Urban air traffic system control architecture switching method and device

Abstract

The invention discloses an urban air traffic system control architecture switching method and device, and relates to the technical field of system engineering and automatic control, and the method comprises the steps: controlling a built adaptive architecture switching control model based on an adaptive control theory and fuzzy logic, and based on a state variable value and a performance index value of a system; the types of the urban air traffic control system architecture and the corresponding model structures are switched in real time by using the self-adaptive architecture switching control model, so that the operation efficiency of the urban air traffic system can be effectively improved, and the loss caused by safety risks is reduced; three types of urban air traffic control system architectures are designed for the urban air traffic system, the command and control requirements of different scenes can be met, and reference is provided for the design of the urban air traffic system control architectures.

Description

Technical Field

[0001] The present application relates to the field of system engineering and automatic control technology, and in particular to a method and device for switching the control architecture of an urban air traffic system based on adaptive control. Background Art

[0002] The urban air traffic system is an innovative way to achieve air traffic within or between cities through new aviation technologies such as electric vertical take-off and landing aircraft (eVTOL). This system can effectively alleviate ground traffic congestion and improve urban traffic efficiency. Since the urban air traffic system is located within the city, it has more stringent requirements in terms of efficiency and safety compared to traditional civil aviation systems and general aviation systems. In terms of efficiency, the urban air traffic system needs to handle a large number of flight requests and provide passenger and logistics services to tens of thousands of urban residents. A study based on population and traffic data of 1,200 cities around the world shows that by 2050, there will be 160,000 passenger-grade unmanned aerial vehicles serving urban traffic worldwide, and will generate annual revenue of US$90 billion. At the same time, foreign research institutions pointed out that in the best case (unconstrained) scenario in the future, the potential demand for the air taxi market and airport shuttle market is 11 million daily trips (accounting for 20% of all daily work trips in the United States). In terms of safety, the huge passenger flow in urban air traffic in the future may bring more safety hazards. At the same time, the urban environment is more complex. For example, as the pressure gradient, surface friction and air density decrease, the wind speed increases with altitude. The higher wind speed in the city makes the take-off and landing operations of aircraft more difficult and dangerous. In addition, buildings will shield the wireless signals required for the operation of urban air traffic, including navigation and most forms of surveillance communications, which will further increase the operational safety risks of the system.

[0003] However, the existing aviation system control architecture is unable to fully cope with the above two challenges. A single architecture is unable to meet the needs of urban air traffic scenarios. Therefore, it is necessary to design a flexible architecture switching method that can quickly switch the architecture operation mode according to the requirements of different scenarios. Summary of the invention

[0004] The purpose of this application is to provide a method and device for switching the control architecture of an urban air traffic system, which can utilize an adaptive architecture switching control model to autonomously switch the type of control architecture of the urban air traffic system according to internal and external risk situations and requirements of different scenarios, thereby improving the operating efficiency and system safety level of the urban air traffic system.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for switching a control architecture of an urban air traffic system, comprising:

[0007] Obtain the state variable values ​​and performance index values ​​of the urban air traffic control system at the current stage, where the state variables are used to reflect the system state; and the performance indexes are used to reflect the system capabilities;

[0008] Determining a state variable error according to the state variable value and the state variable expected value;

[0009] Determining a performance indicator error according to the performance indicator value and the performance indicator expected value;

[0010] The state variable error and the performance index error are used as inputs, and an adaptive architecture switching control model is used to output the optimal type and adjustment plan of the urban air traffic control system architecture, wherein the adaptive architecture switching control model includes an architecture switching fuzzy rule base and an architecture control variable, the architecture switching fuzzy rule base includes a rule set, each rule in the rule set includes a condition and a corresponding result, the condition is a condition determined according to the state variable and the performance index, and the corresponding result characterizes the type of the urban air traffic control system architecture corresponding to the condition; the architecture control variable includes a type variable and an edge relationship variable, the type variable is used to characterize the type of the urban air traffic control system architecture, and the edge relationship variable is used to characterize whether edges are established between elements in the model of the urban air traffic control system architecture; the types of the urban air traffic control system architecture include a centralized urban air traffic control system architecture, a distributed urban air traffic control system architecture, and a semi-distributed urban air traffic control system architecture;

[0011] According to the adjustment plan, the model structure of the urban air traffic control system architecture in the previous stage is adjusted accordingly.

