WO2019242696A1 - 分布式多节点控制系统及方法 - Google Patents

分布式多节点控制系统及方法 Download PDF

Info

Publication number
WO2019242696A1
WO2019242696A1 PCT/CN2019/092124 CN2019092124W WO2019242696A1 WO 2019242696 A1 WO2019242696 A1 WO 2019242696A1 CN 2019092124 W CN2019092124 W CN 2019092124W WO 2019242696 A1 WO2019242696 A1 WO 2019242696A1
Authority
WO
WIPO (PCT)
Prior art keywords
node
control
servo
control node
nodes
Prior art date
Application number
PCT/CN2019/092124
Other languages
English (en)
French (fr)
Inventor
陈理辉
沙琪
王彬
雷宇
郑荣魁
刘江
郭仲才
杜惠
田雪林
Original Assignee
东莞市李群自动化技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 东莞市李群自动化技术有限公司 filed Critical 东莞市李群自动化技术有限公司
Priority to JP2020568673A priority Critical patent/JP7507098B2/ja
Priority to EP19821703.6A priority patent/EP3812856A4/en
Priority to KR1020207037243A priority patent/KR20210022003A/ko
Priority to US17/054,410 priority patent/US11681271B2/en
Publication of WO2019242696A1 publication Critical patent/WO2019242696A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/04—Programme control other than numerical control, i.e. in sequence controllers or logic controllers
    • G05B19/042—Programme control other than numerical control, i.e. in sequence controllers or logic controllers using digital processors
    • G05B19/0421—Multiprocessor system
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/414—Structure of the control system, e.g. common controller or multiprocessor systems, interface to servo, programmable interface controller
    • G05B19/4148—Structure of the control system, e.g. common controller or multiprocessor systems, interface to servo, programmable interface controller characterised by using several processors for different functions, distributed (real-time) systems
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
    • G05B19/408—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by data handling or data format, e.g. reading, buffering or conversion of data
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0262—Confirmation of fault detection, e.g. extra checks to confirm that a failure has indeed occurred
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00—Testing or monitoring of control systems or parts thereof
    • G05B23/02—Electric testing or monitoring
    • G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0267—Fault communication, e.g. human machine interface [HMI]
    • G05B23/027—Alarm generation, e.g. communication protocol; Forms of alarm
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Program initiating; Program switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5083—Techniques for rebalancing the load in a distributed system
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/54—Interprogram communication
    • G06F9/541—Interprogram communication via adapters, e.g. between incompatible applications
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/30—Nc systems
    • G05B2219/33—Director till display
    • G05B2219/33273—DCS distributed, decentralised controlsystem, multiprocessor
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Definitions

