CN116430736A - Multi-agent autonomous cooperative allocation method for aerospace measurement and control - Google Patents
Multi-agent autonomous cooperative allocation method for aerospace measurement and control Download PDFInfo
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Abstract
The application relates to a multi-agent autonomous cooperative allocation method for spaceflight measurement and control. The method comprises the following steps: constructing a mixed integer nonlinear optimization model and designing a description information tuple of the measurement and control network equipment, and carrying out self-adaptive grouping on the measurement and control network equipment represented by the description information tuple by utilizing a data-driven grouping strategy to form a distributed multi-agent system with a coordination center; performing online real-time distribution of large-scale star measurement and control event streams in a multi-agent system, and performing conflict-free arrangement on measurement and control event sets borne by each agent to obtain conflict-free measurement and control event execution sequences on all devices; and designing an event state driven measurement and control equipment state autonomous updating mode and a data distillation calculation mode to update the equipment state and the state of an affiliated intelligent agent in real time so as to complete the online real-time autonomous allocation of the aerospace measurement and control task. The method can improve the online real-time guarantee efficiency of the large-scale star group measurement and control event.
Description
Technical Field
The application relates to the technical field of spacecraft measurement and control, in particular to a multi-agent autonomous collaborative allocation method for aerospace measurement and control.
Background
Aiming at the new characteristics of strong dynamic property, high timeliness, sufficient relevance, large batch property and the like of the future large-scale star group measurement and control requirements, the current heuristic scheduling method based on sequential decision and dynamic segmentation of the star-to-ground visible forecast period is difficult to cope with the new challenges of autonomous, efficient, reliable, real-time online operation and the like of the future large-scale star group management and control on the space measurement and control. In addition, for the equipment in the aerospace measurement and control field, the equipment capability deployed at different positions is heterogeneous, and how to efficiently and comprehensively schedule a large number of heterogeneous measurement and control equipment in multiple types so as to maximize the utilization efficiency and the exerted effectiveness of the aerospace measurement and control equipment is also a new situation for aerospace measurement and control task allocation in a large-scale star group management and control scene.
Disclosure of Invention
Based on the above, it is necessary to provide a multi-agent autonomous collaborative allocation method for aerospace measurement and control, which has good expandability, high reliability, strong adaptability to dynamic events and high on-line operation timeliness.
A multi-agent autonomous collaborative deployment method for aerospace measurement and control, the method comprising:
acquiring measurement and control requirements of a future large-scale star group; analyzing relevant elements existing in space measurement and control task allocation according to measurement and control requirements; the related elements comprise decision variables, constraint conditions and objective functions; constraint conditions comprise satellite-ground visibility constraint, completion period constraint of a satellite group measurement and control event, static non-association constraint of a single measurement and control event and association constraint between events;
Constructing a mixed integer nonlinear optimization model by utilizing decision variables, static non-association constraints of single measurement and control events, association constraints among the events and objective functions, designing description information tuples of measurement and control network equipment with heterogeneous multi-type capacity on the basis of the mixed integer nonlinear optimization model, and carrying out self-adaptive grouping on the measurement and control network equipment represented by the description information tuples by utilizing a data-driven grouping strategy, wherein each grouping forms an agent, and a distributed multi-agent system with a coordination center is formed;
in a distributed multi-agent system, carrying out online real-time distribution on a large-scale star measurement and control event stream according to supportable relation of an agent under jurisdiction equipment to a star satellite and maximum guarantee capacity of each agent by adopting a multi-agent cooperative distribution flow based on a concurrency mechanism to obtain a measurement and control event set shared by each agent;
according to satellite-ground visibility constraint, completion period constraint of a satellite group measurement and control event, static non-association constraint of a single measurement and control event, association constraint among events and event dynamic adjustment strategy with slidable event time window, carrying out event conflict-free arrangement on measurement and control event sets shared by each intelligent agent, and obtaining a measurement and control event execution sequence meeting various constraint conditions on each device;
The state autonomous updating mode of the measurement and control equipment driven by the event state, the data distillation calculation mode and the state of the measurement and control event execution sequence on each equipment are designed to update the state of the equipment and the state of the intelligent agent in real time so as to ensure that the autonomous allocation of the large-scale star group measurement and control events is carried out on line in real time.
In one embodiment, after the autonomous cooperative allocation of the multiple intelligent agents of the measurement and control task of each round of the star group measurement and control event stream is completed, a measurement and control task guarantee efficiency evaluation index is constructed to complete the whole-flow closed-loop evaluation, and a conflict resolution scheme is recommended to a star group user side for auxiliary decision by adopting an autonomous conflict resolution approach based on a knowledge graph for unscheduled events which still exist due to conflict of measurement and control time windows after the completion of one round of allocation.
In one embodiment, the objective function is
wherein ,
indicate->
Whether or not an event is successfully scheduled, if the decision variable +.>
Then->
The method comprises the steps of carrying out a first treatment on the surface of the Otherwise
；/>
Indicate->
The priority of each measurement and control event indicates the criticality of an event, which takes on the value +.>
1 is the most critical level of the event, +.>
Being the least critical level of an event，/>
And the number of measurement and control events is represented.
In one embodiment, the decision variables of the mixed integer nonlinear optimization model include a discrete variable that first selects for which event to execute on which device and a continuous variable that after the selected device the event selects at which time in the timeline to begin execution.
In one embodiment, the descriptive information tuples consist of numbers, names, source codes, deployment locations, supporting carrier bands, and supporting task types.