[0012] In a second aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the urban air traffic system control architecture switching method described in the first aspect above.

[0013] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for switching the control architecture of the urban air traffic system described in the first aspect above.

[0014] In a fourth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the urban air traffic system control architecture switching method described in the first aspect above.

[0015] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0016] The present application provides a method and device for switching the control architecture of an urban air traffic system. The method is based on an adaptive architecture switching control model constructed based on adaptive control theory and fuzzy logic control, and based on the state variable values ​​and performance indicator values ​​of the system, uses the adaptive architecture switching control model to switch the type of urban air traffic control system architecture and the corresponding model structure in real time, which can effectively improve the operating efficiency of the urban air traffic system and reduce the losses caused by safety risks. The present application designs three types of urban air traffic control system architectures for the urban air traffic system, which can meet the command and control requirements of different scenarios, and provides a reference for the design of the control architecture of the urban air traffic system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 This is an application environment diagram of a method for switching a control architecture of an urban air traffic system in Example 1 of the present application;

[0019] Figure 2 A flowchart of a method for switching a control architecture of an urban air traffic system provided in Example 1 of the present application;

[0020] Figure 3 This is a schematic diagram of the structure of the centralized urban air traffic control system architecture model in Example 1 of the present application;

[0021] Figure 4 This is a schematic diagram of the structure of the distributed urban air traffic control system architecture model in Example 1 of the present application;

[0022] Figure 5 This is a structural diagram of a semi-distributed urban air traffic control system architecture model in Example 1 of the present application;

[0023] Figure 6 This is a flowchart of the process of building an adaptive architecture switching control model in Example 1 of the present application;

[0024] Figure 7 A schematic diagram of the structure of a computer device provided in Example 2 of the present application. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0026] In order to make the above-mentioned objects, features and advantages of the present application more obvious and understandable, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0027] Example 1

[0028] The urban air traffic system control architecture switching method and device provided in the embodiments of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the state variable values ​​and performance indicator values ​​of the current stage of the urban air traffic control system to be processed to the server 104. After the server 104 receives the state variable values ​​and performance indicator values, it determines the state variable error according to the state variable values ​​and the expected values ​​of the state variables; determines the performance indicator error according to the performance indicator value and the expected value of the performance indicator; uses the state variable error and the performance indicator error as input, and uses the adaptive architecture switching control model to output the optimal type and adjustment plan of the urban air traffic control system architecture. The server 104 can feedback the obtained optimal type and adjustment plan of the urban air traffic control system architecture to the terminal 102. In addition, in some embodiments, the urban air traffic system control architecture switching method can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly use the urban air traffic system control architecture switching method to process the state variable values ​​and performance indicator values ​​to be processed, or the server 104 can obtain the state variable values ​​and performance indicator values ​​to be processed from the data storage system and use the urban air traffic system control architecture switching method to process them.

[0029] The terminal 102 may be, but is not limited to, various desktop computers, laptop computers, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart vehicle-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers, or may be a cloud server.

[0030] The traditional civil aviation system adopts a centralized control architecture, and all aircraft follow the flight plans and control instructions provided by airports, regional air traffic control and airlines. This architecture allows the system to maintain a very high level of safety. For example, the 2023 Global Commercial Aviation Safety Report shows that the global commercial civil aviation accident rate is 0.8 accidents / million flights, but the side effect of this extremely high safety is that the central command unit is overburdened, resulting in low efficiency and high delay rate. Data shows that more than 45% of flights in the United States were delayed in 2023. Another typical aviation system control architecture is the distributed control architecture of the general aviation system. This type of architecture is mainly based on manual control. Flight service stations in various regions independently control helicopters and drones in the region, and there is no obvious core command unit. This distributed architecture lacks layer-by-layer safety audits and macro-dispatching commands, resulting in low safety. For example, there were 12,368 non-fatal accidents and 2,269 fatal accidents worldwide from 2012 to 2021. However, due to its flexible operation, flight service efficiency is higher. Data shows that the annual flight hours of the US general aviation system exceed 26 million. It can be seen that these system control architectures each have their own advantages, but a single architecture is difficult to meet the needs of urban air traffic scenarios. Therefore, it is necessary to design a flexible architecture switching method that can quickly switch the architecture operation mode according to the needs of different scenarios.

