Multidirectional bending control method, system and equipment for flexible electronic connector

Abstract

The invention provides a multi-direction bending control method, system and device for a flexible electronic connector, and relates to the technical field of electronic connectors, the method comprises the following steps: obtaining a target flexible electronic connector, integrating a plurality of elastic support units, an electromagnetic driving module, a control module and a sensor module in a multi-direction bending control assembly of the connector, bending data of a plurality of parts are acquired through the sensor module; a control module is adopted to analyze and obtain multidirectional bending cooperative control parameters based on a bending demand target, and an electromagnetic driving module is adopted to control a plurality of elastic supporting units to perform multidirectional bending control on the target flexible electronic connector. The flexible electronic connector solves the technical problem that an existing flexible electronic connector is difficult to realize stable adaptation in a complex environment due to the lack of real-time sensing and active control capability for multi-part and multi-direction deformation states, and improves the multi-direction bending control precision, the response flexibility and the operation reliability of the connector.

Description

Technical Field

[0001] This application relates to the field of electronic connector technology, and specifically to a method, system and device for multi-directional bending control of flexible electronic connectors. Background Technology

[0002] As a key component in flexible circuit systems, flexible electronic connectors must not only ensure the transmission of electrical signals but also adapt to complex spatial structures and multi-directional dynamic bending requirements. Most existing flexible electronic connectors utilize highly flexible materials, achieving a certain degree of bending capability through the inherent compliance of the structure. However, this reliance on passive material deformation has several limitations. First, the connector's bending state typically lacks sensing and adjustment capabilities, making precise control over multiple positions and directions difficult. Second, during long-term use, connectors are prone to mechanical fatigue, breakage, or unstable signal transmission due to improper bending. Furthermore, in complex dynamic scenarios, existing flexible electronic connectors cannot adjust in real-time according to environmental changes, limiting their widespread adoption in high-reliability and high-precision applications. Summary of the Invention

[0003] This application provides a multi-directional bending control method, system, and device for flexible electronic connectors. It solves the technical problem that the lack of real-time perception and active control capabilities for the deformation states of multiple parts and directions of flexible electronic connectors in the prior art makes it difficult for connectors to achieve stable adaptation in complex environments, and easily leads to mechanical fatigue and signal loss. It achieves the technical effect of improving the multi-directional bending control accuracy, response flexibility, and operational reliability of flexible electronic connectors.

[0004] In view of the above problems, this application provides a multi-directional bending control method for flexible electronic connectors. The method includes: acquiring a target flexible electronic connector, the flexible electronic connector including a connector body, a flexible circuit board, and a multi-directional bending control component, wherein the connector body is connected to an external device, the flexible circuit board is disposed inside the connector body, and the multi-directional bending control component is distributed in the bending area of ​​the flexible circuit board; the multi-directional bending control component integrates multiple elastic support units, an electromagnetic drive module, a control module, and a sensor module, and acquires bending data of multiple parts of the flexible electronic connector through the sensor module; the control module performs control parameter analysis on the bending data of the multiple parts based on the bending requirement target to obtain multi-directional bending collaborative control parameters; and the electromagnetic drive module controls the multiple elastic support units to perform multi-directional bending control on the target flexible electronic connector based on the multi-directional bending collaborative control parameters.

[0005] Preferably, the step of acquiring bending data of multiple parts of the flexible electronic connector through the sensor module includes: acquiring structural attribute parameters of the flexible electronic connector, including specifications, dimensions, component composition, and material properties; performing finite element simulation based on the structural attribute parameters of the flexible electronic connector to obtain connector bending simulation results; performing stress-strain analysis on the connector bending simulation results to identify a set of key parts, and sequentially deploying sensor modules on the set of key parts, the sensor modules including stress sensors, angle sensors, and velocity sensors; and sensing and monitoring the set of key parts through the sensor modules when the flexible electronic connector performs a bending operation to obtain bending data of the multiple parts.

[0006] Preferably, obtaining the connector bending simulation results includes: determining the mesh type and mesh density based on the geometry and analysis requirements of the flexible electronic connector; performing modeling, mesh generation, and finite element analysis on the structural property parameters of the flexible electronic connector according to the mesh type and mesh density to establish a three-dimensional finite element model of the connector; defining boundary conditions and bending loads based on the bending information of the connector application scenario; and using a solver to perform finite element simulation and solution on the three-dimensional finite element model of the connector based on the boundary conditions and bending loads to obtain the connector bending simulation results.

[0007] Preferably, obtaining the multi-directional bending collaborative control parameters includes: decomposing the bending demand target into demand indicators to obtain a bending performance indicator set; quantifying the bending demand for each performance indicator in the bending performance indicator set to obtain a bending performance indicator demand parameter set; mapping the bending performance indicator demand parameter set to the bending data of the multiple parts for comparison and analysis to obtain multiple part target bending indicator parameters; and using the control module to perform control parameter analysis on the multiple part target bending indicator parameters to obtain the multi-directional bending collaborative control parameters.

[0008] Preferably, obtaining the target bending index parameters for multiple parts includes: filtering and denoising the bending data of the multiple parts and calibrating the data to obtain bending data of multiple standard parts; mapping the bending performance index requirement parameter set to the bending data of the multiple parts and performing correlation analysis to generate bending index requirement parameters for multiple parts; determining bending performance index parameters for multiple parts based on the bending data of the multiple standard parts; and performing deviation comparison analysis between the bending index requirement parameters for multiple parts and the bending performance index parameters for multiple parts to determine the target bending index parameters for multiple parts.

[0009] Preferably, obtaining the multi-directional bending collaborative control parameters includes: initializing a PID bending controller based on the control characteristic information of the flexible electronic connector; using the PID bending controller to analyze the control parameters of the target bending index parameters of the multiple parts to obtain bending control parameters for multiple parts; performing bending simulation and coupling relationship identification on each bending part in the bending control parameters for multiple parts to determine the coupling relationship parameters of the bending parts; performing coupling transfer analysis and function fitting based on the coupling relationship parameters of the bending parts to establish a coupling relationship model; and performing collaborative strategy analysis on the bending control parameters of the multiple parts based on the coupling relationship model to determine the multi-directional bending collaborative control parameters.

[0010] Preferably, determining the multi-directional bending collaborative control parameters includes: acquiring the bending control target and the bending part constraint conditions; extracting characteristics from the coupling relationship model to obtain the bending part coupling path and the bending part coupling strength; and performing distributed collaborative strategy analysis on the bending control parameters of the multiple parts based on the bending control target, the bending part constraint conditions, and the bending part coupling path and the bending part coupling strength to determine the multi-directional bending collaborative control parameters.