In one embodiment, the measurement and control network devices represented by the descriptive information tuples are adaptively grouped by using a data-driven grouping strategy, each grouping forming an agent, forming a distributed multi-agent system with a coordination center, comprising:
self-adaptive grouping is carried out on measurement and control network equipment represented by a description information tuple by utilizing a data-driven grouping strategy, equipment supporting different task types is organized into a group, and when various factors cause unbalanced task loads among the groups, some equipment under the jurisdiction of the low-load group is dynamically transferred to the high-load group;
and each group is regarded as an agent, and each agent manages own measurement and control equipment and is used as a coordination center of the group to carry out communication interaction with other agents, and the whole measurement and control network equipment forms a distributed multi-agent system with the coordination center.
In one embodiment, the concurrency mechanism-based multi-agent collaborative distribution flow includes defining a benchmark revenue book of concurrency events broadcast by the master agent as an event list, and each element in the list can be described as a 5-tuple 
, wherein ：/>
For event number, ++>
For event priority, ++>
Duration required for event, +.>
Measurement and control equipment set supportable for satellite to which event belongs, < ->
A value for event benefit; the exchange book formulated by the auction agent is defined as a 3-tuple +.>
, wherein ,/>
Numbering bid agent->
Event number set for application exchange, +.>
For the event number set of the application exchange +.>
and />
The number of elements in the two sets needs to be kept equal; the buying and selling books made by the auction agent are defined as an event list, each element in the list can be described as a 3-tuple +.>
Wherein the meaning of each element in the tuple is consistent with the meaning of the corresponding element of the tuple in the reference revenue book; when the main control agent evaluates the auction books, the exchange books are preferentially considered, and the rest non-exchanged events are given to the agent with the biggest profit value according to the buying and selling books sent by each auction agent.
In one embodiment, according to a star-to-ground visibility constraint, a completion period constraint of a star group measurement and control event, a static non-association constraint of a single measurement and control event, an association constraint between events and an event dynamic adjustment policy that an event time window is slidable, performing event conflict-free arrangement on a measurement and control event set shared by each agent to obtain a measurement and control event execution sequence satisfying various constraint conditions on each device, the method comprises the following steps:
Based on the event dynamic adjustment strategy with the slidable event time window as a priority rule, sequentially searching candidate measurement and control equipment for the events subjected to priority sorting according to the priority rule, and continuously dynamically inserting new events on the time line of the candidate measurement and control equipment until a conflict-free arrangement scheme is generated on the premise of meeting the satellite-to-ground visibility constraint, the completion period constraint of the satellite group measurement and control events and the association constraint among the events; the priority rules comprise a first priority rule and a second priority rule; the first priority rule is to arrange measurement and control events on equipment executed by the events belonging to the same satellite, and connect the measurement and control events end to end under the condition that the legal execution time periods of the events are met; the second priority rule is that each measurement and control event distributed on the same device is arranged on the available time period of the device as early as possible in the legal execution time period.
In one embodiment, the autonomous update mode of the event state driven measurement and control equipment state is that a trigger threshold of a measurement and control event state relative to the current moment is set, and the event is automatically switched among four states of an ungraded state, an arrangement state, a locking state and an execution state according to the trigger threshold in the event execution process based on a time line; when the event is in an execution state or a locking state, the time window resources occupied by the event on the measurement and control equipment are in an exclusive state, and the event is not available to other events; when the events are in an arrangement state, the time window resources occupied by the events on the measurement and control equipment are in a non-exclusive state, and other events can be preempted for use according to the priority; when the event is in an unsegmented state, the event does not occupy time window resources on any measurement and control equipment, and the event is indicated to be in a state to be arranged.
In one embodiment, the data distillation calculation is
wherein ,
and />
Respectively represent +.>
The +.>
The remaining guaranteed time length and the duration of the event undertaken for the individual measurement and control devices,/->
Indicate->
The individual agents are administered +.>
And a set of measurement and control devices.
According to the multi-agent autonomous cooperative allocation method for aerospace measurement and control, aiming at future large-scale star group measurement and control demands, after a mixed integer nonlinear optimization model is constructed, the preset aerospace measurement and control network equipment with heterogeneous capacities are dynamically grouped by adopting a data-driven self-adaptive grouping strategy, so that a distributed multi-agent system with a coordination center is formed. On the basis, the multi-agent collaborative online real-time distribution based on a concurrency mechanism of the large-scale star group measurement and control event stream is firstly carried out, so that the communication negotiation frequency in a multi-agent system can be effectively reduced, the multi-agent collaborative efficiency is improved, and then the measurement and control event based on time window sliding is dynamically regulated on each agent in parallel so as to obtain the measurement and control event execution sequence on each device meeting each constraint condition; as a connecting bridge of the two stages, the autonomous updating of the state of the measurement and control equipment is used for realizing the real-time updating of the state of the equipment driven by the event state and the state of the intelligent agent, so as to ensure the timeliness of the multi-intelligent system for completing the autonomous allocation of the aerospace measurement and control task; the new scheme gives consideration to optimality and timeliness required by future large-scale star measurement and control on the support of the aerospace measurement and control task, and has the advantages of correct and reasonable generation method, rapid and effective calculation process, good applicability to actual engineering tasks, high reliability, strong expandability and the like.
