Combined nest emergency control method and system

Abstract

The application discloses a combined machine nest emergency control method and system, the method comprises the following steps: each machine nest unit receives the operation state data uploaded by the sensor group monitoring module, and forms a basic state data set for subsequent distributed decision; the current master node performs abnormal detection and fault identification on each node and each position based on the basic state data set; when the current master node fails, dynamic master-slave election is performed, and a temporary master node suitable for taking over the global scheduling authority from each machine nest unit is determined as a new current master node; when the target position of the unmanned aerial vehicle or the corresponding backup landing machine nest of the target position fails, the current master node adopts a two-stage screening method to perform position reselection and determine a new target position. The application improves the continuous operation capability, safety and autonomy of the multi-position machine nest system under complex abnormal working conditions on the basis of retaining centralized scheduling capability.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) control technology, and in particular to a combined UAV nest emergency control method and system. Background Technology

[0002] With the increasing application of drones in scenarios such as inspection, delivery, security, and emergency operations, drone nesting systems have become an important infrastructure for drone parking, recharging, environmental protection, and mission scheduling. Existing multi-drone nesting systems typically adopt a centralized cloud control or centralized master control architecture, that is, a single central control unit or central control cabinet controls and manages multiple nesting units in a unified manner.

[0003] In terms of structural composition, existing multi-position drone nesting systems generally include a central control unit and multiple nesting units. Each nesting unit typically contains parking spaces or bays for drone access and placement, and is equipped with communication modules, nesting door drive mechanisms, power supply or charging interfaces, and environmental monitoring sensors to enable drone parking, recharging, status monitoring, and related control functions. In some combined or matrix-type nesting systems, multiple nesting units are arranged in an array, and the central control cabinet receives task information from the cloud server and performs unified scheduling of each nesting unit.

[0004] In terms of operating principle, the central control unit manages the opening and closing of the hatches of each drone nesting unit, power control, status monitoring, and the take-off and landing process of the drones, based on preset programs or cloud commands. Functions such as drone homing, parking, recharging, and fault alarms typically rely on the central control unit for centralized calculation and decision-making. When abnormal operating conditions occur, the system usually identifies the fault through the central control unit and triggers corresponding preset protection measures.

[0005] Although existing multi-station nested systems can meet the automation requirements under normal operating conditions, they still suffer from problems such as insufficient continuous operation capability, limited resource reconfiguration capability, weak local autonomy capability, and insufficient emergency response capability under complex operating conditions such as main control failure, station malfunction, communication interruption, and abnormal power outage. The main problems and their causes are as follows.

[0006] Single point of failure risk is high:

[0007] Existing multi-host drone nesting systems mostly adopt a centralized control architecture, with system control and scheduling primarily relying on a central control unit or central control cabinet. If the central control unit experiences hardware failure, software anomalies, or communication interruptions, the overall system scheduling capability will be affected, potentially leading to the inability to perform functions such as drone homing, nest door control, recharging, and safety protection. The main reason for this is that existing systems typically employ a centralized control approach, lacking independent collaborative decision-making and control authority reconfiguration capabilities among the individual nesting units, thus easily creating a single point of failure when the main control unit malfunctions.

[0008] Lack of dynamic resource reconfiguration capabilities:

[0009] When a nest unit or its internal parking position or compartment experiences a nest door malfunction, power supply abnormality, actuator malfunction, or communication failure, existing systems typically only lock the fault location or issue an error message. This makes it difficult to promptly utilize other available nest units or compartments to complete the mission migration, easily leading to interrupted UAV homing or mission failure. The main reason for this is that existing systems usually have a strong, fixed correspondence between task allocation and specific drone positions, lacking a dynamic reselection mechanism for multi-drone coordination and a unified resource reconfiguration logic.

[0010] Lack of optimized control capabilities under emergency power supply conditions:

[0011] When the system is in an abnormal power outage or emergency power supply state, the existing nested system usually only maintains basic power supply, lacking a comprehensive analysis of remaining power, load priority, and critical function guarantee requirements. It is difficult to simultaneously meet operating time and safety requirements under limited energy conditions. The main reason is that the existing system usually lacks a local energy consumption prediction and optimization control mechanism for emergency conditions, and cannot dynamically adjust relevant functions according to remaining power and system load status.

[0012] Insufficient local self-governance capacity:

[0013] In existing multi-station nested systems, task scheduling, fault handling, and control decisions typically rely on a central control unit or cloud platform. When the network is interrupted or the central control unit is unavailable, each nested unit often only has local execution functions and cannot independently complete system-level collaborative control and emergency response. The main reason for this is that the control capabilities and decision-making logic of existing systems are mainly concentrated on the central control side, and each nested unit lacks the necessary edge decision-making capabilities and distributed collaboration mechanisms. Summary of the Invention

[0014] Purpose of the invention: To address the problems in the prior art, this invention proposes a combined emergency control method and system for multi-station nests. While retaining centralized scheduling capabilities, it also possesses distributed coordination, dynamic reconfiguration, and emergency optimization control capabilities, thereby improving the continuous operation capability, safety, and autonomy of multi-station nest systems under complex and abnormal operating conditions.

[0015] Technical Solution: A first aspect of this application provides an emergency control method for a modular cell, the modular cell comprising a central control cabinet and various cell units; the method includes:

[0016] Each nest unit receives operational status data uploaded by the sensor group, and performs real-time collection and updating of the node status of the distributed collaborative nodes composed of nest units, the UAV's compartment status stored within each nest unit, and the environmental status, forming a basic status dataset for subsequent distributed decision-making. The basic status dataset includes: node remaining power, node control environment temperature, node control environment humidity, node communication status, node health status, node overall load, compartment power supply status, nest door mechanism status, centering mechanism status, compartment communication status, compartment local environmental temperature, compartment local environmental humidity, visual status, estimated waiting time, and battery swapping mechanism status. The current master control node performs anomaly detection and fault identification on each node and each compartment based on the basic status dataset.