[0011] Preferably, determining the multi-directional bending collaborative control parameters includes: constructing a bending optimization objective function based on the bending control objective; using the bending location constraints, the bending location coupling path, and the bending location coupling strength as coupling constraint terms, and simultaneously dividing the bending control parameters of the multiple locations into distributed nodes to obtain distributed node bending control parameters; initializing the particle swarm search space based on the distributed node bending control parameters; and using the bending optimization objective function based on the coupling constraint terms to perform global iterative optimization within the particle swarm search space to determine the multi-directional bending collaborative control parameters.

[0012] On the other hand, this application also provides a multi-directional bending control system for flexible electronic connectors. The system includes: a target acquisition unit for acquiring a target flexible electronic connector, the flexible electronic connector including a connector body, a flexible circuit board, and a multi-directional bending control component, wherein the connector body is connected to an external device, the flexible circuit board is disposed inside the connector body, and the multi-directional bending control component is distributed in the bending area of ​​the flexible circuit board; an integrated sensing unit for integrating multiple elastic support units, an electromagnetic drive module, a control module, and a sensor module within the multi-directional bending control component, and acquiring bending data of multiple parts of the flexible electronic connector through the sensor module; a control parameter parsing unit for using the control module to parse the bending data of the multiple parts based on the bending requirement target to obtain multi-directional bending collaborative control parameters; and a multi-directional bending control unit for controlling the multiple elastic support units to perform multi-directional bending control on the target flexible electronic connector through the electromagnetic drive module based on the multi-directional bending collaborative control parameters.

[0013] Thirdly, this application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described multi-directional bending control method for flexible electronic connectors.

[0014] One or more technical solutions provided in this application have at least the following beneficial effects: This application provides a multi-directional bending control method for flexible electronic connectors. Focusing on the core requirement of achieving high-precision, controllable bending of flexible electronic connectors in complex environments, a control flow characterized by integrated sensing, analysis, and actuation is designed. First, a basic platform with structural controllability is constructed by acquiring a target flexible electronic connector, including the connector body, flexible circuit board, and multi-directional bending control components. Then, multi-directional bending control components, integrating elastic support units, electromagnetic drive modules, control modules, and sensor modules, are distributed and installed in the bending area of ​​the flexible circuit board, enabling it to have local actuation and state awareness capabilities. The sensor module collects bending data from multiple key locations, and the control module analyzes the data based on externally set bending requirements to generate targeted multi-directional bending collaborative control parameters. Finally, the electromagnetic drive module precisely drives the elastic support unit according to these multi-directional bending collaborative control parameters, thereby achieving coordinated bending control of the flexible electronic connector in multiple directions and locations. Through the synergistic effect of the above-mentioned links, this application effectively improves the adaptability of flexible electronic connectors to complex spatial environments, and significantly enhances the multi-directional bending control accuracy, response flexibility and operational reliability of flexible electronic connectors in high reliability and high flexibility application scenarios.

[0015] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a multi-directional bending control method for flexible electronic connectors provided in an embodiment of this application.

[0017] Figure 2 This is a schematic diagram of the structure of a multi-directional bending control system for flexible electronic connectors provided in an embodiment of this application.

[0018] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0019] Explanation of reference numerals in the attached drawings: Target acquisition unit 10, integrated sensing unit 20, control parameter parsing unit 30, multi-directional bending control unit 40, bus 300, receiver 301, processor 302, transmitter 303, memory 304, bus interface 305. Detailed Implementation

[0020] This application provides a multi-directional bending control method, system, and device for flexible electronic connectors. It solves the technical problem that the lack of real-time perception and active control capabilities for the deformation states of multiple parts and directions of flexible electronic connectors in the prior art makes it difficult for connectors to achieve stable adaptation in complex environments, and easily leads to mechanical fatigue and signal loss. It achieves the technical effect of improving the multi-directional bending control accuracy, response flexibility, and operational reliability of flexible electronic connectors.

[0021] Example 1, as Figure 1 As shown, embodiments of this application provide a multi-directional bending control method for flexible electronic connectors, the method comprising: Step S100: Obtain the target flexible electronic connector, which includes a connector body, a flexible circuit board, and a multi-directional bending control component. The connector body is connected to an external device, the flexible circuit board is disposed inside the connector body, and the multi-directional bending control component is distributed in the bending area of ​​the flexible circuit board.

[0022] Specifically, the first step is to identify and acquire the target flexible electronic connector from the flexible electronics system. This target flexible electronic connector structurally includes a connector body, an internally embedded flexible circuit board, and multi-directional bending control components covering key bending areas of the circuit board. The connector body is used to achieve a stable connection with external devices such as the main control device, display screen, and sensor array, and is typically made of high-strength, lightweight materials. The flexible circuit board is embedded in the connector body based on preset conduction paths and layout requirements, and several bending areas are reserved to allow for deformation. Multi-directional bending control components are evenly distributed in these areas for subsequent deformation control, signal acquisition, and feedback. The flexible circuit board is a circuit board with conductive lines printed on a flexible material substrate (such as polyimide or PET), enabling deformation while maintaining signal transmission capability. This step establishes the physical foundation and structural framework of the entire flexible electronic connector control system.

[0023] Step S200: The multi-directional bending control component integrates multiple elastic support units, an electromagnetic drive module, a control module, and a sensor module. The sensor module collects bending data of multiple parts of the flexible electronic connector.

[0024] Specifically, multiple elastic support units, electromagnetic drive modules, control modules, and sensor modules are deployed in the bending area of ​​the target flexible electronic connector to construct a highly integrated multi-directional bending control component. The elastic support units are structural components capable of reversible deformation under controlled conditions, providing mechanical support and assisting the flexible electronic connector in achieving the desired deformation. The electromagnetic drive module generates a magnetic field by controlling current changes to drive the elastic structure. The control module is the core unit for data processing, control command generation, and execution, and can be implemented using a microcontroller, FPGA (Field-Programmable Gate Array), or embedded system. The sensor module is a sensing component used to collect state information such as deformation, stress, and angle, including stress sensors, angle sensors, and gyroscopes. The sensor module collects deformation information of the flexible electronic connector in real time during operation, including bending angles, applied stress, and bending speeds at key locations. All data is initially processed by the control module and uploaded to the main control system for subsequent control strategy generation. This sensing-feedback closed-loop design provides an active sensing capability for the flexible electronic connector's shape, providing an information foundation for achieving adaptive bending control.

