An information-driven intelligent internet-of-things autonomous control method and node

Abstract

The present disclosure relates to an information-driven intelligent Internet of Things autonomous control method and node. The method comprises: caching measurement and control information obtained from the Internet of Things in a receiving information endpoint; obtaining a first control signal by intelligently analyzing, intelligently deciding and converting the measurement and control information, and caching the first control signal in a first cache; processing a second control signal according to a signal self-loop iteration processing mechanism to obtain a third control signal, and caching the third control signal in a second cache; performing physical mapping processing on a fourth control signal to obtain a device control signal; caching first feedback information in a sending information endpoint; feeding back a device state signal and the fourth control signal in the first cache; performing informatization processing on a fifth control signal to obtain second feedback information, and caching the second feedback information in the sending information endpoint; and sending the feedback information cached in the sending information endpoint to the Internet of Things for sharing. The present disclosure can achieve the intelligent Internet of Things effect of "direct interconnection and active interaction".

Description

Technical Field

[0001] The present disclosure relates to the field of distributed intelligent measurement and control technology, and in particular to an information-driven intelligent Internet of Things autonomous control method and node. Background Art

[0002] In the era of Industry 4.0, intelligent IoT distributed measurement and control systems have become a key technology in fields such as intelligent manufacturing and new energy. Traditional IoT systems, whether focused on sensing and limited to monitoring but without control, or IoT-based network control systems with both monitoring and control capabilities, are centered around various forms of "central controllers" and rely on "instructions" to enable collaboration between different measurement and control nodes (or functional modules) within the system. Examples include programmable logic controller (PLC) industrial automation control systems and the various networked control systems (NCS) derived from them.

[0003] In these traditional IoT systems, the central controller inevitably becomes the weakest link in system reliability, significantly impacting system reliability. Furthermore, when the same functional modules are used in different control systems, customized programming is required to adapt to varying system requirements and application scenarios. This results in long development cycles and high costs, as well as poor system inheritability and replicability, creating a bottleneck for the rapid development of IoT technology. Therefore, achieving intelligent IoT has become a pressing technical challenge. Summary of the Invention

[0004] This disclosure proposes an information-driven intelligent Internet of Things autonomous control method and node, which can achieve the intelligent Internet of Things effect of direct interconnection and autonomous interaction.

[0005] According to one aspect of the present disclosure, a method for autonomous control of an intelligent IoT based on information drive is provided, the method comprising:

[0006] Cache the measurement and control information obtained from the Internet of Things in the receiving endpoint;

[0007] In the information processing step, a first control signal is obtained by performing intelligent analysis, intelligent decision-making and conversion processing on the measurement and control information, and the first control signal is cached in a first cache;

[0008] In the signal processing step, the second control signal is processed according to a signal self-loop iterative processing mechanism to obtain a third control signal, and the third control signal is cached in a second cache, and the second control signal is obtained from the first cache;

[0009] In the physical mapping step, the fourth control signal is physically mapped to obtain a device control signal T, where the device control signal represents a physical control signal capable of directly controlling the controlled device, and the fourth control signal comes from the second cache;

[0010] Obtaining first feedback information in the information processing step and buffering it in the information sending endpoint;

[0011] In the control feedback link, the device status signal and the fourth control signal are fed back and cached in the first cache, wherein the device status signal represents a physical status signal that can directly reflect the working status of the controlled device;

[0012] In the control feedback link, the fifth control signal is subjected to information processing to obtain second feedback information, and the second feedback information is cached in the information sending endpoint, and the fifth control signal is obtained from the first cache;

[0013] The feedback information cached in the information sending endpoint is sent to the Internet of Things for sharing.

[0014] In one possible implementation, the information processing link includes intelligent control algorithm processing and information signal conversion. In the information processing link, obtaining a first control signal by performing intelligent analysis, intelligent decision-making, and conversion processing on the measurement and control information, and caching the first control signal in a first cache, includes:

[0015] performing the intelligent control algorithm processing on the measurement and control information stored in the information receiving endpoint based on first configuration parameters to obtain control decision information, wherein the first configuration parameters are used to configure the intelligent control algorithm used when performing the intelligent control algorithm processing and operating parameters of the intelligent control algorithm used;

[0016] The control decision information is converted into the information signal based on the second configuration parameter to obtain the first control signal, and the first control signal is cached in the first cache, wherein the second configuration parameter is used to configure the information signal conversion method and effect adopted when performing the information signal conversion.

[0017] In a possible implementation, the signal processing step includes routing selection based on a signal router and computation processing based on a signal operator;

[0018] In the signal processing step, processing the second control signal according to a signal self-loop iterative processing mechanism to obtain a third control signal, and buffering the third control signal in a second buffer, includes:

[0019] configuring the signal router based on a third configuration parameter, and configuring the signal operator based on a fourth configuration parameter, wherein the third configuration parameter is used to configure a transfer path for transferring the control signal stored in the first cache from the first cache to the second cache, and the fourth configuration parameter is used to configure a signal operation method and effect used when performing the signal operation processing;

[0020] inputting the second control signal into the signal router to control the second control signal to transfer according to the transfer path configured by the third configuration parameter, obtaining the third control signal, and storing the third control signal in the second cache;

[0021] Among them, the third control signal includes the fourth control signal and the sixth control signal, the fourth control signal indicates a control signal that can directly perform the physical mapping processing, and the sixth control signal indicates a control signal that needs to enter the signal operator to continue the signal self-loop iterative processing; after the sixth control signal enters the signal operator, it can be operated and processed according to the signal operation method configured by the fourth configuration parameter to obtain a seventh control signal, and the seventh control signal is stored in the first cache.

[0022] In a possible implementation, the physical mapping link is used to map the digital control signal in the digital world into the physical control signal required by the controlled device in the physical world;

[0023] In the physical mapping link, performing physical mapping processing on the fourth control signal to obtain a device control signal includes:

[0024] The fourth control signal is physically mapped based on the fifth configuration parameter to obtain the device control signal, and the fifth configuration parameter is used to configure the mapping method and effect adopted when performing the physical mapping.

[0025] In one possible implementation, the signal self-loop iteration mechanism is composed of the first cache, the signal router, the second cache and the signal operator. The control signal from the second cache that needs to participate in the loop iteration processing is processed by the signal operator, enters the first cache again, and is routed by the signal router again, and reaches the second cache through different transfer paths, through one or more cycles until the preset conditions are met.