[0017] When the current master node fails, a dynamic master-slave election is conducted to determine a temporary master node suitable for taking over global scheduling authority from each nest unit as the new current master node;

[0018] When the target drone location or its corresponding alternate landing site malfunctions, the current master control node uses a two-level screening method to reselect the location and determine a new target location.

[0019] Furthermore, when there is an abnormal power outage or the power supply capacity is limited, the current master control node performs energy consumption-time multi-objective optimization control on each load unit of the combined nest based on the basic status data. The energy consumption-time multi-objective optimization control prioritizes ensuring continuous power supply for communication, control, nest door closing and monitoring functions, and cuts off other loads in a timely manner to extend the operating time.

[0020] Furthermore, when the current master control node identifies a severe fault or an unrecoverable serious anomaly occurs during method execution, a tiered safety circuit breaker and black box recording mechanism is activated. The tiered safety circuit breaker includes isolating and disconnecting the fault-related power supply branch, faulty execution mechanism, abnormal communication link, or abnormal compartment. The black box recording mechanism includes writing fault data, fault time, node election results, compartment re-selection results, energy consumption optimization control results, execution instructions, and operation logs into the non-volatile memory corresponding to each nest unit in real time, forming a black box-style operation record.

[0021] Furthermore, the dynamic master-slave election includes: when each nest unit fails to receive the heartbeat signal from the current master node for several consecutive cycles, it determines that the current master node has failed and triggers a dynamic master-slave election process. Each nest unit extracts node-level parameters from the basic state data, constructs an election reputation value, and broadcasts its own election reputation value. Within a preset time window, if node k has the highest election reputation value, node k is determined as the temporary master node, and this temporary master node becomes the new current master node.

[0022] The heartbeat signal refers to the online acknowledgment signal sent by the current master node to each nest unit according to a preset period, indicating that the master node is still in normal operation. If each nest unit does not receive this signal within several consecutive detection periods, it indicates that the master node may have failed, experienced a power outage, or had a communication interruption. Therefore, the current master node is determined to have failed, and a dynamic master-slave election process is triggered.

[0023] Furthermore, the evaluation rules for the election reputation value include: the higher the remaining power of the node, the more suitable the temperature and humidity of the node's control environment, the stronger the node-level communication capability, and the higher the overall health, the higher the node's election reputation value; the greater the overall load of the node, the lower the node's election reputation value; the overall health value measures the reliability of the nest unit, comprehensively evaluates the hardware aging degree, historical failure rate and current performance deviation of the nest unit, and the higher the score, the higher the overall health value.

[0024] Furthermore, the two-level screening method includes safety access determination and comprehensive score selection; the safety access determination: by using the logical product of four binary state variables, namely power supply, cabin door mechanism, centering mechanism and cabin communication status, all candidate cabins that are working normally are screened out to construct a set of safe and usable cabins.

[0025] The nest door mechanism and the centering mechanism are both actuators for the corresponding compartments within the nest unit. The nest door mechanism controls the opening and closing of the nest compartment, opening the door when the drone returns to the nest or takes off, and closing the door when the drone is parked or in abnormal operating conditions, thus achieving protection and safety isolation. The centering mechanism adjusts the drone's position after it lands in the compartment, ensuring it is parked in a predetermined location for subsequent charging, battery swapping, securing, or status monitoring. Therefore, using power supply, the nest door mechanism, the centering mechanism, and the compartment's communication status as safety access conditions is to determine whether the candidate compartment possesses the basic capability for safe access and parking of drones.

[0026] The comprehensive scoring optimization is as follows: in the set of safe and available bays, a comprehensive score is calculated and ranked based on five weighted normalized factors: temperature, humidity, visual quality, waiting time, and battery swapping facility status, and the best score is selected.

[0027] A second aspect of the present invention provides a combined drone nest emergency control system, the system comprising: a central control cabinet, multiple drone nest units, a communication bus, a drone, a cloud server, a mains power input, a UPS uninterruptible power supply, and a sensor group;

[0028] The central control cabinet receives task instructions from the cloud server and performs unified scheduling and control of multiple nested units;

[0029] The nest unit is a distributed execution unit and a collaborative control node. It receives the operating status data uploaded by the sensor group monitoring module and is used to realize the access, parking, recharging, status monitoring and local control of the UAV. In abnormal working conditions, when the current master control node fails, dynamic master-slave election is carried out to determine a temporary master control node suitable for taking over the global scheduling authority from each nest unit as the new current master control node.

[0030] The drone is a controlled object for parking, accessing, or performing operations. It can be parked in the corresponding compartment inside the drone nest unit and interact with the system during the mission. When the target compartment of the drone or the corresponding backup drone nest of the target compartment fails, the current master control node uses a two-level screening method to reselect the compartment and determine a new target compartment.

[0031] The cloud server is used for remote task management, data storage and monitoring analysis, and can communicate with the central control cabinet through wireless communication network or wired network;

[0032] The mains power input is used to provide operating power to the central control cabinet and each unit under normal operating conditions;

[0033] UPS (Uninterruptible Power Supply): Used to provide emergency power to the central control cabinet and each unit when the mains power input is abnormally interrupted, while also playing the roles of voltage stabilization, filtering and power failure protection;

[0034] Sensor arrays are distributed within each nest unit to collect node status, bin status, mechanism status, and environmental status.

[0035] Furthermore, each nest unit's internal load unit includes an edge computing controller, a multi-link communication module, a status awareness module, a data storage unit, an energy management unit, and a nest execution unit;

[0036] The edge computing controller is used to perform functions such as fault identification, status assessment, master-slave election calculation, candidate warehouse screening, energy consumption optimization calculation, and local control strategy invocation.

[0037] The multi-link communication module is used to enable data interaction between the nest unit and the central control cabinet, other nest units, and the UAV;

[0038] The state perception module is installed inside each nest unit and connected to the sensor group. It is used to collect the operating status, environmental status and mechanical status of the nest unit and its internal compartments, and transmit the collected data to the edge computing controller.