[0025] Step S300: The control module analyzes the bending data of the multiple parts based on the bending requirement target to obtain multi-directional bending collaborative control parameters.

[0026] Specifically, bending requirements refer to the functional requirements set by the flexible electronic system or the user regarding the shape changes of the flexible electronic connector, including indicators such as angle range, response time, and path trajectory.

[0027] After receiving bending data from multiple locations, the control module combines this data with preset bending requirements and extracts executable control command parameters through a computational model. First, the overall bending requirement is broken down into performance indicators for each location. Then, the bending data from multiple locations is mapped and compared with the requirement parameters. Through filtering, calibration, and deviation analysis, the target bending indicators for each key location are obtained. The control module uses analytical algorithms (such as PID controllers, neural networks, and fuzzy control) to model, tune, and decouple these target bending indicators, ultimately outputting unified and coordinated multi-directional bending collaborative control parameters for scheduling the coordinated actions of multiple elastic support units.

[0028] Step S400: The electromagnetic drive module controls the multiple elastic support units to perform multi-directional bending control on the target flexible electronic connector based on the multi-directional bending collaborative control parameters.

[0029] Specifically, the multi-directional bending coordinated control parameters output by the control module are transmitted in real time to each electromagnetic drive module. The electromagnetic drive modules precisely adjust the current magnitude, switching frequency, and duration according to the requirements of the multi-directional bending coordinated control parameters, thereby causing each elastic support unit to deform in a specific direction and amplitude. The coordinated deformation of these support units in different directions realizes the multi-directional dynamic bending behavior of the entire flexible electronic connector. The control commands can be continuously corrected based on external conditions or bending feedback information to form an adaptive closed-loop control.

[0030] Furthermore, step S200 includes: Step S210: Obtain the structural attribute parameters of the flexible electronic connector, including specifications, dimensions, component composition, and material properties.

[0031] Step S220: Perform finite element simulation based on the structural property parameters of the flexible electronic connector to obtain the connector bending simulation results.

[0032] Step S230: Perform stress-strain analysis on the connector bending simulation results, identify the set of key parts, and sequentially deploy sensor modules on the set of key parts. The sensor modules include stress sensors, angle sensors, and speed sensors.

[0033] Step S240: When the flexible electronic connector is bent, the sensor module is used to sense and monitor the set of key parts to obtain bending data of the multiple parts.

[0034] Specifically, extract the structural property parameters of the flexible electronic connector from CAD design drawings or physical scan data, including the specification dimensions, component composition, and material properties of the flexible electronic connector. These structural property parameters form the basic input for subsequent finite element simulation modeling, ensuring that the simulation results have accurate engineering significance and physical consistency. Among them, the specification dimensions include physical dimension parameters such as the overall length, width, thickness of the flexible electronic connector, and the layout spacing of key components; the component composition includes the types and spatial layouts of various functional components in the flexible electronic connector, such as the circuit layer, dielectric layer, reinforcement layer, etc.; the material properties include material mechanical property parameters such as the elastic modulus, Poisson's ratio, density, and thermal expansion coefficient of the flexible electronic connector.

[0035] Based on the obtained structural property parameters, construct a three-dimensional model of the flexible electronic connector in the finite element simulation platform, set boundary conditions and loads (such as bending radius, compression force, torque, etc.), simulate the force and deformation process under typical use conditions, and obtain the connector bending simulation results for evaluating the stress conditions of each part of the structure. Finite element simulation provides a scientific means for pre-evaluating the structural performance, helps to detect potential weak areas of the connector in advance, and enables accurate identification and perception design optimization of high-risk parts.

[0036] Based on the connector bending simulation results, identify the key areas of the flexible electronic connector structure, extract multiple regions with local high stress, high strain or critical deformation, and form a set of key parts. Subsequently, sensor modules are arranged on these parts, integrating three types of sensors: stress sensors, angle sensors, and velocity sensors, to form multi-dimensional state monitoring capabilities. Among them, the stress sensor is used to measure the stress magnitude generated inside the material under the action of external forces, and can be in the form of piezoelectric sensors, resistance strain gauges, etc.; the angle sensor is used to detect the change in the relative rotation angle of the local part of the connector, and can be a magnetic encoder, gyroscope, etc.; the velocity sensor is used to monitor the change rate of the angle or position per unit time during the deformation process of the connector to reflect its dynamic response characteristics. The arrangement method of the sensor module can adopt technologies such as surface attachment, embedded integration, or flexible packaging to ensure sensing reliability and connector flexibility compatibility. Exemplarily, the structural property parameters of a bendable connector include: length 100mm, width 6mm, thickness 0.4mm, divided into three layers: a flexible conductor layer (copper), an elastic substrate (PI), and an insulating coating (silicone). The elastic modulus of the copper layer is 110GPa, the PI layer is 2.5GPa, and the silicone layer is 0.5MPa. A stress sensor chip is arranged on the middle copper layer, a micro angle sensor is set at the flank corner, and a velocity sensor based on the Hall effect is installed at the connection end to achieve the linkage monitoring of three key deformation parameters.

[0037] During the operation of the flexible electronic connector, which performs actual bending actions (such as winding, twisting, and bonding), sensor modules deployed at key locations continuously operate, collecting their respective monitoring data in real time. The data is then processed by a signal processing component to reduce noise, filter, and normalize before being uploaded to the control module. This generates a set of data containing stress values, bending angle change curves, and instantaneous deformation rates at multiple key locations under dynamic operation—in other words, bending data from multiple locations—which serves as the core input for generating subsequent control parameters.

[0038] Furthermore, step S220 includes: Step S221: Determine the mesh type and mesh density based on the geometry of the flexible electronic connector and the analysis requirements.

[0039] Step S222: Model the structural property parameters of the flexible electronic connector according to the mesh type and mesh density, perform mesh generation and finite element analysis, and establish a three-dimensional finite element model of the connector.

[0040] Step S223: Define boundary conditions and bending loads based on the bending information of the connector application scenario.

[0041] Step S224: Use the solver to perform finite element simulation on the three-dimensional finite element model of the connector based on the boundary conditions and bending load to obtain the bending simulation results of the connector.

