 。
R i [0,80]The calculation model is as follows:
R i [55,80]the calculation model is as follows:
s5, the availability of the system interval is calculated approximately. Using the algorithm flow in fig. 2, it is possible to obtain:
then, according to formulas (7) and (8), the interval availability of the single unmanned aerial vehicle can be obtained as follows:
R i [0,80]＝0.6527
R i [55,80]＝0.7257
s6, evaluating the availability of the system interval. According to the formula (5), an evaluation result of the availability of the system interval can be obtained:
from the above calculations, it can be seen that the probability level of the unmanned combat system continuously maintaining the task completion capacity during the full task period [0,80] is low, only 65.36%, and A55, 80 is also up to 95% of the expected value. If the index evaluation result is to be improved, a feasible improvement scheme can be analyzed by increasing the total number n of unmanned aerial vehicles input, wherein A0,80 is more than or equal to 95% as target constraint.
When the number n of unmanned aerial vehicles is increased, it can be seen from fig. 3: when the number of unmanned aerial vehicles put into the system is n=35, the method satisfies A55, 80 >95%; when the number of unmanned aerial vehicles put into the system reaches n=40, A [0,80] >95% is satisfied. Therefore, at least 40 unmanned aerial vehicles are required to be put into the unmanned aerial vehicle to meet the task requirements.
The above examples are only illustrative of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention, and various modifications and improvements made by those skilled in the art to the technical solution of the present invention should fall within the scope of protection defined by the claims of the present invention without departing from the spirit of the present invention.
Claims (6)
1. A system interval availability determination method for characterizing task sustainability in an unmanned system, comprising the steps of:
s1, a single unmanned system judges whether the single unmanned system is in an available state or not through sensing the state of a functional module; dividing a single unmanned system into m statesS＝{s 1 ,s 2 ,…,s m -wherein the status of availability of the unmanned system is denoted w= { s 1 ,s 2 ,…,s l ' state indicating unavailability of unmanned system is denoted as f= { s l+1 ,s l+2 ,…,s m -S = W & -F;
s2, defining a state transition rule of a single unmanned system into a calculation module thereof, so as to calculate interval availability R of each unmanned system i [t 1 ,t 2 ]Providing an input;
s21, obtaining the average time of the unmanned system from the state c to the state j through the statistical test data and the simulation data
And use +.>
To characterize the state transition law of the single unmanned system;
s22, obtaining a state transition rate matrix Q= [ Q ] of the single unmanned system cj ] n×n And defined in the computing modules of each unmanned system, wherein: when c is not equal to j, let
When c=j, let q cc ＝-∑ c≠j q cj ；
S3, calculating the interval availability R of the single unmanned system i based on the internally defined state transition rate matrix i [t 1 ,t 2 ]I.e. a single unmanned system i is within a time range t 1 ,t 2 ]Probability of continuously maintaining the available state;
s31, when t 1 When=0, the section availability R of the unmanned system i i [0,t 2 ]Calculated by the following formula:
wherein, gamma i ＝[p 1 ,p 2 ,…,p n ]Representing the initial state probability of the unmanned system i and satisfying Σ c p c =1; if the system is in state s at the initial time r Then there is
Wherein I is |w|×|w| Representing a unit array of dimensions |w|×|w| and 0 |F|×|w| Then a zero matrix of dimension |f|×|w| is represented, with |w| and |f| representing the number of available and unavailable states, respectively, of unmanned system i; q (Q) WW Is a matrix formed by elements determined by the intersection of the rows and columns of the available state coordinates in the transfer rate matrix Q; 1 |W|×1 Representing that none of the elements is "1" and the dimension is |W|×1 column vector;
s32, when t 1 When not equal to 0, the interval availability R of the unmanned system i i [t 1 ,t 2 ]Calculated by the following formula:
s33, solving the formulas (1) and (2) in the step S31 and the step S32 by using a matrix index algorithm by using a single unmanned system
And +.>
The numerical result of the item is further obtained to obtain the interval availability R of each unmanned system i [t 1 ,t 2 ]；