[0039] The data storage unit is connected to the edge computing controller and is used to store status data, fault information, master-slave switching records, warehouse reselection results, energy consumption optimization results, and operation logs to form a black box-style operation record.

[0040] The energy management unit is used to detect the power supply status, perform the switching between mains power and UPS power supply, count the load power consumption, and feed back the remaining power status to the edge computing controller to support energy consumption optimization control under emergency power supply conditions.

[0041] The nest execution unit is used to receive control commands output by the edge computing controller and drive the corresponding execution mechanism to complete the opening and closing of the nest door, the adjustment of the UAV position, charging control or battery swapping control.

[0042] Furthermore, the component connection relationships of the system include:

[0043] Power supply connection: The mains power input is connected to the input terminal of the UPS uninterruptible power supply; the output terminal of the UPS uninterruptible power supply is connected to the central control cabinet and multiple cell units respectively, which are used to provide stable power supply under normal operating conditions and emergency power supply when the mains power is abnormally interrupted; the energy management unit inside each cell unit is connected to the UPS uninterruptible power supply and each load unit in the cell unit respectively, which are used to perform power supply status detection, power consumption statistics and emergency power supply switching control.

[0044] Communication Connections: The central control cabinet communicates with each nest unit via a communication bus, issuing control commands to each nest unit and receiving operational status information uploaded by each nest unit. The nest units are interconnected via the communication bus to form a distributed collaborative network. Preferably, the nest units 103 can form a ring or mesh communication topology, thus maintaining information transmission and collaborative control between nodes even when a local communication link fails. The multi-link communication module within each nest unit is connected to the communication bus to complete data exchange between the nest unit and the central control cabinet and other nest units.

[0045] Internal node connectivity: Within each nest unit, the edge computing controller connects to the multi-link communication module, status awareness module, data storage unit, energy management unit, and nest execution unit. The status awareness module connects to the sensor array to transmit collected environmental, power supply, mechanism, and bay status data to the edge computing controller. After analyzing and processing the data, the edge computing controller outputs control commands to the nest execution unit. The nest execution unit then drives the corresponding actuator to perform nest door control, centering control, charging control, or battery swapping control. The data storage unit connects to the edge computing controller to record the control process and abnormal events. The energy management unit connects to the edge computing controller to provide power supply status and remaining energy information. The multi-link communication module connects to the edge computing controller to enable data interaction between the nest unit and external nodes.

[0046] External Interaction: The central control cabinet communicates with the cloud server via a network interface to upload system operating status, fault information, and operating logs, and to receive task instructions or remote control information. In abnormal operating conditions, when the central control cabinet fails and a certain nest unit takes over the main control authority, the selected nest unit can also interact with the cloud server through its communication module. The drone is placed in the corresponding compartment inside the nest unit and synchronizes its status and interacts with the nest unit. After the drone enters the compartment, it can make electrical connections or signal interactions with the nest unit through a contact interface or wireless means to achieve identification, status synchronization, charging control, or battery swapping cooperation.

[0047] Furthermore, the central control cabinet and multiple nest units constitute a control system for centralized scheduling under normal operating conditions, while multiple nest units form a collaborative network for distributed takeover under abnormal operating conditions through a communication bus; the UPS uninterruptible power supply and energy management unit constitute an emergency power supply system; the sensor group, status perception module, edge computing controller and nest execution unit together constitute the status perception, decision analysis and action execution link.

[0048] Beneficial effects: 1. Reduces the risk of single point of failure and improves the system's autonomous operation capability. Under normal operating conditions, the central control cabinet acts as the default master node for unified scheduling. Under abnormal operating conditions, multiple nested units coordinate in a distributed manner based on the communication bus, and complete dynamic master-slave election and control authority reconstruction through node-level parameters. Thus, when the central control cabinet fails, communication is abnormal, or the master is unavailable, the system can still select a temporary master node from multiple nested units to continue scheduling and control, avoiding system-wide paralysis due to the failure of the central master, thereby reducing the risk of single point of failure under the centralized control architecture and improving the autonomous operation capability of the combined nested system under abnormal operating conditions.

[0049] 2. Enhanced capability for reconfiguration of drone pod resources under fault conditions. This invention combines nest unit-level control with pod-level scheduling. When the original target pod or the original backup pod fails, it can perform safety access determination and comprehensive scoring on candidate pods based on pod-level parameters, and reselect a new backup target pod from the set of safe and available pods. Therefore, the system can promptly complete resource reconfiguration and task migration when pods are abnormal, thereby improving the success rate and flexibility of drone homing, access, and operational support processes.

[0050] 3. Enhance emergency response capabilities under abnormal power outage conditions. This invention utilizes an energy management unit, a UPS uninterruptible power supply, and an energy consumption-time multi-objective optimization mechanism under emergency power supply to comprehensively control the system's remaining electrical energy, load power consumption, and key safety constraints. When the mains power input is interrupted, the system can prioritize power supply to the main control communication, status monitoring, engine compartment door closure, and necessary actuators, and cut off non-critical loads in a timely manner. This extends the system's continuous operating time under limited emergency power conditions and enhances emergency response capabilities under abnormal power outage conditions.

[0051] 4. Improve system security and maintainability. This invention, through a basic state awareness and fault identification mechanism, can continuously monitor node status, warehouse status, power supply status, environmental status, and actuator status. Upon detecting an anomaly, it can further trigger tiered safety circuit breakers to isolate abnormal actuators, abnormal warehouses, or faulty branches, preventing the spread of localized faults. Simultaneously, the system records fault data, master-slave switching processes, warehouse reselection results, energy consumption optimization results, and operational logs through a data storage unit, facilitating subsequent fault tracing, operational analysis, and maintenance optimization, thereby improving the overall security and maintainability of the system. Attached Figure Description

[0052] Figure 1 This is a schematic diagram of a combined emergency control system for machine nests.

[0053] Figure 2 This is a functional structure block diagram of a single nest unit.

[0054] Figure 3 This is a schematic diagram of the node-level distributed master-slave election relationship in a combined nested system.

[0055] Figure 4 This is a schematic diagram illustrating the logic of reselecting backup positions at the position level.