[0026] According to another aspect of the present disclosure, there is provided an information-driven intelligent IoT autonomous control node, the node comprising:

[0027] The information terminal can be directly connected to the Internet of Things and is used to cache the measurement and control information obtained from the Internet of Things in the receiving information endpoint, and send the feedback information cached in the sending information endpoint to the Internet of Things for sharing;

[0028] The signal terminal is directly connected to the controlled device and is used to send device control signals to the controlled device and receive status signals of the controlled device;

[0029] a processing module connected between the information terminal and the signal terminal, configured to, in an information processing phase, perform information processing on the measurement and control information through intelligent analysis, intelligent decision-making, and conversion processing to obtain a first control signal, and cache the first control signal in the first cache; in a signal processing phase, perform signal processing on the second control signal according to a signal self-loop iterative processing mechanism to obtain a third control signal, and cache the third control signal in a second cache, where the second control signal is from the first cache; in a physical mapping phase, perform physical mapping processing on the fourth control signal to obtain a device control signal, where the device control signal represents a physical control signal capable of directly controlling a controlled device, and the fourth control signal is from the second cache; obtain first feedback information in the information processing phase and cache it in the information sending endpoint; in a control feedback phase, feed back and cache a device status signal and the fourth control signal in the first cache, where the device status signal represents a physical status signal capable of directly reflecting the operating status of the controlled device; and in the control feedback phase, perform information processing on the fifth control signal to obtain second feedback information, and cache the second feedback information in the information sending endpoint, where the fifth control signal is from the first cache.

[0030] In one possible implementation, the node has a system-level information feedback function, and can feed back its control operation results or status information to the Internet of Things to drive other nodes in the Internet of Things to perform the collaborative work behavior required by the system, thereby realizing information-driven system-level intelligent Internet of Things autonomous control.

[0031] In one possible implementation, each node connected to the Internet of Things can achieve intelligent, autonomous and collaborative control simply by being driven by the IoT's measurement and control information, without the need for any center or command coordination.

[0032] In the disclosed embodiments, on the one hand, measurement and control information obtained from the Internet of Things can be stored in the receiving information endpoint, and by performing information processing, signal processing, and physical mapping on this measurement and control information, physical control signals capable of directly controlling the controlled devices can be autonomously generated. On the other hand, feedback information cached in the sending information endpoint can be sent to the Internet of Things for sharing. In this way, decentralized and de-instructed intelligent Internet of Things control can be achieved without relying on any central controller in the system and any instructions issued by it, achieving the effect of directly interconnected and actively interactive intelligent Internet of Things, greatly reducing the difficulty of designing and implementing the Internet of Things measurement and control system, and significantly improving its system reliability.

[0033] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, rather than limiting the present disclosure. Other features and aspects of the present disclosure will become clear from the following detailed description of exemplary embodiments with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings herein are incorporated into and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and, together with the specification, are used to explain the technical solutions of the present disclosure.

[0035] Figure 1 A schematic diagram of an information-driven intelligent IoT autonomous control method according to an embodiment of the present disclosure is shown.

[0036] Figure 2 A schematic diagram of an intelligent control algorithm processing module according to an embodiment of the present disclosure is shown.

[0037] Figure 3 A schematic diagram showing an information signal conversion module according to an embodiment of the present disclosure is shown.

[0038] Figure 4 A schematic diagram of a signal router according to an embodiment of the present disclosure is shown.

[0039] Figure 5 A schematic diagram of a signal operator according to an embodiment of the present disclosure is shown.

[0040] Figure 6 A schematic diagram of a digital-physical mapping module according to an embodiment of the present disclosure is shown.

[0041] Figure 7 A schematic diagram of the structure of an information-driven intelligent IoT autonomous control node according to an embodiment of the present disclosure is shown.

[0042] Figure 8 A schematic diagram of an Internet of Things system according to an embodiment of the present disclosure is shown.

[0043] Figure 9A flow chart of an information-driven intelligent IoT autonomous control method according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0044] Various exemplary embodiments, features, and aspects of the present disclosure will be described in detail below with reference to the accompanying drawings. The same reference numerals in the accompanying drawings represent elements with the same or similar functions. Although various aspects of the embodiments are shown in the accompanying drawings, the drawings are not necessarily drawn to scale unless otherwise indicated.

[0045] The word “exemplary” is used exclusively herein to mean “serving as an example, example, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments.

[0046] The term "and / or" herein simply describes an association relationship between associated objects, indicating that three relationships can exist. For example, "A and / or B" can represent the existence of three situations: A alone, A and B simultaneously, and B alone. Furthermore, the term "at least one" herein refers to any combination of at least two of any one or more of a plurality of items. For example, "at least one of A, B, and C" can represent any one or more elements selected from the set consisting of A, B, and C.

[0047] In addition, numerous specific details are provided in the following detailed description to better illustrate the present disclosure. Those skilled in the art will appreciate that the present disclosure can be practiced without certain specific details. In some instances, methods, means, components, and circuits well known to those skilled in the art are not described in detail in order to highlight the main points of the present disclosure.

[0048] The disclosed embodiments provide an information-driven autonomous control method for intelligent IoT. On the one hand, the method can store the measurement and control information obtained from the IoT in an information receiving endpoint, and by performing information processing, signal processing, and physical mapping on the measurement and control information, autonomously generate physical control signals that can directly control the controlled device. On the other hand, the cached feedback information of the information sending endpoint can be sent to the IoT for sharing. Based on this method, decentralized and de-instructed intelligent IoT control can be achieved without relying on any central controller in the IoT measurement and control system and any instructions issued by it, achieving the effect of directly interconnected and actively interactive intelligent IoT, which can greatly reduce the design and real-time difficulty of the IoT measurement and control system and significantly improve its system reliability.

[0049] The information-driven intelligent Internet of Things autonomous control method provided by the embodiments of the present disclosure is designed in an object-oriented manner (i.e., the controlled device), can extract fixed processing procedures and calculation formulas from each information and / or signal processing link required by a commonly used controlled device, and solidify the fixed processing procedures and calculation formulas in the form of firmware in each functional module of the method. The information and / or signal processing procedures and processing effects can be customized through simple parameter configuration, so that the personalized function customization can be realized in a "zero code" programming manner, and the problems of long development cycle, high development cost, poor system inheritance and replicability of the existing Internet of Things measurement and control system are effectively solved.

[0050] The measurement and control information related by the embodiments of the present disclosure can include one or more of measurement information, state information and control information, and of course can also include other information from the Internet of Things, which is not limited by the embodiments of the present disclosure.

