Control system and method for rope-driven neck exoskeleton

Abstract

The invention provides a control system and method for a rope-driven neck exoskeleton, and the system comprises a sensor module which is used for measuring the tension value of a driving rope and the motion angle of the neck in real time; the torque calculation module is used for calculating the torque generated by the driving rope to the neck joint according to the tension value and calculating the magnitude of the load torque according to the neck movement angle and the angular velocity information; the PID control algorithm module is used for calculating a control quantity according to an error between a torque set value and an actual torque measured value, carrying out adaptive adjustment on parameters of a PID controller and carrying out nonlinear compensation on output of the PID controller; and the driving module is used for receiving the control signal output by the PID control algorithm module, converting the control signal into a signal for driving a motor, and generating a driving torque according to the control signal to pull a driving rope. According to the technical scheme, the control precision, the stability and the response speed of the rope-driven neck exoskeleton are improved.

Description

Technical Field

[0001] The present application relates to the field of exoskeleton robot control technology, and in particular to a control system and method for a rope-driven neck exoskeleton. Background Art

[0002] Currently, common rope-driven neck exoskeleton control systems suffer from low control accuracy, poor stability, and slow response speed. Traditional open-loop control systems are unable to sense and adjust the torque of the drive rope in real time, making them difficult to adapt to complex neck movements and load variations. While some closed-loop control systems employ simple control algorithms, they are unable to effectively eliminate control errors due to the nonlinear and time-varying characteristics of rope-driven systems. This results in significant deviations between the exoskeleton's trajectory and the desired trajectory, impacting both the user experience and the system's practicality. Summary of the Invention

[0003] The present application provides a control system and method for a rope-driven neck exoskeleton, which are used to improve the control accuracy, stability and response speed of the rope-driven neck exoskeleton.

[0004] In a first aspect, a control system for a rope-driven neck exoskeleton is provided, comprising:

[0005] A sensor module for measuring the tension of the driving rope and the movement angle of the neck in real time;

[0006] A torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information;

[0007] PID control algorithm module, used to calculate the control quantity according to the error between the torque set value and the actual torque measurement value, and to adaptively adjust the parameters of the PID controller and perform nonlinear compensation on the output of the PID controller;

[0008] The driving module is used to receive the control signal output by the PID control algorithm module and convert it into a signal for driving the motor, and generate a driving torque to pull the driving rope according to the control signal;

[0009] The communication module is used to communicate data with the host computer and to transmit data among the sensor module, the torque calculation module, the PID control algorithm module and the drive module.

[0010] In the above technical solution, a sensor module is set up to measure the tension value of the driving rope and the movement angle of the neck in real time; a torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information; a PID control algorithm module is used to calculate the control quantity according to the error between the torque set value and the actual torque measurement value, and to adaptively adjust the parameters of the PID controller, and to perform nonlinear compensation on the output of the PID controller; a driving module is used to receive the control signal output by the PID control algorithm module and convert it into a signal for driving the motor, and to generate a driving torque to pull the driving rope according to the control signal; a communication module is used to communicate data with the host computer and transmit data between the sensor module, the torque calculation module, the PID control algorithm module and the driving module; the control accuracy, stability and response speed of the rope-driven neck exoskeleton are improved.

[0011] In a specific embodiment, the sensor module includes a tension sensor and an angle sensor, wherein:

[0012] The tension sensor is used to measure the tension value of the driving rope in real time.

[0013] The angle sensor is used to measure the movement angle of the neck.

[0014] In a specific embodiment, the torque calculation module includes a rope force-torque conversion unit and a load torque estimation unit, wherein:

[0015] The rope force-torque conversion unit is used to calculate the torque generated by the driving rope on the neck joint according to the tension value;

[0016] The load torque estimation unit is used to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information.

[0017] In a specific implementation scheme, the PID control algorithm module includes a traditional PID controller and an algorithm innovation unit, wherein:

[0018] The conventional PID controller calculates the control variable based on the error between the torque setting value and the actual torque measurement value;

[0019] The algorithm innovation unit includes an adaptive parameter adjustment subunit and a nonlinear compensation subunit, wherein:

[0020] The adaptive parameter adjustment subunit is used to adaptively adjust the parameters of the PID controller;

[0021] The nonlinear compensation subunit is used to perform nonlinear compensation on the output of the PID controller.

[0022] In a specific embodiment, the driving module includes a motor driver and a driving motor, wherein:

[0023] The motor driver receives the control signal output by the PID control algorithm module and converts it into a signal for driving the motor;

[0024] The driving motor generates a driving torque to pull the driving rope according to the control signal.