  • the present application relates to the field of control technology, and in particular, to a distributed multi-node control system and method.
  • Controllers as the most important parts of industrial robots, have some practical problems in current applications.
  • the entire machine needs to be repaired in the event of a failure, and the cost is high; on the other hand, the controller has a large workload and cannot guarantee the control efficiency.
  • the purpose of this application is to provide a distributed multi-node control system and method to solve the above problems.
  • An embodiment of the present application provides a distributed multi-node control system.
  • the distributed multi-node control system includes a first control node, a second control node, a plurality of servo nodes, and an execution device.
  • the first control node and the The second control node is communicatively connected with the plurality of servo nodes, and the servo node is electrically connected to the execution device, and is configured to control the working state of the corresponding execution device;
  • the first control node is configured To control the working state of at least one of the plurality of servo nodes, and the second control node is configured to control the working state of at least one of the plurality of servo nodes.
  • the distributed multi-node control system further includes a scheduling control node, and the scheduling control node is communicatively connected with the first control node and the second control node, respectively; the scheduling control node is configured to be preset according to a preset Obtain working status information of the first control node and the second control node at a time interval, and adjust the number of the first servo nodes corresponding to the first control node and the first The number of the second servo nodes corresponding to the two control nodes.
  • first control node and the second control node are both an asymmetric dual-core architecture.
  • the first control node includes a first kernel running a Linux system and a second kernel running a real-time operating system (RTOS) system.
  • the first kernel is configured to receive a control instruction, and to receive the received control.
  • An instruction is sent to the second kernel, and the second kernel calculates an execution instruction corresponding to each of the first servo nodes according to a control instruction and the corresponding first servo node, and distributes the corresponding execution instruction to the first kernel.
  • Servo node is configured to receive a control instruction, and to receive the received control.
  • An instruction is sent to the second kernel, and the second kernel calculates an execution instruction corresponding to each of the first servo nodes according to a control instruction and the corresponding first servo node, and distributes the corresponding execution instruction to the first kernel.
  • the first control node includes a shared storage area, and the first core converts data to be transmitted to the second core into transmission data according to a preset protocol, and stores the data in the shared storage area;
  • the first kernel reminds the second kernel to retrieve the transmitted data from a corresponding location in the shared storage area.
  • the servo node has a symmetrical dual-core architecture, and the corresponding dual-cores are all configured to run an RTOS system.
  • the first control node acquires working state data of the first servo node and a corresponding execution device at a preset time interval, and if the working state data acquired by the first control node belongs to an abnormal state Data, start an abnormal warning work; the second control node obtains working status data of the second servo node and the corresponding execution device at a preset time interval, and if the work is obtained by the second control node If the status data belongs to abnormal status data, the abnormal warning work is started.
  • the execution device includes a control motor and an input / output (IO) device.
  • IO input / output
  • An embodiment of the present application provides a distributed multi-node control method, which is applied to the foregoing distributed multi-node control system;
  • the first control node includes a first kernel and a second kernel, and the method includes: the first kernel Receiving a control instruction; the first core sends the received control instruction to the second core; the second core calculates each of the first according to the control instruction and the corresponding first servo node An execution instruction corresponding to a servo node; the second kernel sends the execution instruction to the corresponding first servo node; the first servo node controls the corresponding execution device according to the received execution instruction Working status.
  • the distributed multi-node control system further includes a scheduling control node, and the scheduling control node is communicatively connected with the first control node and the second control node, respectively; the method further includes: The node acquires working state information of the first control node and the second control node according to a preset time interval.
  • a first control node and a second control node in a distributed multi-node control system are communicatively connected to multiple servo nodes, so that the first control node is configured to control the multi-node
  • the working status of at least one first servo node among the plurality of servo nodes further controls the corresponding execution equipment
  • the second control node is configured to control the working status of at least one second servo node among the plurality of servo nodes, thereby controlling the corresponding Execution equipment. That is, real-time calculation is shared by multiple control nodes, thereby implementing distributed control and speeding up the calculation. And this multi-node coordinated system facilitates maintenance and saves maintenance costs.
  • FIG. 1 shows a schematic diagram of a distributed multi-node control system provided by a preferred embodiment of the present application.
  • FIG. 2 shows another schematic diagram of a distributed multi-node control system provided by a preferred embodiment of the present application.
  • FIG. 3 shows a schematic diagram of a first control node provided by a preferred embodiment of the present application.
  • FIG. 4 shows a flowchart of steps in a distributed multi-node control method provided by a preferred embodiment of the present application.
  • FIG. 5 shows another part of the flowchart of the steps of the distributed multi-node control method provided by the preferred embodiment of the present application.
  • Icons 100-distributed multi-node control system; 10-control node; 11- first control node; 111- first kernel; 112- second kernel; 113- shared storage area; 12- second control node; 20- Servo node; 21- first servo node; 22- second servo node; 30- execution equipment; 40- dispatch control node.
  • FIG. 1 is a schematic diagram of a distributed multi-node control system 100 according to a preferred embodiment of the present application.
  • the distributed multi-node control system 100 includes a control node 10, a plurality of servo nodes 20, and an execution device 30.
  • the control node 10 is communicatively connected to the servo node 20, and the servo node 20 is electrically connected to the execution device 30.
  • the above-mentioned distributed multi-node control system 100 further includes a scheduling control node 40.
  • the control node 10 may include, but is not limited to, a first control node 11 and a second control node 12.
  • the scheduling control node 40 is communicatively connected with the first control node 11 and the second control node 12 respectively.
  • the first control node 11 and the second control node 12 are communicatively connected to the plurality of servo nodes 20, respectively.
  • the first control node 11 is configured to control the working state of at least one of the plurality of servo nodes 20, and the second control node 12 is configured to control at least one of the plurality of servo nodes 20.
  • the dispatch control node 40 may be configured to assign a servo node 20 controlled by each control node 10.
  • the scheduling control node 40 is further configured to obtain the first control node 11 and the second control node 12 at a preset time interval.
  • the working state information and according to the working state information, the number of the first servo nodes 21 corresponding to the first control node 11 and the number of the second servo nodes 22 corresponding to the second control node 12 are adjusted.
  • the above working state information may include system occupation information, load information, and the like.
  • the embodiments of the present application alleviate the work of each control node 10 by allocating multiple servo nodes 20 to multiple control nodes 10 Volume, which improves the operation speed.
  • the first control node 11 and the second control node 12 are both asymmetric dual-core architectures.
  • the first control node 11 includes a first kernel 111 running a Linux system and a second kernel 112 running an RTOS system.
  • the first kernel 111 is configured to receive a control instruction and send the received control instruction.
  • the second kernel 112 calculates an execution instruction corresponding to each of the first servo nodes 21 according to a control instruction and the corresponding first servo node 21, and distributes the execution instructions to the corresponding one First servo node 21.
  • the first kernel 111 running the Linux system is responsible for communication and interaction with the outside world, receiving instructions and parameters, and the like.
