CN111756580B - Cooperative operation synchronization method and system for multi-node system - Google Patents
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Abstract
The invention relates to a method and a system for synchronizing cooperative operation of a multi-node system, wherein the method comprises the steps of calculating the average time error of all operation nodes in the system by a master control node and the discrete degree of the corresponding time error; calculating the integral time error of the system according to the average time errors of all the operation nodes and the discrete degree of the corresponding time errors; the master control node issues tasks in advance according to the whole time error, the system combines the centralized type and the distributed type, the problem that a multi-node system in the prior art is poor in synchronism and coordination is solved, the time synchronism of the multi-node system is improved, the multi-node synchronous cooperation capacity is enhanced, and the system environment adaptability is also improved.
Description
Technical Field
The invention relates to the technical field of multi-node system cooperative operation, in particular to a multi-node system cooperative operation synchronization method and system.
Background
For the cooperative operation of a multi-node system, no matter an unmanned aerial vehicle, an unmanned ship, an unmanned vehicle or other unmanned platforms, the main difficulties include two items, namely the synchronization of time errors of control commands and the selection of a multi-node cooperative model.
For the time error synchronization of the control command, the prior art only considers the time synchronization and ignores the space synchronization, and chinese patent document CN103889046B discloses an underwater sensor network time synchronization method, which utilizes the collision of a data packet sent by a standard time node and a node to be synchronized at the receiving end of the node to be synchronized to determine the time when the information sent by the standard time node meets the data packet sent by the node to be synchronized for the last time before the information reaches the node to be synchronized; taking the moment as a reference time point, and writing an equation in a row; the above processes are repeated for many times to obtain a binary linear equation set, and the time offset and the drift rate are calculated, so that the influence of node movement is eliminated, and chinese patent document CN105680975B discloses a time synchronization method for a master-slave structure multi-node network, in which each node of the network is physically connected by a wire, and two clock synchronization mechanisms are designed: one is an answer-type mechanism and the other is a broadcast-type mechanism. The answering mechanism obtains the accurate time of sending and receiving each message through FPGA clock sampling; calculating average transmission time delay and master-slave clock offset in an answer-back synchronization mode, and compensating time accuracy to achieve nanosecond-level high-accuracy time synchronization; the broadcast mechanism can achieve high-precision time synchronization in a broadcast synchronization mode under the condition of neglecting channel transmission delay.
However, the above patents all adopt the transmission delay of a data packet from one node to another node to calculate the time deviation between the two nodes, so as to correct the time deviation to achieve the purpose of time synchronization. When a plurality of nodes are far away from each other or are transmitted through the internet, the importance of spatial synchronization is highlighted, and if the control command cannot reach the operation node at the actual execution time, the operation processing of the whole system is disturbed.
For the collaboration model aspect, the prior art adopts a centralized or distributed model. The centralized type means that the master control node masters all environment information and control information and is responsible for planning and distributing all tasks and issuing instructions, the centralized type fault tolerance performance is low, when a certain operation node is abnormal, the whole system is usually crashed, meanwhile, the environmental applicability is poor, only specific tasks can be aimed at, and the optimization and adjustment of the surrounding environment are difficult to perform. The distributed type has no main control node, all operation nodes are equal in time and can independently make decisions, but each node takes priority on its own task, so that the overall task efficiency is low, and the significance of cooperative operation is lost.
Disclosure of Invention
Aiming at the problems in the prior art, the invention discloses a cooperative operation synchronization method and a cooperative operation synchronization system for a multi-node system, which solve the problem of poor synchronization and coordination of the multi-node system in the prior art, improve the time synchronization of the multi-node system, enhance the synchronous cooperation capability of the multi-node system and improve the environmental adaptability of the system.
The specific technical scheme disclosed by the invention is as follows: a cooperative operation synchronization method of a multi-node system comprises the following steps:
s01, the master control node is in A1Sending a synchronous message to one of the operation nodes at any time;
s02, the operation node is in A2Receiving the synchronous message, and at A3Sending a delay measurement request message to a master control node at any moment;
s03, the master control node is in A4Receiving a delay measurement request message at any moment;
s04, the master control node is according to A1、A2、A3、A4Calculating the average time error between the master control node and the operation node and the dispersion degree of the time error of the operation node at four moments;
s05, the master control node respectively calculates the average time error and the discrete degree of the corresponding time error for all the operation nodes in the system;
s06, calculating the integral time error of the system according to the average time errors of all the operation nodes and the discrete degrees of the corresponding time errors;
and S07, the master control node issues tasks to all the operation nodes in advance according to the time error and the expected execution time of the whole system.