[0025] In a specific implementation scheme, the communication module includes a host computer communication interface and an inter-module communication bus, wherein:

[0026] The host computer communication interface is used for data communication with the host computer;

[0027] The inter-module communication bus is used for data transmission among the sensor module, the torque calculation module, the PID control algorithm module and the drive module.

[0028] In a specific implementation scheme, the adaptive parameter adjustment subunit adopts a fuzzy control algorithm to determine the adjustment amount of the PID controller parameters according to the magnitude of the torque error and the error change rate through a preset fuzzy rule base.

[0029] In a specific embodiment, the nonlinear compensation subunit determines the nonlinear compensation term according to the rope tension and the joint angle by a table lookup method or a function approximation method, and superimposes the nonlinear compensation term on the output signal of the PID controller.

[0030] In a specific implementation scheme, the host computer communication interface of the communication module includes a serial communication interface, an Ethernet communication interface and a wireless communication interface;

[0031] The inter-module communication bus includes a CAN bus and an I2C bus.

[0032] In a second aspect, a control method for a rope-driven neck exoskeleton is provided, comprising the following steps:

[0033] The sensor module is used to measure the tension of the driving rope and the movement angle of the neck in real time;

[0034] The torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and the magnitude of the load torque is calculated according to the neck movement angle and angular velocity information;

[0035] The PID control algorithm module is used to calculate the control quantity according to the error between the torque set value and the actual torque measurement value, and the parameters of the PID controller are adaptively adjusted, and the output of the PID controller is nonlinearly compensated;

[0036] The drive module receives the control signal output by the PID control algorithm module and converts it into a signal for driving the motor, and generates a driving torque to pull the driving rope according to the control signal;

[0037] The communication module is used to perform data communication with the host computer, and to perform data transmission between the sensor module, the torque calculation module, the PID control algorithm module and the drive module.

[0038] In the above technical solution, a sensor module is set up to measure the tension value of the driving rope and the movement angle of the neck in real time; a torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information; a PID control algorithm module is used to calculate the control quantity according to the error between the torque set value and the actual torque measurement value, and to adaptively adjust the parameters of the PID controller, and to perform nonlinear compensation on the output of the PID controller; a driving module is used to receive the control signal output by the PID control algorithm module and convert it into a signal for driving the motor, and to generate a driving torque to pull the driving rope according to the control signal; a communication module is used to communicate data with the host computer and transmit data between the sensor module, the torque calculation module, the PID control algorithm module and the driving module; the control accuracy, stability and response speed of the rope-driven neck exoskeleton are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A structural block diagram of the control system for a rope-driven neck exoskeleton provided in an embodiment of the present application;

[0040] Figure 2 This is a flowchart of the control method for the rope-driven neck exoskeleton provided in an embodiment of the present application. DETAILED DESCRIPTION

[0041] The present application will be further described in detail below through the accompanying drawings and examples, through which the features and advantages of the present application will become more clear and distinct.

[0042] The word "exemplary" is used exclusively herein to mean "serving as an example, example, or illustration." Any embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other embodiments. Although various aspects of the embodiments are shown in the drawings, the drawings are not necessarily drawn to scale unless otherwise indicated.

[0043] In addition, the technical features involved in different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0044] To facilitate understanding of the control system and method for a rope-driven neck exoskeleton provided in the embodiments of the present application, its application scenarios are first described. The control system and method for a rope-driven neck exoskeleton provided in the embodiments of the present application are used to improve the control accuracy, stability, and response speed of a rope-driven neck exoskeleton. Currently, common rope-driven neck exoskeleton control systems suffer from problems such as low control accuracy, poor stability, and slow response speed. Traditional open-loop control systems are unable to sense and adjust the torque of the drive rope in real time, making it difficult to adapt to complex neck movements and load changes. While some closed-loop control systems employ simple control algorithms, they are unable to effectively eliminate control errors when faced with the nonlinear and time-varying characteristics of rope-driven systems, resulting in significant deviations between the exoskeleton's motion trajectory and the desired trajectory, impacting the user experience and the system's practicality. To this end, the embodiments of the present application provide a control system and method for a rope-driven neck exoskeleton to improve the control accuracy, stability, and response speed of a rope-driven neck exoskeleton. These are described in detail below with reference to specific examples and accompanying drawings.