  • the second kernel 112 running the RTOS system is configured to process according to the data received from the first kernel 111 to generate a corresponding execution instruction of each first servo node 21, and the execution instruction may refer to a servo instruction.
  • the second kernel 112 sends the generated execution instruction to the corresponding first servo node 21 through the network.
  • the first control node 11 includes a shared storage area 113.
  • the first core 111 converts data to be sent to the second core 112 into transmission data according to a preset protocol, and stores the data in the shared storage area 113.
  • the first kernel 111 reminds the second kernel 112 to retrieve the transmission data from a corresponding position in the shared storage area 113. That is, the data sent by the Linux system can be converted into data recognizable by the RTOS system through a preset protocol. Of course, the data sent by the RTOS system can also be converted into data recognizable by the Linux system through a preset protocol.
  • the first control node 11 obtains the working state data of the first servo node 21 and the corresponding execution device 30 at a preset time interval. If the working state data obtained by the first control node 11 belongs to abnormal state data, an abnormal warning work is started.
  • the method for determining the work status data is abnormal status data: the work status data fed back from the servo node 20 or the corresponding execution device 30 may be compared with the expected work status data to determine whether it belongs to the abnormal status data. It may also be determined according to whether the abnormal state information is included in the work state data fed back by the servo node 20 or the corresponding execution device 30.
  • the abnormality warning work may be performed by displaying the identification of the equipment corresponding to the abnormal state data on the display unit of the first control node 11, for example, the working state data fed back by the servo node 20 to the first control node 11 is abnormal.
  • the status data displays the identification information of the servo node 20 on the display unit, which is convenient for maintenance personnel to perform maintenance.
  • the second control node 12 includes a third kernel running a Linux system and a fourth kernel running an RTOS system
  • the third kernel is configured to receive a control instruction and send the received control instruction to the A fourth kernel, which calculates an execution instruction corresponding to each second servo node 22 according to a control instruction and the corresponding second servo node 22, and distributes the execution instruction to the corresponding second servo node 22 .
  • the third kernel running the Linux system is responsible for communication and interaction with the outside world, receiving instructions and parameters.
  • the fourth kernel running the RTOS system is configured to process according to the data received from the third kernel to generate a corresponding execution instruction for each second servo node 22, and the execution instruction may be a servo instruction.
  • the fourth kernel sends the generated execution instruction to the corresponding second servo node 22 through the network.
  • the second control node 12 also includes a shared storage area 113.
  • the third core converts data to be sent to the fourth core into transmission data according to a preset protocol, and stores the data in the shared storage area 113.
  • the preset protocol can convert data sent by the Linux system into data that can be recognized by the RTOS system.
  • the third core puts the transmission data into the shared storage area 113, it sends a trigger instruction to the fourth core to remind the fourth core to take out the transmission data from the corresponding position in the shared storage area 113.
  • the second control node 12 obtains working state data of the second servo node 22 and the corresponding execution device 30 at a preset time interval. If the working state data belongs to abnormal state data, the abnormal warning work is started.
  • the servo node 20 is a symmetric dual-core architecture.
  • the two cores corresponding to the servo node 20 are configured to run an RTOS system.
  • the task allocation is performed according to a preset task allocation algorithm.
  • the execution device 30 may be a control motor or an IO device.
  • FIG. 4 is a flowchart of steps in a distributed multi-node control method provided by a preferred embodiment of the present application.
  • the distributed multi-node control method is applied to the aforementioned distributed multi-node control system 100.
  • the above distributed multi-node control method includes the following steps:
  • step S101 the first core 111 of the first control node 11 receives a control instruction generated by a user operation.
  • step S102 the first core 111 sends the received control instruction to the second core 112.
  • the first core 111 may first convert the control instruction according to a preset protocol into the transfer data recognized by the second core 112 and then store the shared data in the shared storage area 113, and then the first core 111 triggers the second core 112 obtains a control instruction converted into recognizable transfer data from the shared storage area 113.
  • step S103 the second kernel 112 calculates an execution instruction corresponding to each of the first servo nodes 21 according to the control instruction and the corresponding first servo node 21.
  • step S104 the second core 112 sends the execution instructions to the corresponding first servo nodes 21 respectively.
  • step S105 the first servo node 21 controls a working state of the corresponding execution device 30 according to the received execution instruction.
  • the above distributed multi-node control method may further include the following steps:
  • step S201 the scheduling control node 40 obtains working state information of the first control node 11 and the second control node 12 at a preset time interval.
  • the above-mentioned working state information may refer to system resource occupation information, load information, and the like of the control node 10.
  • step S202 the scheduling control node 40 adjusts the number of the first servo nodes 21 corresponding to the first control node 11 and the second servo nodes corresponding to the second control node 12 according to the working status information. Number of 22.
  • the above-mentioned distributed multi-node control method may further include: the first control node 11 acquires the working state data of the first servo node 21 at a preset time interval, and if the first control node 11 obtains the If the working state data belongs to abnormal state data, the abnormal warning work related to the first servo node 21 is started.
  • the first control node 11 obtains the working status data of the execution device 30 through the first servo node 21 at a preset time interval. If the obtained working status data belongs to abnormal status data, it starts an abnormality warning related to the execution device 30 jobs.
  • the second control node 12 obtains the working status data of the second servo node 22 at a preset time interval.
  • the second control node 12 starts The abnormality warning related to the servo node 22 works.
  • the second control node 12 obtains the working status data of the corresponding execution device 30 through the second servo node 22 according to a preset time interval. If the obtained work status data belongs to abnormal status data, it starts the Abnormal warning works. Therefore, if a certain node fails during operation, it can be replaced with a new node of the same type without replacing the whole machine. After reconfiguration, it can continue to run, which is convenient and saves costs. Then replace the node for troubleshooting.
  • the advantage of this is that it does not affect production and reduces maintenance costs.
  • the distributed multi-node control system includes a first control node, a second control node, a plurality of servo nodes, and an execution device.
  • a first control node and the second control node are respectively communicatively connected to the plurality of servo nodes, and the servo nodes are electrically connected to the execution equipment, and are configured to control the working state of the corresponding execution equipment;
  • a first control node is configured to control an operating state of at least one first servo node of the plurality of servo nodes, and a second control node is configured to control an operation of at least one second servo node of the plurality of servo nodes status.
  • the real-time calculation is shared by multiple control nodes, so as to realize distributed control and speed up the calculation. And this multi-node coordinated system facilitates maintenance and saves maintenance costs.
  • each block in the flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more components configured to implement a specified logical function. Executable instructions. It should also be noted that in some alternative implementations, the functions marked in the blocks may also occur in a different order than those marked in the drawings.
  • each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts can be implemented in a dedicated hardware-based system that performs the specified function or action. , Or it can be implemented with a combination of dedicated hardware and computer instructions.
  • the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
  • the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present application is essentially a part that contributes to the existing technology or a part of the technical solution can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present application.
  • the foregoing storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks or optical disks and other media that can store program codes .