[0051] Figure 1 A schematic diagram of the information-driven intelligent Internet of Things autonomous control method according to the embodiments of the present disclosure is shown. As shown in Figure 1 , the measurement and control information from the Internet of Things is first cached in the receiving information endpoint (also referred to as information endpoint R), and the control signal (referred to as first control signal) obtained after the information processing link (i.e., intelligent analysis, intelligent decision and conversion processing) is cached in the first cache (also referred to as control signal Buf1). The control signal (referred to as second control signal) in the first cache is then processed through the signal processing link (i.e., signal processing according to the signal self-loop iteration processing mechanism), and the control signal (referred to as third control signal) obtained after the processing is cached in the second cache (also referred to as control signal Buf2). Finally, a part of the third control signal in the second cache (referred to as fourth control signal) is processed through the physical mapping link (i.e., physical mapping processing), and the physical control signal (referred to as device control signal, corresponding to Figure 1 physical signal T in FIG. 1) capable of directly controlling the controlled device is obtained. At the same time, the feedback information (including first feedback information and second feedback information) is generated based on the control decision information and the control signal in the first cache, and is fed back to the Internet of Things in the form of a sending information endpoint (also referred to as information endpoint S), so as to further realize the information-driven intelligent Internet of Things autonomous control function at the system level of the Internet of Things.

[0052] As shown in Figure 1 , the information-driven intelligent Internet of Things autonomous control method mainly involves: the main information or signal processing links such as the information processing link, the signal processing link, the physical mapping link and the control feedback link, and a plurality of information or signal buffers between these links, such as the buffer: control signal Buf1 between the information processing link and the signal processing link, and the buffer: control signal Buf2 between the signal processing link and the physical mapping link.

[0053] In one possible implementation, the information processing step includes intelligent control algorithm processing and information signal conversion. In other words, Figure 1 The information processing link shown mainly involves two functional modules, namely the intelligent control algorithm module and the information signal conversion module. Among them, the main function of the intelligent control algorithm module is to perform intelligent control algorithm processing on the measurement and control information stored in the information endpoint R, generate corresponding control decision information, and select and configure the intelligent control algorithm through parameter C0 (called the first parameter). The main function of the information signal conversion module is to convert the above control decision information into the corresponding control signal (i.e., the first control signal), and cache it in the control signal Buf1 (i.e., the first cache), and can configure its conversion method and effect through parameter C1 (called the second parameter). Of course, the information processing link can also involve other functional modules, which can be set according to needs, and this is not limited to the embodiment of the present disclosure.

[0054] The first parameter can be used to configure the intelligent control algorithm and its operating parameters when performing intelligent control algorithm processing, and the second parameter can be used to configure the information signal conversion method and effect when performing information signal conversion.

[0055] Figure 2 Schematic diagram of the intelligent control algorithm module according to the embodiment of the present disclosure is shown. Figure 2 As shown in the figure, the intelligent control algorithm module integrates common control algorithms including but not limited to neural networks, fuzzy control, proportional-integral-differential (PID) control and direct mapping. Since these control algorithms have relatively fixed calculation formulas and calculation processes, they can be solidified in the control algorithm processing module in the form of firmware. When these control algorithms are applied in different scenarios, the main difference is only in the different operating parameters. For example, when the PID algorithm is applied in different scenarios, the difference is usually in K P , K I and K D The values ​​are different. Therefore, in the embodiment of the present disclosure, in different application scenarios, different intelligent control algorithms can be selected through the parameter C0 (i.e., the first configuration parameter), and the correlation coefficient and control characteristics of the selected intelligent control algorithm can be configured, thereby realizing the "zero-code" programming and parameter personalized function customization of the intelligent control algorithm under information-driven conditions. In addition, for measurement and control information that does not require information-level processing, a direct mapping method can be selected to pass the information backward, ultimately realizing the personalized function customization transformation from external measurement and control information from the Internet of Things to local internal control decision information R'.

[0056] Parameter C0 can be determined by the application scenario. The corresponding relationship between the application scenario and parameter C0 can be set as needed, and the specific setting can be made by the user as needed. Figure 2 As shown, the parameters C0 may include algorithm selection parameters and algorithm operation parameters.

[0057] Figure 3 FIG. 1 is a schematic diagram showing an information signal conversion module according to an embodiment of the present disclosure. Figure 3 As shown, the information signal conversion module integrates information signal conversion units with different principles and functions, including but not limited to D trigger, T trigger, monostable trigger and threshold comparison. The basic working principle of each information signal conversion unit is to reconstruct the corresponding control signal (i.e., the first control signal) based on the input control decision information R' (including R1', R2', R3' and R4', etc.) and other configuration information (not shown, input as needed, for example, it can be a measurement and control cycle, etc.). The first control signal (including D[k], D[k+1], D[k+2] and D[k+3], etc.) output by the information signal conversion module can be temporarily stored in the control signal Buf1 (i.e., the first cache). Similar to the personalized function customization of the control algorithm processing module, the information signal conversion module can customize its conversion principle and conversion effect (i.e., the information signal conversion method) through the parameter C1 (i.e., the second configuration parameter), thereby realizing the "zero code" programming and parameter customization of the information signal conversion function. For example, Figure 3 The main function of the threshold comparison unit shown in FIG is to reduce the dimension of the input analog control decision information R' to form the subsequent required I / O control signal (such as Figure 3 The comparison threshold required here can come from the parameter C1 or from the control decision information R' to meet the application requirements of different scenarios, which is not limited in the embodiment of the present disclosure.

[0058] The parameter C1 may be determined by the application scenario, wherein the corresponding relationship between the application scenario and the parameter C1 may be set as needed, and may be specifically set by the user as needed.

[0059] like Figure 1 As shown, the first control signal is cached in the first cache. Of course, in addition to the first control signal, the first cache also stores other control signals, such as the fourth control signal, the seventh control signal, and the device status signal. The generation process of these signals will be described later and will not be repeated here. In the embodiment of the present disclosure, the second control signal comes from the first cache. It can be seen that after the second control signal enters the signal processing link, it can be processed according to the signal self-loop processing mechanism to obtain the third control signal.

[0060] In a possible implementation, the signal processing step includes routing selection based on a signal router and computation processing based on a signal operator. In other words, Figure 1 The signal processing link shown mainly involves two functional modules: a signal router and a signal operator. The main function of the signal router is to determine the transfer path of the control signal from the control signal Buf1 to the control signal Buf2 according to the parameter C2 (i.e., the third configuration parameter). The main function of the signal operator is to realize the control signal operation processing from the control signal Buf2 to the control signal Buf1. Here, the signal operation methods used in the control signal operation processing include but are not limited to signal operation methods such as logical operations, sequential logic operations, and timing counting. Of course, the signal processing link can also involve other functional modules, which can be set as needed, and the embodiments of the present disclosure are not limited to this.

[0061] The third control signal represents a control signal obtained by processing the second control signal. The third control signal is cached in the second cache. Figure 1 As shown, after the third control signal enters the second cache, it is divided into two parts for subsequent processing. Specifically, a part of the control signal (i.e., the sixth control signal) emitted from the control signal Buf2 is processed by the signal operator to obtain the seventh control signal, and the seventh control signal can enter the control signal Buf1 again, and can again pass through the signal router through different transfer paths to reach the control signal Buf2, thus forming an iterative processing mechanism for signal self-loop. The number of loop iterations can be set as needed. During the entire signal self-loop process, only simple configuration parameters C2 (i.e., the third configuration parameter) and C3 (i.e., the fourth configuration parameter) are required, that is, the personalized function customization of the process sequence and process effect within the entire signal processing link can be achieved in a "zero-code" programming manner to meet the complex signal processing requirements required by different application scenarios.