Drawings
FIG. 1 is a flow chart of a multi-agent autonomous collaborative deployment method for aerospace measurement and control in one embodiment;
FIG. 2 is a schematic diagram of a multi-agent system in one embodiment;
FIG. 3 is a flow chart of multi-agent collaborative distribution based on concurrency mechanisms in one embodiment;
FIG. 4 is a flow chart of an event dynamic adjustment strategy based on event time window slidability in another embodiment;
FIG. 5 is a schematic diagram of an event state driven autonomic update pattern of a measurement and control device state in one embodiment;
FIG. 6 is a schematic diagram of a current capability matrix of a smart agent in one embodiment;
FIG. 7 is a schematic diagram of a knowledge graph representing measurement and control equipment entities and event entities and relationships therebetween, in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying 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 present application.
In one embodiment, as shown in fig. 1, a multi-agent autonomous collaborative deployment method for aerospace measurement and control is provided, which includes the following steps:
102, acquiring measurement and control requirements of a large-scale star group in the future; analyzing relevant elements existing in space measurement and control task allocation according to measurement and control requirements; the related elements comprise decision variables, constraint conditions and objective functions; constraints include a star-to-ground visibility constraint, a completion period constraint for a star cluster measurement and control event, a static non-associated constraint for a single measurement and control event, and an associated constraint from event to event.
The measurement and control requirements of the future large-scale star group comprise the star group, measurement and control equipment, visibility prediction of satellites and equipment and the star group measurement and control requirements. Analyzing relevant elements existing in space measurement and control task allocation according to measurement and control requirements, and measuring and controlling the first element in event stream for large-scale star group
For each measurement and control event, the decision variable is +.>
Represents->
The event is at->
The starting execution time on the measurement and control equipment which can be supported by the functions. If->
The event is not selected at +.>
Executing on the measurement and control device, determining the variable +.>
The method comprises the steps of carrying out a first treatment on the surface of the Otherwise, go (L)>
Indicate->
The event is selected at->
Executing on the measurement and control devices, and determining the starting execution time as +.>
. For a measurement and control event stream at a certain moment, it is assumed that there is a common +.>
Measurement and control event(s)>
When the measurement and control equipment is used, the decision variable set is as follows:
After the decision variable is determined, the constraint observed by the decision variable in the optimization process needs to be analyzed, and certain constraint is generated on the decision variable by all factors according to visibility prediction of the constellation, measurement and control equipment, satellites and equipment and the constellation measurement and control requirement. These constraints include both static, unassociated constraints for a single measurement and control event, and associated constraints from event to event.
Further, the static non-associated constraints are mainly of the following four types:
in the formula ,
indicate->
Whether or not the event is selected at +.>
Discrete decision variables to be executed on the individual measurement and control devices, if continuous decision variables +.>
Then->
The method comprises the steps of carrying out a first treatment on the surface of the Otherwise->
。/>
and />
Respectively represent +.>
The satellite to which the event belongs is at->
Starting time and ending time of visibility forecast on each measurement and control device; />
Is->
The duration required for each event;
and />
Respectively represent +.>
The earliest starting time and the latest ending time of the time period required by each event; />
Is when->
Event and->
When the satellite to which the event belongs is different, the>
The measurement and control service of the personal equipment is performed by the +.>
Satellite steering to which event belongs->
The antenna steering time length of the satellite to which the event belongs, which is equal to +.>
Release duration and +. >
The sum of the preparation durations of the individual events.
Wherein the constraint represented by the formula (2) is that the satellite to which each event belongs has supportability requirements such as frequency band and function on the measurement and control equipment, for example, the first
The supportable device of the satellite to which the event belongs is +.>
Sleeve (I)>
) The method comprises the steps of carrying out a first treatment on the surface of the And secondly, each event can be successfully executed for 1 time at most on the supportable measurement and control equipment. The constraint represented by equation (3) indicates that each event is visibility-constrained on its supportable measurement and control device. The constraint represented by equation (4) indicates that each event has its own completion period constraint. The constraint expressed by the formula (5) indicates that on any measurement and control device, two adjacent events cannot intersect when arranged on a time line; if two adjacent events belong to the same satellite, the switching time is +.>
Is 0.
In addition, the association constraints between events are mainly of the following two types:
in the formula ,
is when->
Event and->
When the association constraint exists among the events, the interval time of the two events;
is composed of->
And a measurement and control event set formed by events with association constraint.
Wherein the constraint represented by equation (6) indicates that both events have sequential logic requirements or time interval requirements on the timeline when 
The two events are indicated to have time interval requirements with stronger constraint force; when->
The two events are only required to finish time sequence, and no time interval is required; the constraint represented by formula (7) indicates that the formula is expressed by +.>
Event postAt least the association event set is completed>
This is a non-limiting association constraint consisting of the number of event completions.
After the measurement and control event is selected to be executed on which equipment and the starting time of the execution is decided to be used as the decision variable of the autonomous allocation problem of the space measurement and control task, the solution of the autonomous allocation problem of the space measurement and control task is converted into a set of decision variablesXAnd (3) selecting a group of decision variables which meet all constraint conditions in formulas (2) - (7) and can optimize the objective function value. Wherein, for the key measurement and control event with high priority, the optimization target is to ensure 100% successful arrangement; for the rest of the events, the optimization goal is to schedule as much success as possible. Thus, the optimization objective is expressed as:
in the formula ,
indicate->
Whether or not an event is successfully scheduled, if the decision variable +.>
Then->
The method comprises the steps of carrying out a first treatment on the surface of the Otherwise
。/>
Indicate->
Priority of each measurement and control event, indicating the key degree of an event, which takes on the value of 
1 is the most critical level of the event, +.>
Is the least critical level of the event.
