CN119188814B - A prosthetic hand system and method based on force/position hybrid fuzzy control - Google Patents
A prosthetic hand system and method based on force/position hybrid fuzzy controlInfo
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- CN119188814B CN119188814B CN202411335149.5A CN202411335149A CN119188814B CN 119188814 B CN119188814 B CN 119188814B CN 202411335149 A CN202411335149 A CN 202411335149A CN 119188814 B CN119188814 B CN 119188814B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J15/00—Gripping heads and other end effectors
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J15/00—Gripping heads and other end effectors
- B25J15/0009—Gripping heads and other end effectors comprising multi-articulated fingers, e.g. resembling a human hand
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1612—Programme controls characterised by the hand, wrist, grip control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1628—Programme controls characterised by the control loop
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
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- Engineering & Computer Science (AREA)
- Robotics (AREA)
- Mechanical Engineering (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Orthopedic Medicine & Surgery (AREA)
- Prostheses (AREA)
- Control Of Position Or Direction (AREA)
Abstract
本发明提供了一种基于力/位混合模糊控制的假肢手系统及方法，包括假肢手本体，以及力反馈模块，用于获取相应指尖的接触压力；位置反馈模块，用于获取各关节的运动信息，并根据所述运动信息计算对应关节的屈曲/伸展角度以及内收/外展角度，确定各关节的位置信息；控制模块，用于根据各指尖的接触压力，利用阻抗模型动态调整假肢手在抓握过程中所施加的力，并将力控制指令转换为位置控制指令，结合所述位置控制指令和各关节的位置信息，得到最终控制信号，发送给相应的驱动模块。本发明可以保证高精度控制效果的同时，降低控制器的设计复杂性。
The present invention provides a prosthetic hand system and method based on force/position hybrid fuzzy control. The system comprises a prosthetic hand body, a force feedback module for obtaining the contact pressure of corresponding fingertips, a position feedback module for obtaining motion information of each joint, and calculating the flexion/extension angles and adduction/abduction angles of the corresponding joint based on this motion information to determine the position information of each joint. A control module for dynamically adjusting the force applied by the prosthetic hand during grasping using an impedance model based on the contact pressure of each fingertip, converting force control commands into position control commands, and combining these position control commands with the position information of each joint to generate a final control signal, which is then sent to the corresponding drive module. The present invention can ensure high-precision control while reducing the design complexity of the controller.
Description
Technical Field
The invention belongs to the field of artificial limb control, and particularly relates to a prosthetic hand system and a prosthetic hand method based on force/position mixed fuzzy control.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
Human hand grasping is an indispensable capability in human daily life and work, and its complexity and flexibility have been the focus of research in the prosthetic hand design and robot control fields. The human hand can perform various types of gripping actions, from fine pinching to strong gripping, and various feedback mechanisms of the human body are not separated. The force/position mixed feedback control is a control strategy of combining force feedback and position feedback and is widely applied to a robot control system. Compared with simple force feedback or position feedback, the force/position mixed feedback can sense and adapt to complex environments more comprehensively, and the interaction capability of the robot in uncertain environments is improved. In simple force feedback control, position errors are liable to occur, and especially when a fragile object is gripped, damage to the object may be caused if there is no support for position feedback. In the simple position feedback control, however, the change of the external force may be ignored, resulting in a grip failure or unstable control. The force/bit mixed feedback can integrate the information of the two, so that the system can find balance between force and position, and the stability of grasping is ensured.
Impedance control is used as a common robot force/position hybrid control strategy, and the dynamic response characteristic of the robot under the action of external force is controlled by adjusting the force-displacement relationship between the robot and the environment, so that flexible interaction behavior is realized. The control method does not directly control the applied force or the accurate position of the tail end of the robot, but enables the robot to show proper flexibility and stability when interacting with the environment by adjusting the mechanical impedance (namely rigidity, damping and inertia) of the system, and can safely and effectively operate in different tasks and environments. Fuzzy control is a control method based on fuzzy logic and is used for solving the problems of uncertainty and nonlinear systems. The control of the system is realized by converting expert experience and knowledge into fuzzy rules. In the dynamic change of the interaction between the prosthetic hand and the object, the relation between the impedance parameter and the tissue model of the system is difficult to establish a specific mathematical model, but the change has a corresponding trend. Thus, a fuzzy control algorithm may be employed to estimate the correlation coefficient in the impedance model.
Since the impedance control is a hybrid control of position and force by adjusting the relationship between the force and the trajectory of the robot tip, the accuracy requirements for the controller are very high. Accurate impedance control not only requires real-time monitoring and feedback of the state of the system, but also requires a controller that can respond and adjust quickly in complex operating environments. However, as control accuracy increases, the design of the controller becomes more and more complex, often requiring more sensors, higher computational power, and more complex algorithms to implement. How to reduce the design complexity of the controller and the hardware dependence and the calculation burden of the system while ensuring the high-precision control effect is a main problem to be solved currently.