[0062] The third configuration parameter can be used to configure a transfer path for the control signal stored in the first cache to be transferred from the first cache to the second cache. The fourth configuration parameter can be used to configure a signal operation method and effect used in signal operation processing.

[0063] Figure 4 The schematic diagram of the signal router according to the embodiment of the present disclosure is shown. The signal router is equivalent to the signal matrix switch in terms of logical function. The control signal from the control signal Buf1 (ie, the second control signal, such as Figure 4 The signals input from different columns of the signal matrix switch (i.e., the third control signal) are sequentially buffered into the control signal Buf2 (as shown in D[0] to D[5] in FIG1 ). Figure 4D'[0] to D'[4] shown in the figure). In the embodiment of the present disclosure, the parameter C2 is used to determine whether the intersections of the rows and columns of the signal matrix switch are connected together. Figure 4 As shown, it is assumed that the intersections of rows and columns are not connected. After parameter configuration, the white circles indicate that the rows and columns are connected, thus forming a specific signal transfer path, that is, the control signal input from this row will be transferred to this column and finally stored in the control signal Buf2. For example, Figure 4 D[0] becomes D'[1] after passing through the signal switch and is stored in the control signal Buf2. D[1] becomes D'[5] (not shown) after passing through the signal switch and is stored in the control signal Buf2. It is worth noting that each control signal position in the control signal Buf2 can only receive one control signal from the control signal Buf1, while each control signal from the control signal Buf1 can flow to multiple control signal positions in the control signal Buf2 at the same time, thereby realizing personalized transfer path control of signal flow in the form of "zero code" programming.

[0064] Figure 5 FIG. 1 is a schematic diagram showing a signal operator according to an embodiment of the present disclosure. Figure 5 As shown, part of the control signal Buf2 (ie, the sixth control signal, for example Figure 5 D'[0], D'[a-1] to D'[a]-D'[p-1]) will be directly input into the signal operator, processed by different signal operation methods (ie, the seventh control signal is obtained), and then enter the control signal Buf1 again (such as Figure 5 D[j], D[u-1], D[u] to D[k-1], etc. in the signal operator. The signal operator integrates signal operation methods including but not limited to combinational logic, sequential logic, and timing counting. Since the processing flow and logical expression of these signal operation methods are relatively fixed, they can be solidified in the signal operator in the form of firmware. When in use, only parameter C3 (i.e., the fourth configuration parameter) needs to be changed to meet the personalized signal processing requirements of different application scenarios. For example, if Figure 5 As shown, the control signals D'[0] and D'[a-1] from the control signal Buf1 are directly input into the combinational logic operation unit for combinational logic operation processing. The combinational logic operation unit is configured with different logical operation relationships through parameter C3, thereby achieving universal logical operation on the input control signals. The operation results D[j] and D[u-1] of the combinational logic operation unit are then stored in the control signal Buf1 again.

[0065] In one possible implementation, the signal self-loop iteration mechanism is composed of a first cache, a signal router, a second cache, and a signal operator. The control signal from the second cache that needs to participate in the loop iteration processing is processed by the signal operator, enters the first cache again, and is routed through the signal router again. It reaches the second cache through different transfer paths and goes through one or more cycles until the preset conditions are met.

[0066] Among them, the signal router and signal operator can refer to Figure 4 and Figure 5 I will not elaborate on this here. The preset conditions can be set as needed, and can be set specifically according to the scene. It is understandable that for scenes with more complex signal processing, the number of cycles is greater, and for scenes with simpler signal processing, the number of cycles is less. Figure 4 The signal router and Figure 5 The combined application of the signal operators shown can realize complex signal processing processes such as signal self-loop iterative operations that may be required in certain application scenarios.

[0067] In addition, if Figure 1 As shown, there is a part of the control signal Buf2 (ie, the fourth control signal) which can directly enter the subsequent physical mapping link after being processed by the signal operator.

[0068] In one possible implementation, the physical mapping link is used to map the digital control signal in the digital world into the physical control signal required by the controlled device in the physical world. Figure 1 The physical mapping link shown mainly involves the digital-physical mapping module, whose main function is to map the digital control signal in the digital world into the physical control signal required by the controlled device in the physical world, thereby directly controlling the controlled device. It can also achieve personalized customization of the physical signal output mode and output effect by simply configuring parameter C4 (the fifth parameter) in a "zero-code" programming manner.

[0069] Figure 6A schematic diagram of a digital-physical mapping module according to an embodiment of the present disclosure is shown. Taking into account the commonly used interface forms of controlled devices in the industrial field, the digital control signal (i.e., the fourth control signal) from the control signal Buf2 needs to be mapped in some way before it can be converted into a physical control signal (i.e., device control signal) that the controlled device can directly receive. The physical mapping module contains a variety of mapping methods for different functions, including but not limited to physical mapping methods such as switch quantity → dry contact, switch quantity → wet contact, switch quantity → communication protocol, analog quantity → voltage signal, analog quantity → current signal, analog quantity → PWM signal, analog quantity → communication protocol, etc. In response to the different interface requirements of the controlled device, the most appropriate physical mapping method can be selected through parameter C4 (i.e., the fifth configuration parameter) to meet the personalized function customization of its physical control signal. For example, if the controlled device is a relay interface, the mapping method of switch quantity → dry contact can be selected through the unit selection parameter, and the personalized signal output characteristics such as the pulse width (i.e., operating parameters) of the corresponding dry contact pulse signal can be further customized through the unit operation parameter, and finally the physical control signal required by the controlled device is output.

[0070] In the embodiment of the present disclosure, Figure 1 As shown, the feedback information stored in the information-sending endpoint includes first feedback information and second feedback information. The first feedback information is feedback information obtained when processing information at the local information level. The second feedback information is feedback information obtained by performing information processing on the fifth control signal. The fifth control signal originates from the first cache. As previously described, the signals in the first cache, in addition to the first control signal, also include a device status signal from the controlled device, a fourth control signal from the second cache, and a seventh control signal generated through signal self-loop iterative processing. The device status signal represents a physical status signal that directly reflects the operating status of the controlled device. The fifth control signal can be a portion of these signals, and the specific signals in the first cache used as the fifth control signal can be determined as needed. In one example, signals in the first cache other than the first control signal can be used as the fifth control signal. Of course, all signals in the first cache can also be used as the fifth control signal, and this is not limited in the present embodiment. The first feedback information and the second feedback information are both cached in the information-sending endpoint, i.e., the information endpoint S. The feedback information cached in the information-sending endpoint (at least including the first and second feedback information) can be sent to the Internet of Things for sharing.