And 104, constructing a mixed integer nonlinear optimization model by utilizing decision variables, static non-associated constraints of single measurement and control events, associated constraints among the events and objective functions, designing description information tuples of measurement and control network equipment with heterogeneous multi-type capacity on the basis of the mixed integer nonlinear optimization model, and carrying out self-adaptive grouping on the measurement and control network equipment represented by the description information tuples by utilizing a data-driven grouping strategy, wherein each grouping forms an agent, and a distributed multi-agent system with a coordination center is formed.
Designing a description information tuple of the measurement and control equipment with heterogeneous multi-type capability based on a mixed integer nonlinear optimization model, wherein the description information tuple of the measurement and control equipment is 6-tuple of the description information of the measurement and control equipment
Is expressed as follows:
in the formula ,
is the number of the measurement and control equipment,/->
Is the name->
Is the source code of the source,
is the deployment location->
Is a supporting carrier band, ">
Is a support task type.
The self-adaptive dynamic grouping strategy is to carry out self-adaptive grouping according to the description information 6-tuple data of each measurement and control device, and compile devices supporting different task types into a group, so that the task guarantee capability of each grouping is approximately equivalent, the comprehensive capability of the managed devices in each grouping is ensured to be balanced as much as possible, for example, devices only supporting a single telemetry downlink task, devices only supporting a single remote uplink task, comprehensive devices supported by the uplink and downlink tasks and the like exist in each grouping; in addition, the dynamic property of the self-adaptive dynamic grouping strategy under the data driving is also reflected in that when various factors such as equipment faults and the like cause unbalanced task loads among the groups, some equipment under the control of the groups with low loads can be dynamically transferred to the groups with high loads, and the grouping load balancing effect in the system operation process is realized.
Therefore, each group can be regarded as an agent, each agent manages its own measurement and control equipment and acts as a coordination center of the group to perform communication interaction with other agents, so that the whole measurement and control network equipment forms a distributed multi-agent system with a coordination center, as shown in fig. 2, the multi-agent system comprises but not limited to three agents shown in fig. 2, each agent manages its own multiple equipment and acts as a coordination center of the group to perform communication interaction with other agents, so that the whole measurement and control network equipment forms a distributed multi-agent system with a coordination center.
And 106, carrying out online real-time distribution on the large-scale star measurement and control event stream by adopting a multi-agent cooperative distribution flow based on a concurrency mechanism according to the supportable relation of the device under the jurisdiction of the agents to the star satellite and the maximum guarantee capability of each agent in the distributed multi-agent system to obtain a measurement and control event set shared by each agent.
In the multi-agent cooperative allocation flow based on the concurrency mechanism, the first agent pair is that of the second agent pair
Benefit value ∈of individual event>
The calculation formula of (2) is as follows:
in the formula ,
and />
Respectively represent +.>
The individual agents are administered +. >
A set of measurement and control devices and a pair +.>
The satellite to which the event belongs is supportable +.>
A set of devices; />
and />
and />
Respectively represent +.>
The +.>
The remaining guaranteed duration and the duration of the born event of the measurement and control equipment and the duration of the rolling period of the multi-intelligent system based on the time line operation.
As can be seen from equation (10), for a measurement and control event, the greater the average remaining duration of an agent for its supported devices, the smaller the sum of the duration of the events that have been undertaken and the greater the number of devices under the jurisdiction of the agent, the higher the calculated benefit value of the event, i.e. the easier it is to obtain ownership of the event. This also shows that in the multi-agent cooperative distribution based on the concurrency mechanism, the supportable capability of the measurement and control equipment under the jurisdiction of the agents to the satellite, the maximum guarantee capability of each agent and the load balance of the events borne by the agents are comprehensively considered.
In the multi-agent collaborative distribution flow based on concurrency mechanism shown in fig. 3, a reference revenue book of concurrency events broadcast by a master agent is defined as an event list, and each element in the list can be described as a 5-tuple 
, wherein ：/>
For event number, ++>
For event priority, ++>
Duration required for event, +.>
Measurement and control equipment set supportable for satellite to which event belongs, < ->
A value for event benefit; the exchange book formulated by the auction agent is defined as a 3-tuple +.>
, wherein ：/>
Numbering bid agent->
Event number set for application exchange, +.>
For the event number set of the application exchange +.>
and />
The number of elements in the two sets needs to be kept equal; the buying and selling books made by the auction agent are defined as an event list, each element in the list can be described as a 3-tuple +.>
Wherein the meaning of each element in the tuple is consistent with the meaning of the corresponding element of the tuple in the reference revenue book. In addition, when the main control agent evaluates the auction books, the exchange books are preferentially considered, and the remaining non-exchanged events are given to the agent with the biggest profit value according to the buying and selling books sent by each auction agent. This also indicates that for concurrent events, the exchange book and the buy-sell book will achieve a collision-free match, i.e. in the final matched auction book, the aggregate set of both the application-in event set in the exchange book and the buy-in event set in the buy-sell book is exactly the concurrent event set.
The multi-agent cooperative allocation flow based on the concurrency mechanism can effectively reduce the communication negotiation frequency in the multi-agent system, and is beneficial to improving the multi-agent cooperative efficiency. The concurrency mechanism is mainly embodied in two aspects, namely, an agent with the strongest remaining guarantee capacity is used as a main control agent, and a reference profit book of the concurrency event is manufactured by taking the calculated event profit value as a reference, so that high-quality auction agents are screened out; and secondly, a mechanism that a plurality of events can be simultaneously auctioned is introduced, so that multi-round collaborative allocation required by the plurality of events is changed into one round.