[0045] refer to Figure 1 and Figure 2 , Figure 1 A structural block diagram of the control system for a rope-driven neck exoskeleton provided in an embodiment of the present application; Figure 2 This is a flowchart of the control method for the rope-driven neck exoskeleton provided in an embodiment of the present application.

[0046] exist Figure 1 In the embodiment of the present application, a control system for a rope-driven neck exoskeleton is provided, comprising:

[0047] A sensor module for measuring the tension of the driving rope and the movement angle of the neck in real time;

[0048] A torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information;

[0049] PID control algorithm module, used to calculate the control quantity according to the error between the torque set value and the actual torque measurement value, and to adaptively adjust the parameters of the PID controller and perform nonlinear compensation on the output of the PID controller;

[0050] The driving module is used to receive the control signal output by the PID control algorithm module and convert it into a signal for driving the motor, and generate a driving torque to pull the driving rope according to the control signal;

[0051] The communication module is used to communicate data with the host computer and to transmit data among the sensor module, the torque calculation module, the PID control algorithm module and the drive module.

[0052] In the above technical solution, a sensor module is set up to measure the tension value of the driving rope and the movement angle of the neck in real time; a torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information; a PID control algorithm module is used to calculate the control quantity according to the error between the torque set value and the actual torque measurement value, and to adaptively adjust the parameters of the PID controller, and to perform nonlinear compensation on the output of the PID controller; a driving module is used to receive the control signal output by the PID control algorithm module and convert it into a signal for driving the motor, and to generate a driving torque to pull the driving rope according to the control signal; a communication module is used to communicate data with the host computer and transmit data between the sensor module, the torque calculation module, the PID control algorithm module and the driving module; the control accuracy, stability and response speed of the rope-driven neck exoskeleton are improved.

[0053] Specifically, the beneficial effects include:

[0054] 1. Control accuracy is significantly improved

[0055] Precise torque sensing and calculation: The sensor module accurately measures the tension of the drive rope and the neck's angle of motion in real time, providing precise data for torque calculation. Based on this data, the torque calculation module uses scientific mechanical calculation methods to precisely calculate the torque exerted by the drive rope on the neck joint and the load torque. This precise torque calculation enables the system to more accurately grasp actual torque, laying a solid foundation for subsequent precise control.

[0056] Adaptive parameter adjustment: The PID control algorithm module has the ability to adaptively adjust the parameters of the PID controller. During the operation of the rope-driven neck exoskeleton system, the characteristics of the system will continue to change due to the complexity of the human neck movement and the dynamic changes in the load. Traditional fixed-parameter PID control is difficult to adapt to such changes, while the adaptive adjustment mechanism of the present invention can automatically adjust the proportional, integral and differential parameters of the PID controller in real time according to the error between the torque set value and the actual torque measurement value and the error change rate. This dynamic adjustment enables the control algorithm to better match the current state of the system, thereby significantly reducing the control error, greatly improving the accuracy of torque control, and enabling the exoskeleton to more accurately follow the movement intentions of the human neck.

[0057] 2. System stability is greatly enhanced

[0058] Nonlinear Compensation Mechanism: Rope-driven systems inherently contain numerous nonlinear factors, such as rope friction and elastic deformation. These factors can adversely affect control performance, leading to system oscillation, overshoot, and other issues, reducing system stability. The PID control algorithm module of this invention incorporates a nonlinear compensation subunit, which performs targeted nonlinear compensation on the PID controller output based on real-time state information such as rope tension and joint angles. By compensating for these nonlinear factors, the system operates more smoothly, effectively reducing control deviations and fluctuations caused by nonlinear characteristics and enhancing system stability under various operating conditions.

[0059] Closed-Loop Feedback Control: The entire system utilizes a torque closed-loop control strategy, continuously comparing the set torque value with the actual torque measurement and adjusting the control signal accordingly, forming a complete feedback control loop. This closed-loop control method monitors the system's operating status in real time. If a deviation between the actual torque and the set value is detected, the system immediately responds by adjusting the drive motor output to quickly bring the actual torque close to the set value. This fast and accurate feedback adjustment mechanism effectively suppresses the impact of external interference and internal parameter changes on system stability, ensuring that the rope-driven neck exoskeleton system maintains stable operating conditions during long-term operation.