[0071] The control feedback link mainly involves the physical-digital mapping module, the internal feedback path of the digital signal, and the signal information conversion module. Among them, the main function of the physical-digital mapping module is to convert the physical signal in the physical world (representing the working state of the controlled device) into the digital control signal in the digital world (specifically Figure 1The main function of the digital signal internal feedback path is to transfer the signal in the control signal Buf2 (essentially a digital control signal, specifically the fourth control signal) directly to the control signal Buf1 cache. Based on the above digital signal internal feedback path, as shown in FIG. Figure 1 As shown, the control signals at each layer can be aggregated into the control signal Buf1. On the one hand, they can continue to participate in the signal self-loop iterative operation in the signal processing link, achieving the closed-loop processing effect within the method. On the other hand, after the information processing of the signal information conversion module in this link, the second feedback information is obtained and further fed back to the Internet of Things in the form of information endpoint S, realizing information feedback and multi-device collaborative control at the IoT system level. The main function of the signal information conversion module is to perform information processing on the signal in the control signal Buf1 (essentially a digital control signal) and then further feed it back to the Internet of Things in the form of information endpoint S.

[0072] Figure 7 The schematic diagram of the structure of the information-driven intelligent IoT autonomous control node according to the embodiment of the present disclosure is shown. The information-driven intelligent IoT autonomous control node can be used to control the controlled devices in the Internet of Things. The information-driven intelligent IoT autonomous control node is based on Figure 1 The intelligent IoT autonomous control method based on information drive is shown in Figure 1. Figure 7 As shown in the figure, the information-driven intelligent IoT autonomous control node includes an information terminal, a signal terminal and a processing module.

[0073] like Figure 7 As shown, the information terminal is directly connected to the Internet of Things and is used to cache measurement and control information obtained from the Internet of Things in the receiving information endpoint and send feedback information cached in the sending information endpoint to the Internet of Things for sharing. The information terminal can specifically be an interaction unit. The signal terminal is directly connected to the controlled device and is used to send device control signals to the controlled device. The signal terminal can specifically be a signal interface, such as Out1 to Outn, where n represents the number of signal interfaces and is an integer greater than 0.

[0074] a processing module connected between the information terminal and the signal terminal, configured to, in an information processing phase, perform information processing on the measurement and control information through intelligent analysis, intelligent decision-making, and conversion processing to obtain a first control signal, and cache the first control signal in the first cache; in a signal processing phase, perform signal processing on the second control signal according to a signal self-loop iterative processing mechanism to obtain a third control signal, and cache the third control signal in a second cache, where the second control signal is from the first cache; in a physical mapping phase, perform physical mapping processing on the fourth control signal to obtain a device control signal, where the device control signal represents a physical control signal capable of directly controlling a controlled device, and the fourth control signal is from the second cache; obtain first feedback information in the information processing phase and cache it in the information sending endpoint; in a control feedback phase, feed back and cache a device status signal and the fourth control signal in the first cache, where the device status signal represents a physical status signal capable of directly reflecting the operating status of the controlled device; and in the control feedback phase, perform information processing on the fifth control signal to obtain second feedback information, and cache the second feedback information in the information sending endpoint, where the fifth control signal is from the first cache.

[0075] In the disclosed embodiment, the information-driven intelligent IoT autonomous control node has dual-end interface features of both the information end and the signal end. All information-driven intelligent IoT autonomous control nodes can connect to the IoT through the information end, and automatically store the measurement and control information received from the IoT in the receiving information endpoint, or automatically send the measurement and control information and feedback information in the sending information endpoint to the IoT for information sharing. The components that can realize the above functions include but are not limited to various information interaction function modules based on IPT technology (Information Pipeline Technology), such as IPCAN, IPLAN, IPWIFI, etc. The signal end of the information-driven intelligent IoT autonomous control node is generally a personalized signal interface related to the controlled device. The information-driven intelligent IoT autonomous control node can directly connect to the controlled device through the signal end, and its main function is to transmit the physical control signal (i.e., device control signal) required by the controlled device. The signal interface includes but is not limited to I / O wiring terminals, 4-20mA analog signal interface terminals, RS485 bus interface terminals and other wiring terminals or other connectors.

[0076] In one possible implementation, the node has a system-level information feedback function, and can feed back its control operation results or status information to the Internet of Things to drive other nodes in the Internet of Things to perform the collaborative work behavior required by the system, thereby realizing information-driven system-level intelligent Internet of Things autonomous control.

[0077] In one possible implementation, each node connected to the Internet of Things can achieve intelligent autonomous collaborative control simply by being driven by the Internet of Things measurement and control information, without the need for any center or instruction coordination. In other words, the nodes provided in the embodiments of the present disclosure can achieve intelligent autonomous collaborative control by being driven by the Internet of Things measurement and control information without the coordination of any system center and the instructions issued by it. Among them, the center can refer to the system control center (that is, the central controller) of the system, and the instruction can refer to the instruction issued by the central controller.

[0078] In the disclosed embodiment, the information-driven intelligent IoT autonomous control node is distributed and does not require a central controller. All information-driven intelligent IoT autonomous control nodes can be directly connected to the IoT through their information terminals, and directly connected to the controlled devices through their signal terminals. Therefore, the information-driven intelligent IoT autonomous control node can directly obtain various types of information required to control the behavior of the controlled devices from the IoT, and then autonomously form the physical control signals required by the controlled devices within the node through the method described in this article, thereby realizing intelligent autonomous control of the controlled devices. At the same time, its control operation results or status information can also be fed back to the IoT in a timely manner to further drive other nodes in the IoT to perform other collaborative work behaviors required by the system, thereby ultimately achieving the information-driven intelligent IoT autonomous control effect.

[0079] Figure 8 FIG. 1 shows a schematic diagram of an Internet of Things system according to an embodiment of the present disclosure. Figure 8 As shown, in the Internet of Things system, including but not limited to the information-driven intelligent Internet of Things autonomous control node (such as Figure 7 As shown, it is referred to as intelligent IoT control node for short). For example, Figure 8 The intelligent IoT monitoring node shown in the figure does not fall within the scope of the embodiments of the present disclosure. Its function is to obtain corresponding measurement signals from sensors and publish the obtained measurement and control information for sharing in the IoT after intelligent information processing. In this IoT, the functions of each node (including but not limited to intelligent IoT control nodes and intelligent IoT monitoring nodes) are relatively independent. Its information end can be directly connected to the IoT in the form of a standard interface and realize automatic interaction of its measurement and control information. Its signal end can be directly connected to the corresponding controlled device or sensor and other functional components, and can independently complete the corresponding measurement or control function.