And step 108, carrying out event conflict-free arrangement on the measurement and control event set shared by each agent according to satellite-ground visibility constraint, completion period constraint of the satellite group measurement and control event, static non-association constraint of single measurement and control event, association constraint among events and event dynamic adjustment strategy with slidable event time window, so as to obtain a measurement and control event execution sequence meeting various constraint conditions on each device.
For each agent, taking into account the satellite-to-ground visibility constraint, the completion period constraint of the constellation measurement and control event, the static non-association constraint of a single measurement and control event and the association constraint between events, the conflict-free arrangement of the undertaken events is completed by utilizing an event dynamic adjustment strategy based on the sliding of an event time window. The association constraint between the events in the star cluster measurement and control event stream mainly comprises two types, wherein one type is a time sequence logic constraint or a time interval constraint of event execution; another category is a non-limiting constraint consisting of the number of completions in the set of associated events, e.g. by 
At least complete +.>
Individual, wherein->
. The main idea of the event dynamic adjustment strategy based on the sliding of the event time window is to design a priority rule according to the problem model constructed in the step 102, search candidate measurement and control equipment for the events after priority ordering in sequence based on the priority rule, and continuously dynamically insert new events on the time line of the equipment until a conflict-free arrangement scheme is generated on the premise of meeting various constraints. FIG. 4 shows a process of event dynamic adjustment strategy based on event time window sliding, which comprises several key steps of initial setting, searching based on priority rules, constraint judgment, neighborhood operation and termination condition judgment.
(1) Initial setup
Establishing a device execution time line based on the current moment and the rolling period, reading preset occupied time period information of each device, and taking a complement on the time line to obtain an available time period set of each device; intersection is taken of the satellite-to-ground visibility constraint and the completion period constraint of the event to obtain a legal execution period set of each event.
(2) Priority rule based search
The first priority rule is to arrange measurement and control events on equipment executed by the events belonging to the same satellite preferentially, and connect the measurement and control events end to end as far as possible under the condition that the legal execution time periods of the events are met; the purpose of this priority rule is to avoid the situation that the measurement and control device wastes time because it needs to turn the antenna when tracking different satellites twice in succession. The second priority rule is that each measurement and control event allocated on the same device should be arranged on the available period of the device as early as possible in its legal execution period, so as to shorten the completion time span of all events.
(3) Constraint judgment and neighborhood manipulation
After the search based on the priority rule is executed, if the constraint condition is not met, domain sliding operation is needed to be carried out on the execution time line of the equipment in the legal execution time period of the event through the time window of the event so as to meet the association constraint among the events; if all the constraint conditions are met, the field insertion operation is directly executed, and a time window of the event is added to the available time period of the equipment to form a current latest event execution plan.
(4) Termination condition judgment
Judging whether an unordered event exists or not, if not, acquiring a measurement and control event execution sequence meeting various constraints on each device; otherwise, the search, constraint judgment and neighborhood operation based on the priority rule are continuously executed until the termination condition is reached.
In addition, after the dynamic adjustment of events based on the sliding of the time window is completed, the events which violate the association constraint or the events which are not arranged still exist, the events can be fed back to the multi-agent cooperative allocation stage again, and the events are dynamically transferred to other agents by means of the multi-agent autonomous cooperative mechanism to be completed, so that the purpose of constraint repair of the events which violate the association constraint or the purpose of secondary allocation of the events which are not arranged is realized.
As shown in fig. 5, the autonomous update mode of the event state driven measurement and control device state is to set a trigger threshold of the measurement and control event state relative to the current moment, and the event is automatically switched among the four states of the unset state, the arrangement state, the locking state and the execution state according to the trigger threshold in the event execution process based on the time line; when the event is in an execution state or a locking state, the time window resources occupied by the event on the measurement and control equipment are in an exclusive state, and the event is not available to other events; when the events are in an arrangement state, the time window resources occupied by the events on the measurement and control equipment are in a non-exclusive state, and other events can be preempted for use according to the priority; when the event is in an unsegmented state, the event does not occupy time window resources on any measurement and control equipment, and the event is indicated to be in a state to be arranged.
Further, the current capability matrix capable of effectively representing the update of the state of the agent is designed, as shown in fig. 6, there are a plurality of devices, wherein a bold dashed box indicates that the device has assumed the event duration matrix, and a blank solid box indicates the remaining guarantee duration matrix of the device. According to the first 
Data distillation calculation formula of 'many-to-one' mapping from measurement and control equipment state to intelligent body state>
Can be expressed as formula (11), th +.>
Personal agent pair->
Calculation formula of the supportable ability of individual events +.>
Can be expressed as formula (12) as follows:
in addition, an event bearing list of the measurement and control equipment under the jurisdiction of the intelligent agent is constructed, and each element in the list can be described as a 2-tuple
, wherein ：/>
Is the device number>
Is the set of numbers of events undertaken by the device during the current scroll cycle. Therefore, the intelligent agent can perform reverse reasoning according to the constructed event bearing list, and measurement and control events influenced by the running state of the equipment can be timely obtained, so that the follow-up multi-intelligent agent system can transfer the influenced events to other supportable intelligent agent-administered equipment for execution, and the aerospace measurement and control events can be well distributed.