Further, the master control node can automatically adjust and calculate the update frequency of the average time error of each operation node according to the discrete degree of the time error of each operation node and the preset system operation precision: and when the discrete degree of the time errors is reduced, the updating frequency of the average time errors in the operation node is reduced, otherwise, the updating frequency of the average time errors in the operation node is increased.
The time error is one of the systematic errors, which is also called the discipline error. Under certain measurement conditions, when the same measured size is repeatedly measured for multiple times, the magnitude and the sign (positive value or negative value) of an error value are kept unchanged; or an error that changes in a certain rule when conditions change. The time error in the invention refers to the time difference of information transmission between the main control node and the operation node, and the time difference can be approximately considered to be unchanged or small in change fluctuation in a very short time.
The discrete degree refers to the difference degree between values of variables which are observed randomly to measure the risk size, and in the invention, the discrete degree refers to the difference degree between a plurality of time errors which are randomly selected and calculated by an operation node to judge whether the time errors in the operation node are stable or not. There are many indexes that can be used to measure the degree of difference between observation time errors, and the most common ones in statistical analysis and inference are range differences, mean differences, standard deviations, and so on.
Further, the method for calculating the time error of each operation node comprises the following steps:
d＝[(A2-A1)+(A4-A3)]/2，
where d is the time error of a single job node.
Further, the method for calculating the discrete degree of the time error of each operation node comprises the following steps:
where t is the discrete degree of the time error of a single operation node, d1、d2、…、dnThe time error of the latest n times in the operation node;
the time error is the average of the latest n time errors of the operation node.
Further, the method for calculating the time error of the whole system in step S06 includes:
da＝[(t1/tmax)+(t2/tmax)+...+(tn/tmax)]×dmax，
wherein the content of the first and second substances,
respectively, the average time error of each operation node of the system, and the discrete degree of the corresponding time error is t1、t2、...、tn；tmaxIs dmaxCorresponding to the degree of dispersion of the time error.
Further, the specific operation method for the master control node to issue the task in the step S07 is as follows: and after the master control node calculates the time error da of the whole system, issuing the job task with the execution time of T to each job node at the time of T1, wherein the time of T1 is earlier than the time of T by the time of da.
The invention also discloses a cooperative operation synchronization system of the multi-node system, which comprises: the main control node module is used for calculating the time error of each operation node, the discrete degree of the corresponding time error and the time error of the whole system, issuing a task instruction to each operation node and coordinating each operation node to perform operation; the operation node module is used for receiving the task instruction of the main control node and automatically planning specific task operation according to the task instruction to complete an operation task; the data link communication module is used for information transmission between the operation nodes and the main control node; and the plurality of groups of operation nodes are respectively in transmission link with the main control node through a data link communication module, and all the operation nodes share information through the data link communication module.
Wherein the job node module includes: the system comprises a sensor module, a behavior driving module, a motion coordination module and a task planning module, wherein the task planning module, the motion coordination module and the behavior driving module act in a sequential control mode, the behavior driving module reads data of the sensor module,
the task planning module is used for analyzing the self sensing information to obtain sensing knowledge, generating specific task planning according to the sensing knowledge and combining the task instruction of the main control node, and sharing task planning information of other operation nodes;
the motion coordination module analyzes the data of the sensor to obtain sensing information, performs motion planning according to the sensing information and the task planning information, and shares the motion planning information of other operation nodes;
the behavior driving module is used for reading and storing sensor data and sensor data sharing other operation nodes;
the sensor module senses the measured information and can convert the sensed information into sensor data.
The centralized system is a central node composed of one or more host computers, data is stored in the central node in a centralized manner, all service units of the whole system are deployed on the central node in a centralized manner, all functions of the system are processed in a centralized manner, and the centralized system has the greatest characteristic that the deployment structure is simple, but the defects are obvious: when the number of the operation nodes is large, the response speed is slow; and aiming at different operation nodes, programs and resources, separate configuration is needed, and the configuration on a centralized system is difficult and low in efficiency.
