CN115358630A

CN115358630A - Space mission control method and system based on intelligent closed-loop control

Info

Publication number: CN115358630A
Application number: CN202211129750.XA
Authority: CN
Inventors: 魏育成; 徐成华; 秦刚
Original assignee: Zhongke Jiudu Beijing Spatial Information Technology Co ltd
Current assignee: Zhongke Jiudu Beijing Spatial Information Technology Co ltd
Priority date: 2022-09-16
Filing date: 2022-09-16
Publication date: 2022-11-18

Abstract

The invention relates to a space mission control method and system based on intelligent closed-loop control, comprising the following steps: collecting state information data related to the space mission; judging whether a fault occurs according to the collected state information data and fault judgment knowledge in the knowledge base module; if the fault occurs, generating a corresponding disposal strategy by combining the collected state information data according to the fault disposal knowledge in the knowledge base module; and finishing the handling of the fault according to the generated handling strategy. The invention can sense, make intelligent decision and dispose intelligently in time, reduce manual intervention operation, enhance disposal timeliness and ensure task safety and spacecraft safety.

Description

Space mission management and control method and system based on intelligent closed-loop control

Technical Field

The invention relates to the technical field of spacecraft task management and control, in particular to a method and a system for managing and controlling a space mission based on intelligent closed-loop control.

Background

With the increasing number of spacecrafts, tasks are implemented more and more frequently, in order to enhance task safety and improve task execution efficiency, the management center of each spacecraft increasingly depends on the automation and the intellectualization of a task management and control system, and manual intervention is reduced. The task execution rough process comprises the following steps: the method comprises the steps of task planning, measurement and control station control, spacecraft control parameter calculation, spacecraft operation control and data station control. Taking a ground observation task as an example, after receiving an observation requirement (time period, area, observation quality requirement and the like) provided by a user, a management center formulates a task plan according to the current resource use conditions of a satellite position, a measurement and control station, a data station and the like, when the task is implemented, an uplink remote control channel is established by controlling the measurement and control station, the spacecraft sidesway is controlled by sending a remote control instruction, a camera is set to start, data is downloaded, the data is shut down and the like, and the observation data is downloaded and stored by controlling the data station. The task execution mode mainly goes through two phases:

the method comprises the steps that a first-stage manual operation is used as a main tool set and a task management and control system provides an auxiliary tool set, task managers transmit task information through documents, a task plan and an implementation program are formulated, spacecraft control parameters are calculated by means of the tool set to generate injection instruction data, ground station equipment is manually controlled to establish an uplink measurement and control channel, the injection instruction data are sent to a spacecraft through the uplink measurement and control channel for real-time task control, and a data station is arranged to receive observation data and store the observation data;

and the second stage task management and control system is automatically executed as a main task and an auxiliary task judgment position, receives the task requirement sent by the user, automatically makes a control plan according to the resource occupation conditions of the spacecraft, the measurement and control station and the data station, and automatically completes the control and coordination of the spacecraft, the measurement and control station and the data station to complete the observation task at the start moment of the task time. And if the task is abnormal in the implementation process, manually judging the reason of the abnormality and carrying out emergency disposal.

The existing scheme mainly takes the second-stage scheme as a main scheme, and the task execution automation is basically realized. The system composition is shown in fig. 3, and comprises three layers of task planning, task scheduling and task execution.

And the task planning receives a task requirement sent by a user, accepts and judges the legality through the task requirement, reasonably appoints a task plan according to the resource occupation states of the spacecraft, the ground station and the data station through the task requirement, occupies resources in a time period appointed by the user, and records the task configuration of the user.

And traversing the task plan in real time by task scheduling, reading the task plan at the start moment of the task, transmitting task parameters to the task for execution, and starting an independent task executor.

After the task executor is started, modules such as measurement and control station control, data station control, spacecraft control, control parameter calculation and the like are remotely called according to a pre-arranged task template and by combining with the transmitted task parameters, and the task is completed in a matching manner.

The current scheme realizes the one-way automatic control of task execution, reduces the labor cost to a certain extent, but has the following defects:

1. task execution exception handling depends on manual intervention, and when an exception occurs in the task execution process, an operator on duty is required to check the task state, judge the reason of the exception, and carry out emergency handling according to a handling plan. The duty personnel need to pay attention to the task state in time, and the task can be guaranteed to be successfully executed only by timely disposing when abnormality occurs.

2. The whole system perception linkage mechanism is deficient, the task execution state and the state monitoring of each subsystem require an operator on duty to pay attention to the state of each subsystem all the time, and if a spacecraft, ground station equipment, computer network equipment and the like have faults, the operator on duty is required to judge the influence degree on the task, adjust a task plan, perform fault handling and recover task operation. Because manual intervention is needed, hidden dangers influencing task safety and spacecraft safety exist.