In the multi-agent autonomous cooperative allocation method for aerospace measurement and control, aiming at future large-scale star group measurement and control requirements, after a mixed integer nonlinear optimization model is constructed, the preset aerospace measurement and control network equipment with heterogeneous capacity is dynamically grouped by adopting a data-driven self-adaptive grouping strategy, so that a distributed multi-agent system with a coordination center is formed. On the basis, the multi-agent collaborative online real-time distribution based on a concurrency mechanism of the large-scale star group measurement and control event stream is firstly carried out, so that the communication negotiation frequency in a multi-agent system can be effectively reduced, the multi-agent collaborative efficiency is improved, and then the measurement and control event based on time window sliding is dynamically regulated on each agent in parallel so as to obtain the measurement and control event execution sequence on each device meeting each constraint condition; as a connecting bridge of the two stages, the state autonomous updating of the measurement and control equipment is used for realizing the real-time updating of the state of the equipment driven by the event state and the state of the intelligent agent so as to ensure the timeliness of the multi-intelligent-agent system for completing the autonomous guarantee of the aerospace measurement and control task; the new scheme gives consideration to optimality and timeliness required by future large-scale star measurement and control on the support of the aerospace measurement and control task, and has the advantages of correct and reasonable generation method, rapid and effective calculation process, good applicability to actual engineering tasks, high reliability, strong expandability and the like.
In one embodiment, after the autonomous cooperative allocation of the multiple intelligent agents of the measurement and control task of each round of the star group measurement and control event stream is completed, a measurement and control task guarantee efficiency evaluation index is constructed to complete the whole-flow closed-loop evaluation, and a conflict resolution scheme is recommended to a star group user side for auxiliary decision by adopting an autonomous conflict resolution approach based on a knowledge graph for unscheduled events which still exist due to conflict of measurement and control time windows after the completion of one round of allocation.
In a specific embodiment, after the autonomous cooperative allocation of a plurality of agents of the measurement and control task of a round of star group measurement and control event stream is completed, according to the principle of 'full-flow closed loop', a measurement and control task guarantee efficiency evaluation index is constructed to complete full-flow closed loop evaluation, and the evaluation result can promote the transparent presentation of the task situation borne by measurement and control network equipment in the online real-time operation process of the plurality of agent systems; if the event which is not arranged due to the conflict of the measurement and control time window exists, an autonomous conflict resolution approach based on a knowledge graph is further adopted to recommend a conflict resolution scheme to a star group user side, so that the auxiliary decision making effect of 'people on a loop' is achieved.
Further, the measurement and control task guarantee efficiency evaluation index comprises a first step of 
Complete utilization of individual agents +.>
And Idle Rate->
The calculation formulas of the two are as follows:
in the process of generating a conflict resolution scheme, a plurality of events and legal law enforcement periods of the device governed by the events are shown in fig. 7, and a knowledge map capable of effectively characterizing the event conflict relationship is further constructed by carrying out conflict entity labeling on the accumulated conflict resolution experience data, and completing knowledge representation, relationship extraction and knowledge reasoning to form a plurality of triples of data which are mutually associated and are composed of conflict entities and relationships between the conflict entities.
In one embodiment, the objective function is
wherein ,
indicate->
Whether or not an event is successfully scheduled, if the decision variable +.>Then->
The method comprises the steps of carrying out a first treatment on the surface of the Otherwise
；/>
Indicate->
The priority of each measurement and control event indicates the criticality of an event, which takes on the value +.>
1 is the most critical level of the event, +.>
For the least critical class of events, +.>And the number of measurement and control events is represented.
In one embodiment, the decision variables of the mixed integer nonlinear optimization model include a discrete variable that first selects for which event to execute on which device and a continuous variable that after the selected device the event selects at which time in the timeline to begin execution.
In one embodiment, the descriptive information tuples consist of numbers, names, source codes, deployment locations, supporting carrier bands, and supporting task types.
In one embodiment, the measurement and control network devices represented by the descriptive information tuples are adaptively grouped by using a data-driven grouping strategy, each grouping forming an agent, forming a distributed multi-agent system with a coordination center, comprising:
self-adaptive grouping is carried out on measurement and control network equipment represented by a description information tuple by utilizing a data-driven grouping strategy, equipment supporting different task types is organized into a group, and when various factors cause unbalanced task loads among the groups, some equipment under the jurisdiction of the low-load group is dynamically transferred to the high-load group;
and each group is regarded as an agent, and each agent manages own measurement and control equipment and is used as a coordination center of the group to carry out communication interaction with other agents, and the whole measurement and control network equipment forms a distributed multi-agent system with the coordination center.
In one embodiment, the concurrency mechanism-based multi-agent collaborative distribution flow includes defining a benchmark revenue book of concurrency events broadcast by the master agent as an event list, and each element in the list can be described as a 5-tuple 
, wherein ：/>
For event number, ++>
For event priority, ++>
Duration required for event, +.>
Measurement and control equipment set supportable for satellite to which event belongs, < ->
A value for event benefit; the exchange book formulated by the auction agent is defined as a 3-tuple +.>
, wherein ,/>
Numbering bid agent->
Event number set for application exchange, +.>
For the event number set of the application exchange +.>
and />
The number of elements in the two sets needs to be kept equal; the buying and selling books made by the auction agent are defined as an event list, each element in the list can be described as a 3-tuple +.>
Wherein the meaning of each element in the tuple is the corresponding element of the tuple in the reference profit bookThe meaning of the element is consistent; when the main control agent evaluates the auction books, the exchange books are preferentially considered, and the rest non-exchanged events are given to the agent with the biggest profit value according to the buying and selling books sent by each auction agent.