A distributed system is a software system built on top of a network. The distributed system has high cohesiveness and transparency due to the characteristics of software, one distributed system has various general physical and logical resources, tasks can be dynamically distributed, and information exchange is realized by the dispersed physical and logical resources through a computer network. The distributed system has the advantages of resource sharing, high calculation speed, high reliability and the like, but the control of a distributed system is usually a typical distributed control without a uniform central control. Therefore, the distributed system usually needs a corresponding synchronization mechanism to coordinate the work of each part in the system,
the system combines a distributed system and a centralized system to form a hybrid system, a main control node responsible for issuing task commands and performing cooperative data processing is reserved, the data processing amount of the operation node is simplified, the operation node is concentrated in specific tasks and does not need to participate in complex operation, the operation node has certain autonomous control and calculation capacity, the task commands issued by the main control node can be automatically analyzed, the main control node does not need to send specific task operation, and an intermediate layer service interface is formed between the main control node and the operation node, so that the maintenance difficulty of the system is greatly reduced.
Further, the data link communication module adopts one or more transmission modes of Ethernet, physical direct connection, Bluetooth, ZigBee, 2.4G and 27M.
Furthermore, when the sensor data of one or more operation nodes is abnormal, the abnormal operation node judges whether the self adjustment influences the change of the motion coordination module in other operation nodes, if not, the abnormal operation node keeps the normal operation of the operation node through self optimization adjustment; and if so, sending a request to the main control node by the abnormal operation node, and enabling the main control node to issue the task command again.
Compared with the prior art, the invention has the following advantages:
1) according to the invention, the overall time error of the multi-node system is calculated, the task instruction is issued in advance, all the operation nodes normally perform operation tasks in preset time, and the time and space synchronization precision of the operation of the multi-node system is ensured.
2) The main control node in the multi-node system can calculate the discrete degree of the time error of each operation node in real time and automatically adjust the updating frequency of the time error, the system processing load and the link data occupation are dynamically adjusted on the premise of ensuring the system precision, the operation nodes with stable time errors only occupy the very low data processing capacity and the data link bandwidth of the main control node, the delay state of the system can be accurately obtained, more data processing capacity and data link bandwidth can be reserved in the main control node for processing operation tasks, and the system processing efficiency is effectively improved.
3) The system adopts a hybrid model, integrates the advantages of a distributed and centralized model, has high fault tolerance rate due to information sharing among a plurality of operation nodes, does not influence the whole system even if a certain operation node is crashed, has strong environmental adaptability, simultaneously has a main control node and an operation node with certain autonomous control capability, and can automatically analyze a task command sent by the main control node, so that an intermediate layer service interface is formed between the main control node and the operation node, the aim of decoupling on processing is fulfilled, and the maintenance difficulty of the system is greatly reduced.
4) When a certain operation node is abnormal, the system can automatically judge and repair the operation node to ensure that the operation task is normally performed, and has strong fault tolerance and self-repairing capability.
Drawings
FIG. 1 is a flow chart of the calculation of the average time error between the master node and the job node according to the embodiment of the present invention;
FIG. 2 is a flow chart of an adaptive update frequency of an average time error in a worker node according to an embodiment of the present invention;
FIG. 3 is a block diagram of a cooperative operation synchronization system of a multi-node system according to an embodiment of the present invention;
FIG. 4 is a block diagram of shared information in a worker node in an embodiment of the invention;
fig. 5 is a flowchart of repairing an abnormal operation node according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, and it should be understood that the embodiments described herein are merely for the purpose of illustrating and explaining the present invention and are not intended to limit the present invention.