Disclosure of Invention

The invention aims to provide a space mission management and control method and system based on intelligent closed-loop control, which can sense, make intelligent decision and perform intelligent treatment in time, reduce manual intervention operation, enhance treatment timeliness and ensure mission safety and spacecraft safety.

In order to achieve the above object, the embodiments of the present invention provide the following technical solutions:

the space mission control method based on intelligent closed-loop control comprises the following steps:

s1, collecting state information data related to a space mission;

s2, judging whether a fault occurs according to the acquired state information data and fault judgment knowledge in the knowledge base module; if the fault occurs, generating a corresponding disposal strategy by combining the collected state information data according to the fault disposal knowledge in the knowledge base module;

and S3, finishing the handling of the fault according to the generated handling strategy.

Further, the collected state information data comprises task state data and system state data, wherein,

the task state data are control parameters obtained by calculation in the task execution process, and the control parameters comprise measurement and control station control parameters, data station control parameters and spacecraft control parameters;

the system state data comprises a measurement and control station state parameter, a data station state parameter, a spacecraft state parameter, a computer network state parameter and a software system state parameter;

after the state information data related to the space mission is collected, the mission state data and the system state data are stored as a list of < parameter identification, parameter type and parameter value >.

Furthermore, the step of judging whether a fault occurs according to the collected state information data and fault judgment knowledge in the knowledge base module comprises:

the fault judgment knowledge in the knowledge base module is stored in a list form of < fault identification and state parameter expression >, wherein the fault identification is a 32-bit unsigned integer which uniquely identifies a fault, and the state parameter expression is a logic expression of task state parameters;

acquiring fault judgment knowledge, traversing a list of the fault judgment knowledge, acquiring parameter values from state information data according to task state parameters contained in a state parameter expression of each item of fault judgment knowledge, calculating the result of the state parameter expression, judging that a fault occurs if the result is met, and generating a fault identifier.

Furthermore, if it is determined that a fault occurs, generating a corresponding disposal strategy by combining the collected state information data according to fault disposal knowledge in the knowledge base module, wherein the step comprises the following steps of:

the fault handling knowledge in the knowledge base module is stored in a list form of < fault identification, handling command, handling parameter set >;

and searching and acquiring a handling command and a handling parameter set from the fault handling knowledge according to the generated fault identifier, acquiring a variable parameter from the state information data according to the parameter identifier in the handling parameter set, and generating a corresponding handling strategy.

Still further, the step of completing the handling of the fault according to the generated handling policy includes:

and (3) task planning: receiving a treatment strategy, generating a task plan, and planning related resources according to the task plan;

task scheduling: loading a task plan, and controlling related resources in task scheduling according to the resource planning;

and (3) task execution: and calculating control parameters, and performing measurement and control station control, data station control or spacecraft control according to the control parameters.

Still further, the method further comprises the step S4: and reading the acquired task state data, the generated disposal strategy and the disposed result, evaluating the disposed result, and updating and adjusting the fault judgment knowledge and the fault disposal knowledge in the knowledge base module.

Space mission management and control system based on intelligent closed-loop control includes:

the state perception module is used for collecting state information data related to the spacecraft tasks;

the knowledge base module is used for storing fault judgment knowledge and fault disposal knowledge;

the comprehensive situation studying and judging module is used for judging whether a fault occurs according to the acquired state information data and fault judging knowledge; if judging that the fault occurs, sending a fault identifier to a disposal strategy generating module;

the disposal strategy generation module is used for receiving the fault identification, generating a corresponding disposal strategy by combining the collected state information data according to the fault disposal knowledge, and sending the disposal strategy to the disposal strategy execution module;

and the handling strategy execution module is used for finishing the handling of the fault according to the handling strategy.

Furthermore, the acquired state information data comprises task state data and system state data, wherein the task state data are control parameters obtained by calculation in the task execution process and comprise measurement and control station control parameters, data station control parameters and spacecraft control parameters; the system state data comprises a measurement and control station state parameter, a data station state parameter, a spacecraft state parameter, a computer network state parameter and a software system state parameter;

and the task state data and the system state data are stored as a list of < parameter identification, parameter type, parameter value >;

the fault handling knowledge in the knowledge base module is stored in the form of a list of < fault identification, handling command, set of handling parameters >.