[0031] In view of the above problems, this embodiment proposes an effective urban air traffic system architecture switching method. By considering the performance and safety requirements of different scenarios of urban air traffic, three typical urban air traffic system control architectures are designed. On this basis, an adaptive architecture switching control model is constructed. The urban air traffic system control architecture can be autonomously switched according to internal and external risk situations, and the control model parameters can be adaptively adjusted to ensure better control effects, thereby improving the operating efficiency and system safety level of the urban air traffic system.

[0032] In an exemplary embodiment, a method for switching the control architecture of an urban air traffic system is provided. The method is executed by a computer device, and can be executed by a computer device such as a terminal or a server alone, or by a terminal and a server together. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps 201 to 208. Among them:

[0033] Step 201, obtaining the state variable values ​​and performance index values ​​of the urban air traffic control system at the current stage, wherein the state variables are used to reflect the system state; and the performance indexes are used to reflect the system capability.

[0034] Step 202: Determine a state variable error according to the state variable value and the state variable expected value.

[0035] Step 203: determining a performance indicator error according to the performance indicator value and the performance indicator expected value.

[0036] Step 204: using the state variable error and the performance indicator error as inputs, and using an adaptive architecture switching control model to output the optimal type and adjustment plan of the urban air traffic control system architecture, wherein the adaptive architecture switching control model includes an architecture switching fuzzy rule base and an architecture control variable, the architecture switching fuzzy rule base includes a rule set, each rule in the rule set includes a condition and a corresponding result, the condition is a condition determined according to the state variable and the performance indicator, and the corresponding result represents the type of the urban air traffic control system architecture corresponding to the condition; the architecture control variable includes a type variable and an edge relationship variable, the type variable is used to represent the type of the urban air traffic control system architecture, and the edge relationship variable is used to represent whether edges are established between elements in the model of the urban air traffic control system architecture; the types of the urban air traffic control system architecture include a centralized urban air traffic control system architecture, a distributed urban air traffic control system architecture, and a semi-distributed urban air traffic control system architecture;

[0037] Step 205: adjusting the model structure of the urban air traffic control system architecture of the previous stage according to the adjustment plan.

[0038] This embodiment takes into account the safety and efficiency requirements of urban air traffic operations, designs three typical urban air traffic control system architectures: centralized, distributed, and semi-distributed, and then establishes an adaptive architecture switching control model based on adaptive control theory, which can autonomously switch the urban air traffic system control architecture according to the internal and external risk situation and the capabilities of different architecture types. This method takes into account the capabilities and characteristics of different control architectures, as well as the adaptability and resilience of the urban air traffic system under an uncertain operating environment, which can effectively improve the operating efficiency of the urban air traffic system and reduce the losses caused by safety risks.

[0039] In order to make those skilled in the art more aware of the specific implementation process of the urban air traffic system control architecture switching method provided by this embodiment, a specific explanation is given below.

[0040] The urban air traffic system control architecture switching method provided in this embodiment is as follows: Figure 2 As shown, specifically including:

[0041] Step A: Design different types of urban air traffic control architectures.