[0056] Figure 5 This is a schematic diagram of energy consumption-time multi-objective optimization control under emergency power supply conditions. Detailed Implementation

[0057] The technical solution of the present invention will be further described below with reference to the accompanying drawings.

[0058] Example 1:

[0059] like Figure 1 As shown, this invention provides an emergency control system for a modular drone nesting system. The system 101 includes a central control cabinet 102, multiple drone nesting units 103, a communication bus 104, a drone 105, a cloud server 106, a mains power input 107, a UPS uninterruptible power supply 108, and a sensor array. This embodiment provides four drone nesting units, numbered 103-1, 103-2, 103-3, and 103-4 in the figure. These components cooperate to achieve drone parking, access, recharging, status monitoring, centralized scheduling, and distributed emergency control under abnormal operating conditions.

[0060] The functions of each component in an emergency control system for a modular nest are described below:

[0061] Central control cabinet 102: The main control device of the system under normal operating conditions, used to receive task instructions issued by the cloud server 106 and to perform unified scheduling and control of multiple machine nest units 103. Preferably, the central control cabinet 102 includes a central control unit, a main control chip, and a communication gateway, used to realize functions such as task parsing, status summary, scheduling decision, control instruction issuance, and external communication.

[0062] Multiple nested units 103: distributed execution units and collaborative control nodes, preferably arranged in a matrix. Each nested unit can act as an independent edge control terminal, receiving operational status data uploaded by the sensor group monitoring module, for UAV access, parking, recharging, status monitoring, and local control. Under abnormal operating conditions, each nested unit can also participate in master-slave election, authority takeover, and collaborative emergency control; the dynamic master-slave election determines a temporary master node suitable for taking over global scheduling authority from among the nested units as the new current master node.

[0063] Communication bus 104: Used to connect the central control cabinet 102 with multiple nested units 103, and to connect the communication links between the nested units to form a system-level communication network. Preferably, the communication bus 104 can adopt a CAN bus, RS485 bus, or other wired communication methods suitable for industrial sites; in a preferred embodiment, the multiple nested units 103 can form a ring or mesh communication topology to improve communication redundancy and fault tolerance.

[0064] Drone 105: A controlled object for parking, access, or operation. It can be parked in a corresponding compartment within the drone nest unit and interacts with the nest system during mission execution. After Drone 105 returns to its nest, the corresponding nest unit can perform operations such as parking, position adjustment, charging, or battery swapping. If the target compartment of Drone 105 or its corresponding backup nest fails, the current master control node will use a two-level screening method to reselect a new target compartment.

[0065] Cloud server 106: Used for remote task management, data storage, and monitoring and analysis. It can communicate with the central control cabinet 102 via a wireless communication network or a wired network. The cloud server 106 sends task information, operating strategies, or remote control commands to the central control cabinet 102, and receives operating status data, fault information, and log records uploaded by the system.

[0066] Mains input 107: External power supply interface for the system, used to provide working power to the central control cabinet 102 and each unit under normal operating conditions.

[0067] UPS uninterruptible power supply 108: used to provide emergency power to the critical loads in the central control cabinet 102 and each unit when the mains power input 107 is abnormally interrupted. It can also play the roles of voltage stabilization, filtering and power failure protection to ensure that the system still has the necessary communication, monitoring and control capabilities under abnormal power failure conditions.

[0068] Sensor array: Distributed within each drone nesting unit, used to collect node status, bay status, mechanism status, and environmental status. Preferably, the sensor array includes temperature and humidity sensors, current / voltage detection elements, position detection elements, and sensors for detecting the drone's position status, providing input data for system fault identification, status assessment, and control decisions.

[0069] Combined with appendix Figure 2 As shown, a single nest unit 201 includes at least an edge computing controller 202, a multi-link communication module 203, a state awareness module 204, a data storage unit 205, an energy management unit 206, and a nest execution unit 207.

[0070] Edge computing controller 202: Located inside each hive unit, it is the core decision-making module of the hive unit and is used to perform functions such as fault identification, status assessment, master-slave election calculation, candidate warehouse screening, energy consumption optimization calculation and local control strategy invocation.

[0071] Multi-link communication module 203: Located inside each nest unit, it is used to realize data interaction between the nest unit and the central control cabinet 102, other nest units, and the UAV 105. Preferably, the multi-link communication module 203 can simultaneously support bus communication and wireless communication to improve the reliability of communication between nodes.

[0072] Status awareness module 204: Located inside each nest unit and connected to the sensor group, it is used to collect the operating status, environmental status and mechanical status of the nest unit and its internal compartments, and transmit the collected data to the edge computing controller 202.

[0073] Data storage unit 205: Connected to edge computing controller 202, it is used to store status data, fault information, master-slave switching records, warehouse reselection results, energy consumption optimization results, and operation logs to form a black box-style operation record.

[0074] Energy Management Unit 206: Located inside each unit, it is used to detect the power supply status, perform the switching between mains power and UPS power supply, count the load power consumption, and feed back the remaining power status to the edge computing controller 202 to support energy consumption optimization control under emergency power supply conditions.

[0075] Nest execution unit 207: Located inside each nest unit, it is used to receive control commands output by the edge computing controller 202 and drive the corresponding execution mechanism to complete actions such as opening and closing the nest door, adjusting the position of the UAV, charging control or battery swapping control.

[0076] The connection relationships of the components of an emergency control system for a modular nest are described below:

[0077] Power supply connections: The mains input 107 is connected to the input terminal of the UPS uninterruptible power supply 108; the output terminals of the UPS uninterruptible power supply 108 are connected to the central control cabinet 102 and multiple unit cells 103, respectively, to provide stable power supply under normal operating conditions and emergency power supply in case of abnormal mains power interruption. The energy management unit 206 inside each unit cell is connected to the UPS uninterruptible power supply 108 and each load unit within the unit cell, respectively, to perform power supply status detection, power consumption statistics, and emergency power supply switching control.