Furthermore, the comprehensive situation studying and judging module acquires fault judgment knowledge when judging whether a fault occurs, traverses a list of the fault judgment knowledge, obtains parameter values from the state information data according to task state parameters contained in a state parameter expression of each item of fault judgment knowledge, calculates the result of the state parameter expression, judges that a fault occurs if the result is satisfied, generates a fault identifier, and sends the fault identifier to the disposal strategy generating module.

Furthermore, when the disposal policy generation module generates a disposal policy, the disposal policy generation module searches and acquires a disposal command and a disposal parameter set from the failure disposal knowledge according to the failure identifier sent by the comprehensive situation studying and judging module, acquires a variable parameter from the state information data according to the parameter identifier in the disposal parameter set, generates a corresponding disposal policy, and sends the disposal policy to the disposal policy execution module.

Furthermore, the system also comprises a disposal evaluation learning module which is used for reading the collected task state data and the generated disposal strategy, and the disposed result, evaluating the disposed result, and updating and adjusting the fault judgment knowledge and the fault disposal knowledge in the knowledge base module.

Compared with the prior art, the invention has the beneficial effects that:

(1) The invention constructs a sensing-judging-decision-handling closed-loop control system model of the space mission, replaces the judgment and operation of an operator on duty, and automatically coordinates task planning and task scheduling to handle after a fault is found by judging the global situation of the system; particularly, when each subsystem breaks down or task execution is abnormal, sensing, intelligent decision and intelligent disposal can be carried out in time, manual intervention operation is reduced, disposal timeliness is enhanced, and task safety and spacecraft safety are guaranteed.

(2) The disposal evaluation learning module adjusts the expert knowledge in the knowledge base module in real time according to the failure disposal result and historical statistical information (historical task state data and system state data); by automatically optimizing and adjusting expert knowledge, the fault judgment criterion and the disposal strategy are more accurate, the probability of false alarm and false alarm is reduced, and the correctness of the disposal process is further ensured.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.

FIG. 1 is a schematic diagram of the system of the present invention;

FIG. 2 is a flow chart of the method of the present invention;

fig. 3 is a schematic diagram of a system in the prior art.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.

Example (b):

the invention is realized by the following technical scheme, as shown in fig. 1, the space mission management and control system based on intelligent closed-loop control comprises a state sensing module, a knowledge base module, a comprehensive situation studying and judging module, a disposal strategy generating module, a disposal strategy executing module and a disposal evaluation learning module, wherein:

the comprehensive situation studying and judging module is used for judging whether a fault occurs according to the acquired state information data and fault judgment knowledge; if judging that the fault occurs, sending a fault identifier to a disposal strategy generation module;

the handling strategy execution module is used for finishing the handling of the fault according to the handling strategy;

and the disposal evaluation learning module is used for updating and adjusting the fault judgment knowledge and the fault disposal knowledge in the knowledge base module.

In detail, the acquired state information data comprises task state data and system state data, wherein the task state data are control parameters obtained by calculation in a task execution process, and the control parameters comprise measurement and control station control parameters, data station control parameters and spacecraft control parameters; the system state data comprises a measurement and control station state parameter, a data station state parameter, a spacecraft state parameter, a computer network state parameter and a software system state parameter. And the task state data and the system state data are stored as a list of < parameter identification, parameter type, parameter value >.

The fault judgment knowledge in the knowledge base module is stored in a list form of < fault identification and state parameter expression >, wherein the fault identification is a 32-bit unsigned integer which uniquely identifies a fault, and the state parameter expression is a logic expression of task state parameters. The fault handling knowledge in the knowledge base module is stored in the form of a list of < fault identification, handling command, set of handling parameters >.

The comprehensive situation studying and judging module acquires fault judgment knowledge when judging whether a fault occurs, traverses a list of the fault judgment knowledge, acquires parameter values from state information data according to task state parameters contained in a state parameter expression of each fault judgment knowledge, calculates the result of the state parameter expression, judges that the fault occurs if the result is met, generates a fault identifier, and sends the fault identifier to the disposal strategy generating module.

When the disposal policy generating module generates a disposal policy, the disposal policy generating module searches and acquires a disposal command and a disposal parameter set from the failure disposal knowledge according to the failure identifier sent by the comprehensive situation studying and judging module, acquires a variable parameter from the state information data according to the parameter identifier in the disposal parameter set, generates a corresponding disposal policy, and sends the disposal policy to the disposal policy executing module.

When the treatment strategy execution module finishes the treatment of the fault, the treatment strategy execution module receives the treatment strategy, generates a task plan and performs related resource planning according to the task plan; loading a task plan, and controlling related resources in task scheduling according to the resource planning; and calculating control parameters, and performing measurement and control station control, data station control or spacecraft control according to the control parameters.