[0060] 3. Response speed is significantly faster

[0061] Fast parameter response: In the PID control algorithm module, the adaptive parameter adjustment strategy can quickly increase the proportional coefficient when the torque error is large. This increase in the proportional coefficient makes the system more sensitive to errors and responds more quickly to changes in the desired torque. When the human neck makes a sudden and rapid movement, the system can promptly sense the change in the torque setpoint and quickly adjust the PID parameters to quickly generate the corresponding drive torque, pulling the drive rope and allowing the exoskeleton to quickly follow the neck movement, significantly shortening the system's response time.

[0062] Efficient Data Transmission and Processing: The communication module is responsible for data communication with the host computer and facilitates data transmission between the sensor module, torque calculation module, PID control algorithm module, and drive module. By adopting a high-speed, reliable communication protocol and an optimized data transmission architecture, data between modules can be transmitted accurately and in real time. Furthermore, the algorithms and programs within each module have been carefully designed and optimized to rapidly process collected data and make appropriate control decisions. This efficient data transmission and processing capability enables the system to complete the entire process from data acquisition to control signal output in an instant, further improving the system's responsiveness and enabling the rope-driven neck exoskeleton to better adapt to the rapid movements of the human neck.

[0063] In a specific embodiment, the sensor module includes a tension sensor and an angle sensor, wherein:

[0064] The tension sensor is used to measure the tension value of the driving rope in real time.

[0065] The angle sensor is used to measure the movement angle of the neck.

[0066] Specifically, the beneficial effects include:

[0067] Accurate data acquisition lays the foundation for control: A tension sensor measures the drive rope tension in real time, and an angle sensor precisely measures the neck's movement angle, providing the system with accurate, real-time critical data. This data forms the basis for subsequent torque calculations and control decisions, ensuring the system's accurate perception of the entire rope-driven neck exoskeleton's state and enabling precise control.

[0068] Improved system adaptability and reliability: Different people experience varying neck motion and loads. Real-time monitoring by two sensors allows the system to adapt to these changes. When the neck's motion or load changes, the sensors quickly provide feedback, enabling the system to rapidly adjust its control strategy. This ensures the exoskeleton operates stably and reliably under diverse operating conditions, effectively enhancing the system's adaptability to complex environments.

[0069] In a specific embodiment, the torque calculation module includes a rope force-torque conversion unit and a load torque estimation unit, wherein:

[0070] The rope force-torque conversion unit is used to calculate the torque generated by the driving rope on the neck joint according to the tension value;

[0071] The load torque estimation unit is used to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information.

[0072] Specifically, the beneficial effects include:

[0073] Precise torque calculation improves control accuracy: The rope force-torque conversion unit uses real-time measured tension to accurately calculate the torque exerted by the driving rope on the neck joint based on the geometric relationship between the rope and the joint. This provides the system with precise driving torque information, ensuring that control instructions are generated based on accurate torque data and reducing control errors caused by torque calculation deviations.

[0074] Comprehensive load consideration enhances system stability: The load torque estimation unit combines information about the neck's movement angle and angular velocity to estimate the load torque. This fully accounts for changes in load caused by the neck's own gravity and muscle action during movement. This allows the system to anticipate and compensate for load effects during control, avoiding exoskeleton instability caused by sudden load changes. This enhances the system's ability to cope with complex load conditions and ensures overall operational stability.

[0075] In a specific implementation scheme, the PID control algorithm module includes a traditional PID controller and an algorithm innovation unit, wherein:

[0076] The conventional PID controller calculates the control variable based on the error between the torque setting value and the actual torque measurement value;

[0077] The algorithm innovation unit includes an adaptive parameter adjustment subunit and a nonlinear compensation subunit, wherein:

[0078] The adaptive parameter adjustment subunit is used to adaptively adjust the parameters of the PID controller;

[0079] The nonlinear compensation subunit is used to perform nonlinear compensation on the output of the PID controller.

[0080] Specifically, the beneficial effects include:

[0081] Adaptive adjustment improves dynamic control performance: The adaptive parameter adjustment subunit automatically adjusts PID controller parameters based on the error and changes between the set torque value and the actual measured value. When system characteristics fluctuate due to changes in load or the complexity of neck movements, the parameters are quickly optimized to ensure that the control algorithm always adapts to the current working conditions, reducing control errors. This allows the exoskeleton to follow neck movements more accurately and respond more quickly, effectively coping with dynamic changes.

[0082] Nonlinear compensation ensures smooth operation: The nonlinear compensation subunit compensates the PID controller output for nonlinear factors such as rope friction and elastic deformation in the rope drive system. This eliminates the negative impact of nonlinear factors on control effectiveness, preventing system oscillation and overshoot, and ensuring smooth operation of the exoskeleton in all motion states. This improves user comfort and safety, and enhances the overall stability and reliability of the system.