[0042] Designing different types of urban air traffic control system architectures means analyzing the components and interactions in the urban air traffic control system and designing three types of urban air traffic control system architecture models: centralized, distributed, and semi-distributed. The specific approach of step A includes the following four steps:

[0043] Starting from the airspace management, operation services, safety supervision, air transportation, communication, navigation and surveillance capabilities of the urban air traffic system, the systems or subsystems required to support different capabilities are analyzed to form a set of system components. The elements of this scenario include 1) national safety brain (including national air traffic control system, central service platform of manned service operator A and national safety supervision system); 2) edge management centers of regions 1, 2 and 3 (including provincial air traffic control system, provincial operation management platform and airports in each region); 3) N aircraft; 4) various infrastructures, including M meteorological sensors, R navigation satellites, S surveillance radars, T surveillance cameras, U navigation base stations, V communication satellites, W 5G communication base stations and third-party data service providers. On this basis, the possible interactive relationships between these elements are analyzed to form a set of relationships between the elements. Table 1 shows some of the relationships in the set.

[0044] Table 1: Illustration of some relations in the relation set

[0045] Feature name Feature name relation Regional Operators Regional Air Traffic Control Flight Plan Submission Regional Operators Regional Air Traffic Control Risk information reporting Regional Air Traffic Control Regional Operators Risk management plan issued Regional Air Traffic Control Regional Operators Flight plan approval … … …

[0046] Step A2: Design a centralized urban air traffic control system architecture model.

[0047] First, according to the characteristics of centralized control, the interaction relationship between elements in different levels and between different levels of the system is designed. Then, the centralized control process of the urban air traffic system is designed. Finally, based on the complex network theory, the established system architecture is modeled as a centralized urban air traffic control system architecture super network model. In the super network, the elements and interaction relationships at different levels correspond to the network nodes and edges of the corresponding levels respectively, and the interaction relationships between elements at different levels correspond to the coupling edges between networks at different levels, such as Figure 3The centralized urban air traffic control system architecture model shown in Figure 1. The "layer" here refers to the decision-making layer of the urban air traffic control system architecture, which is divided into three layers: cloud, edge, and end. In the centralized architecture, the cloud elements are located in the central cloud server or server cluster, which can receive the risk situation and operation indicator data of each region, and make decisions on macro-level airspace management, traffic control, safety assessment, and operation scheduling, such as the national air traffic control system and the national urban air traffic operation management center platform. The edge elements are located in the edge cloud server or server cluster in a specific area, which can transmit the risk situation and operation indicator data of their respective regions to each other, and make decisions on the operation plan formulation, airport operation, plan approval, route planning, emergency management, etc. in a specific area, such as the air traffic control system, regional operators, and airports in a certain province. The end elements are various manned and unmanned aircraft, which only accept instructions from edge-level elements to fly.

[0048] Among them, the so-called "centralized command and control" means that in the urban air traffic control system, various types of aircraft at the end level are centrally commanded by the edge-level management system, and there is no collaboration between the aircraft.

[0049] Step A3: Design a distributed urban air traffic control system architecture model.

[0050] First, according to the characteristics of distributed command and control, the interaction relationship between elements in different levels and between different levels of the system is designed, and then the distributed control process of the urban air traffic system is designed. Finally, based on the complex network theory, the established system architecture is modeled as a distributed urban air traffic control system architecture hypernetwork model, such as Figure 4 The distributed urban air traffic control system architecture model shown in Figure 1. In the distributed architecture, cloud elements no longer manage and control edge elements. Edge elements no longer transmit and collaborate, but only receive aircraft data in their own area and provide basic information support, such as weather, terrain, and flight information. Aircraft on the end communicate through the communication network, transmit their respective flight plans, route information, and flight information, and formulate and adjust flight plans and routes.

[0051] Among them, the so-called "distributed command and control" means that in the urban air traffic control system, the cloud-level and edge-level systems no longer directly command and control aircraft. Aircraft collaborate through information sharing, and aircraft formulate and adjust flight plans and routes themselves.

[0052] Step A4: Design a semi-distributed urban air traffic control system architecture model.