[0042] Specifically, mesh type refers to the element geometry used to discretize continuous structures in finite element analysis, such as one-dimensional beam elements, two-dimensional shell elements, and three-dimensional solid elements. Mesh density refers to the number of meshes or the degree of refinement within a unit area, usually measured in the number of elements per millimeter or the average element side length. Based on the specific geometry of the flexible electronic connector (e.g., layered structures, curved bending paths, slender flexible regions) and the analysis objectives (e.g., local stress concentration analysis, overall shape trend prediction), an appropriate mesh type is selected: for example, two-dimensional shell elements can be used for models in structures where the thickness is much smaller than the length and width; while three-dimensional solid elements are used for structures with significant stress gradients in the thickness direction. Mesh density is locally refined based on the distribution of key parts, while sparser meshes can be used in ordinary areas to optimize overall simulation efficiency and accuracy. For example, for a flexible electronic connector with a 0.5mm thick multi-layer structure, shell elements are used for modeling. A high-density mesh with a side length of 0.05mm is set in the connection parts with a bending radius of less than 10mm, and a low-density mesh with a side length of 0.2mm is set in other areas, achieving a balance between fine local analysis and fast overall solution.

[0043] The acquired structural property parameters are input into the finite element software, and geometric modeling and mesh generation are performed based on the selected mesh parameters. Layered modeling is performed on the multi-layered composite structure of the flexible electronic connector (such as conductor layer, insulation layer, and reinforcement layer), and corresponding material properties are assigned to each layer to obtain a three-dimensional finite element model of the connector.

[0044] Based on the practical application scenarios of flexible electronic connectors (such as winding around a cylinder or attaching to a curved surface), boundary conditions and loads are set in the finite element software. Boundary conditions can be one end fixed (representing the connector has been soldered to a circuit board) and the other end subjected to controlled displacement (representing external pulling or torsion), or relative rotation can be simulated using a rigid body reference point. Bending loads can be defined as displacement boundaries at specific angles, torque loading, or pressure distribution, simulating parameters such as the bending angle range (e.g., 0° to 180°) and bending speed. For example, when simulating a flexible electronic connector attached to the surface of a robotic arm, one end of the connector is fixed, and the other end is subjected to a 90° displacement boundary around the Y-axis to simulate the winding deformation that occurs during its operation.

[0045] The solver of the finite element method (FEM) software is invoked to perform the solution process based on the constructed 3D finite element model of the connector and the set boundary conditions and bending loads. After solving, the numerical results such as the stress distribution cloud map, strain concentration area, maximum displacement and its location of the connector are output as the bending simulation results of the connector. This accurately reflects the deformation mode and weak areas of the structure under actual stress conditions, providing data support for the identification of key areas, subsequent sensor deployment and control strategy design.

[0046] Furthermore, step S300 includes: Step S310: Decompose the bending requirement target into requirement indicators to obtain a set of bending performance indicators.

[0047] Step S320: Quantify the bending requirements for each performance index in the bending performance index set to obtain the bending performance index requirement parameter set.

[0048] Step S330: Map the set of bending performance index requirements to the bending data of the multiple parts for comparison and analysis to obtain the target bending index parameters of the multiple parts.

[0049] Step S340: The control module is used to analyze the target bending index parameters of the multiple parts to obtain multi-directional bending collaborative control parameters.

[0050] Specifically, the system first receives preset bending requirements, which can be input by designers or automatically generated based on product specifications. Typical bending requirements include, but are not limited to, the following: maximum bending angle range, bending action response time, angle control accuracy, fatigue life requirements, number of bends per unit time, and structural deformation uniformity requirements. Next, the overall target is logically decomposed using a predefined rule base or decision tree model, transforming it into a set of more fundamental and quantifiable performance indicators. For example, if the target includes "±180° precise control, error less than 2°, cycle life ≥100,000 times," it can be broken down into the following set of performance indicators: maximum allowable bending angle, bending angle error tolerance, control response delay time, bending operation frequency, single bending stress limit, and minimum bending radius. Factors considered during the decomposition process include: the physical structural limitations of the flexible electronic connector, the load-bearing capacity of the flexible circuit board, the internal space of the connector, electromagnetic drive characteristics, and the feasibility of sensor deployment.

[0051] Based on the set of bending performance indicators, each bending performance indicator is numerically assigned, i.e., demand quantification, to obtain the specific target parameter set corresponding to each performance indicator, i.e., the bending performance indicator demand parameter set. The quantification process is based on the following three types of data sources: product design specifications or industry standards, historical test data or calibration models in the database, and finite element simulation results or experimental prototype measured values. In actual operation, firstly, the corresponding unit, dimension, and quantification strategy are set for each bending performance indicator. For example, the "maximum bending angle" is set to the unit °, with an acceptable range of [±0°, ±180°]; the "control error" is set to the error percentage or angle deviation, with a recommended threshold not exceeding ±2°; then, a parameter calibration module is introduced, combining material properties (such as Young's modulus, yield stress), geometric features (thickness, length, curvature), and sensor response characteristics (such as angular resolution, delay time), and using interpolation, regression analysis, or multi-objective optimization models to calculate the corresponding bending performance indicator demand parameters for each bending performance indicator.

[0052] The set of bending performance index requirements obtained in the previous step is compared with the bending data of multiple parts acquired by the sensor module. By establishing a mapping relationship model (such as linear regression, interpolation function or neural network mapping), the deviation between the actual response of each part and the target parameters is found, the key difference areas are analyzed, the control targets to be achieved by each part are determined, and the target bending index parameters of multiple parts are obtained.

[0053] After receiving target bending index parameters from multiple parts, the control module analyzes the parameters of each control channel based on its control model (such as PID, LQR, or fuzzy control) to obtain preliminary control parameters. Simultaneously, it identifies the linkage and coupling relationships between different parts, adjusts the control inputs for each part, and avoids interference from local control to other parts. Finally, a set of multi-directional bending collaborative control parameters is formed, such as the elastic unit drive current sequence, time control window, and angle correction factor, and then sent to the electromagnetic drive module.

[0054] Furthermore, step S330 includes: Step S331: Filter and denoise the bending data of the multiple parts and calibrate the data to obtain bending data of multiple standard parts.

[0055] Step S332: Map the set of bending performance index requirements parameters to the bending data of the multiple parts and perform correlation analysis to generate bending index requirements parameters for multiple parts.

[0056] Step S333: Determine the bending performance index parameters of multiple parts based on the bending data of the multiple standard parts.

[0057] Step S334: Compare and analyze the deviations between the bending index requirement parameters and the bending performance index parameters of the multiple parts to determine the target bending index parameters of the multiple parts.