[0078] Communication Connections: The central control cabinet 102 communicates with each nest unit via the communication bus 104, used to issue control commands to each nest unit and receive operating status information uploaded by each nest unit. The nest units are also interconnected via the communication bus 104 to form a distributed collaborative network. Preferably, the nest units can form a ring or mesh communication topology, thus maintaining information transmission and collaborative control between nodes even when a local communication link fails. The multi-link communication module 203 within each nest unit is connected to the communication bus 104 to complete data exchange between the nest unit and the central control cabinet 102 and other nest units.

[0079] Internal node connections: Within each nest unit, the edge computing controller 202 is connected to the multi-link communication module 203, the status awareness module 204, the data storage unit 205, the energy management unit 206, and the nest execution unit 207. The status awareness module 204 is connected to a sensor array to transmit collected environmental, power supply, mechanism, and compartment status data to the edge computing controller 202. After analyzing and processing the data, the edge computing controller 202 outputs control commands to the nest execution unit 207. The nest execution unit 207 then drives the corresponding actuator to complete nest door control, centering control, charging control, or battery swapping control. The data storage unit 205 is connected to the edge computing controller 202 to record the control process and abnormal events. The energy management unit 206 is connected to the edge computing controller 202 to provide power supply status and remaining energy information. The multi-link communication module 203 is connected to the edge computing controller 202 to enable data interaction between the nest unit and external nodes.

[0080] External Interaction: The central control cabinet 102 communicates with the cloud server 106 via a network interface to upload system operating status, fault information, and operating logs, and to receive task instructions or remote control information. In abnormal operating conditions, when the central control cabinet 102 fails and a specific nesting unit takes over control, the selected nesting unit can also interact with the cloud server 106 via its communication module. The drone 105 is placed in its corresponding compartment within the nesting unit and synchronizes its status and interacts with the nesting unit. After accessing the compartment, the drone 105 can establish an electrical connection or signal interaction with the nesting unit via a contact interface or wireless means to achieve identification, status synchronization, charging control, or battery swapping coordination.

[0081] As can be seen from the above-mentioned components and their connections, the central control cabinet 102 and multiple nested units 103 constitute a control system for "centralized scheduling under normal operating conditions," while the multiple nested units 103 form a collaborative network for "distributed takeover under abnormal operating conditions" through a communication bus 104; the UPS uninterruptible power supply 108 and the energy management unit 206 constitute an emergency power supply system; the sensor group, the status perception module 204, the edge computing controller 202, and the nested execution unit 207 together constitute a status perception, decision analysis, and action execution link. Therefore, this invention can achieve unified scheduling under normal operating conditions and autonomous takeover and emergency control under abnormal operating conditions.

[0082] Example 2:

[0083] This invention discloses an emergency control method for a modular storage unit, employing a distributed hierarchical control mechanism of "centralized scheduling under normal operating conditions and distributed takeover under abnormal operating conditions." Under normal operating conditions, the central control cabinet 102 acts as the master control node to uniformly schedule each storage unit. In cases of central control cabinet 102 failure, target storage unit malfunction, communication anomalies, or abnormal power outages, each storage unit enters a distributed autonomous operation mode via the communication bus 104. It then sequentially executes basic status perception and fault identification, node-level dynamic master-slave election, storage unit-level backup storage unit reselection, energy consumption-time multi-objective optimization under emergency power supply, and graded safety circuit breaking and operation recording, thereby achieving continuous operation and safe control of the modular storage unit system under abnormal operating conditions.

[0084] In this invention, multiple nesting units 103 constitute distributed collaborative nodes in a combined nesting system. Therefore, parameters related to the overall operational capability, communication capability, power supply capability, health status, and control takeover capability of the nesting unit are defined as node-level parameters. The specific location within the nesting unit used for UAV access, parking, alternate landing, or operational support is defined as a "housing location," and parameters related to the availability, access security, and operational support capabilities of that location are defined as "housing location-level parameters." Node-level parameters are used for master-slave election and control authority reconfiguration, while housing-level parameters are used for candidate housing location screening, scoring, and alternate landing target determination.

[0085] Under normal operating conditions, the central control cabinet 102 receives task instructions from the cloud server 106 and, based on the status information uploaded by each nest unit, uniformly schedules tasks such as takeoff, homing, parking, recharging, and battery swapping of the UAV 105. After receiving control instructions, each nest unit drives the corresponding actuator to complete the relevant actions through the nest execution unit 207, and the status perception module 204 continuously provides feedback on the execution status and environmental status.

[0086] Under normal operating conditions, preferably, the central control cabinet 102 serves as the system's default master control node, communicating with the cloud server 106 to receive takeoff, homing, standby, or battery swapping mission commands from the UAV 105. Each nest unit collects the operating status of its own nest unit and its corresponding compartment through the status perception module 204, and uploads it to the central control cabinet 102 through the multi-link communication module 203. The central control cabinet 102 determines the target nest unit and target compartment based on the status information uploaded by each nest unit, and issues control commands to the corresponding nest unit. After receiving the control commands, the target nest unit controls the hatch opening and closing mechanism through the nest execution unit 207 to open the nest hatch, enabling the UAV 105 to complete access and landing; after the UAV 105 lands, the nest execution unit 207 further controls the UAV centering mechanism to complete position adjustment, and controls the battery swapping mechanism to perform battery swapping operations when necessary. During execution, the status perception module 204 continuously collects the position of the actuator, the motor drive current, the ambient temperature and humidity, and the visual status, and feeds them back to the edge computing controller 202 and the central control cabinet 102. At the same time, the data storage unit 205 records them locally.

[0087] Under abnormal operating conditions, the system shall perform emergency control according to the following procedure:

[0088] Step 1: Basic Status Awareness and Fault Identification

[0089] The control module in each hive unit receives operational status data uploaded by the monitoring module, collects and updates node status, bay status, and environmental status in real time, and forms a basic status dataset for subsequent distributed decision-making. This basic status data includes at least: remaining node power, node control environment temperature, node control environment humidity, node communication status, node health status, node overall load, bay power supply status, hive door mechanism status, centering mechanism status, bay communication status, bay local environmental temperature, bay local environmental humidity, visual status, estimated waiting time, and battery swapping mechanism status.