[0053] Firstly, according to the characteristics of semi-distributed command and control, the interaction relationship between elements in different levels and between different levels of the system is designed. Then, the semi-distributed control process of the urban air traffic system is designed. Finally, based on the complex network theory, the established system architecture is modeled as a semi-distributed urban air traffic control system architecture hypernetwork model, such as Figure 5 The semi-distributed urban air traffic control system architecture model shown in the figure. In the semi-distributed architecture, the cloud elements do not manage and control the edge elements. The edge elements can transmit information and collaborate with each other. At the same time, some edge-level elements will command a small number of aircraft in their own responsible areas and provide them with basic information, flight plans and routes. Some aircraft on the end will upload flight status, flight intelligence and risk situation to the edge elements, and receive flight plans and routes issued by the edge. Other aircraft do not interact with the edge elements, but only share and collaborate with each other, and formulate and adjust flight plans and routes by themselves.

[0054] Among them, the "semi-distributed command and control" is a form of command and control between "centralized command and control" and "distributed command and control". It means that in the urban air traffic control system, the systems at the cloud level do not perform command and control, and some systems at the edge level directly command and control some aircraft. A few aircraft accept the command from the edge and pass the command and control information to other aircraft. Other aircraft formulate and adjust their own flight plans and routes based on the information.

[0055] Step B: Construct an adaptive architecture switching control model.

[0056] Constructing an adaptive architecture switching control model, the specific meaning of which is: according to the three types of system architecture super network models designed in step A, determine the state variables and performance indicators that need to be paid attention to in the system, and construct an architecture switching control model, which can switch the architecture type according to the changes in state variables and performance indicators, and adjust the structure of the architecture super network. Figure 6 As shown, the specific implementation of step B includes the following four steps:

[0057] Step B1: Determine the state variables in the system according to scenario requirements.

[0058] Select some elements with high correlation with scenario requirements from the system architecture hypernetwork model and design their state variables, such as the flight health level of aircraft, the maximum aircraft density in each airspace, meteorological conditions, etc. The state variables of the system are used to reflect the state of the system at any time. Changes in state variables can immediately reflect changes in the system state. Therefore, they can be used as a control basis in scenarios with high control real-time requirements.

[0059] Step B2: Determine system performance indicators based on scenario requirements.

[0060] According to the scenario requirements, analyze the system capabilities corresponding to the requirements, and design and select indicators that can quantitatively evaluate the system capabilities based on the system capabilities. For example, in the urban air passenger transport scenario, you can choose indicators such as request satisfaction rate and average detour flight time.

[0061] Step B3: Construct architecture control variables.

[0062] The architecture control variables are the edge relationships between the UATCS architecture type and the architecture hypernetwork model, where the UATCS architecture type X is an integer variable with values ​​of 1-3, corresponding to the “centralized”, “distributed” and “semi-distributed” architectures, respectively. The edge relationship of the architecture hypernetwork model is an adjacency matrix E between elements, where each element e ij It is an integer variable ranging from 0 to 1. If it is 1, it means there is an interaction relationship between the elements (accusation or information interaction), and if it is 0, there is no interaction relationship.

[0063] Step B4: Fuzzify the error of the state variable and the error value of the performance index.

[0064] According to fuzzy theory, the error level membership function of each state variable and the index is set, and the error value range is fuzzified. The membership function is used to describe the degree to which the error value belongs to a certain error level. The independent variable of the membership function is the precise error value, and the dependent variable is the degree to which the error value belongs to the error level. The error refers to the difference between the current actual value (measured value) and the expected value (target value). For example, the error of the state variable of the maximum aircraft density in the airspace can be divided into five levels: negative large, negative small, zero, positive small and positive large, corresponding to 10 aircraft per cubic kilometer or more less than the expected value, 5-10 aircraft per cubic kilometer less than the expected value, 0-5 aircraft per cubic kilometer less or more than the expected value, 5-10 aircraft per cubic kilometer more than the expected value, and 10 aircraft per cubic kilometer more than the expected value. If the current error is 15 more than the expected value, the corresponding membership of the positive large level is the highest, which belongs to positive large. In practical applications, specific classification rules can be determined based on scenario requirements and expert experience.