In one embodiment, according to a star-to-ground visibility constraint, a completion period constraint of a star group measurement and control event, a static non-association constraint of a single measurement and control event, an association constraint between events and an event dynamic adjustment policy that an event time window is slidable, performing event conflict-free arrangement on a measurement and control event set shared by each agent to obtain a measurement and control event execution sequence satisfying various constraint conditions on each device, the method comprises the following steps:
Based on the event dynamic adjustment strategy with the slidable event time window as a priority rule, sequentially searching candidate measurement and control equipment for the events subjected to priority sorting according to the priority rule, and continuously dynamically inserting new events on the time line of the candidate measurement and control equipment until a conflict-free arrangement scheme is generated on the premise of meeting the satellite-to-ground visibility constraint, the completion period constraint of the satellite group measurement and control events and the association constraint among the events; the priority rules comprise a first priority rule and a second priority rule; the first priority rule is to arrange measurement and control events on equipment executed by the events belonging to the same satellite, and connect the measurement and control events end to end under the condition that the legal execution time periods of the events are met; the second priority rule is that each measurement and control event distributed on the same device is arranged on the available time period of the device as early as possible in the legal execution time period.
In a specific embodiment, after the dynamic adjustment of the events based on the sliding of the time window is completed on each device so as to form a measurement and control event execution sequence, if the event violates the association constraint in the measurement and control event execution sequence or the event does not appear in the execution sequence, constraint repair can be performed again for the event violated the association constraint in multi-agent cooperative allocation or secondary allocation can be performed for the non-arranged event, so that the 'closed loop optimization' of the autonomous guarantee of the multi-agent of the measurement and control task is realized.
In one embodiment, the autonomous update mode of the event state driven measurement and control equipment state is that a trigger threshold of a measurement and control event state relative to the current moment is set, and the event is automatically switched among four states of an ungraded state, an arrangement state, a locking state and an execution state according to the trigger threshold in the event execution process based on a time line; when the event is in an execution state or a locking state, the time window resources occupied by the event on the measurement and control equipment are in an exclusive state, and the event is not available to other events; when the events are in an arrangement state, the time window resources occupied by the events on the measurement and control equipment are in a non-exclusive state, and other events can be preempted for use according to the priority; when the event is in an unsegmented state, the event does not occupy time window resources on any measurement and control equipment, and the event is indicated to be in a state to be arranged.
In a specific embodiment, as time goes forward, an event in the measurement and control event stream sequentially goes through four states of task ungrounded state, task arrangement state, task locking state and execution state; according to different stages of the event occupying the time window resource of the measurement and control equipment, the state of the measurement and control equipment is divided into an exclusive state and a non-exclusive state, wherein when the event is in a locking state and an execution state, the occupied time window resource of the measurement and control equipment is in the exclusive state, otherwise, the time window resource of the measurement and control equipment is in the non-exclusive state.
When the state autonomous updating mode of the measurement and control equipment driven by the event state is designed, a measurement and control event reverse reasoning process influenced by the real-time running state of the measurement and control equipment is also required to be constructed, the influenced measurement and control events are timely obtained, and the influence events are conveniently self-organized and dynamically transferred to other supportable intelligent agent-administered equipment for execution by a subsequent multi-intelligent agent system.
In one embodiment, the data distillation calculation is
wherein ,
and />
Respectively represent +.>
The +.>
The remaining guaranteed time length and the duration of the event undertaken for the individual measurement and control devices,/->
Indicate->
The individual agents are administered +.>
And a set of measurement and control devices.
It should be understood that, although the steps in the flowchart of fig. 1 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 1 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of other steps or sub-steps of other steps.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. The multi-agent autonomous cooperative allocation method for aerospace measurement and control is characterized by comprising the following steps of:
acquiring measurement and control requirements of a future large-scale star group; analyzing relevant elements existing in space measurement and control task allocation according to the measurement and control requirements; the related elements comprise decision variables, constraint conditions and objective functions; the constraint conditions comprise satellite-ground visibility constraint, completion period constraint of a satellite group measurement and control event, static non-association constraint of a single measurement and control event and association constraint between events;
Constructing a mixed integer nonlinear optimization model by utilizing the decision variables, static non-association constraints of single measurement and control events, association constraints among the events and objective functions, designing description information tuples of measurement and control network equipment with heterogeneous multi-type capacity on the basis of the mixed integer nonlinear optimization model, and carrying out self-adaptive grouping on the measurement and control network equipment represented by the description information tuples by utilizing a data-driven grouping strategy, wherein each grouping forms an agent, so as to form a distributed multi-agent system with a coordination center;
in the distributed multi-agent system, on-line real-time distribution is carried out on a large-scale star measurement and control event stream by adopting a multi-agent cooperative distribution flow based on a concurrency mechanism according to the supportable relation of the device under the jurisdiction of the agents to the star satellite and the maximum guarantee capability of each agent, so as to obtain a measurement and control event set shared by each agent;
according to satellite-ground visibility constraint, completion period constraint of a satellite group measurement and control event, static non-association constraint of a single measurement and control event, association constraint among events and event dynamic adjustment strategy with slidable event time window, carrying out event conflict-free arrangement on a measurement and control event set shared by each intelligent agent to obtain a measurement and control event execution sequence meeting various constraint conditions on each device;
The state autonomous updating mode of the measurement and control equipment driven by the event state, the data distillation calculation mode and the state of the measurement and control event execution sequence on each equipment are designed to update the state of the equipment and the state of the intelligent agent in real time so as to ensure that the autonomous allocation of the large-scale star group measurement and control events is carried out on line in real time.