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Theoretical Computer Science (AREA)
  • Software Systems (AREA)
  • Human Computer Interaction (AREA)
  • Manufacturing & Machinery (AREA)
  • General Engineering & Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Programmable Controllers (AREA)
  • Testing And Monitoring For Control Systems (AREA)
  • Safety Devices In Control Systems (AREA)
  • General Factory Administration (AREA)
  • Control By Computers (AREA)
  • Numerical Control (AREA)

Abstract

一种分布式多节点控制系统（100）及方法，涉及控制技术领域。其中，所述分布式多节点控制系统（100）包括：第一控制节点（11）、第二控制节点（12）、多个伺服节点（20）及执行设备（30），所述第一控制节点（11）和所述第二控制节点（12）分别与所述多个伺服节点（20）通信连接，所述伺服节点（20）与所述执行设备（30）电性连接，配置成控制对应的所述执行设备（30）的工作状态；所述第一控制节点（11）配置成控制所述多个伺服节点（20）中的至少一个第一伺服节点（21）的工作状态，所述第二控制节点（12）配置成控制所述多个伺服节点（20）中的至少一个第二伺服节点（22）的工作状态。通过多个控制节点（10）分担实时的运算量，从而实现分布式的控制，加快运算速度。且这种多节点协调配合的系统，便于维修，节约维修成本。