[0065] Step B5: Establish a fuzzy rule base for architecture switching.

[0066] A fuzzy rule base is established based on expert experience. Each rule in the rule set is expressed in the form of "if-then". For example, if the maximum aircraft density in the airspace is positive and the weather conditions are extremely poor, then switch to a centralized control architecture. The specific setting of fuzzy rules can be determined according to scenario requirements and expert experience.

[0067] Step B6: Infer the architecture type based on the fuzzy rule base.

[0068] According to the error level of the input state variable and the error level of the performance index value, all fuzzy rules are substituted for query. If a rule meets the conditions, the corresponding switching result is output.

[0069] Step B7: Adjust the structure of the architecture super network.

[0070] The edges of the super network are adjusted according to the architecture type after switching. If the switched architecture is centralized, edges are built between all cloud-level elements and edge-level elements in the super network. At the same time, edges are established between all edge-level elements and aircraft elements in the corresponding area (i.e., end level), and the corresponding cells in the adjacency matrix E are set to 1. All aircraft elements are disconnected from the edges, and the corresponding cells in the adjacency matrix E are set to 0. If the switched architecture is distributed, all cloud-level elements and edge-level elements in the super network are disconnected, all edge-level elements and aircraft elements in the corresponding area are disconnected, and the corresponding cells in the adjacency matrix E are set to 0. All aircraft elements establish edges with aircraft within their communication range, and the corresponding cells in the adjacency matrix E are set to 1. If the switched architecture is semi-distributed, all cloud-level elements and edge-level elements in the super network are disconnected, and the corresponding cells in the adjacency matrix E are set to 0. The adjustment of other edges can be modeled as a network structure optimization problem. The objective function can be designed according to scenario requirements and solved using an optimization algorithm.

[0071] Step B8: Adaptively adjust the membership function parameters of the error level according to the performance indicator error threshold.

[0072] Set the error threshold of each performance index i to Q i If the error of any performance indicator exceeds the threshold, the standard genetic algorithm is used to optimize the error level of all state variables and the membership function parameter value of the performance indicator error level. The goal is to minimize the error value of the performance indicator. Each individual in the algorithm represents a set of membership function parameters. The number of iterations is T, and the adjusted membership function parameter value is finally output.

[0073] Step C: Switch to the optimal architecture based on risk situation and operating indicators.

[0074] The optimal architecture is switched according to the risk situation and operation indicators. The specific meaning is: the current state variable data of the system is obtained through sensing devices such as radar, meteorological sensors, satellites, and aircraft status sensors. At the same time, the current performance indicator value is calculated based on the operator data and safety monitoring data. The state variables and performance indicator values ​​are compared with their expected values ​​to obtain error values ​​and input them into the architecture switching control model described in step B to calculate the switching architecture type and adjust the structure of the architecture super network.

[0075] This embodiment has the following beneficial effects:

[0076] 1) This embodiment designs three types of control architectures for the urban air traffic system, which can meet the command and control requirements of different scenarios and provide a reference for the design of the control architecture of the urban air traffic system;

[0077] 2) This embodiment uses a hypernetwork model to model the system control architecture, which can effectively characterize the interactive relationships between elements at different levels and between different levels in the urban air traffic system, and at the same time provide a quantitative calculation model basis for the adjustment of the system control architecture;

[0078] 3) Once the traditional aviation system control architecture is put into use, it will not change. It is difficult to adaptively adjust the architecture according to the changes in the scene and give full play to the respective advantages of different architectures. The architecture switching control model proposed in this embodiment based on adaptive control theory and fuzzy logic control can switch the system control architecture type and specific structure in real time according to the system state variables and performance index values, and can adaptively adjust the control model parameters, which can effectively improve the operating efficiency of the urban air traffic system and reduce the losses caused by safety risks.

[0079] In summary, this urban air traffic system control architecture switching method based on adaptive control can improve the flexibility of system control in practice and provide good support for the management and control of the urban air traffic system.