S4, the single unmanned system calculates the availability R of the system interval i [t 1 ,t 2 ]Reporting to the cluster head of the unmanned system to obtain the rest available unmanned in the current systemThe system quantity u and the corresponding number thereof, wherein u is { k, k+1, …, n };
s5, the unmanned system cluster head utilizes the system interval availability parameter R reported by each unmanned system according to the system task success criterion i [t 1 ,t 2 ]Obtaining the availability A t of system interval 1 ,t 2 ]；
S51, defining a systematic task success criterion; over a period of time t 1 ,t 2 ]In the system formed by n unmanned systems, if the number of the systems in the available state in the system is always at least k, the system task is considered to be successful;
s52, a calculation module of the system cluster head utilizes the system interval availability parameter R reported by each unmanned system i [t 1 ,t 2 ]Generating u state transition probability matrixes P i Evaluating the availability of the system interval by using a finite Markov chain embedding method; by defining a finite state Markov chain { M (j), j=1, 2, …, u }, the state space of which is denoted as B= {0,1, …, k }, after characterizing the addition of the unmanned system to the system, the whole unmanned system is at [ t ] 1 ,t 2 ]The number of systems in available state owned internally;
the remaining entries are all 0, indicating that no such state transition exists;
s53, u state transition probability matrixes P obtained by system cluster heads i The availability of the system interval is obtained according to the formula (5):
wherein: pi= [1,0, …,0] 1×(k+1) Representing the state of the markov chain { M (j), j=1, 2, …, u } in the initial condition as b= {0};
the method is used for summing the probabilities that the number of the available systems in the system is greater than or equal to k, and converting the interval availability into a digital form through pi and U;
s6, the cluster head of the unmanned system obtains the availability A t of the system interval of the system according to the obtained body 1 ,t 2 ]And the number u of available systems remaining in the system to decide whether the system is to continue executing/canceling tasks;
s61, when the availability of system interval A [ t ] 1 ,t 2 ]When σ is not less than and the number of available systems remaining in the system u is not less than k, the system continues to perform tasks, where σ represents a given threshold.
S62, except for the case of the step S61, the system cancels the task.
2. The method for determining availability of a system interval representing task sustainability in an unmanned system according to claim 1, wherein the system is an ensemble of n identical, heterogeneous individual systems, and the status of each system is divided into a plurality of levels to represent the availability of the individual system, and the system's ability to execute tasks is characterized by a time span [ t ] 1 ,t 2 ]The number of systems in a usable state.
3. The method for determining availability of a system interval indicating task sustainability in an unmanned system according to claim 1, wherein the number of states of the single system, the division of available/unavailable states in step S1, includes the same case and the different case.
4. The method for determining availability of a system interval indicating task sustainability in an unmanned system according to claim 1, wherein the state transition rule of the single system in step S2 includes the same situation and the different situation.
5. The method for determining availability of a system interval indicating task sustainability in an unmanned system according to claim 1, wherein in the system in step S5, the original state is S e B ands not equal to k, if the single unmanned system i is at [ t ] 1 ,t 2 ]When the internal is continuously in the available state, after the internal is added into the system, the system state becomes s+1, and the state transition probability is R i [t 1 ,t 2 ]The method comprises the steps of carrying out a first treatment on the surface of the If a single unmanned system i is at t 1 ,t 2 ]If the internal failure is continuously in the unavailable state, the system state after the addition is still s, and the state transition probability is 1-R i [t 1 ,t 2 ]。
6. The method for determining availability of a system interval indicating task sustainability in an unmanned system according to claim 1, wherein when the initial state S e B and s=k in the system in step S5, no matter the individual unmanned system i is at [ t ] 1 ,t 2 ]Whether the internal is continuously in a usable state or not, the system state is still k after the internal is added, namely the state transition probability is 1.
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