[0080] Taking the liquid level control of the sewage pool in a sewage treatment plant as an example, suppose a sewage treatment plant needs to use a variable frequency pump and a fixed frequency pump to achieve equal liquid level control of the sewage pool. Figure 8The sensor 2 connected to the smart IoT monitoring node 2 shown in the figure is a liquid level sensor of the sewage pool, the controlled device 1 connected to the smart IoT control node 1 is a variable frequency pump, and the controlled device 3 connected to the smart IoT control node 3 is a fixed frequency pump.

[0081] The information driven autonomous collaborative control process of the intelligent IoT control node 1 and the intelligent IoT control node 3 is as follows: the intelligent IoT control node 1 (variable frequency pump control node) automatically caches the information such as the liquid level and liquid level change rate obtained from the IoT and from the intelligent IoT monitoring node 2 to the corresponding information endpoints R1 and R2 within the node (refer to Figure 7 ), and at the same time, automatically caches the operating status information obtained from the Internet of Things and from the intelligent Internet of Things control node 3 in its corresponding information endpoint R3, and caches the preset target information of the liquid level control from the Internet of Things in its corresponding information endpoint R4. This node uses the real-time measurement and control information in the information endpoints R1 to R4 to make autonomous decisions based on the above method and realize the start and stop control and speed control of the variable frequency pump connected to it, and publishes its actual operating status to the Internet of Things in the form of information endpoint S. Similarly, the intelligent Internet of Things control node 3 (fixed frequency pump control node) will also automatically cache the liquid level, liquid level change rate and other information obtained from the intelligent Internet of Things monitoring node 2 in its corresponding information endpoints R1 and R2 respectively, and automatically cache the operating status information obtained from the Internet of Things and from the intelligent Internet of Things control node 1 in its corresponding information endpoint R3, and cache the preset target information of the liquid level control from the Internet of Things in its corresponding information endpoint R4. This node uses the measurement and control information from endpoints R1 to R4 to autonomously decide and start / stop the connected fixed-frequency pump based on the aforementioned method. It also publishes its actual operating status to the IoT in the form of endpoint S. As a result, the variable-frequency pump and the fixed-frequency pump will jointly use the preset liquid level control target information from the IoT as their control target, achieving precise liquid level control in the sewage tank through autonomous intelligent collaborative control. This entire process requires no intervention from a central controller or coordinated instructions, and is fully driven by IoT information to achieve autonomous decision-making and control. For example, if intelligent IoT control node 1 learns that the sewage level is rapidly rising and the fixed-frequency pump connected to intelligent IoT control node 3 is not started, it will autonomously increase the speed of the variable-frequency pump. If the liquid level continues to rise, intelligent IoT control node 3 will autonomously start the fixed-frequency pump to help the variable-frequency pump suppress the rise in the liquid level. Since both pumps are operating simultaneously, the liquid level may begin to drop. Upon learning this information, intelligent IoT control node 1 will autonomously reduce the speed of the variable-frequency pump until the liquid level stabilizes near the preset control target. On the contrary, if the sewage level drops rapidly, the intelligent IoT control nodes 1 and 3 will also autonomously make corresponding intelligent control results to achieve the preset liquid level control target.

[0082] Figure 9 A flowchart of an information-driven intelligent Internet of Things autonomous control method according to an embodiment of the present disclosure is shown. The method can be applied to an information-driven intelligent Internet of Things autonomous control node, for example Figure 7 The information-driven intelligent Internet of Things autonomous control node is shown. As Figure 9 As shown, the method can include:

[0083] In step S300, the measurement and control information obtained from the Internet of Things is cached in a receiving information endpoint.

[0084] The measurement and control information can represent relevant information needed when controlling the controlled device. In the embodiment of the present disclosure, as Figure 1 As shown, the information-driven intelligent Internet of Things autonomous control device can include information endpoints. Wherein R1 to Rn are receiving information endpoints for caching measurement and control information, n represents the number of receiving information endpoints for caching measurement and control information, and n is a positive integer. The measurement and control information can represent relevant information needed when controlling the controlled device. For example, the measurement and control information can be liquid level, liquid level change rate, operating state information of other information-driven intelligent Internet of Things autonomous control nodes, liquid level control preset target information, etc. The above are only exemplary descriptions of measurement and control information and are not intended to limit the measurement and control information. In the embodiment of the present disclosure, different information endpoints can cache information with different physical meanings. For example, R1 can cache liquid level information, R2 can cache liquid level change rate information, R3 can cache operating state information, and R4 can cache liquid level control preset target information. The above are only exemplary caching methods of information endpoints and are not intended to limit the specific physical meanings of each information endpoint.

[0085] In step S301, in the information processing link, a first control signal is obtained by intelligently analyzing, intelligently deciding, and converting processing the measurement and control information, and the first control signal is cached in a first cache.

[0086] The first control signal represents a digital control signal for operation. In one possible implementation, the information processing includes intelligent control algorithm processing and information signal conversion. Based on this, step S301 can include: performing the intelligent control algorithm processing on the measurement and control information stored in the information endpoint based on a first configuration parameter to obtain control decision information; performing the information signal conversion on the control decision information based on a second configuration parameter to obtain the first control signal, and caching the first control signal in the first cache.

[0087] In the embodiment of the present disclosure, information processing is divided into two parts, the first part is to perform intelligent control algorithm processing, and the second part is to perform information signal conversion. The result of the intelligent control algorithm processing, that is, the control decision information, is the comprehensive processing result of various information required to complete the control of the controlled device. Taking the variable frequency pump as the controlled device as an example, by making a comprehensive decision on information such as the liquid level, the rate of change of the liquid level, the working status of other pumps, etc., control decision information that can characterize whether the variable frequency pump needs to be started, whether the variable frequency pump needs to be shut down, or whether the speed of the variable frequency pump needs to be adjusted (lowered or increased) is obtained. Since the control decision information cannot be directly processed as a digital signal, it is necessary to convert the decision control signal into an information signal (that is, from information to signal) to facilitate further various digital signal processing including but not limited to timing and combinational logic operations.

[0088] The first configuration parameter is used to configure the intelligent control algorithm used when performing the intelligent control algorithm processing and the operating parameters of the intelligent control algorithm used. The second configuration parameter is used to configure the information signal conversion method and effect used when performing the information signal conversion. Figure 2 As shown, the first configuration parameter (i.e., parameter C0) includes an algorithm selection parameter and an algorithm operation parameter. The algorithm selection parameter can be used to indicate the intelligent control algorithm to be adopted. For example, in a feasible implementation, the algorithm selection parameter can be used to control the algorithm unit to which information flows, thereby realizing the selection of the control algorithm. Figure 3 As shown, the second configuration parameter (i.e., parameter C1) can be used to indicate the information signal conversion method adopted. The first configuration parameter and the second configuration parameter can be determined by the application scenario. The correspondence between the application scenario and the first configuration parameter, as well as the correspondence between the application scenario and the second configuration parameter, can be set as needed, and can be specifically set by the user according to needs.