Example (b):
this embodiment sprays unmanned aerial vehicle for 5 pesticides and carries out the pesticide in coordination to the farmland and spray the operation:
referring to fig. 1, a method for synchronizing cooperative operations of a multi-node system disclosed in this embodiment includes the following steps:
s01, the master control node is in A1Sending a synchronous message (Sync) message to one unmanned aerial vehicle operation node at any moment;
s02, the unmanned aerial vehicle operation node is in A2Receiving a synchronization message (Sync) message, and at A3Sending a Delay measurement request (Delay _ Req) message back to the master control node at any moment to indicate that the equipment is online;
s03, the master control node is in A4Receiving a Delay measurement request (Delay _ Req) message at a time;
s04, the master control node is according to A1、A2、A3、A4The time error between the master control node and the unmanned aerial vehicle operation node is calculated at four moments as follows:
d＝[(A2-A1)+(A4-A3)]/2，
and the discrete degree of the time error of the unmanned aerial vehicle operation node:
wherein, t1Degree of dispersion of time error of operation node 1, d1、d2、…、dnThe time error of the latest n times in the operation node;
the average time error of the latest n time errors of the operation node is obtained;
s05, the master control node calculates average time errors of all unmanned aerial vehicle operation nodes in the system respectively
And the degree of dispersion t corresponding to the time errori；
S06, average time error according to all unmanned aerial vehicle operation nodes
And the degree of dispersion t corresponding to the time erroriAnd calculating the time error of the whole system:
da＝[(t1/tmax)+(t2/tmax)+(t3/tmax)+(t4/tmax)+(t5/tmax)]×dmax，
wherein the content of the first and second substances,
respectively, the average time error of each unmanned aerial vehicle operation node of the system, and the discrete degree of the corresponding time error is t1、t2、t3、t4、t5；tmaxIs dmaxThe degree of dispersion of the corresponding time error;
and S07, dividing the farmland into a plurality of areas by the master control node, coordinating the unmanned aerial vehicles to carry out spraying tasks, formulating a spraying task instruction, wherein the expected execution time of the task instruction is T, and issuing the task instruction to all the unmanned aerial vehicle operation nodes by the master control system at the time T1, wherein the time T1 is earlier than the time T by da.
As shown in fig. 2, the master control node may automatically adjust and calculate the update frequency of the average time error of each unmanned aerial vehicle operation node according to the dispersion degree of the time error of each unmanned aerial vehicle operation node and the preset system operation precision: when the discrete degree of time error reduces, reduce the update frequency of average time error in this unmanned aerial vehicle operation node, otherwise when the discrete degree of time error increases, increase the update frequency of average time error in this unmanned aerial vehicle operation node.
Referring to fig. 3, the operation process of the cooperative work synchronization system in this embodiment is as follows:
the main control node calculates the integral time error of the system by calculating the time error of each unmanned aerial vehicle operation node and the discrete degree of the corresponding time error, formulates a pesticide spraying and area task instruction responsible for the pesticide spraying, and sends the task instruction to each unmanned aerial vehicle operation node in advance through a data link.
As shown in fig. 4, the acceleration sensors in the unmanned aerial vehicle operation nodes monitor the motion of the unmanned aerial vehicle in real time, the behavior driving module stores sensor data in real time, the motion coordination module analyzes the sensor data to obtain data of the operation direction and the displacement distance of the unmanned aerial vehicle, and the mission planning module analyzes the data to obtain the motion state of the unmanned aerial vehicle according to the operation direction and the displacement distance. After the task planning module receives a task instruction of the main control node, specific spraying paths and spraying amount information are automatically generated by combining the real-time motion state of the unmanned aerial vehicle and are sent to the motion coordination module, the specific control instruction of the unmanned aerial vehicle is generated by the motion coordination module and is executed by the behavior driving module, the unmanned aerial vehicle is controlled to spray according to the planned paths, meanwhile, the unmanned aerial vehicle operation nodes are communicated in real time through data links, and data are shared mutually.
Optionally, the data link communication module may adopt one or more transmission modes of ethernet, physical direct connection, bluetooth, ZigBee, 2.4G, and 27M.