Description

分布式多节点控制系统及方法
相关申请的交叉引用
本申请要求于2018年06月20日提交中国专利局的申请号为CN201810637356.4、名称为“分布式多节点控制系统及方法”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及控制技术领域，具体而言，涉及一种分布式多节点控制系统及方法。
背景技术
随着科技的发展，工业机器人以其稳定性和高效性，会在以后的生产中扮演越来越重要的角色。越来越多的行业会使用机器人来代替人完成重复性高的工作。控制器，作为工业机器人最重要的零部件，在当前的应用当中存在一些实际的问题。一方面由于控制器集成度高，一旦出现故障则需整机维修，成本很高；另一方面，控制器承担工作量大，无法保证控制效率。
发明内容
本申请的目的在于提供一种分布式多节点控制系统及方法，以解决上述问题。
为了解决上述问题，本申请实施例采用的技术方案如下：
本申请实施例提供了一种分布式多节点控制系统，所述分布式多节点控制系统包括：第一控制节点、第二控制节点、多个伺服节点及执行设备，所述第一控制节点和所述第二控制节点分别与所述多个伺服节点通信连接，所述伺服节点与所述执行设备电性连接，配置成控制对应的所述执行设备的工作状态；所述第一控制节点配置成控制所述多个伺服节点中的至少一个第一伺服节点的工作状态，所述第二控制节点配置成控制所述多个伺服节点中的至少一个第二伺服节点的工作状态。
进一步地，所述分布式多节点控制系统还包括调度控制节点，所述调度控制节点分别与所述第一控制节点和所述第二控制节点通信连接；所述调度控制节点配置成按照预设的时间间隔获取所述第一控制节点和所述第二控制节点的工作状态信息，并依据所述工作状态信息调整所述第一控制节点对应的所述第一伺服节点的数量及所述第二控制节点对应的所述第二伺服节点的数量。
进一步地，所述第一控制节点及第二控制节点均为非对称双核架构。
进一步地，所述第一控制节点包括运行Linux系统的第一内核及运行实时操作系统(RTOS)系统的第二内核，所述第一内核配置成接收控制指令，并将接收到的所述控制指令发送至所述第二内核，所述第二内核根据控制指令及对应的所述第一伺服节点，计算每 一个所述第一伺服节点对应的执行指令，并分发至对应的所述第一伺服节点。
进一步地，所述第一控制节点包括共享存储区域，所述第一内核将需向所述第二内核发送的数据按照预设的协议转换为传送数据，并存放于所述共享存储区域；所述第一内核提醒所述第二内核从所述共享存储区域中的对应位置取出所述传送数据。
进一步地，所述伺服节点为对称双核架构，对应的双核均配置成运行RTOS系统。
进一步地，所述第一控制节点按照预设的时间间隔获取所述第一伺服节点及对应的执行设备的工作状态数据，若所述第一控制节点获取到的所述工作状态数据属于异常状态数据，则启动异常警示工作；所述第二控制节点按照预设的时间间隔获取所述第二伺服节点及对应的执行设备的工作状态数据，若所述第二控制节点获取到的所述工作状态数据属于异常状态数据，则启动异常警示工作。
进一步地，所述执行设备包括控制电机及输入输出(IO)设备。
本申请实施例提供了一种分布式多节点控制方法，应用于前述分布式多节点控制系统；所述第一控制节点包括第一内核及第二内核，所述方法包括：所述第一内核接收控制指令；所述第一内核将接收到的所述控制指令发送至所述第二内核；所述第二内核根据控制指令及对应的所述第一伺服节点，计算每一个所述第一伺服节点对应的执行指令；所述第二内核将所述执行指令分别发送至对应的所述第一伺服节点；所述第一伺服节点根据接收到的所述执行指令控制对应的所述执行设备的工作状态。
进一步地，所述分布式多节点控制系统还包括调度控制节点，所述调度控制节点分别与所述第一控制节点和所述第二控制节点通信连接；所述方法还包括：所述调度控制节点按照预设的时间间隔获取所述第一控制节点和所述第二控制节点的工作状态信息。
与现有技术相比，本申请提供的一种分布式多节点控制系统中的第一控制节点与第二控制节点分别与多个伺服节点通信连接，以便第一控制节点配置成控制所述多个伺服节点中的至少一个第一伺服节点的工作状态进而控制对应的执行设备，第二控制节点配置成控制所述多个伺服节点中的至少一个第二伺服节点的工作状态，进而控制对应的执行设备。也就是，通过多个控制节点分担实时的运算量，从而实现分布式的控制，加快运算速度。且这种多节点协调配合的系统，便于维修，节约维修成本。
为使本申请的上述目的、特征和优点能更明显易懂，下文特举较佳实施例，并配合所附附图，作详细说明如下。
附图说明
为了更清楚地说明本申请实施例的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，应当理解，以下附图仅示出了本申请的某些实施例，因此不应被看作是对范围的限定，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这 些附图获得其他相关的附图。
图1示出了本申请较佳实施例提供的分布式多节点控制系统的示意图。
图2示出了本申请较佳实施例提供的分布式多节点控制系统的示意图的另一种。
图3示出了本申请较佳实施例提供的第一控制节点的示意图。
图4示出了本申请较佳实施例提供的分布式多节点控制方法的步骤流程图。
图5示出了本申请较佳实施例提供的分布式多节点控制方法的步骤流程图的另一部分。
图标：100-分布式多节点控制系统；10-控制节点；11-第一控制节点；111-第一内核；112-第二内核；113-共享存储区域；12-第二控制节点；20-伺服节点；21-第一伺服节点；22-第二伺服节点；30-执行设备；40-调度控制节点。
具体实施方式
下面将结合本申请实施例中附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本申请一部分实施例，而不是全部的实施例。通常在此处附图中描述和示出的本申请实施例的组件可以以各种不同的配置来布置和设计。因此，以下对在附图中提供的本申请的实施例的详细描述并非旨在限制要求保护的本申请的范围，而是仅仅表示本申请的选定实施例。基于本申请的实施例，本领域技术人员在没有做出创造性劳动的前提下所获得的所有其他实施例，都属于本申请保护的范围。
应注意到：相似的标号和字母在下面的附图中表示类似项，因此，一旦某一项在一个附图中被定义，则在随后的附图中不需要对其进行进一步定义和解释。同时，在本申请的描述中，术语“第一”、“第二”等仅用于区分描述，而不能理解为指示或暗示相对重要性。
第一实施例
请参考图1，图1为本申请较佳实施例提供的分布式多节点控制系统100的示意图。如图1所示，该分布式多节点控制系统100包括控制节点10、多个伺服节点20及执行设备30。控制节点10与伺服节点20通信连接，伺服节点20与执行设备30电性连接。
在本申请实施例中，如图2所示，上述分布式多节点控制系统100还包括调度控制节点40。所述控制节点10可以但不限于包括第一控制节点11和第二控制节点12。调度控制节点40分别与第一控制节点11及第二控制节点12通信连接。第一控制节点11与所述第二控制节点12分别与上述多个伺服节点20通信连接。第一控制节点11配置成控制所述多个伺服节点20中的至少一个第一伺服节点21的工作状态，所述第二控制节点12配置成控制所述多个伺服节点20中的至少一个第二伺服节点22的工作状态。调度控制节点40可配置成分配每个控制节点10所控制的伺服节点20。
进一步地，为了充分利用每一个控制节点10资源，在本申请实施例中，调度控制节点40还配置成按照预设的时间间隔获取所述第一控制节点11与所述第二控制节点12的工作 状态信息，并依据所述工作状态信息调整所述第一控制节点11对应的所述第一伺服节点21的数量及所述第二控制节点12对应的所述第二伺服节点22的数量。上述工作状态信息可以包括系统占用信息、负载信息等。
相较于相关技术中将所有伺服设备集中由一台控制器控制的策略而言，本申请实施例通过将多个伺服节点20分配给多个控制节点10，从而减轻每一个控制节点10的工作量，提高了运算速度。
在本申请实施例中，上述第一控制节点11及第二控制节点12均为非对称双核架构。
可选地，第一控制节点11包括运行Linux系统的第一内核111及运行RTOS系统的第二内核112，所述第一内核111配置成接收控制指令，并将接收到的所述控制指令发送至所述第二内核112，所述第二内核112根据控制指令及对应的所述第一伺服节点21，计算每一个所述第一伺服节点21对应的执行指令，并分发至对应的所述第一伺服节点21。运行Linux系统的第一内核111负责与外界的通信和交互，接收指令和参数等。运行RTOS系统的第二内核112配置成根据从第一内核111接收到的数据进行处理，以生成每一个第一伺服节点21的对应的执行指令，上述执行指令可以是指伺服指令。第二内核112将生成的执行指令通过网络发送至对应的第一伺服节点21。