Disclosure of Invention
In order to solve the problems, the invention provides a prosthetic hand system and a method based on force/position mixed fuzzy control. The external force control loop is realized by using an impedance model according to the inverse kinematics of the prosthetic hand, and the damping and the rigidity of the impedance model are calculated by using a fuzzy control algorithm, so that the damping and the rigidity can be self-adjusted in real time according to different contact environments. The internal position Control loop is realized by using a Model-Free Control (MFC) controller based on an Ultra-Local Model (ULM), and all the characteristics and uncertainties of the system are integrated into one unknown item, so that the complexity of the design of the controller is greatly reduced. And the time lag estimator is used for estimating the value of the unknown item, and the introduction of the time lag estimator also reduces the requirement on accurate model parameters.
According to some embodiments, the present invention employs the following technical solutions:
A prosthetic hand system based on force/position hybrid fuzzy control, comprising:
the artificial hand body comprises a palm platform, a plurality of finger structures are arranged on the palm platform, each finger structure is provided with a plurality of joints, and each joint is provided with a driving module;
The force feedback module comprises a plurality of finger tip parts which are respectively arranged on the finger structures and used for acquiring the contact pressure of the corresponding finger tips;
The position feedback module comprises a plurality of positions which are respectively arranged at each joint and used for acquiring the motion information of each joint, calculating the buckling/stretching angle and the adduction/abduction angle of the corresponding joint according to the motion information and determining the position information of each joint;
The control module is connected with the force feedback module and the position feedback module, and is used for dynamically adjusting the force applied by the prosthetic hand in the grasping process by utilizing the impedance model according to the contact pressure of each fingertip, converting the force control instruction into a position control instruction, combining the position control instruction and the position information of each joint to obtain a final control signal, and transmitting the final control signal to the corresponding driving module;
The driving module is used for controlling and driving the motor of the prosthetic hand, receiving the signals from the control module, and converting the signals into specific motor driving instructions so as to ensure that all parts of the prosthetic hand can operate in a coordinated manner.
As an alternative implementation manner, the force feedback module comprises an FSR sensor, the FSR sensor is connected with a voltage conversion module, and the voltage conversion module is used for performing linear voltage-resistance conversion of the FSR sensor in a resistance voltage division manner, so as to realize measurement of contact pressure.
As an alternative embodiment, the position feedback module includes an ADXL345 module, where the ADXL345 module is connected to an analog switch module, and the analog switch module is used to control selection of each ADXL345 module.
As an alternative embodiment, each joint is driven by a motor, and the driving module is connected with the motor and is used for converting the final control signal generated by the control module into a corresponding motor action so as to adjust the motion of the corresponding joint of the prosthetic hand to complete the designated task.
As an alternative embodiment, the control module may be implemented by a ATMega/2560 chip, and includes an external force control loop configured to calculate an ideal impedance characteristic according to the contact pressure of each fingertip and a preset or acquired expected force by using a fuzzy controller, generate a position change instruction corresponding to a target interaction force according to the impedance characteristic by using an impedance model, and convert the position change instruction into bending angle information of each joint of the prosthetic hand by using an inverse kinematics model of the prosthetic hand in combination with position information of the object to be grasped.
As an alternative embodiment, the fuzzy controller is configured to fuzzify the desired force f d and the actual contact force f e by using a fuzzy control theory, and defuzzify the system control amount by using the variation relationship of the damping B f, the rigidity K f, the damping B i and the rigidity K i of the prosthetic hand system, the desired force f d and the actual contact force f e of the grasping object as a fuzzy reasoning rule to obtain a deterministic relationship between the fuzzy control input variable (f d,fe) and the system control amount (B f、Kf、Bi and K i).
The control module comprises an internal position control loop, wherein the internal position control loop is configured to take position information of each joint of the prosthetic hand body and bending angle information of an external force control loop as input, obtain a final control signal by using an MFC controller, calculate the value of an unknown item in the MFC controller by using a time lag estimator, and output the final control signal to the prosthetic hand body to realize closed loop control.
A prosthetic hand control method based on force/position mixed fuzzy control, comprising the following steps:
acquiring contact pressure of each fingertip;
acquiring motion information of each joint, calculating buckling/stretching angles and adduction/abduction angles of the corresponding joints according to the motion information, and determining position information of each joint;
and dynamically adjusting the force applied by the prosthetic hand in the process of grasping by using an impedance model according to the contact pressure of each fingertip, converting the force control instruction into a position control instruction, and combining the position control instruction and the position information of each joint to obtain a final control signal.
As an alternative embodiment, the process of dynamically adjusting the force applied by the prosthetic hand during the grasping process using the impedance model according to the contact pressure of each fingertip, and converting the force control command into the position control command includes:
And comparing the contact pressure of each fingertip with a preset or acquired expected force, calculating an ideal impedance characteristic by using a fuzzy controller, generating a position change instruction corresponding to the target interaction force according to the impedance characteristic by using an impedance model, combining the position information of the grasping object, and converting the position change instruction into bending angle information of each joint of the prosthetic hand by using an inverse kinematics model of the prosthetic hand.
As an alternative embodiment, the process of combining the position control command and the position information of each joint to obtain the final control signal includes:
The position information of each joint of the prosthetic hand body and the bending angle information of the external force control ring are taken as input, the MFC controller is utilized to obtain a final control signal, the time lag estimator is used for calculating the value of an unknown item in the MFC controller, and the final control signal is output to the prosthetic hand body to realize closed loop control.