2. The multi-agent autonomic co-formulation method of claim 1, further comprising:
after the autonomous cooperative allocation of the multiple intelligent agents of the measurement and control tasks of a star group measurement and control event stream is completed, a measurement and control task guarantee efficiency evaluation index is constructed to complete the whole-flow closed-loop evaluation, and a conflict resolution scheme is recommended to a star group user side by adopting an autonomous conflict resolution approach based on a knowledge graph for unscheduled events which still exist due to the conflict of measurement and control time windows after the completion of one round of allocation to carry out auxiliary decision.
3. The multi-agent autonomic co-formulation method as claimed in claim 1, wherein the objective function is
wherein ,
indicate->
Whether or not an event is successfully scheduled, if the decision variable +.>
Then->
The method comprises the steps of carrying out a first treatment on the surface of the Otherwise->
；/>
Indicate->
The priority of each measurement and control event indicates the criticality of an event, which takes on the value +. >
1 is the most critical level of the event, +.>
For the least critical class of events, +.>
And the number of measurement and control events is represented.
4. The multi-agent autonomic co-formulation method of claim 1, wherein the decision variables of the mixed integer nonlinear optimization model include a discrete variable that first selects for which event to execute on which device and a continuous variable that the event selects to begin executing at which time of the timeline after the device is selected.
5. The multi-agent autonomic co-deployment method of any of claims 1 to 4, wherein the descriptive information tuples consist of numbers, names, source codes, deployment locations, support carrier bands, and support task types.
6. The multi-agent autonomous co-deployment method of claim 5, wherein the measurement and control network devices represented by the descriptive information tuples are adaptively grouped using a data-driven grouping strategy, each grouping comprising an agent, forming a distributed multi-agent system with a coordination center, comprising:
self-adaptive grouping is carried out on measurement and control network equipment represented by a description information tuple by utilizing a data-driven grouping strategy, equipment supporting different task types is organized into a group, and when various factors cause unbalanced task loads among the groups, some equipment under the jurisdiction of the low-load group is dynamically transferred to the high-load group;
And regarding each group as an agent, managing the measurement and control equipment of each agent and communicating and interacting with other agents as a coordination center of the group, and forming a distributed multi-agent system with the coordination center by the whole measurement and control network equipment.
7. The multi-agent autonomic co-deployment method of claim 1, wherein the concurrency mechanism-based multi-agent collaborative distribution process includes defining a benchmark revenue book of concurrency events broadcast by the master agent as an event list, each element in the list being describable as a 5-tuple
, wherein ：/>
For event number, ++>
For event priority, ++>
Duration required for event, +.>
Measurement and control equipment set supportable for satellite to which event belongs, < ->
A value for event benefit; the exchange book formulated by the auction agent is defined as a 3-tuple
, wherein ,/>
Numbering bid agent->
For the set of event numbers to apply for swap-in,
for the event number set of the application exchange +.>
and />
The number of elements in the two sets needs to be kept equal; the buying and selling books formulated by the auction agent are defined as an event list, and each element in the list can be described as a 3-tuple 
Wherein the meaning of each element in the tuple is consistent with the meaning of the corresponding element of the tuple in the reference revenue book; when the main control agent evaluates the auction books, the exchange books are preferentially considered, and the rest non-exchanged events are given to the agent with the biggest profit value according to the buying and selling books sent by each auction agent.
8. The multi-agent autonomous collaborative allocation method according to claim 1, wherein the event conflict-free arrangement is performed on the measurement and control event set shared by each agent according to a satellite-to-ground visibility constraint, a completion period constraint of a satellite group measurement and control event, a static non-association constraint of a single measurement and control event, an association constraint between events and an event dynamic adjustment policy that an event time window is slidable, so as to obtain a measurement and control event execution sequence that satisfies various constraint conditions on each device, comprising:
the event dynamic adjustment strategy with the slidable event time window is a priority rule, candidate measurement and control equipment is searched for the events subjected to priority sequencing in sequence according to the priority rule, and new events are continuously and dynamically inserted into the time line of the candidate measurement and control equipment until a conflict-free arrangement scheme is generated on the premise that satellite-to-ground visibility constraint, completion period constraint of satellite group measurement and control events, static non-association constraint of single measurement and control events and association constraint among the events are met; the priority rules comprise a first priority rule and a second priority rule; the first priority rule is to arrange measurement and control events on equipment executed by the events belonging to the same satellite, and connect the measurement and control events end to end under the condition that the legal execution time periods of the events are met; the second priority rule is that each measurement and control event distributed on the same device is arranged on the available time period of the device as early as possible in the legal execution time period.
9. The multi-agent autonomous collaborative allocation method according to claim 1, wherein the event state driven autonomous update mode of the measurement and control device state is a trigger threshold for setting a measurement and control event state relative to a current time, and the event is automatically switched among four states of unset state, arrangement state, locking state and execution state according to the trigger threshold in a time line-based event execution process; when the event is in an execution state or a locking state, the time window resources occupied by the event on the measurement and control equipment are in an exclusive state, and the event is not available to other events; when the events are in an arrangement state, the time window resources occupied by the events on the measurement and control equipment are in a non-exclusive state, and other events can be preempted for use according to the priority; when the event is in an unsegmented state, the event does not occupy time window resources on any measurement and control equipment, and the event is indicated to be in a state to be arranged.
10. The multi-agent autonomic co-formulation method as defined in claim 1, wherein the data distillation calculation formula is
wherein ,
and />
Respectively represent +.>
The +.>
The remaining guaranteed time length and the duration of the event undertaken for the individual measurement and control devices,/->
Indicate- >
The individual agents are administered +.>
And a set of measurement and control devices.
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