And when the disposal evaluation learning module updates and adjusts the knowledge base module, the collected task state data, the generated disposal strategy and the disposed result are read, the disposed result is evaluated, and the fault judgment knowledge and the fault disposal knowledge in the knowledge base module are updated and adjusted.

The knowledge base module, the comprehensive situation studying and judging module, the disposal strategy generating module and the disposal strategy executing module in the system form a brain-intelligent management module serving as a management and control system, judge and operate the system state and the task state global situation, and autonomously coordinate task planning and task scheduling for disposal after a fault is found instead of the judgment and operation of an operator on duty.

Based on the system, the scheme also provides an aerospace task control method based on intelligent closed-loop control, and the method comprises the following steps:

s1, collecting state information data related to the space mission.

The state information data collected by the state perception module comprise task state data and system state data, wherein the task state data are control parameters obtained by calculation in the task execution process and comprise measurement and control station control parameters, data station control parameters and spacecraft control parameters; the system state data comprises a measurement and control station state parameter, a data station state parameter, a spacecraft state parameter, a computer network state parameter and a software system state parameter.

After the state information data related to the space mission is collected, the state sensing module stores the mission state data and the system state data into a list of < parameter identification, parameter type and parameter value >, and provides the list to other modules such as a comprehensive situation studying and judging module to obtain the parameter value according to the parameter identification. The parameter identification is described by a hierarchical structure, for example, a measurement and control station control parameter identification command is State ID.DevID.Control.ParamID, a spacecraft control parameter identification is named SatID.DevID.Control.ParamID, a measurement and control station state parameter identification command is State ID.DevID.State.ParamID, a spacecraft state parameter identification is named SatID.DevID.State.ParamID, a computer network state parameter identification is named network DevID.State.ParamID, and a software system state parameter identification is named software ID.State.ParamID.

S2, judging whether a fault occurs according to the acquired state information data and fault judgment knowledge in the knowledge base module; if the fault occurs, generating a corresponding disposal strategy according to the fault disposal knowledge in the knowledge base module and by combining the collected state information data.

The fault judgment knowledge in the knowledge base module is stored in a list form of < fault identification and state parameter expression >, wherein the fault identification is a 32-bit unsigned integer which uniquely identifies a fault, and the state parameter expression is a logic expression of task state parameters.

The fault handling knowledge in the knowledge base module is stored in the form of a list of < fault identification, handling command, handling parameter set >.

And fault judgment knowledge and fault disposal knowledge in the knowledge base module are formed in the knowledge storage and knowledge base module by modeling the knowledge in advance through expert knowledge.

The comprehensive situation studying and judging module acquires fault judgment knowledge, traverses a list of the fault judgment knowledge, acquires parameter values from state information data according to task state parameters contained in a state parameter expression of each item of fault judgment knowledge, calculates the result of the state parameter expression, judges that a fault occurs if the result is met, generates a fault identifier, and sends the fault identifier to the disposal strategy generating module.

And the handling strategy generation module searches and acquires a handling command and a handling parameter set from the fault handling knowledge according to the sent fault identifier, acquires a variable parameter from the state information data according to the parameter identifier in the handling parameter set, and generates a corresponding handling strategy.

It should be noted that, for the handling of the determined fault by the handling policy execution module in this step, if the fault can be handled in the current task, the handling is performed by instructing task scheduling; and if the task can not be processed in the current task, commanding the task scheduling to terminate the task and commanding the task planning to adjust the task plan. And if no task is executed, commanding the task to plan a newly-added emergency fault disposal plan, and adjusting a subsequent task plan according to the disposal condition.

And S4, reading the acquired task state data, the generated disposal strategy and the disposed result, evaluating the disposed result, and updating and adjusting the fault judgment knowledge and the fault disposal knowledge in the knowledge base module.

The disposal evaluation learning module updates and adjusts the knowledge base module in two modes, namely manual entry and automatic adjustment, adopts a manual entry mode for new knowledge, adopts real-time update and adjustment according to the end of historical data statistics for knowledge related to historical data statistics, for example, the upper limit and the lower limit of a certain state are judged, the values of the upper limit and the lower limit are adjusted in real time by adopting a historical data statistics method, and the knowledge data stored in the knowledge base module are modified through a knowledge update interface provided by the knowledge base module.

And data related to the task execution step and the result are formed in the process of collecting the fault treatment result, the treatment effect is evaluated, knowledge modeling is carried out according to the task execution step, the result and the evaluation conclusion, new fault judgment knowledge or fault treatment knowledge is formed, and the knowledge data in the knowledge base module is updated and adjusted.