[0083] In a specific embodiment, the driving module includes a motor driver and a driving motor, wherein:

[0084] The motor driver receives the control signal output by the PID control algorithm module and converts it into a signal for driving the motor;

[0085] The driving motor generates a driving torque to pull the driving rope according to the control signal.

[0086] Specifically, the beneficial effects include:

[0087] Precise signal conversion ensures accurate transmission of control commands: The motor driver, acting as a bridge for signal conversion, accurately receives the control signals output by the PID control algorithm module and efficiently converts them into signals recognizable by the drive motor. This process avoids distortion and errors during signal transmission and conversion, ensuring that control commands are transmitted to the drive motor in their original form. This provides the foundation for precise control, enabling the exoskeleton to move precisely as required.

[0088] Efficient drive torque generation improves system responsiveness and performance: The drive motor rapidly generates appropriate drive torque to pull the drive rope based on the converted control signal. It quickly responds to changes in the control signal and adjusts torque output in a timely manner, enabling the exoskeleton to quickly follow the movements of the human neck. This efficient drive torque generation not only improves system responsiveness but also enhances the exoskeleton's support and assistance for neck movements, improving overall system performance and user experience.

[0089] In a specific implementation scheme, the communication module includes a host computer communication interface and an inter-module communication bus, wherein:

[0090] The host computer communication interface is used for data communication with the host computer;

[0091] The inter-module communication bus is used for data transmission among the sensor module, the torque calculation module, the PID control algorithm module and the drive module.

[0092] Specifically, the beneficial effects include:

[0093] Efficient host computer interaction enables remote monitoring and control: The host computer communication interface builds a data bridge between the system and the host computer, enabling the host computer to obtain real-time exoskeleton operating data, such as tension, angle, torque, and other key information, facilitating remote monitoring of equipment status. The host computer can also send control commands to the slave computer through this interface, enabling remote parameter adjustment and function configuration. This improves system operability and management efficiency, facilitating troubleshooting and performance optimization.

[0094] Stable inter-module communication ensures coordinated system operation: The inter-module communication bus ensures stable and efficient data transmission between modules such as sensors, torque calculation, PID control algorithms, and drives. Each module can exchange information promptly and accurately, forming a tight collaborative working mechanism. This prevents control deviations caused by data transmission delays or errors, improves system response speed and control accuracy, and ensures stable and reliable operation of the exoskeleton under various operating conditions.

[0095] In a specific implementation scheme, the adaptive parameter adjustment subunit adopts a fuzzy control algorithm to determine the adjustment amount of the PID controller parameters according to the magnitude of the torque error and the error change rate through a preset fuzzy rule base.

[0096] Specifically, the beneficial effects include:

[0097] Enhanced flexibility and adaptability of parameter adjustment: The fuzzy control algorithm does not rely on precise mathematical models. Instead, it can flexibly adjust PID controller parameters based on fuzzy and uncertain information such as torque error and error rate of change, using a pre-defined fuzzy rule base. During operation, the human neck's movements are complex and varied, and load conditions are difficult to accurately predict. This subunit can quickly respond to these changes, making parameter adjustments more tailored to actual needs and adaptable to different operating conditions.

[0098] Improved system control performance and stability: Parameter adjustment is determined based on a fuzzy rule base, avoiding the control lag and overshoot issues that can occur with traditional fixed parameter adjustment methods when facing complex changes. It precisely adjusts PID parameters, enabling more timely and accurate torque error adjustments, effectively reducing errors and improving control precision. It also enhances system stability during dynamic changes, reducing oscillations and fluctuations, and providing users with a smoother and more comfortable experience.

[0099] In a specific embodiment, the nonlinear compensation subunit determines the nonlinear compensation term according to the rope tension and the joint angle by a table lookup method or a function approximation method, and superimposes the nonlinear compensation term on the output signal of the PID controller.

[0100] Specifically, the beneficial effects include:

[0101] Precisely eliminate nonlinear interference and improve control accuracy: Rope-driven systems are subject to nonlinear factors such as rope friction and elastic deformation, which can severely impact control accuracy. The nonlinear compensation subunit determines the nonlinear compensation term based on rope tension and joint angle using a lookup table or function approximation method. This accurately quantifies the impact of these nonlinear factors on control and superimposes them on the PID controller output signal, effectively offsetting nonlinear interference and bringing the exoskeleton's actual output torque closer to the set value, significantly improving control accuracy.