[0090] The current master control node performs anomaly detection and fault identification on each node and each warehouse based on the aforementioned basic status data. When power supply anomalies, communication anomalies, environmental parameter exceeding limits, or actuator malfunctions are detected, a corresponding fault identifier is generated, forming a fault status set, which serves as the input basis for subsequent node-level master-slave election, warehouse-level backup reselection, energy consumption optimization control, and safety circuit breaker. Furthermore, the current master control node can classify faults into minor, moderate, and severe faults based on their impact range and severity.

[0091] Step 2: Dynamic Master-Slave Election Method Based on Node-Level Parameters

[0092] like Figure 3As shown, preferably, when each nest unit fails to receive the heartbeat signal from the current master node for several consecutive cycles, the current master node is deemed to have failed, and a dynamic master-slave election process is triggered. Each nest unit extracts node-level parameters from the basic status data, constructs an election reputation value, and determines a temporary master node suitable for taking over global scheduling authority. The node-level parameters include at least the node's remaining power, node control environment temperature, node control environment humidity, node-level communication capability, node overall health, and node overall load.

[0093] For the Each nested unit constructs a node-level state vector. :

[0094]

[0095] in:

[0096] : Represents a node The remaining battery power.

[0097] : Represents a node The ambient temperature of the area where the control module is located.

[0098] : Represents a node The ambient humidity of the area where the control module is located.

[0099] : Represents a node The node-level communication capability score.

[0100] : Represents a node The comprehensive health score is used to quantify the overall reliability of the nesting unit. It comprehensively evaluates the hardware aging degree, historical failure rate and current performance deviation of the unit. The higher the score, the "healthier" the node is and the more suitable it is to serve as a temporary master in case of anomalies.

[0101] : Represents a node The current overall load indicates the intensity of tasks and resource utilization currently being undertaken.

[0102] Build node election reputation value Based on the aforementioned node-level parameters, the edge computing controller 202 calculates the election reputation value of the nodes. Its expression is:

[0103]

[0104] in:

[0105] : Indicates the baseline full-charge capacity.

[0106] : Indicates the node control ambient temperature threshold.

[0107] : Indicates the threshold for controlling ambient humidity at the node.

[0108] : Indicates the maximum score for node-level communication capability.

[0109] : Indicates the maximum allowable total load.

[0110] : represents the weight coefficients of each evaluation factor, satisfying...

[0111]

[0112] Among them, the higher the remaining power of a node, the more suitable the temperature and humidity of the node's control environment, the stronger the node-level communication capability, and the higher the overall health, the higher the node's election reputation value; the greater the overall load of a node, the lower its election reputation value.

[0113] Each nesting unit broadcasts its campaign reputation value via communication bus 104. Within a preset time window... Inside, if node satisfy:

[0114] and

[0115] Then determine the node It serves as a temporary master node, and this node takes over the global scheduling authority of the system.

[0116] After the election, the remaining nesting units enter slave node status and report their node status and warehouse status to the temporary master node, accepting its subsequent scheduling and control. This temporary master node continues to perform functions such as task scheduling, anomaly identification, candidate warehouse screening, and emergency control, thereby ensuring system continuity even if the central control cabinet 102 fails. Through this method, the system can elect a temporary master node with strong continuous operation capability, high communication capability, and excellent overall reliability from multiple nesting units based on node-level parameters, becoming the new current master node.

[0117] Step 3: Reselecting Alternate Positions Based on Position-Level Parameters

[0118] like Figure 4As shown, preferably, when the original target bay or the original alternate landing bay fails, the current master control node extracts bay-level parameters from the basic status dataset formed in step 1, and performs bay reselection for candidate bays in the combined bay to determine a new alternate landing target bay.

[0119] For the For each candidate position, construct a position-level state vector. :

[0120]

[0121] in:

[0122] : Indicates position The power supply status.

[0123] : Indicates position The status of the hatch mechanism.

[0124] : Indicates position The status of the central institution.

[0125] : Indicates position The warehouse-level communication status.

[0126] : Indicates position The local ambient temperature.

[0127] : Indicates position The local ambient humidity.

[0128] : Indicates position Visual quality score.

[0129] : Indicates position The estimated waiting time.

[0130] : Indicates position The status score of the battery swapping mechanism.

[0131] To ensure that candidate positions first meet the basic access security conditions, a two-level screening method is adopted for position reselection, including security access judgment and comprehensive score selection.

[0132] 1. Security Access Determination

[0133] For candidate positions Construct security access variables Its expression is:

[0134]

[0135] in, , , and All are binary variables (1 for normal, 0 for abnormal).

[0136] When the candidate bay meets the requirements of normal power supply, normal nest door mechanism, normal centering mechanism, and normal bay communication status. ;otherwise, Only when At that time, position Enter the safe and available position set .

[0137] This leads to the construction of a safe and available set of positions:

[0138]

[0139] in, This indicates the total number of compartments in a modular nest.

[0140] when If the current combined nesting structure does not have any available alternate landing slots, the system will trigger the upper-level scheduling module or an external alternate landing strategy.

[0141] 2. Overall score selection

[0142] For candidate positions that have passed the safety access assessment Construct a comprehensive scoring function based on position-level parameters. Its expression is:

[0143]

[0144] The parameters in the formula are defined as follows:

[0145] : Indicates the local ambient temperature threshold of the storage area.

[0146] : Indicates the local humidity threshold of the warehouse.

[0147] : Indicates the maximum allowed waiting time.

[0148] : represents the weight coefficients of each evaluation factor, satisfying...

[0149]

[0150] Among them, the lower the local ambient temperature, the lower the local ambient humidity, and the shorter the expected waiting time, the higher the corresponding score; the higher the visual quality and the better the condition of the battery swapping mechanism, the higher the corresponding score.