[0089] The above information processing process can refer to Figure 1 , the intelligent control algorithm processing process can refer to Figure 2 , the information signal conversion process can refer to Figure 3 , I will not go into details here.

[0090] Step S302 : In the signal processing phase, the second control signal is processed according to a signal self-loop iterative processing mechanism to obtain a third control signal, and the third control signal is cached in a second cache.

[0091] The second control signal comes from the first cache, and the specific second control signal can represent the control signal in the first cache. The second control signal includes but is not limited to the first control signal, the fourth control signal, the seventh control signal and the device status signal.

[0092] In a possible implementation, the signal processing includes routing selection based on a signal router and operation processing based on a signal operator. Based on this, step S302 can include: configuring the signal router based on a third configuration parameter and configuring the signal operator based on a fourth configuration parameter; inputting the second control signal into the signal router to control the second control signal to transfer along a transfer path configured by the third configuration parameter, obtaining a third control signal, and storing the third control signal in a second buffer.

[0093] The third control signal includes the fourth control signal and a sixth control signal. The fourth control signal represents a control signal that can directly perform the physical mapping processing. The sixth control signal represents a control signal that needs to enter the signal operator to continue the signal self-loop iteration processing. After the sixth control signal enters the signal operator, the sixth control signal can perform operation processing according to a signal operation mode configured by the fourth configuration parameter to obtain a seventh control signal. The seventh control signal is stored in the first buffer.

[0094] The third configuration parameter is used to configure a transfer path of the control signal stored in the first buffer from the first buffer to the second buffer. The fourth configuration parameter is used to configure a signal operation mode and effect used when the signal operation processing is performed. The third configuration parameter and the fourth configuration parameter can also be determined by an application scenario, and a corresponding relationship can be set as needed.

[0095] In the embodiments of the present disclosure, the signal processing of the second control signal is divided into two parts. The first part is control signal transfer, and the second part is control signal operation. The two parts are implemented by a signal router and a signal operator respectively. The main function of the signal router is to determine a transfer path of the control signal from the first buffer to the second buffer according to a third configuration parameter. The control signal stored in the first buffer is referred to as the second control signal, and the control signal stored in the second buffer is referred to as the third control signal.

[0096] In the embodiments of the present disclosure, a part of the control signals in the second buffer (that is, the sixth control signal) obtains a seventh control signal after being processed by the signal operator. The seventh control signal can enter the first buffer again and can reach the second buffer again through a different transfer path by the signal router. Thus, a loop iteration processing of the control signal is formed. Another part of the control signals in the second buffer (that is, the fourth control signal) can directly perform the subsequent physical mapping processing after being processed by the signal operator. In the embodiments of the present disclosure, the control signals in the second buffer are referred to as the third control signal. The control signals in the third control signal that do not enter the first buffer again are referred to as the fourth control signal. The control signals in the third control signal that enter the first buffer again are referred to as the sixth control signal.

[0097] The above signal processing process can refer to Figure 1 , signal router can refer to Figure 4 , the signal operator can refer to Figure 5 , I will not go into details here.

[0098] Step S303: In the physical mapping step, physical mapping is performed on the fourth control signal to obtain a device control signal.

[0099] The device control signal represents a physical control signal that can directly control the controlled device. The fourth control signal comes from the second cache. The physical mapping can convert the digital control signal into a physical control signal that is compatible with the interface of the controlled device.

[0100] In one possible implementation, the physical mapping is used to map the digital control signal in the digital world into the physical control signal required by the controlled device in the physical world. Based on this, step S303 may include: performing physical mapping on the fourth control signal based on the fifth configuration parameter to obtain the device control signal. The fifth configuration parameter is used to configure the mapping method and effect adopted when performing the physical mapping. The fifth configuration parameter can be determined by the application scenario. Specifically, Figure 6 As shown, the fifth configuration parameter (ie, C4) may include a unit selection parameter and a unit operation parameter, wherein the unit selection parameter may be used to indicate the selected mapping mode, and the unit operation parameter may be used to indicate the operation parameter of the selected mapping mode.

[0101] Step S304: obtaining first feedback information in the information processing link and buffering it in the information sending endpoint.

[0102] The first feedback information represents feedback information obtained when information processing is performed at the local information level.

[0103] Step S305: In the control feedback link, the device status signal and the fourth control signal are fed back and buffered in the first buffer.

[0104] The device status signal refers to a physical status signal that can directly reflect the working status of the controlled device.

[0105] Step S306: In the control feedback link, the fifth control signal is subjected to information processing to obtain second feedback information, and the second feedback information is cached in the information sending endpoint.

[0106] The fifth control signal comes from the first cache.

[0107] Step S307, send the feedback information buffered in the sending information endpoint to the Internet of Things for sharing.

[0108] As shown in Figure 1 S1 to Sm are sending information endpoints for buffering feedback information, m represents the number of sending information endpoints for buffering feedback information, and m is a positive integer. The feedback information can include but is not limited to decision control information, state information of the controlled device, etc. For example, the feedback information can be actual running state information of a variable frequency pump, actual running state information of a fixed frequency pump, etc. The above is only an exemplary description of the feedback information and is not used to limit the feedback information. In the embodiments of the present disclosure, different feedback information can also be pre-configured with corresponding sending information endpoints, which will not be described here.

[0109] The feedback information in step S307 at least includes the first feedback information in step S304 and the second feedback information in step S306. The first feedback information is feedback information obtained when the information processing is performed at the local information level. The second feedback information is feedback information obtained by information processing of the fifth control signal. In addition to the first control signal and the seventh control signal obtained by processing, the fifth control signal also includes a device state signal from the controlled device and a fourth control signal from the second buffer. The device state signal represents a physical state signal that can directly reflect the working state of the controlled device. The first feedback information and the second feedback information are both buffered in the sending information endpoint. These feedback information (at least including the first feedback information and the second feedback information) buffered in the sending information endpoint can be sent to the Internet of Things for sharing. The process of obtaining the feedback information can refer to Figure 1 , which will not be described here.

[0110] In the embodiments of the present disclosure, on the one hand, the measurement and control information obtained from the Internet of Things can be stored in the receiving information endpoint, and by performing information processing, signal processing and physical mapping on the measurement and control information at the local information level, physical control signals capable of directly controlling the controlled device can be autonomously generated. On the other hand, the feedback information buffered in the sending information endpoint can be sent to the Internet of Things for sharing. In this way, without relying on any central controller in the system and any instructions issued by the central controller, the intelligent Internet of Things control can be realized in a decentralized and instruction-free manner, achieving the effect of direct interconnection and active interaction of the intelligent Internet of Things, which can greatly reduce the design and implementation difficulty of the Internet of Things measurement and control system and greatly improve the system reliability.