[0102] Enhanced system stability and optimized user experience: The addition of nonlinear compensation terms reduces system oscillations and overshoot caused by nonlinear factors, making the exoskeleton more stable and reliable during operation. Whether the human neck moves slowly or rapidly, the system responds quickly and accurately, providing users with more stable and comfortable support and assistance, enhancing the user experience and safety of using the exoskeleton.

[0103] In a specific implementation scheme, the host computer communication interface of the communication module includes a serial communication interface, an Ethernet communication interface and a wireless communication interface;

[0104] The inter-module communication bus includes a CAN bus and an I2C bus.

[0105] Specifically, the beneficial effects include:

[0106] A wide range of host computer communication options improves convenience and applicability: The serial communication interface is simple and reliable, suitable for short-range, low-speed communication scenarios; the Ethernet communication interface enables high-speed, long-distance data transmission, facilitating connection to remote host computers; and the wireless communication interface eliminates cable constraints, facilitating flexible device deployment and mobility. A variety of interface formats meet the host computer communication needs of different scenarios, ensuring a suitable method for laboratory debugging, clinical application, and remote monitoring, improving system applicability and ease of use.

[0107] Optimizing inter-module communication to ensure efficient and stable operation: The CAN bus, with its high real-time performance, high reliability, and strong anti-interference capabilities, is suitable for high-speed, large-scale data transmission between modules, ensuring timely and accurate information exchange between modules. The I2C bus, with its low pin count and simple wiring, is suitable for transmitting small amounts of data between modules. Combining these two, appropriately selected based on the data transmission requirements of different modules, ensures efficient and stable inter-module communication, making the overall operation of the exoskeleton system more reliable.

[0108] In a specific implementation scheme, the control system for the rope-driven neck exoskeleton includes a sensor module, a torque calculation module, a PID control algorithm module, a drive module and a communication module. The modules cooperate with each other to jointly complete the torque closed-loop control of the rope-driven neck exoskeleton.

[0109] Furthermore, the sensor module includes:

[0110] Tension sensor: Installed on the drive rope, it measures the rope tension in real time. Using a high-precision, high-sensitivity strain gauge, the tension sensor accurately senses minute changes in rope tension and converts the tension signal into an electrical output.

[0111] Angle sensors are installed at key joints of the neck exoskeleton to measure the angle of movement of the neck. Using high-precision encoders or gyroscopes, these sensors can accurately and in real time capture neck posture information, providing a basis for torque calculation and control.

[0112] The torque calculation module includes:

[0113] The rope force-torque conversion unit uses the driving rope tension measured by the tension sensor and the rope's geometric parameters (such as the location of the rope's connection point with the joint and the rope's effective length) to calculate the torque exerted by the driving rope on the neck joint using the principles of mechanics. The specific calculation formula is: M = F × d, where M is the torque, F is the rope tension, and d is the vertical distance from the rope's force to the joint's rotation center.

[0114] Load Torque Estimation Unit: Considering that the neck exoskeleton is affected by loads such as neck muscle force and gravity during movement, this unit estimates the load torque by establishing a dynamic model of neck motion and combining it with the angle and angular velocity information measured by the angle sensor. This dynamic model is constructed using the Lagrange or Newton-Euler equations, and the accuracy of load torque estimation is improved through real-time updating and optimization of model parameters.

[0115] The PID control algorithm module includes:

[0116] Traditional PID controller: The traditional PID controller calculates the control quantity u(t) according to the error e(t) between the torque set value and the actual torque measurement value, using the three steps of proportional (P), integral (I), and differential (D).

[0117] Algorithm Innovation Unit

[0118] Adaptive Parameter Adjustment Subunit: To address the nonlinear and time-varying nature of the rope-driven neck exoskeleton system, a fuzzy control algorithm is used to adaptively adjust the PID controller's parameters, Kp, Ki, and Kd. This algorithm uses a pre-defined fuzzy rule base to determine the parameter adjustments based on the torque error e(t) and the error rate of change de(t) / dt. For example, when the error is large, the proportional coefficient Kp is increased to speed up the system's response. When the error is small, the proportional coefficient Kp is appropriately decreased and the integral coefficient Ki is increased to eliminate steady-state errors.