[0058] Specifically, filtering and denoising refers to the process of removing or correcting invalid or abnormal data such as environmental noise and electronic interference in bending data from multiple locations. Data calibration aligns the raw data with a standard reference system, giving the data a unified spatial or physical meaning. Standard bending data refers to standardized data that has been filtered and calibrated, and can be directly used for control and analysis. The collected bending data from multiple locations often suffers from discrete fluctuations, temperature drift errors, and zero-point offsets. First, filters are applied to perform multi-order low-pass filtering, Kalman filtering, or wavelet denoising to remove high-frequency jitter and outliers. Then, based on the sensor calibration table or reference experimental curves, calibration factors are applied to various raw data (angle, voltage, stress) to unify them into standard physical units. For example, the stress sensor outputs a raw voltage signal U=1.84V, which, after filtering, yields a smooth curve. Comparing this to the calibration curve: σ=0.145×U+0.02, the stress value σ=0.287MPa is obtained and written into the standard bending data table.

[0059] Based on structural properties, finite element analysis results, or control strategy mapping matrices, system-level performance parameters (such as maximum angle, stress threshold, and response time) are mapped to each bending component using proportional, gradient, or weighted allocation methods. For example, based on the component's distance from the center point in the flexible connector, material hardness, or deformation capacity, interpolation functions or correlation matrices are used to generate individual target performance values, resulting in multiple bending performance parameter requirements for each component. For instance, through a finite element analysis model, the relationship between the bending angles of each component and the overall target angle is analyzed to determine which components of the connector need to achieve specific bending angles to achieve the overall target angle. Simultaneously, other performance indicators such as bending speed are also analyzed using similar methods to determine the bending performance parameter requirements for each component, ensuring that the overall system performance targets are reasonably decomposed into controllable units, effectively enhancing control accuracy and distributed response consistency.

[0060] Based on the calibrated standard bending data, the actual bending performance parameters for each part are calculated sequentially. For example, for bending angle data, the standard angle data collected by the sensors can be directly used as the actual bending angle parameter. For stress data, spatial interpolation and fitting of data collected by multiple stress sensors can be performed to obtain stress distribution cloud maps of various parts of the connector, thereby determining the stress values ​​of key parts as actual stress parameters. For bending speed data, the rate of change of angle per unit time can be calculated to obtain the actual bending speed parameter. These parameters constitute a set of bending performance parameters for multiple parts, comprehensively reflecting the current actual bending state of the connector and providing accurate actual data for subsequent deviation comparison analysis.

[0061] The bending performance parameters for each component are compared and analyzed against the required bending performance parameters to calculate the deviation between the current and desired states (i.e., the difference between the bending performance parameters and the required bending performance parameters). Based on the direction and magnitude of the deviation, a threshold judgment mechanism or a PID reverse compensation model is used to update the bending performance parameters for each component. For example, if the angle of a component is insufficient, its target bending angle is increased; if the stress exceeds the limit, the control objective will shift to a conservative response. Finally, the target bending performance parameters for multiple components are output as inputs to the next stage control module.

[0062] Furthermore, step S340 includes: Step S341: Based on the control characteristic information of the flexible electronic connector, initialize the PID bending controller, and use the PID bending controller to analyze the control parameters of the target bending index parameters of the multiple parts to obtain the bending control parameters of the multiple parts.

[0063] Step S342: Perform bending simulation and coupling relationship identification on each bending part in the multiple bending control parameters to determine the coupling relationship parameters of the bending parts.

[0064] Step S343: Based on the coupling relationship parameters of the bending part, perform coupling transfer analysis and function fitting to establish a coupling relationship model.

[0065] Step S344: Based on the coupling relationship model, perform collaborative strategy analysis on the bending control parameters of the multiple parts to determine the multi-directional bending collaborative control parameters.

[0066] Specifically, a PID bending controller refers to a local feedback control module based on a proportional-integral-derivative (PI-DE) control algorithm, used to control the dynamic response behavior of flexible structures. Based on parameters such as the structural material characteristics, response frequency, and control accuracy requirements of the flexible electronic connector, the P, I, and D control gain coefficients of the PID controller are set or adaptively adjusted. For each bending control point, the corresponding PID controller is invoked, its target bending index parameter is used as the setpoint, and the current feedback state is compared in real time to analyze the output control quantity, which is recorded as the bending control parameter (such as electromagnetic force, current amplitude, execution duration, etc.), thus obtaining bending control parameters for multiple points.

[0067] Based on a three-dimensional finite element model or multibody dynamics model, joint simulation is performed on the structural response under the input control parameters of each part. The consistency or correlation of the angle and stress response variation trends between adjacent parts is extracted, and the coupling relationship is identified using correlation coefficient analysis or dynamic response sensitivity matrix analysis. For example, the control change Δθ of part i i The passive response Δθ caused by part j ij Then calculate the coupling coefficient γ ij =Δθ ij / Δθ i Finally, the coupling parameters of the bending section are output. For example, when the angle of control part 1 increases by 10°, the passive response angle of part 2 increases by 1.8°, then its coupling coefficient γ 12 =0.18, indicating that there is a strong positive coupling relationship between control part 1 and part 2.

[0068] Based on the coupling parameters of the bending sections extracted in the previous step, the response function forms between sections are obtained by fitting using least squares fitting, neural network modeling, or multinomial regression methods, establishing a coupling relationship model to deduce the dynamic transmission effect of control changes on the global response. If the model is significantly nonlinear, piecewise fitting or a time-series-based dynamic response network is used to establish an approximate model. An example of a coupling relationship model is as follows: θ2(t) = 0.15 × θ1(t) + 0.06 × dθ1(t) / dt + 0.01 × θ3(t), indicating that the response of section 2 is affected not only by the control angle of section 1, but also by its dynamic rate of change and the disturbance of section 3. By constructing a coupling relationship model, cross-section response prediction and global control linkage planning can be achieved, improving the overall coordination capability under complex bending paths.

[0069] By calling the coupling relationship model, a global impact backtracking and feedforward intervention analysis is performed on the bending control parameters of multiple parts. A constrained optimization model is constructed, and a multi-objective optimization algorithm (such as particle swarm optimization and genetic algorithm) is used to solve the multi-parameter joint problem. The optimization result output is a multi-directional bending collaborative control parameter set, which includes the control command, electromagnetic control parameters, feedback adjustment frequency, etc. for each part.

[0070] Furthermore, step S344 includes: Step S344-1: Obtain the bending control target and the constraint conditions of the bending part.