Therefore, the disposal evaluation learning module enables the intelligent management module to have a knowledge learning function, can receive the expert knowledge manually input through the case-based knowledge modeling tool, or receive the expert knowledge autonomously learned by the disposal evaluation learning module, automatically maintains the relevant knowledge in the knowledge base module, and provides support for comprehensive situation study and judgment and disposal strategy generation.

And the treatment evaluation learning module adjusts the expert knowledge in the knowledge base in real time according to the fault treatment result and historical statistical information (including historical task state data and system state data). By automatically optimizing and adjusting expert knowledge, the fault judgment criteria and the disposal strategy are more accurate, the probability of false alarm and false alarm is reduced, and the correctness of the disposal process is further ensured.

In conclusion, the scheme constructs a sensing-judging-decision-handling closed-loop control system model of the space mission, replaces the judgment and operation of operators on duty, and automatically coordinates task planning and task scheduling to handle after a fault is found by judging the global situation of the system; particularly, when each subsystem breaks down or task execution is abnormal, sensing, intelligent decision and intelligent disposal can be carried out in time, manual intervention operation is reduced, disposal timeliness is enhanced, and task safety and spacecraft safety are guaranteed.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. The space mission control method based on intelligent closed-loop control is characterized by comprising the following steps: the method comprises the following steps:

s1, collecting state information data related to a space mission;

2. The aerospace mission management and control method based on intelligent closed-loop control according to claim 1, wherein: the collected state information data comprises task state data and system state data, wherein,

the task state data are control parameters obtained by calculation in the task execution process, and comprise measurement and control station control parameters, data station control parameters and spacecraft control parameters;

3. The aerospace task management and control method based on intelligent closed-loop control according to claim 2, wherein: the step of judging whether faults occur according to the collected state information data and fault judgment knowledge in the knowledge base module comprises the following steps:

the fault judgment knowledge in the knowledge base module is stored in a list form of < fault identification and state parameter expression >, wherein the fault identification is a 32-bit unsigned integer uniquely identifying a fault, and the state parameter expression is a logic expression of task state parameters;

4. The aerospace task management and control method based on intelligent closed-loop control according to claim 3, wherein: if the judgment result shows that the fault occurs, generating a corresponding disposal strategy by combining the collected state information data according to the fault disposal knowledge in the knowledge base module, wherein the step comprises the following steps of:

5. An aerospace task management and control method based on intelligent closed-loop control according to any one of claims 1-4, wherein: the step of completing the handling of the fault according to the generated handling policy comprises:

and (3) task planning: receiving a disposal strategy, generating a task plan, and planning related resources according to the task plan;

6. The aerospace task management and control method based on intelligent closed-loop control according to claim 1, wherein: further comprising step S4: and reading the acquired task state data, the generated disposal strategy and the disposed result, evaluating the disposed result, and updating and adjusting the fault judgment knowledge and the fault disposal knowledge in the knowledge base module.

7. Space mission management and control system based on intelligent closed-loop control, its characterized in that: the method comprises the following steps:

the comprehensive situation studying and judging module is used for judging whether a fault occurs according to the acquired state information data and fault judging knowledge; if judging that the fault occurs, sending a fault identifier to a disposal strategy generation module;

8. An intelligent closed-loop-control-based space mission management and control system according to claim 7, wherein: the acquired state information data comprises task state data and system state data, wherein the task state data are control parameters obtained by calculation in the task execution process and comprise measurement and control station control parameters, data station control parameters and spacecraft control parameters; the system state data comprises a measurement and control station state parameter, a data station state parameter, a spacecraft state parameter, a computer network state parameter and a software system state parameter;

9. An aerospace task management and control system based on intelligent closed-loop control according to claim 8, wherein: the comprehensive situation studying and judging module acquires fault judgment knowledge when judging whether a fault occurs, traverses a list of the fault judgment knowledge, acquires parameter values from state information data according to task state parameters contained in a state parameter expression of each fault judgment knowledge, calculates the result of the state parameter expression, judges that the fault occurs if the result is met, generates a fault identifier, and sends the fault identifier to the disposal strategy generating module.

10. An aerospace task management and control system based on intelligent closed-loop control according to claim 9, wherein: when the disposal policy generating module generates a disposal policy, the disposal policy generating module searches and acquires a disposal command and a disposal parameter set from the failure disposal knowledge according to the failure identifier sent by the comprehensive situation studying and judging module, acquires a variable parameter from the state information data according to the parameter identifier in the disposal parameter set, generates a corresponding disposal policy, and sends the disposal policy to the disposal policy executing module.