[0119] Nonlinear Compensation Subunit: Considering the nonlinear factors of the rope-driven system, such as friction and elastic deformation, a nonlinear compensation term is introduced to correct the PID controller output. This nonlinear compensation term is determined using table lookup or function approximation based on state information such as rope tension and joint angle. For example, a mapping table is established between rope tension and friction torque. During control, the corresponding friction torque compensation value is obtained by looking up the table based on the real-time measured rope tension and then added to the PID controller output.

[0120] The driver module includes:

[0121] Motor Driver: Receives the control signal from the PID control algorithm module and converts it into a voltage or current signal suitable for driving the motor. The motor driver uses a high-performance servo driver with advantages such as fast response and high-precision control, capable of precisely controlling the motor's speed and torque.

[0122] Drive Motor: Connected to the drive cable, it generates a corresponding drive torque based on the control signal from the motor driver, pulling the drive cable to achieve movement of the neck exoskeleton. The drive motor uses a brushless DC motor or stepper motor, which offers compact size, high torque, and high efficiency.

[0123] The communication module includes:

[0124] Host computer communication interface: Used for data communication with the host computer to set control parameters, monitor system status, and store and analyze data. The host computer communication interface can use serial communication (such as RS232, RS485), Ethernet communication, or wireless communication (such as Wi-Fi, Bluetooth).

[0125] Inter-module communication bus: This enables data transmission and communication between the sensor module, torque calculation module, PID control algorithm module, and drive module. The inter-module communication bus uses high-speed, reliable communication protocols such as the CAN bus or I2C bus to ensure data synchronization and real-time performance between modules.

[0126] In the above technical solution, the beneficial effects include:

[0127] Improve control accuracy: By introducing an adaptive parameter adjustment subunit, the parameters of the PID controller are automatically adjusted according to the real-time status of the rope-driven neck exoskeleton system. This can better adapt to the nonlinearity and time-varying nature of the system, effectively reduce control errors, and improve the accuracy of torque control.

[0128] Enhanced system stability: The nonlinear compensation subunit corrects the output of the PID controller, compensating for the impact of nonlinear factors such as friction and elastic deformation in the rope drive system on the control performance, enhancing system stability and reducing system oscillation and overshoot.

[0129] Faster response: The adaptive parameter adjustment strategy increases the proportional coefficient when the error is large, allowing the system to respond more quickly to changes in the desired torque. This improves the system's response speed and enables the neck exoskeleton to follow the movement of the human neck more promptly.

[0130] Good scalability and versatility: This control system adopts a modular design with independent modules, facilitating system upgrades and maintenance. Furthermore, by adjusting the parameters and algorithms of the PID control algorithm module, it can be adapted to different types and specifications of rope-driven neck exoskeleton systems, demonstrating its excellent versatility.

[0131] exist Figure 2 In an embodiment of the present application, a control method for a rope-driven neck exoskeleton is provided, comprising the following steps:

[0132] The sensor module is used to measure the tension of the driving rope and the movement angle of the neck in real time;

[0133] The torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and the magnitude of the load torque is calculated according to the neck movement angle and angular velocity information;

[0134] The PID control algorithm module is used to calculate the control quantity according to the error between the torque set value and the actual torque measurement value, and the parameters of the PID controller are adaptively adjusted, and the output of the PID controller is nonlinearly compensated;

[0135] The drive module receives the control signal output by the PID control algorithm module and converts it into a signal for driving the motor, and generates a driving torque to pull the driving rope according to the control signal;

[0136] The communication module is used to perform data communication with the host computer, and to perform data transmission between the sensor module, the torque calculation module, the PID control algorithm module and the drive module.

[0137] In the above technical solution, a sensor module is set up to measure the tension value of the driving rope and the movement angle of the neck in real time; a torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information; a PID control algorithm module is used to calculate the control quantity according to the error between the torque set value and the actual torque measurement value, and to adaptively adjust the parameters of the PID controller, and to perform nonlinear compensation on the output of the PID controller; a driving module is used to receive the control signal output by the PID control algorithm module and convert it into a signal for driving the motor, and to generate a driving torque to pull the driving rope according to the control signal; a communication module is used to communicate data with the host computer and transmit data between the sensor module, the torque calculation module, the PID control algorithm module and the driving module; the control accuracy, stability and response speed of the rope-driven neck exoskeleton are improved.

[0138] Those skilled in the art will appreciate that the present application may be implemented as a system, method, or computer program product.

[0139] Therefore, the present disclosure may be implemented in the following forms: entirely in hardware, entirely in software (including firmware, resident software, microcode, etc.), or in a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the present disclosure may be implemented in the form of a computer program product embodied in one or more computer-readable media, wherein the computer-readable media contains computer-readable program code.