[0080] The present application also provides an application scenario, which applies the above-mentioned urban air traffic system control architecture switching method. Specifically: The urban air traffic system control architecture switching method provided in this embodiment can be applied in air traffic operation scenarios. Air traffic operation scenarios include content data processing links, flight scheduling links, and real-time monitoring links. The urban air traffic system control architecture switching method provided in this embodiment is an important step in the flight scheduling link.

[0081] Example 2

[0082] This embodiment provides a computer device, which may be a server or a terminal. Its internal structure diagram may be as follows: Figure 7As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store any data in the urban air traffic system control architecture switching method. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the urban air traffic system control architecture switching method provided in Example 1 is implemented.

[0083] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0084] Example 3

[0085] This embodiment provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the urban air traffic system control architecture switching method provided in Embodiment 1 is implemented.

[0086] Example 4

[0087] This embodiment provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, the urban air traffic system control architecture switching method provided in Embodiment 1 is implemented.

[0088] Example 5

[0089] This embodiment provides a computer program product, including a computer program, which, when executed by a processor, implements the urban air traffic system control architecture switching method provided in Embodiment 1.

[0090] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0091] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0092] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0093] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0094] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for switching control architecture of an urban air traffic system, characterized in that: The urban air traffic system control architecture switching method comprises: Obtain the state variable values ​​and performance index values ​​of the urban air traffic control system at the current stage, where the state variables are used to reflect the system state; and the performance indexes are used to reflect the system capabilities; Determining a state variable error according to the state variable value and the state variable expected value; Determining a performance indicator error according to the performance indicator value and the performance indicator expected value; The state variable error and the performance index error are used as inputs, and an adaptive architecture switching control model is used to output the optimal type and adjustment plan of the urban air traffic control system architecture, wherein the adaptive architecture switching control model includes an architecture switching fuzzy rule base and an architecture control variable, the architecture switching fuzzy rule base includes a rule set, each rule in the rule set includes a condition and a corresponding result, the condition is a condition determined according to the state variable and the performance index, and the corresponding result characterizes the type of the urban air traffic control system architecture corresponding to the condition; the architecture control variable includes a type variable and an edge relationship variable, the type variable is used to characterize the type of the urban air traffic control system architecture, and the edge relationship variable is used to characterize whether edges are established between elements in the model of the urban air traffic control system architecture; the types of the urban air traffic control system architecture include a centralized urban air traffic control system architecture, a distributed urban air traffic control system architecture, and a semi-distributed urban air traffic control system architecture; According to the adjustment plan, the model structure of the urban air traffic control system architecture of the previous stage is adjusted accordingly.

2. The urban air traffic system control architecture switching method according to claim 1, characterized in that: Before executing the step of "obtaining the state variable values ​​and performance indicator values ​​of the urban air traffic control system at the current stage", the urban air traffic system control architecture switching method further includes: Obtaining an element set and an element relationship set in the urban air traffic control system, wherein the elements in the element set refer to various types of systems, subsystems or devices required to support the capabilities of the urban air traffic control system; and the element relationship in the element relationship set refers to the interactive relationship between the elements; According to the element set and the element relationship set, a model of the urban air traffic control system architecture is constructed, wherein the model of the urban air traffic control system architecture includes a centralized urban air traffic control system architecture model, a distributed urban air traffic control system architecture model and a semi-distributed urban air traffic control system architecture model; the model of the urban air traffic control system architecture is divided into a cloud layer, an end layer and an edge layer according to the decision-making level, the decision-making level of the elements at the cloud layer is the highest, and the decision-making level of the elements at the edge layer is the lowest; in the centralized urban air traffic control system architecture model, the elements at the cloud layer control the elements at the edge layer, the elements at the end layer control the elements at the edge layer of the corresponding area, and the elements at the edge layer communicate with each other. Information interaction is performed between elements at the end level, and no information interaction is performed between elements at the end level; in the distributed urban air traffic control system architecture model, elements at the cloud level do not control elements at the edge level, elements at the end level do not control elements at the edge level of the corresponding area, there is no information interaction between elements at the edge level, and information interaction is performed between elements at the end level; in the semi-distributed urban air traffic control system architecture model, elements at the cloud level do not control elements at the edge level, some elements at the end level control elements at the edge level of the corresponding area, and another part of elements at the end level do not control elements at the edge level of the corresponding area, information interaction is performed between elements at the edge level, some elements at the end level interact with each other, and no information interaction is performed between other parts of elements at the end level.