进一步地，上述过程中Linux系统与RTOS系统之间需要进行数据传递，然而不同系统之间数据交互依然存在不兼容问题。为了解决这一问题，在本申请实施例中，如图3所示，第一控制节点11包括共享存储区域113。所述第一内核111将需向所述第二内核112发送的数据按照预设的协议转换为传送数据，并存放于所述共享存储区域113。所述第一内核111提醒所述第二内核112从所述共享存储区域113中的对应位置取出所述传送数据。也就是，通过预设的协议可以将Linux系统发送的数据转换为RTOS系统可识别的数据。当然还可以通过预设的协议将RTOS系统发送的数据转换为Linux系统可识别的数据。
在本申请实施例中，第一控制节点11按照预设的时间间隔获取所述第一伺服节点21及对应的执行设备30的工作状态数据。若所述第一控制节点11获取到的工作状态数据属于异常状态数据，则启动异常警示工作。可选地，判定工作状态数据属于异常状态数据的方式：可以是根据伺服节点20或对应的执行设备30反馈的工作状态数据与预期的工作状态数据进行比较，进而判定是否属于异常状态数据。还可以是根据伺服节点20或对应的执行设备30反馈的工作状态数据中是否包括异常信息进行判定。可选地，上述异常警示工作可以是通过在第一控制节点11的显示单元展示异常状态数据所对应的设备的标识，例如，一个伺服节点20向第一控制节点11反馈的工作状态数据属于异常状态数据，则在显示单元上展示该伺服节点20的标识信息，方便维护人员对其进行检修。
可选地，第二控制节点12包括运行Linux系统的第三内核及运行RTOS系统的第四内 核，所述第三内核配置成接收控制指令，并将接收到的所述控制指令发送至所述第四内核，所述第四内核根据控制指令及对应的所述第二伺服节点22，计算每一个所述第二伺服节点22对应的执行指令，并分发至对应的所述第二伺服节点22。运行Linux系统的第三内核负责与外界的通信和交互，接收指令和参数等。运行RTOS系统的第四内核配置成根据从第三内核接收到的数据进行处理，以生成每一个第二伺服节点22的对应的执行指令，上述执行指令可以是指伺服指令。第四内核将生成的执行指令通过网络发送至对应的第二伺服节点22。
进一步地，第二控制节点12也包括共享存储区域113。所述第三内核将需向所述第四内核发送的数据按照预设的协议转换为传送数据，并存放于所述共享存储区域113。需要说明的是，该预设的协议可以将Linux系统发送的数据转换为RTOS系统可识别的数据。所述第三内核将传送数据放入共享存储区域113后，向第四内核发送触发指令，以提醒所述第四内核从所述共享存储区域113中的对应位置取出该传送数据。
在本申请实施例中，所述第二控制节点12按照预设的时间间隔获取所述第二伺服节点22及对应的执行设备30的工作状态数据，若所述第二控制节点12获取到的所述工作状态数据属于异常状态数据，则启动异常警示工作。
在本申请实施例中，上述伺服节点20为对称双核架构。该伺服节点20对应的两个内核均配置成运行RTOS系统。在伺服节点20接收到执行指令后，依据两个内核的系统资源占用情况，按照预设的任务分配算法进行任务分配。
在本申请实施例中，上述执行设备30可以是控制电机，也可以是IO设备。
第二实施例
请参考图4，图4为本申请较佳实施例提供的一种分布式多节点控制方法的步骤流程图。该分布式多节点控制方法应用于上述的分布式多节点控制系统100。
如图4所示，上述分布式多节点控制方法包括以下步骤：
步骤S101，第一控制节点11的第一内核111接收到用户操作产生的控制指令。
步骤S102，所述第一内核111将接收到的所述控制指令发送至所述第二内核112。
在本实施例中，可以是第一内核111先将控制指令按照预设的协议转换为第二内核112可识别的传递数据再存放于共享存储区域113，再由第一内核111触发第二内核112从该共享存储区域113中获取转化为可识别的传递数据的控制指令。
步骤S103，第二内核112根据控制指令及对应的第一伺服节点21，计算每一个所述第一伺服节点21对应的执行指令。
步骤S104，所述第二内核112将所述执行指令分别发送至对应的所述第一伺服节点21。
步骤S105，所述第一伺服节点21根据接收到的所述执行指令控制对应的所述执行设 备30的工作状态。
需要说明的是，所有控制节点10接收到用户操作产生的控制指令或参数等处理流程与上述步骤基本相同，在此不再赘述。
进一步地，如图5所示，上述分布式多节点控制方法还可以包括以下步骤：
步骤S201，所述调度控制节点40按照预设的时间间隔获取所述第一控制节点11与所述第二控制节点12的工作状态信息。
在本申请实施例中，上述工作状态信息可以是指控制节点10的系统资源占用信息、负载信息等。
步骤S202，所述调度控制节点40依据所述工作状态信息调整所述第一控制节点11对应的所述第一伺服节点21的数量及所述第二控制节点12对应的所述第二伺服节点22的数量。
进一步地，上述分布式多节点控制方法还可以包括：第一控制节点11按照预设的时间间隔获取所述第一伺服节点21工作状态数据，若所述第一控制节点11获取到的所述工作状态数据属于异常状态数据，则启动对该第一伺服节点21相关的异常警示工作。第一控制节点11按照预设的时间间隔通过第一伺服节点21获取执行设备30的工作状态数据，若获取到的该工作状态数据属于异常状态数据，则启动对该执行设备30相关的异常警示工作。第二控制节点12按照预设的时间间隔获取所述第二伺服节点22工作状态数据，若所述第二控制节点12获取到的所述工作状态数据属于异常状态数据，则启动对该第二伺服节点22相关的异常警示工作。第二控制节点12按照预设的时间间隔通过第二伺服节点22获取对应的执行设备30的工作状态数据，若获取到的该工作状态数据属于异常状态数据，则启动对该执行设备30相关的异常警示工作。从而，在运行期间，如果有某个节点出现故障，可以直接使用新的相同类型的节点进行替换，不需进行整机替换，进行重新配置之后，就可继续运行，方便，节约成本。然后将被替换掉的节点进行故障排查，这样做的好处是，不影响生产，降低维护成本。
综上所述，本申请提供的一种分布式多节点控制系统及方法，所述分布式多节点控制系统包括：第一控制节点、第二控制节点、多个伺服节点及执行设备，所述第一控制节点和所述第二控制节点分别与所述多个伺服节点通信连接，所述伺服节点与所述执行设备电性连接，配置成控制对应的所述执行设备的工作状态；所述第一控制节点配置成控制所述多个伺服节点中的至少一个第一伺服节点的工作状态，所述第二控制节点配置成控制所述多个伺服节点中的至少一个第二伺服节点的工作状态。通过多个控制节点分担实时的运算量，从而实现分布式的控制，加快运算速度。且这种多节点协调配合的系统，便于维修，节约维修成本。
在本申请所提供的几个实施例中，应该理解到，所揭露的装置和方法，也可以通过其它的方式实现。以上所描述的装置实施例仅仅是示意性的，例如，附图中的流程图和框图显示了根据本申请的多个实施例的装置、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点上，流程图或框图中的每个方框可以代表一个模块、程序段或代码的一部分，所述模块、程序段或代码的一部分包含一个或多个配置成实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现方式中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个连续的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或动作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
另外，在本申请各个实施例中的各功能模块可以集成在一起形成一个独立的部分，也可以是各个模块单独存在，也可以两个或两个以上模块集成形成一个独立的部分。
所述功能如果以软件功能模块的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者设备中还存在另外的相同要素。
以上所述仅为本申请的优选实施例而已，并不用于限制本申请，对于本领域的技术人员来说，本申请可以有各种更改和变化。凡在本申请的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本申请的保护范围之内。应注意到：相似的标号和字母在下面的附图中表示类似项，因此，一旦某一项在一个附图中被定义，则在随后的附图中不需要对其进行进一步定义和解释。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应所述以权利要求的保护范围为准。