[0140] Any combination of one or more computer-readable media can be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or device.

[0141] Although the embodiments of the present application have been shown and described above, it should be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application. Various substitutions and improvements may be made to the present application on this basis, all of which fall within the scope of protection of the present application.

Claims

1. A control system for a rope-driven neck exoskeleton, characterized in that: include: A sensor module for measuring the tension of the driving rope and the movement angle of the neck in real time; A torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information; PID control algorithm module, used to calculate the control quantity according to the error between the torque set value and the actual torque measurement value, and to adaptively adjust the parameters of the PID controller and perform nonlinear compensation on the output of the PID controller; The driving module is used to receive the control signal output by the PID control algorithm module and convert it into a signal for driving the motor, and generate a driving torque to pull the driving rope according to the control signal; The communication module is used to communicate data with the host computer and to transmit data between the sensor module, the torque calculation module, the PID control algorithm module and the drive module.

2. The control system for a rope-driven neck exoskeleton according to claim 1, characterized in that: The sensor module includes a tension sensor and an angle sensor, wherein: The tension sensor is used to measure the tension value of the driving rope in real time. The angle sensor is used to measure the movement angle of the neck.

3. The control system for a rope-driven neck exoskeleton according to claim 2, characterized in that: The torque calculation module includes a rope force-torque conversion unit and a load torque estimation unit, wherein: The rope force-torque conversion unit is used to calculate the torque generated by the driving rope on the neck joint according to the tension value; The load torque estimation unit is used to calculate the magnitude of the load torque according to the neck movement angle and angular velocity information.

4. The control system for the rope-driven neck exoskeleton according to claim 3, characterized in that: The PID control algorithm module includes a traditional PID controller and an algorithm innovation unit, wherein: The conventional PID controller calculates the control variable based on the error between the torque setting value and the actual torque measurement value; The algorithm innovation unit includes an adaptive parameter adjustment subunit and a nonlinear compensation subunit, wherein: The adaptive parameter adjustment subunit is used to adaptively adjust the parameters of the PID controller; The nonlinear compensation subunit is used to perform nonlinear compensation on the output of the PID controller.

5. The control system for the rope-driven neck exoskeleton according to claim 4, characterized in that: The driving module includes a motor driver and a driving motor, wherein: The motor driver receives the control signal output by the PID control algorithm module and converts it into a signal for driving the motor; The driving motor generates a driving torque to pull the driving rope according to the control signal.

6. The control system for the rope-driven neck exoskeleton according to claim 5, characterized in that: The communication module includes a host computer communication interface and an inter-module communication bus, wherein: The host computer communication interface is used for data communication with the host computer; The inter-module communication bus is used for data transmission among the sensor module, the torque calculation module, the PID control algorithm module and the drive module.

7. The control system for the rope-driven neck exoskeleton according to claim 6, characterized in that: The self-adaptive parameter adjustment subunit adopts a fuzzy control algorithm and determines the adjustment amount of the PID controller parameters through a preset fuzzy rule base according to the magnitude of the torque error and the error change rate.

8. The control system for the rope-driven neck exoskeleton according to claim 7, characterized in that: The nonlinear compensation subunit determines the nonlinear compensation term according to the rope tension and the joint angle by using a table lookup method or a function approximation method, and superimposes the nonlinear compensation term on the output signal of the PID controller.

9. The control system for the rope-driven neck exoskeleton according to claim 8, characterized in that: The host computer communication interface of the communication module includes a serial communication interface, an Ethernet communication interface and a wireless communication interface; The inter-module communication bus includes a CAN bus and an I2C bus.

10. A control method for a rope-driven neck exoskeleton, characterized in that: The following steps are involved: The sensor module is used to measure the tension of the driving rope and the movement angle of the neck in real time; The torque calculation module is used to calculate the torque generated by the driving rope on the neck joint according to the tension value, and the magnitude of the load torque is calculated according to the neck movement angle and angular velocity information; The PID control algorithm module is used to calculate the control quantity according to the error between the torque setting value and the actual torque measurement value, and the parameters of the PID controller are adaptively adjusted, and the output of the PID controller is nonlinearly compensated; The drive module receives the control signal output by the PID control algorithm module and converts it into a signal for driving the motor, and generates a driving torque to pull the driving rope according to the control signal; The communication module is used to perform data communication with the host computer, and to perform data transmission between the sensor module, the torque calculation module, the PID control algorithm module and the drive module.

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