[0071] Step S344-2: Extract characteristics from the coupling relationship model to obtain the coupling path and coupling strength of the bending part.

[0072] Step S344-3: Based on the bending control target and bending part constraints, as well as the bending part coupling path and bending part coupling strength, perform distributed collaborative strategy analysis on the bending control parameters of the multiple parts to determine the multi-directional bending collaborative control parameters.

[0073] Specifically, bending control targets refer to the performance indicators that the flexible electronic connector needs to achieve, such as spatial position changes, bending angles, and motion trajectories, either as a whole or in parts. The system receives bending control targets from user input or from the upper-level planning system and parses them into target parameter vectors (such as global path, location angle settings, and dynamic response time). Simultaneously, it calls the flexible electronic connector structural model to extract the constraints for each bending location, including physical or functional constraints such as maximum and minimum angle limits, maximum strain tolerance, structural link limitations, and displacement synchronization limitations.

[0074] Based on the established coupling relationship model, a graph structure modeling method (such as a directed weighted graph) is used to represent all bending parts as nodes and coupling relationships as edges, with edge weights representing coupling strength. Furthermore, a graph traversal algorithm (such as Floyd or Dijkstra) is used to extract the coupling paths from the target control point to any response point, and the coupling superposition strength of each path is calculated to obtain the coupling paths and coupling strengths of the bending parts.

[0075] Based on the bending control objective, a bending optimization objective function is constructed. Constraints at the bending points, their coupling paths, and coupling strength are used as constraints. Distributed collaborative strategy analysis is performed on the bending control parameters of multiple points. Iterative coordinated control algorithms (such as cooperative gradient descent, Lagrange multiplier method, and local update global projection) are employed to solve the problem, obtaining the optimal control solution set that satisfies the coupling relationship and physical constraints. This is the multi-directional bending collaborative control parameter, realizing a closed-loop decision-making control mechanism from coupling prediction to strategy fusion. This ensures that all control points are globally coordinated and consistent while satisfying constraints, improving the compliance, accuracy, and response stability of the structure's movements.

[0076] Furthermore, step S344-3 includes: Steps S344-31: Construct a bending optimization objective function based on the bending control objective.

[0077] Step S344-32: The bending part constraint conditions, the bending part coupling path and the bending part coupling strength are used as coupling constraint terms. At the same time, the bending control parameters of the multiple parts are divided into distributed nodes to obtain distributed node bending control parameters.

[0078] Steps S344-33: Initialize the particle swarm search space according to the distributed node bending control parameters.

[0079] Steps S344-34: Using the bending optimization objective function based on the coupling constraint term, perform global iterative optimization in the particle swarm search space to determine the multi-directional bending cooperative control parameters.

[0080] Specifically, firstly, an optimization objective function is constructed based on the bending control objective of the flexible electronic connector. This bending control objective may include multi-dimensional indicators such as the target bending angle, terminal spatial pose, curvature distribution uniformity, and stress limitation. The above objective parameters are defined as evaluation indicators of the optimization variables, and the following optimization objective function is constructed: in, These are the fitness values ​​for bending control parameters at multiple locations. This represents a set of bending control parameters for multiple parts. The first corresponding to the bending control parameter Item response function, For the first Target value for bending control. For the first The weighting coefficients of the bending control objective are used. This objective function serves as the fitness function in the particle swarm optimization algorithm, providing a clear evaluation basis for subsequent optimization.

[0081] The flexible electronic connector further divides its multiple bending control components into several control nodes, each containing a corresponding elastic support unit and sensor module, forming a distributed control structure. Simultaneously, based on the bending component constraints, coupling paths, and coupling strengths, the following constraint models are established: spatial exclusion constraints (e.g., certain components cannot bend simultaneously), coupling delay constraints (e.g., time response relationships between adjacent units), energy distribution constraints (e.g., power supply limitations), and bending coordination constraints (e.g., path consistency, angle transmission consistency, etc.). This coupling information is formalized as coupling constraint terms and embedded in the optimization model. Furthermore, the bending control parameters of multiple components are mapped to the local control parameters of each control node, forming a distributed node bending control parameter set.

[0082] Based on the aforementioned objective function and the distributed node bending control parameter set, a search space for particle swarm optimization is constructed. Let the number of particles be P, and each particle correspond to a complete set of bending control parameters, including multiple distributed node bending control parameters. The initialization phase includes the following: randomly initializing the position X for each particle. i and speed V i The coupling constraint term is satisfied; the inertia weight ω, learning factors c1 and c2, and the number of search iterations are set; each particle records its own optimal position P. i The group records the globally optimal position G. best By employing the methods described above, a particle swarm optimization structure is constructed, providing a foundation for the subsequent collaborative optimization of bending control parameters.

[0083] By utilizing the bending optimization objective function based on coupling constraints, a global iterative optimization is performed within the particle swarm search space. The optimal control, namely the multi-directional bending cooperative control parameters, is found through the flight and iteration of particles in the search space. In each iteration, the position X of each particle is optimized. i Fitness evaluation is performed to determine its performance under the bending optimization objective function, and updates are made based on the following strategy: each particle retains its current best historical position P. i The group records the globally optimal position G. best If the current particle violates the coupling constraint, its fitness is set to a penalty value. After the iteration satisfies the maximum number of iterations or the fitness convergence condition, the global optimal position G at this point is output. best The corresponding bending control parameters are used as the final multi-directional bending collaborative control parameters.

[0084] In summary, the multi-directional bending control method for flexible electronic connectors provided in this application has the following beneficial effects: This application provides a multi-directional bending control method for flexible electronic connectors. Focusing on the core requirement of achieving high-precision, controllable bending of flexible electronic connectors in complex environments, a control flow characterized by integrated sensing, analysis, and driving is designed. First, a basic platform with structural controllability is constructed by acquiring a target flexible electronic connector, including the connector body, flexible circuit board, and multi-directional bending control components. Then, multi-directional bending control components, integrating elastic support units, electromagnetic drive modules, control modules, and sensor modules, are distributed and arranged in the bending area of ​​the flexible circuit board, enabling it to have local driving and state awareness capabilities. The sensor module collects bending data from multiple key locations, and the control module analyzes the data based on externally set bending requirements to generate targeted multi-directional bending collaborative control parameters. Finally, the electromagnetic drive module precisely drives the elastic support unit according to these multi-directional bending collaborative control parameters, thereby achieving coordinated bending control of the flexible electronic connector in multiple directions and locations. Overall, through the synergistic effect of the above-mentioned links, the embodiments of this application effectively improve the adaptability of flexible electronic connectors to complex spatial environments, and significantly enhance the multi-directional bending control accuracy, system response flexibility and operational reliability of flexible electronic connectors in high reliability and high flexibility application scenarios.