As shown in fig. 5, when the acceleration sensor data of an operation node of an unmanned aerial vehicle is abnormal, the operation node of the unmanned aerial vehicle judges whether self adjustment affects the change of a motion coordination module in another operation node, and if not, the abnormal operation node performs self optimization adjustment to keep the operation node operating normally; and if so, sending a request to the main control node by the abnormal operation node, and enabling the main control node to issue the task command again. For example, when acceleration data detected by a certain acceleration sensor in an unmanned aerial vehicle operation node obviously deviates from the range of normal acceleration values, the unmanned aerial vehicle operation node judges whether the acceleration sensor measures wrongly, if so, the acceleration sensor is compensated and corrected through the values detected by other acceleration sensors, if not, the acceleration sensor is damaged, the unmanned aerial vehicle operation node shuts down the sensor, and other acceleration sensors are adopted to replace the acceleration sensor to work. And if the unmanned aerial vehicle driving assembly is judged not to have a measurement error of the sensor but has a problem, if the electric power is insufficient or the motor is damaged, a request is automatically sent to the main control node to inform an operator of maintenance, and the main control node issues a task instruction again to coordinate other unmanned aerial vehicle operation nodes to replace the unmanned aerial vehicle operation nodes to carry out spraying operation.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (6)
1. A cooperative work synchronization method of a multi-node system is characterized by comprising the following steps:
s01, the master control node is in
Sending a synchronous message to one of the operation nodes at any time;
s02, the operation node is
Receive the sameStep(s) message(s) and
sending a delay measurement request message to a master control node at any moment;
s03, the master control node is in
Receiving a delay measurement request message at any moment;
s04, the master control node is according to
Calculating the average time error between the master control node and the operation node and the dispersion degree of the time error of the operation node at four moments;
s05, the master control node respectively calculates the average time error and the discrete degree of the corresponding time error for all the operation nodes in the system;
s06, calculating the integral time error of the system according to the average time errors of all the operation nodes and the discrete degrees of the corresponding time errors;
s07, the main control node issues tasks to all operation nodes in advance according to the time error and the expected execution time of the whole system,
the method for calculating the time error of each operation node comprises the following steps:
wherein is
Time error of a single job node;
the method for calculating the discrete degree of the time error of each operation node comprises the following steps:
wherein the content of the first and second substances,tas a discrete degree of time error for a single job node,
is the latest n time errors in the operation node, and
the time error is the average time error of the latest n time errors of the operation node;
the method for calculating the time error of the whole system in the step S06 includes:
wherein the content of the first and second substances,
；
respectively, the average time error of each operation node of the system, and the corresponding discrete degree of the time error is
；
Is that
Corresponding to the degree of dispersion of the time error.
2. The cooperative job synchronization method for multi-node systems according to claim 1, wherein the master node automatically adjusts the frequency of calculating the average time error of each job node according to the dispersion degree of the time error of the job node and the system job precision: and when the discrete degree of the time errors is reduced, the updating frequency of the average time errors in the operation node is reduced, otherwise, the updating frequency of the average time errors in the operation node is increased.
3. The method for synchronizing cooperative work in a multi-node system according to claim 2, wherein the specific operation method for the master node to issue the task in the step S07 is as follows: and after the master control node calculates the time error da of the whole system, issuing the job task with the execution time of T to each job node at the time of T1, wherein the time of T1 is earlier than the time of T by the time of da.
4. A cooperative job synchronization system of a multi-node system for implementing the cooperative job synchronization method according to any one of claims 1 to 3, the system comprising: the main control node module is used for calculating the time error of each operation node, the discrete degree of the corresponding time error and the time error of the whole system, issuing a task instruction to each operation node and coordinating each operation node to perform operation; the operation node module is used for receiving the task instruction of the main control node and automatically planning specific task operation according to the task instruction to complete an operation task; the data link communication module is used for information transmission between the operation nodes and the main control node; multiunit operation node respectively with master control node passes through data link communication module transmission link, simultaneously through data link communication module information sharing between all operation nodes, its characterized in that, include in the operation node module:
the sensor module senses the measured information and can convert the sensed information into sensor data to be output;
the behavior driving module is used for storing the sensor data output by the sensor module of the behavior driving module and the sensor data sharing other operation nodes;
the motion coordination module is used for analyzing the data of the sensor to obtain sensing information, performing motion planning according to the sensing information and the task planning information, and sharing the motion planning information of other operation nodes;
and the task planning module is used for analyzing the self sensing information to obtain sensing knowledge, generating specific task planning according to the sensing knowledge and combining the task instruction of the main control node, and sharing task planning information of other operation nodes.
5. The system for synchronizing the cooperative operations of a multi-node system according to claim 4, wherein the data link communication module employs one or more transmission modes selected from the group consisting of network, physical direct connection, Bluetooth, ZigBee, 2.4G, and 27M.
6. The system of claim 5, wherein when the sensor data of one or more operation nodes is abnormal, the abnormal operation node determines whether its own adjustment affects the change of the motion coordination module in other operation nodes, and if not, the abnormal operation node maintains its normal operation through its own optimization adjustment; and if so, sending a request command to the main control node by the abnormal operation node, and making the main control node perform task re-decision.
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| CN111756580A (en) | 2020-10-09 |
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