Claims (10)

  1. 一种分布式多节点控制系统，其特征在于，所述分布式多节点控制系统包括：第一控制节点、第二控制节点、多个伺服节点及执行设备，所述第一控制节点和所述第二控制节点分别与所述多个伺服节点通信连接，所述伺服节点与所述执行设备电性连接，配置成控制对应的所述执行设备的工作状态；所述第一控制节点配置成控制所述多个伺服节点中的至少一个第一伺服节点的工作状态，所述第二控制节点配置成控制所述多个伺服节点中的至少一个第二伺服节点的工作状态。
  2. 如权利要求1所述的分布式多节点控制系统，其特征在于，所述分布式多节点控制系统还包括调度控制节点，所述调度控制节点分别与所述第一控制节点和所述第二控制节点通信连接；所述调度控制节点配置成按照预设的时间间隔获取所述第一控制节点和所述第二控制节点的工作状态信息，并依据所述工作状态信息调整所述第一控制节点对应的所述第一伺服节点的数量及所述第二控制节点对应的所述第二伺服节点的数量。
  3. 如权利要求1所述的分布式多节点控制系统，其特征在于，所述第一控制节点及所述第二控制节点均为非对称双核架构。
  4. 如权利要求3所述的分布式多节点控制系统，其特征在于，所述第一控制节点包括运行Linux系统的第一内核及运行RTOS系统的第二内核，所述第一内核配置成接收控制指令，并将接收到的所述控制指令发送至所述第二内核，所述第二内核根据所述控制指令及对应的所述第一伺服节点，计算每一个所述第一伺服节点对应的执行指令，并分发至对应的所述第一伺服节点。
  5. 如权利要求4所述的分布式多节点控制系统，其特征在于，所述第一控制节点包括共享存储区域，所述第一内核将需向所述第二内核发送的数据按照预设的协议转换为传送数据，并存放于所述共享存储区域；所述第一内核提醒所述第二内核从所述共享存储区域中的对应位置取出所述传送数据。
  6. 如权利要求1所述的分布式多节点控制系统，其特征在于，所述伺服节点为对称双核架构，对应的双核均配置成运行实时操作系统(RTOS)系统。
  7. 如权利要求1所述的分布式多节点控制系统，其特征在于，所述第一控制节点按照预设的时间间隔获取所述第一伺服节点及对应的执行设备的工作状态数据，若所述第一控制节点获取到的所述工作状态数据属于异常状态数据，则启动异常警示工作；所述第二控制节点按照预设的时间间隔获取所述第二伺服节点及对应的执行设备的工作状态数据，若所述第二控制节点获取到的所述工作状态数据属于异常状态数据，则 启动异常警示工作。
  8. 如权利要求1所述的分布式多节点控制系统，其特征在于，所述执行设备包括控制电机及输入输出(IO)设备。
  9. 一种分布式多节点控制方法，其特征在于，应用于如权利要求1-8任一项所述的分布式多节点控制系统；所述第一控制节点包括第一内核及第二内核，所述方法包括：
    所述第一内核接收控制指令；
    所述第一内核将接收到的所述控制指令发送至所述第二内核；
    所述第二内核根据所述控制指令及对应的所述第一伺服节点，计算每一个所述第一伺服节点对应的执行指令；
    所述第二内核将所述执行指令分别发送至对应的所述第一伺服节点；
    所述第一伺服节点根据接收到的所述执行指令控制对应的所述执行设备的工作状态。
  10. 如权利要求9所述的分布式多节点控制方法，其特征在于，所述分布式多节点控制系统还包括调度控制节点，所述调度控制节点分别与所述第一控制节点和所述第二控制节点通信连接；所述方法还包括：
    所述调度控制节点按照预设的时间间隔获取所述第一控制节点和所述第二控制节点的工作状态信息；
    所述调度控制节点依据所述工作状态信息调整所述第一控制节点对应的所述第一伺服节点的数量及所述第二控制节点对应的所述第二伺服节点的数量。
PCT/CN2019/092124 2018-06-20 2019-06-20 分布式多节点控制系统及方法 WO2019242696A1 (zh)

Priority Applications (4)

Application Number Priority Date Filing Date Title
JP2020568673A JP7507098B2 (ja) 2018-06-20 2019-06-20 分散型マルチノード制御システム及び方法
EP19821703.6A EP3812856A4 (en) 2018-06-20 2019-06-20 DISTRIBUTED AND PROCESS MULTI-NODE CONTROL SYSTEM
KR1020207037243A KR20210022003A (ko) 2018-06-20 2019-06-20 분산식 다중 노드 제어 시트템 및 방법
US17/054,410 US11681271B2 (en) 2018-06-20 2019-06-20 Distributed multi-node control system and method, and control node

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201810637356.4 2018-06-20
CN201810637356.4A CN108614460B (zh) 2018-06-20 2018-06-20 分布式多节点控制系统及方法

Publications (1)

Publication Number Publication Date
WO2019242696A1 true WO2019242696A1 (zh) 2019-12-26

Family

ID=63665428

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/092124 WO2019242696A1 (zh) 2018-06-20 2019-06-20 分布式多节点控制系统及方法

Country Status (6)

Country Link
US (1) US11681271B2 (zh)
EP (1) EP3812856A4 (zh)
JP (1) JP7507098B2 (zh)
KR (1) KR20210022003A (zh)
CN (1) CN108614460B (zh)
WO (1) WO2019242696A1 (zh)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108614460B (zh) * 2018-06-20 2020-11-06 东莞市李群自动化技术有限公司 分布式多节点控制系统及方法
WO2023174550A1 (en) * 2022-03-18 2023-09-21 Telefonaktiebolaget Lm Ericsson (Publ) Methods, computing nodes and system for controlling a physical entity

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7136725B1 (en) * 2001-06-21 2006-11-14 Paciorek Ronald R Load shed notification method, product, and apparatus
CN101174960A (zh) * 2006-10-30 2008-05-07 丹东华通测控有限公司 冗余式智能型网络通讯控制器
CN101226397A (zh) * 2008-02-04 2008-07-23 南京理工大学 高可靠性分布式以太网测控系统
CN101620437A (zh) * 2008-07-02 2010-01-06 中国铝业股份有限公司 一种生产网络的连接方法及生产网络连接系统
CN104898481A (zh) * 2015-05-05 2015-09-09 湘潭大学 一种并联逆变器动态重构方法
CN105824303A (zh) * 2016-05-17 2016-08-03 上海颖电控制技术有限公司 一种基于物联网的分布式智能仪表控制系统及其方法
CN108614460A (zh) * 2018-06-20 2018-10-02 东莞市李群自动化技术有限公司 分布式多节点控制系统及方法