[0085] Example 2, as Figure 2 As shown, based on the same inventive concept as in Embodiment 1 above, this application provides a multi-directional bending control system for flexible electronic connectors, the system comprising: The target acquisition unit 10 is used to acquire a target flexible electronic connector. The flexible electronic connector includes a connector body, a flexible circuit board, and a multi-directional bending control component. The connector body is connected to an external device, the flexible circuit board is disposed inside the connector body, and the multi-directional bending control component is distributed in the bending area of ​​the flexible circuit board.

[0086] The integrated sensing unit 20 is used to integrate multiple elastic support units, electromagnetic drive modules, control modules, and sensor modules within the multi-directional bending control assembly, and to acquire bending data of multiple parts of the flexible electronic connector through the sensor module.

[0087] The control parameter parsing unit 30 is used to parse the bending data of the multiple parts based on the bending demand target by the control module to obtain multi-directional bending collaborative control parameters.

[0088] The multi-directional bending control unit 40 is used to control the target flexible electronic connector to bend in multiple directions by the multiple elastic support units based on the multi-directional bending collaborative control parameters through the electromagnetic drive module.

[0089] Furthermore, in this embodiment of the application, the integrated sensing unit 20 is also used to perform the following steps: The structural attribute parameters of the flexible electronic connector are obtained, including specifications, dimensions, component composition, and material properties. Finite element simulation is performed based on these parameters to obtain bending simulation results. Stress-strain analysis is conducted on the bending simulation results to identify a set of key components. Sensor modules, including stress sensors, angle sensors, and velocity sensors, are then sequentially deployed on these key component sets. During bending operations of the flexible electronic connector, the sensor modules are used to sense and monitor the set of key components, obtaining bending data for each component.

[0090] Furthermore, in this embodiment of the application, the integrated sensing unit 20 is also used to perform the following steps: Based on the geometry and analysis requirements of the flexible electronic connector, the mesh type and mesh density are determined; the structural property parameters of the flexible electronic connector are modeled, meshed, and analyzed using finite element methods according to the mesh type and mesh density to establish a three-dimensional finite element model of the connector; boundary conditions and bending loads are defined based on the bending information of the connector application scenario; the three-dimensional finite element model of the connector is solved using a solver based on the boundary conditions and bending loads to obtain the bending simulation results of the connector.

[0091] Furthermore, in this embodiment of the application, the control parameter parsing unit 30 is also used to perform the following steps: The bending requirement target is broken down into requirement indicators to obtain a set of bending performance indicators; each performance indicator in the set of bending performance indicators is quantified to obtain a set of bending performance indicator requirement parameters; the set of bending performance indicator requirement parameters is mapped to the bending data of the multiple parts for comparison and analysis to obtain multiple parts target bending indicator parameters; the control module is used to analyze the control parameters of the multiple parts target bending indicator parameters to obtain multi-directional bending collaborative control parameters.

[0092] Furthermore, in this embodiment of the application, the control parameter parsing unit 30 is also used to perform the following steps: The bending data of the multiple locations are filtered, denoised, and calibrated to obtain bending data of multiple standard locations. The bending performance index requirement parameter set is mapped to the bending data of the multiple locations for correlation analysis to generate bending index requirement parameters for multiple locations. Based on the bending data of the multiple standard locations, the bending performance index parameters for multiple locations are determined. The deviation comparison analysis between the bending index requirement parameters and the bending performance index parameters for multiple locations is performed to determine the target bending index parameters for the multiple locations.

[0093] Furthermore, in this embodiment of the application, the control parameter parsing unit 30 is also used to perform the following steps: Based on the control characteristic information of the flexible electronic connector, a PID bending controller is initialized. The PID bending controller is then used to analyze the control parameters of the target bending index parameters for multiple parts, obtaining bending control parameters for each part. Bending simulation and coupling relationship identification are performed on each bending part among the bending control parameters to determine the bending part coupling relationship parameters. Based on the bending part coupling relationship parameters, coupling transfer analysis and function fitting are performed to establish a coupling relationship model. Based on the coupling relationship model, collaborative strategy analysis is conducted on the bending control parameters for multiple parts to determine multi-directional bending collaborative control parameters.

[0094] Furthermore, in this embodiment of the application, the control parameter parsing unit 30 is also used to perform the following steps: Obtain the bending control target and bending part constraints; extract characteristics from the coupling relationship model to obtain the bending part coupling path and bending part coupling strength; based on the bending control target, bending part constraints, bending part coupling path and bending part coupling strength, perform distributed cooperative strategy analysis on the bending control parameters of the multiple parts to determine the multi-directional bending cooperative control parameters.

[0095] Furthermore, in this embodiment of the application, the control parameter parsing unit 30 is also used to perform the following steps: Based on the bending control objective, a bending optimization objective function is constructed; the bending location constraints, the bending location coupling path, and the bending location coupling strength are used as coupling constraint terms; simultaneously, the bending control parameters of the multiple locations are divided into distributed nodes to obtain distributed node bending control parameters; based on the distributed node bending control parameters, a particle swarm search space is initialized; using the bending optimization objective function and the coupling constraint terms, global iterative optimization is performed in the particle swarm search space to determine the multi-directional bending cooperative control parameters.

[0096] Through the foregoing detailed description of the multi-directional bending control method for flexible electronic connectors, those skilled in the art can clearly understand that the multi-directional bending control system for flexible electronic connectors in this embodiment corresponds to the system disclosed in Embodiment 2, and has corresponding functional modules and beneficial effects as it is similar to the method disclosed in Embodiment 1. For relevant details, please refer to the description in the method section.

[0097] In embodiment three, based on the same inventive concept as the multi-directional bending control method for flexible electronic connectors in embodiment one, this application also provides an electronic device, including: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the steps of the method described in embodiment one.

[0098] like Figure 3 As shown, the bus architecture is represented by bus 300. Bus 300 may include any number of interconnected buses and bridges, connecting various circuits including one or more processors represented by processor 302 and memory represented by memory 304. Bus 300 may also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same element, i.e., a transceiver, providing a unit for communicating with various other devices over a transmission medium. Processor 302 is responsible for managing bus 300 and general processing, while memory 304 can be used to store data used by processor 302 during operation.