[0151] 3. Determining the target position

[0152] In a safe and available warehouse set In the selection process, the candidate position with the highest overall score is chosen as the new target position for rebalancing. The expression for this is:

[0153]

[0154] Using the above methods, the system can safely screen and reconstruct candidate berths based on berth-level parameters, thereby determining new alternate landing targets under the condition of failure of the original target berth.

[0155] Step 4: Energy consumption-time multi-objective optimization method under emergency power supply.

[0156] like Figure 5 As shown, preferably, when the system detects an interruption in the mains power input 107, the energy management unit 206 switches the system to the UPS uninterruptible power supply 108 power supply mode and reports the emergency power supply status to the current master control node. Based on the basic status data formed in step 1, the master control scheduling results determined in step 2, and the backup target warehouse results determined in step 3, the current master control node performs energy consumption-time multi-objective optimization control on each load unit of the system.

[0157] The optimized control aims to extend the system's continuous operating time under emergency power conditions, ensure continuous power supply to critical functions, and maintain necessary safety conditions. These critical functions include at least communication functions, control functions, nest door closing functions, and key monitoring functions.

[0158] Based on the remaining power status provided by the power module and the power consumption information of each load unit, a system power change model is established:

[0159]

[0160] in:

[0161] : Indicates time The system's remaining power supply capacity.

[0162] : Indicates the system's base power consumption.

[0163] : indicates the first The switching state of each load unit, with values ​​ranging from 0 to 1. (0 means off, 1 means on).

[0164] : indicates the first The power consumption corresponding to each load unit.

[0165] Based on this, an optimization model is constructed with the goal of extending the system's sustainable operating time and satisfying key safety constraints. Its objective function is: And satisfy the following constraints:

[0166]

[0167]

[0168] : Indicates the system's sustainable operating time under emergency power supply conditions (optimization objective).

[0169] : Indicates the total energy that the emergency power supply unit can provide.

[0170] This indicates that the nest hatch should remain closed and safe at the end of the optimization process.

[0171] Furthermore, model predictive control is employed for the load switching sequence. Rolling optimization is carried out to prioritize ensuring continuous power supply for communication, control, nest door closure, and critical monitoring functions, while cutting off non-critical loads as needed, thereby achieving tiered energy consumption control and runtime optimization in emergency situations.

[0172] Through the above methods, the system can balance safety, continuity, and energy utilization efficiency under abnormal power outages or limited power supply conditions, thereby improving the emergency survivability of the modular cell system.

[0173] Step 5: Graded safety fuse tripping and black box recording

[0174] When a severe fault is identified in step 1, or when an unrecoverable serious anomaly occurs during the execution of steps 2, 3, or 4, the system activates the graded safety circuit breaker and black box recording mechanism.

[0175] The graded safety circuit breaker includes isolating and disconnecting fault-related power supply branches, faulty actuators, abnormal communication links, or abnormal compartments to block the fault propagation path and reduce secondary risks; at the same time, the system keeps critical control modules, critical communication modules, and necessary safety monitoring modules in a minimum safe operating state.

[0176] At the same time, fault data, fault time, node election results, warehouse reselection results, energy consumption optimization control results, execution instructions and operation logs are written in real time to the non-volatile memory corresponding to each nest unit, forming a black box-style operation record.

[0177] The operation records are used for fault tracing, responsibility determination, model correction and system optimization, thereby improving the traceability and engineering application reliability of the combined nest system in complex emergency scenarios.

[0178] Through the aforementioned graded safety circuit breaker and black box recording mechanism, the system can achieve rapid loss prevention and full-process traceability under severe fault conditions, thereby improving the overall safety and operational reliability of the system.

Claims

1. A combined nest emergency control method, characterized in that, The modular cell includes a central control cabinet and various cell units; the method includes: Each nest unit receives operational status data uploaded by the sensor group, and collects and updates the node status of the distributed collaborative nodes composed of each nest unit, the location status of the UAV stored inside each nest unit, and the environmental status in real time, forming a basic status dataset for subsequent distributed decision-making; the current master control node performs anomaly detection and fault identification on each node and each location based on the basic status dataset. When the current master node fails, a dynamic master-slave election is conducted to determine a temporary master node suitable for taking over global scheduling authority from each nest unit as the new current master node; When the target drone location or its corresponding alternate landing site malfunctions, the current master control node uses a two-level screening method to reselect the location and determine a new target location.

2. The combined nest emergency control method according to claim 1, characterized in that, The method also includes, when there is an abnormal power outage or limited power supply, the current master control node performs energy consumption-time multi-objective optimization control on each load unit of the combined nest based on basic status data; the energy consumption-time multi-objective optimization control prioritizes ensuring continuous power supply for communication, control, nest door closing and monitoring functions.

3. The combined nest emergency control method according to claim 1, characterized in that, The method further includes activating a tiered safety circuit breaker and black box recording mechanism when the current master control node identifies a severe fault or an unrecoverable serious anomaly occurs during method execution; the tiered safety circuit breaker includes isolating and disconnecting the fault-related power supply branch, fault execution mechanism, abnormal communication link or abnormal compartment; the black box recording mechanism includes writing fault data, fault time, node election results, compartment re-selection results, energy consumption optimization control results, execution instructions and operation logs into the non-volatile memory corresponding to each nest unit in real time to form a black box operation record.

4. The combined nest emergency control method according to claim 1, characterized in that, The dynamic master-slave election includes: when each nest unit fails to receive the heartbeat signal of the current master node for several consecutive cycles, it determines that the current master node has failed and triggers the dynamic master-slave election process; each nest unit extracts node-level parameters from the basic state data, constructs an election reputation value, and each nest unit broadcasts its own election reputation value. Within a preset time window, if node k has the highest election reputation value, node k is determined as the temporary master node, and this temporary master node becomes the new current master node.

5. The combined nest emergency control method according to claim 4, characterized in that, The evaluation rules for election reputation value include the higher the remaining power of the node, the more suitable the temperature and humidity of the node's control environment, the stronger the node-level communication capability, and the higher the overall health. The higher the overall load of a node, the lower its election reputation score. The overall health score is used to quantify the reliability of a nest unit, comprehensively assessing the hardware aging degree, historical failure rate, and current performance deviation of the nest unit. The higher the score, the higher the overall health score.