Family Cites Families (26)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH08179816A (ja) * 1994-12-26 1996-07-12 Shimadzu Corp 分散型制御システム
CN1273890C (zh) * 2004-04-30 2006-09-06 浙江大学 Arm处理器架构的微内核设计方法
JP2006059308A (ja) 2004-08-17 2006-03-02 Hiroki Maruchi 汎用化されリアルタイム可能な情報処理装置
US9201703B2 (en) 2006-06-07 2015-12-01 International Business Machines Corporation Sharing kernel services among kernels
CN101662551B (zh) * 2008-08-29 2012-02-22 深圳市东进通讯技术股份有限公司 企业融合通信系统
CN102117061B (zh) * 2009-12-31 2014-09-17 北京国电智深控制技术有限公司 一种分布式控制系统
US9471532B2 (en) * 2011-02-11 2016-10-18 Microsoft Technology Licensing, Llc Remote core operations in a multi-core computer
DE102011107169A1 (de) * 2011-07-13 2013-01-17 Kuka Roboter Gmbh Steuerung eines Roboter
GB2501676A (en) 2012-03-30 2013-11-06 Torquing Technology Ltd Autonomous cell control system
US8768492B2 (en) 2012-05-21 2014-07-01 Tait Towers Manufacturing Llc Automation and motion control system
JP2015197802A (ja) 2014-04-01 2015-11-09 キヤノン株式会社 情報処理装置、情報処理方法及びプログラム
JP6563187B2 (ja) 2014-11-12 2019-08-21 株式会社東芝 分散制御システム、制御装置及び制御方法
US10437212B2 (en) 2015-04-28 2019-10-08 Schneider Electric Systems Usa, Inc. Distributed computing in a process control environment
CN106293893B (zh) 2015-06-26 2019-12-06 阿里巴巴集团控股有限公司 作业调度方法、装置及分布式系统
US10514683B2 (en) 2015-09-16 2019-12-24 Profire Energy, Inc. Distributed networking system and method to implement a safety state environment
CN105183570A (zh) * 2015-09-22 2015-12-23 上海斐讯数据通信技术有限公司 向核心进程发送大量qinq配置数据的系统及其方法
CN106874142B (zh) * 2015-12-11 2020-08-07 华为技术有限公司 一种实时数据容错处理方法及系统
CN105871740B (zh) * 2016-06-27 2019-04-23 联想(北京)有限公司 一种分布式网络的通信方法、系统和控制节点
CN106301522B (zh) * 2016-08-20 2020-05-26 航天恒星科技有限公司 遥感卫星地面站数据接收任务的可视化故障诊断方法及系统
CN106444685A (zh) * 2016-12-06 2017-02-22 中国船舶重工集团公司第七〇九研究所 分布式控制系统及其动态调度资源的方法
JP3211204U (ja) * 2017-04-12 2017-06-29 コリア インスティチュート オブ オーシャン サイエンス アンド テクノロジー 船舶及び海洋プラント生産シミュレーションの統合ソリューションシステム
CN107037795B (zh) * 2017-04-19 2020-07-14 唐志 一种工业过程控制工艺引导系统
US10467056B2 (en) * 2017-05-12 2019-11-05 Google Llc Configuration of application software on multi-core image processor
CN107577185B (zh) * 2017-09-14 2019-10-25 浙江国自机器人技术有限公司 一种任务执行方法及基于多核处理器的控制器
JP6897462B2 (ja) * 2017-09-27 2021-06-30 オムロン株式会社 制御システムおよび通信方法
CN107765613A (zh) * 2017-12-07 2018-03-06 成都量之星科技有限公司 一种智能机器人的分布式控制系统

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7136725B1 (en) * 2001-06-21 2006-11-14 Paciorek Ronald R Load shed notification method, product, and apparatus
CN101174960A (zh) * 2006-10-30 2008-05-07 丹东华通测控有限公司 冗余式智能型网络通讯控制器
CN101226397A (zh) * 2008-02-04 2008-07-23 南京理工大学 高可靠性分布式以太网测控系统
CN101620437A (zh) * 2008-07-02 2010-01-06 中国铝业股份有限公司 一种生产网络的连接方法及生产网络连接系统
CN104898481A (zh) * 2015-05-05 2015-09-09 湘潭大学 一种并联逆变器动态重构方法
CN105824303A (zh) * 2016-05-17 2016-08-03 上海颖电控制技术有限公司 一种基于物联网的分布式智能仪表控制系统及其方法
CN108614460A (zh) * 2018-06-20 2018-10-02 东莞市李群自动化技术有限公司 分布式多节点控制系统及方法

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP3812856A4 *

Also Published As

Publication number Publication date
CN108614460B (zh) 2020-11-06
US20210240163A1 (en) 2021-08-05
EP3812856A4 (en) 2022-06-08
CN108614460A (zh) 2018-10-02
EP3812856A1 (en) 2021-04-28
US11681271B2 (en) 2023-06-20
JP2021530760A (ja) 2021-11-11
KR20210022003A (ko) 2021-03-02
JP7507098B2 (ja) 2024-06-27

Similar Documents

Publication Publication Date Title
CN105279603B (zh) 可动态配置的大数据分析系统及方法
US9531636B2 (en) Extending processing capacity of server
JP2020518065A (ja) ジョブサーバを使用した大規模な分散システムでの機械学習モデルのトレーニング
JP2022008781A (ja) 分散型トレーニング方法、システム、デバイス、記憶媒体、及びプログラム
KR102428091B1 (ko) 키 밸류 장치를 위한 애플리케이션 인식 입출력 완료 모드 변환기의 방법
EP3126975A1 (en) Dynamically identifying target capacity when scaling cloud resources
WO2019242696A1 (zh) 分布式多节点控制系统及方法
CN102521051B (zh) 应用于图算法的Map Reduce系统中的任务调度方法、装置和系统
EP3301636A1 (en) System and method for smart grid dynamic regulation pools
US20160091889A1 (en) Numerical control system
CN106293893A (zh) 作业调度方法、装置及分布式系统
CN103942097A (zh) 一种数据处理方法、装置及具备相应装置的计算机
CN105162632A (zh) 一种服务器集群故障自动处理系统
CN111443870B (zh) 一种数据处理的方法、设备及存储介质
CN105589748A (zh) 一种业务请求处理方法及装置
Yin et al. Real-time task processing for spinning cyber-physical production systems based on edge computing
CN110114732A (zh) 可编程控制器、管理装置和控制系统
CN110320837A (zh) 一种可边缘计算的工业电脑
CN116700933B (zh) 一种面向异构算力联邦的多集群作业调度系统和方法
CN105159706A (zh) 一种流程化程序页面配置的执行方法及系统
Abouee-Mehrizi et al. Exact analysis of capacitated two-echelon inventory systems with priorities
Meng-Meng et al. A task scheduling approach for real-time stream processing
CN110161893A (zh) 从机装置、控制系统、响应数据的通信方法以及存储介质
JP2019036020A (ja) 制御システム
KR102553966B1 (ko) 에너지관리시스템에서의 서버장치 및 이의 동작방법

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19821703

Country of ref document: EP

Kind code of ref document: A1

ENP Entry into the national phase

Ref document number: 2020568673

Country of ref document: JP

Kind code of ref document: A

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 2019821703

Country of ref document: EP

Effective date: 20210120