[0099] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A multi-directional bending control method for flexible electronic connectors, characterized in that, The method includes: A target flexible electronic connector is obtained, the flexible electronic connector including a connector body, a flexible circuit board and a multi-directional bending control component, wherein the connector body is connected to an external device, the flexible circuit board is disposed inside the connector body, and the multi-directional bending control component is distributed in the bending area of ​​the flexible circuit board; The multi-directional bending control component integrates multiple elastic support units, an electromagnetic drive module, a control module, and a sensor module. The sensor module collects bending data from multiple parts of the flexible electronic connector. The control module is used to analyze the bending data of the multiple parts based on the bending demand target to obtain multi-directional bending collaborative control parameters. The electromagnetic drive module controls the multiple elastic support units to perform multi-directional bending control on the target flexible electronic connector based on the multi-directional bending collaborative control parameters.

2. The multi-directional bending control method for flexible electronic connectors as described in claim 1, characterized in that, The process of acquiring bending data for multiple parts of the flexible electronic connector through the sensor module includes: Obtain the structural property parameters of the flexible electronic connector, including specifications, dimensions, component composition, and material properties; Finite element simulation was performed based on the structural property parameters of the flexible electronic connector to obtain the connector bending simulation results. Stress-strain analysis is performed on the connector bending simulation results to identify a set of key parts, and sensor modules are sequentially deployed on the set of key parts. The sensor modules include stress sensors, angle sensors and velocity sensors. When the flexible electronic connector is bent, the sensor module senses and monitors the set of key parts to obtain bending data of the multiple parts.

3. The multi-directional bending control method for flexible electronic connectors as described in claim 2, characterized in that, The obtained connector bending simulation results include: Based on the geometry of the flexible electronic connector and the analysis requirements, determine the mesh type and mesh density; The structural property parameters of the flexible electronic connector are modeled, meshed, and analyzed using finite element methods according to the mesh type and mesh density to establish a three-dimensional finite element model of the connector. Define boundary conditions and bending loads based on the bending information of the connector application scenario; The connector's three-dimensional finite element model is solved using a solver based on the boundary conditions and bending load to obtain the connector bending simulation results.

4. The multi-directional bending control method for flexible electronic connectors as described in claim 1, characterized in that, The obtained multi-directional bending collaborative control parameters include: The bending requirement target is broken down into requirement indicators to obtain a set of bending performance indicators; The bending requirement is quantified for each performance index in the bending performance index set to obtain the bending performance index requirement parameter set; The bending performance index requirement parameter set is mapped to the bending data of the multiple parts for comparison and analysis to obtain the target bending index parameters of the multiple parts. The control module is used to analyze the target bending index parameters of the multiple parts to obtain multi-directional bending collaborative control parameters.

5. The multi-directional bending control method for flexible electronic connectors as described in claim 4, characterized in that, The method of obtaining target bending index parameters for multiple locations includes: The bending data of the multiple locations are filtered, denoised, and calibrated to obtain bending data of multiple standard locations. The bending performance index requirement parameter set is mapped to the bending data of the multiple parts and associated and parsed to generate bending index requirement parameters for multiple parts. Based on the bending data of the multiple standard locations, the bending performance index parameters of the multiple locations are determined; By comparing and analyzing the deviations between the bending index requirements parameters and the bending performance index parameters of the multiple parts, the target bending index parameters of the multiple parts are determined.

6. The multi-directional bending control method for flexible electronic connectors as described in claim 4, characterized in that, The process of obtaining multi-directional bending collaborative control parameters includes: Based on the control characteristic information of the flexible electronic connector, the PID bending controller is initialized, and the PID bending controller is used to analyze the control parameters of the target bending index parameters of the multiple parts to obtain the bending control parameters of the multiple parts. For each bending location in the multiple bending control parameters, bending simulation and coupling relationship identification are performed to determine the coupling relationship parameters of the bending location; Based on the coupling relationship parameters of the bending section, coupling transfer analysis and function fitting are performed to establish a coupling relationship model; Based on the coupling relationship model, a collaborative strategy analysis is performed on the bending control parameters of the multiple parts to determine the multi-directional bending collaborative control parameters.

7. The multi-directional bending control method for flexible electronic connectors as described in claim 6, characterized in that, The determination of multi-directional bending collaborative control parameters includes: Obtain the bending control target and the constraint conditions of the bending part; The coupling relationship model is subjected to feature extraction to obtain the coupling path and coupling strength of the bending part; Based on the bending control target and bending location constraints, as well as the bending location coupling path and bending location coupling strength, a distributed collaborative strategy analysis is performed on the bending control parameters of the multiple locations to determine the multi-directional bending collaborative control parameters.

8. The multi-directional bending control method for flexible electronic connectors as described in claim 7, characterized in that, Determining the multi-directional bending collaborative control parameters includes: Based on the bending control objective, a bending optimization objective function is constructed; The bending part constraint conditions, the bending part coupling path and the bending part coupling strength are used as coupling constraint terms. At the same time, the bending control parameters of the multiple parts are divided into distributed nodes to obtain distributed node bending control parameters. Initialize the particle swarm search space based on the distributed node bending control parameters; Using the bending optimization objective function based on the coupling constraint term, global iterative optimization is performed in the particle swarm search space to determine the multi-directional bending cooperative control parameters.

9. A multi-directional bending control system for flexible electronic connectors, characterized in that, The system is used to execute the multi-directional bending control method for flexible electronic connectors according to any one of claims 1-8, comprising: A target acquisition unit is used to acquire a target flexible electronic connector. The flexible electronic connector includes a connector body, a flexible circuit board, and a multi-directional bending control component. The connector body is connected to an external device, the flexible circuit board is disposed inside the connector body, and the multi-directional bending control component is distributed in the bending area of ​​the flexible circuit board. An integrated sensing unit is used to integrate multiple elastic support units, an electromagnetic drive module, a control module, and a sensor module within the multi-directional bending control component, and to acquire bending data of multiple parts of the flexible electronic connector through the sensor module. The control parameter parsing unit is used to parse the bending data of the multiple parts based on the bending demand target by the control module to obtain multi-directional bending collaborative control parameters. A multi-directional bending control unit is used to control the target flexible electronic connector to bend in multiple directions by the multiple elastic support units based on the multi-directional bending collaborative control parameters through the electromagnetic drive module.

10. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the multi-directional bending control method for flexible electronic connectors as described in any one of claims 1-8.

Images