6. The combined nest emergency control method according to claim 1, characterized in that, The two-level screening method includes safety access determination and comprehensive score selection; the safety access determination is to screen out all candidate bays that are working normally by using the logical product of four binary state variables: power supply, nest door mechanism, centering mechanism and bay communication status, and construct a set of safe and usable bays. The comprehensive scoring optimization is as follows: in the set of safe and available bays, a comprehensive score is calculated and ranked based on five weighted normalized factors: temperature, humidity, visual quality, waiting time, and battery swapping facility status, and the best score is selected.

7. A combined emergency control system for a nest-like structure implementing the method of claim 1, characterized in that, The system includes: a central control cabinet, multiple nesting units, a communication bus, a drone, a cloud server, mains power input, a UPS uninterruptible power supply, and a sensor array; The central control cabinet receives task instructions from the cloud server and performs unified scheduling and control of multiple nested units; The nest unit is a distributed execution unit and a collaborative control node. It receives the operating status data uploaded by the sensor group monitoring module and is used to realize the access, parking, recharging, status monitoring and local control of the UAV. In abnormal working conditions, when the current master control node fails, dynamic master-slave election is carried out to determine a temporary master control node suitable for taking over the global scheduling authority from each nest unit as the new current master control node. The drone is a controlled object for parking, accessing, or performing operations. It can be parked in the corresponding compartment inside the drone nest unit and interact with the system during the mission. When the target compartment of the drone or the corresponding backup drone nest of the target compartment fails, the current master control node uses a two-level screening method to reselect the compartment and determine a new target compartment. The cloud server is used for remote task management, data storage and monitoring analysis, and can communicate with the central control cabinet through wireless or wired networks. The mains power input is used to provide operating power to the central control cabinet and each unit under normal operating conditions; UPS uninterruptible power supplies are used to provide emergency power to the central control cabinet and each unit when the mains power input is abnormally interrupted; Sensor arrays are distributed within each nest unit to collect node status, bin status, mechanism status, and environmental status.

8. The combined nest emergency control system according to claim 7, characterized in that, Each nest unit's internal load units include an edge computing controller, a multi-link communication module, a status awareness module, a data storage unit, an energy management unit, and a nest execution unit; The edge computing controller is used to perform functions such as fault identification, status assessment, master-slave election calculation, candidate warehouse screening, energy consumption optimization calculation, and local control strategy invocation. The multi-link communication module is used to enable data interaction between the nest unit and the central control cabinet, other nest units, and the UAV; The state perception module is installed inside each nest unit and connected to the sensor group. It is used to collect the operating status, environmental status and mechanical status of the nest unit and its internal compartments, and transmit the collected data to the edge computing controller. The data storage unit is connected to the edge computing controller and is used to store status data, fault information, master-slave switching records, warehouse reselection results, energy consumption optimization results, and operation logs to form a black box-style operation record. The energy management unit is used to detect the power supply status, perform the switching between mains power and UPS power supply, count the load power consumption, and feed back the remaining power status to the edge computing controller. The nest execution unit is used to receive control commands output by the edge computing controller and drive the corresponding execution mechanism to complete the opening and closing of the nest door, the adjustment of the UAV position, charging control or battery swapping control.

9. A combined emergency control system for a hive according to claim 8, characterized in that, The component connection relationships of the system include: Power supply connection: The mains power input is connected to the input terminal of the UPS uninterruptible power supply; the output terminal of the UPS uninterruptible power supply is connected to the central control cabinet and multiple cell units respectively, which are used to provide stable power supply under normal operating conditions and emergency power supply when the mains power is abnormally interrupted; the energy management unit inside each cell unit is connected to the UPS uninterruptible power supply and each load unit in the cell unit respectively, which are used to perform power supply status detection, power consumption statistics and emergency power supply switching control. Communication connection relationship: The central control cabinet communicates with each nest unit through the communication bus, and is used to send control commands to each nest unit and receive the operating status information uploaded by each nest unit; the nest units are interconnected through the communication bus to form a distributed collaborative network; the multi-link communication module inside each nest unit is connected to the communication bus to complete the data exchange between the nest unit and the central control cabinet and other nest units. Internal node connectivity: Within each nest unit, the edge computing controller connects to the multi-link communication module, status awareness module, data storage unit, energy management unit, and nest execution unit. The status awareness module connects to the sensor array to transmit collected environmental, power supply, mechanism, and bay status data to the edge computing controller. After analyzing and processing the data, the edge computing controller outputs control commands to the nest execution unit. The nest execution unit then drives the corresponding actuator to perform nest door control, centering control, charging control, or battery swapping control. The data storage unit connects to the edge computing controller to record the control process and abnormal events. The energy management unit connects to the edge computing controller to provide power supply status and remaining energy information. The multi-link communication module connects to the edge computing controller to enable data interaction between the nest unit and external nodes. External Interaction: The central control cabinet communicates with the cloud server via a network interface to upload system operating status, fault information, and operating logs, and to receive task instructions or remote control information. In abnormal operating conditions, when the central control cabinet fails and a certain nest unit takes over the main control authority, the selected nest unit can also interact with the cloud server through its communication module. The drone is placed in the corresponding compartment inside the nest unit and synchronizes its status and interacts with the nest unit. After the drone enters the compartment, it can make electrical connections or signal interactions with the nest unit through a contact interface or wireless means to achieve identification, status synchronization, charging control, or battery swapping cooperation.

10. A combined emergency control system for a hive according to claim 9, characterized in that, The central control cabinet and multiple nest units constitute a control system for centralized scheduling under normal operating conditions. Multiple nest units are connected by a communication bus to form a collaborative network for distributed takeover under abnormal operating conditions. The UPS uninterruptible power supply and energy management unit constitute an emergency power supply system. The sensor group, status perception module, edge computing controller and nest execution unit together constitute the status perception, decision analysis and action execution link.

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