3. The urban air traffic system control architecture switching method according to claim 1, characterized in that: The process of constructing the adaptive architecture switching control model specifically includes: Determine the state variables and performance indicators of the urban air traffic control system according to scenario requirements; Construct architectural control variables; Determine the error level membership function of each state variable and the error level membership function of each performance index according to fuzzy theory, wherein the error refers to the difference between the measured value of the state variable or the performance index and the corresponding expected value; Determining the error level of the state variable and the error level of the performance indicator according to the error level membership function of the state variable and the error level membership function of the performance indicator; Taking the error level of the state variable and the error level of the performance indicator as conditions and the type of the urban air traffic control system architecture as a result, establishing a fuzzy rule base for architecture switching; Determining the type of traffic control system architecture according to the architecture switching fuzzy rule base; Determining the value of the architecture control variable according to the type of the traffic control system architecture; adjusting the model structure of the urban air traffic control system architecture according to the value of the architecture control variable; Determine whether an error of any of the performance indicators exceeds an error threshold, and obtain a first determination result; If the first judgment result is yes, a genetic algorithm is used to optimize the parameters of the error level membership function of all the state variables and the error level membership function of the performance index, wherein the objective function in the genetic algorithm is a function constructed with the goal of minimizing the target error, and the target error refers to the error of the performance index that exceeds the error threshold; The error level membership function of the state variable and the error level membership function of the performance index corresponding to the optimized parameters are used as the new error level membership function of the state variable and the error level membership function of the performance index, and the step of "determining the error level of the state variable and the error level of the performance index according to the error level membership function of the state variable and the error level membership function of the performance index" is returned; If the first judgment result is no, the construction of the adaptive architecture switching control model is completed.

4. The urban air traffic system control architecture switching method according to claim 1, characterized in that: The adjustment plan specifically includes: When the type of the optimal urban air traffic control system architecture is the centralized urban air traffic control system architecture, the adjustment scheme is to establish edges between all cloud-level elements and edge-level elements in the centralized urban air traffic control system architecture model, to establish edges between all edge-level elements and end-level elements in the corresponding region, to establish edges between all edge-level elements, and to disconnect edges between all end-level elements; When the type of the optimal urban air traffic control system architecture is the distributed urban air traffic control system architecture, the adjustment scheme is to disconnect the edges between all cloud-level elements and edge-level elements in the model of the distributed urban air traffic control system architecture, disconnect the edges between all edge-level elements and end-level elements in the corresponding area, disconnect the edges between all edge-level elements, and establish edges between all end-level elements within a preset communication range; When the type of the optimal urban air traffic control system architecture is the semi-distributed urban air traffic control system architecture, the adjustment plan is to disconnect the edges between all cloud-level elements and edge-level elements in the model of the semi-distributed urban air traffic control system architecture, establish connections between some elements in the end level and elements in the edge level in the corresponding area, disconnect the edges between another part of the end level and elements in the edge level in the corresponding area, establish connections between all edge-level elements, establish connections between some elements in the end level, and disconnect the edges between another part of the elements in the end level.

5. The method for switching the control architecture of an urban air traffic system according to claim 1, characterized in that: The edge relationship variables are represented in the form of an adjacency matrix.

6. The urban air traffic system control architecture switching method according to claim 1, characterized in that: The rules are expressed in an "if-then" format and are set based on expert experience and scenario requirements.

7. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the urban air traffic system control architecture switching method according to any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the urban air traffic system control architecture switching method described in any one of claims 1 to 6 is implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the urban air traffic system control architecture switching method described in any one of claims 1 to 6 is implemented.

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