[0111] Having described above several embodiments of the disclosure, any modifications and variations that fall within the scope of the described embodiments are also intended to be within the scope of the disclosure. As will be apparent to those skilled in the art, some modifications and variations to the embodiments described above can be practiced while staying within the scope and spirit of the described embodiments. The foregoing description of the described embodiments has been presented for the purposes of illustration and description. It is not intended to be exhaustive or to limit the described embodiments to the precise form disclosed. Many modifications and variations are possible in light of the above teachings. It is intended that the disclosed embodiments be limited only by the claims.

Claims

1. An information-driven intelligent IoT autonomous control method, characterized in that: The method comprises: Cache the measurement and control information obtained from the Internet of Things in the receiving endpoint; In the information processing step, a first control signal is obtained by performing intelligent analysis, intelligent decision-making and conversion processing on the measurement and control information, and the first control signal is cached in a first cache; In the signal processing step, the second control signal is processed according to the signal self-loop iterative processing mechanism to obtain a third control signal, and the third control signal is cached in the second cache. The second control signal comes from the first cache, wherein the signal self-loop iterative processing mechanism is composed of the first cache, a signal router, a second cache, and a signal operator. The control signal from the second cache that needs to participate in the loop iterative processing enters the first cache again after being processed by the signal operator, and is routed by the signal router again before reaching the second cache via a different transfer path, through one or more cycles, until a preset condition is met; In the physical mapping step, the fourth control signal is physically mapped to obtain a device control signal T, where the device control signal represents a physical control signal capable of directly controlling the controlled device, and the fourth control signal comes from the second cache; Obtaining first feedback information in the information processing step and buffering it in the information sending endpoint; In the control feedback link, the device status signal and the fourth control signal are fed back and cached in the first cache, wherein the device status signal represents a physical status signal that can directly reflect the working status of the controlled device; In the control feedback link, the fifth control signal is subjected to information processing to obtain second feedback information, and the second feedback information is cached in the information sending endpoint, and the fifth control signal is from the first cache; The feedback information cached in the information sending endpoint is sent to the Internet of Things for sharing.

2. The method according to claim 1, characterized in that The information processing link includes intelligent control algorithm processing and information signal conversion. In the information processing link, a first control signal is obtained by performing intelligent analysis, intelligent decision-making and conversion processing on the measurement and control information, and the first control signal is cached in a first cache, including: performing the intelligent control algorithm processing on the measurement and control information stored in the information receiving endpoint based on first configuration parameters to obtain control decision information, wherein the first configuration parameters are used to configure the intelligent control algorithm used when performing the intelligent control algorithm processing and operating parameters of the intelligent control algorithm used; The control decision information is converted into the information signal based on the second configuration parameter to obtain the first control signal, and the first control signal is cached in the first cache, wherein the second configuration parameter is used to configure the information signal conversion method and effect adopted when performing the information signal conversion.

3. The method according to claim 1, characterized in that The signal processing link includes routing selection based on a signal router and calculation processing based on a signal operator; The signal processing step includes performing signal processing on the second control signal according to a signal self-loop iterative processing mechanism to obtain a third control signal, and buffering the third control signal in a second buffer, including: configuring the signal router based on a third configuration parameter, and configuring the signal operator based on a fourth configuration parameter, wherein the third configuration parameter is used to configure a transfer path for transferring the control signal stored in the first cache from the first cache to the second cache, and the fourth configuration parameter is used to configure a signal operation method and effect used when performing the signal operation processing; inputting the second control signal into the signal router to control the second control signal to transfer according to the transfer path configured by the third configuration parameter, obtaining the third control signal, and storing the third control signal in the second cache; Among them, the third control signal includes the fourth control signal and the sixth control signal, the fourth control signal indicates a control signal that can directly perform the physical mapping processing, and the sixth control signal indicates a control signal that needs to enter the signal operator to continue the signal self-loop iterative processing; after the sixth control signal enters the signal operator, it can be operated and processed according to the signal operation method configured by the fourth configuration parameter to obtain a seventh control signal, and the seventh control signal is stored in the first cache.

4. The method according to claim 1, wherein The physical mapping link is used to map the digital control signal in the digital world into the physical control signal required by the controlled device in the physical world; In the physical mapping link, performing physical mapping processing on the fourth control signal to obtain a device control signal includes: The fourth control signal is physically mapped based on a fifth configuration parameter to obtain the device control signal, and the fifth configuration parameter is used to configure a mapping method and effect adopted when performing the physical mapping.

5. An information-driven intelligent IoT autonomous control node, characterized in that: The nodes include: The information terminal can be directly connected to the Internet of Things and is used to cache the measurement and control information obtained from the Internet of Things in the receiving information endpoint, and send the feedback information cached in the sending information endpoint to the Internet of Things for sharing; The signal terminal is directly connected to the controlled device and is used to send device control signals to the controlled device and receive status signals of the controlled device; The processing module is connected between the information end and the signal end, and is used to process the measurement and control information through intelligent analysis, intelligent decision-making and conversion processing in the information processing link to obtain a first control signal, and cache the first control signal in the first cache; in the signal processing link, the second control signal is processed according to the signal self-loop iteration processing mechanism to obtain a third control signal, and cache the third control signal in the second cache, the second control signal comes from the first cache, wherein the signal self-loop iteration processing mechanism is composed of the first cache, the signal router, the second cache and the signal operator, the control signal from the second cache that needs to participate in the loop iteration processing, after the operation processing of the signal operator, enters the first cache again, and after being routed by the signal router again, it is processed by different The transfer path reaches the second cache and passes through one or more cycles until the preset conditions are met; in the physical mapping link, the fourth control signal is physically mapped to obtain a device control signal, the device control signal represents a physical control signal that can directly control the controlled device, and the fourth control signal comes from the second cache; in the information processing link, first feedback information is obtained and cached in the information sending endpoint; in the control feedback link, the device status signal and the fourth control signal are fed back and cached in the first cache, the device status signal represents a physical status signal that can directly reflect the working status of the controlled device; in the control feedback link, the fifth control signal is information-processed to obtain second feedback information, and the second feedback information is cached in the information sending endpoint, and the fifth control signal comes from the first cache.

6. The node according to claim 5, characterized in that The node has a system-level information feedback function, and can feed back its control operation results or status information to the Internet of Things to drive other nodes in the Internet of Things to perform the collaborative work behavior required by the system, thereby realizing system-level intelligent Internet of Things autonomous control based on information drive.

7. The node according to claim 5, characterized in that Each node connected in the Internet of Things only needs to be driven by the Internet of Things measurement and control information, without the need for any center or command coordination, and can achieve intelligent and autonomous collaborative control.

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