Compared with the prior art, the invention has the beneficial effects that:
1. The prosthetic hand system based on the force/position mixed fuzzy control provided by the invention uses the FSR sensor and the ADXL345 module to acquire fingertip force information and joint angle information of the prosthetic hand, so that the prosthetic hand system is convenient to integrate;
2. The number of ADXL345 modules in the prosthetic hand system based on the force/position mixed fuzzy control can be increased or decreased according to the number of drivers of the prosthetic hand, and the application range is wide;
3. The prosthetic hand controller based on the force/bit mixed fuzzy control is designed according to the ULM, all the characteristics and the uncertainty of the system are integrated into one unknown item, and the complexity of the design of the controller is greatly reduced;
4. The prosthetic hand controller based on force/bit mixed fuzzy control provided by the invention uses the time lag estimator to estimate the value of an unknown item, so that the requirement on accurate model parameters is greatly reduced;
5. The prosthetic hand controller based on the force/position mixed fuzzy control provided by the invention utilizes a fuzzy control algorithm to estimate the damping and rigidity of the impedance model, so that the damping and rigidity of the impedance model can be self-regulated in real time according to different contact environments, the flexibility and the accuracy of the prosthetic hand are improved, and the capability of adapting to different object shapes and materials is enhanced.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 is a schematic diagram of the mounting locations of the FSR sensor and ADXL345 module on a prosthetic hand in a force/position hybrid fuzzy control system according to the present invention;
FIG. 2 is a schematic diagram of the force/bit hybrid fuzzy control system and the communication between the parts according to the present invention;
FIG. 3 is an overall framework of a force/bit hybrid fuzzy controller in accordance with the present invention;
Fig. 4 shows one possible way of establishing a rectangular coordinate system for a prosthetic hand.
Wherein 1 is the prosthetic hand, 2 is FSR sensor, 3 is ADXL345 module, 4 is first prosthetic finger joint, 5 is second prosthetic finger joint, 6 is third prosthetic finger joint, 7 is fourth prosthetic finger joint.
Detailed Description
The invention will be further described with reference to the drawings and examples.
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the invention. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present invention. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
Embodiments of the application and features of the embodiments may be combined with each other without conflict.
Example 1
The present embodiment provides a prosthetic hand system based on force/position hybrid fuzzy control, comprising:
The artificial hand body comprises a palm platform, a plurality of finger structures are arranged on the palm platform, each finger structure is provided with a plurality of joints, each joint is driven by an independent motor, and the motor is driven by a driving module;
And the force feedback module is responsible for acquiring a pressure signal when the fingertip contacts the object. In this embodiment, the module adopts a voltage conversion mode based on resistance voltage division, and the FSR sensor detects the pressure change of the prosthetic finger tip in real time. The FSR sensor can effectively capture the contact pressure between the finger tip of the artificial limb and the surface of the object, ensure that the magnitude of the applied force can be adjusted in real time when the artificial limb executes the grasping task, and prevent the object from being damaged due to grasping too tightly or from falling due to loosening too much.
And the position feedback module is mainly responsible for motion detection and position signal acquisition of the prosthetic hand. In this embodiment, the module uses an ADXL345 chip, which is a high-precision three-axis acceleration sensor for obtaining motion information of each joint of the five fingers of the prosthetic hand. By monitoring the acceleration data, the chip can calculate the flexion/extension angle and the adduction/abduction angle of each joint, thereby providing real-time positional information for the prosthetic hand.
Meanwhile, the high sensitivity and low power consumption of the ADXL345 chip enable the ADXL345 chip to keep high-precision data acquisition under complex motion conditions. This module provides a reliable position signal input for the prosthetic hand so that the overall system can respond quickly and accurately when performing different tasks.
The control module is realized by adopting ATMega and 2560 chips and is used for collecting, processing, calculating and transmitting all input data and generating proper control signals. The module analyzes the state of the prosthetic hand in real time by processing data from the force feedback module and the position feedback module, and generates a corresponding control strategy according to an MFC algorithm based on the ULM. The application of the MFC algorithm enables the module to realize complex control functions through real-time learning and optimization without depending on an accurate system model. The control module can make intelligent decisions in different scenes through the built-in computing capability, and the actions of the prosthetic hand are adjusted to adapt to specific task requirements, such as grabbing, moving, rotating and the like, so that complex action control is realized. In addition, the module can transmit data to an upper computer for storage in a wired or wireless mode.
The driving module is mainly responsible for controlling and driving the motor of the prosthetic hand. The module receives signals from the control module and converts the signals into specific motor driving instructions, so that the coordination operation of all parts of the prosthetic hand can be ensured. Accurate control of the motor is a key for realizing efficient operation of the prosthetic hand, and flexible movement of each joint of the prosthetic hand can be realized through the driving module, so that various complex operation requirements are met. The driving module has high-speed response capability, can execute control commands instantly, and ensures the stability and accuracy of the prosthetic hand.
As shown in fig. 1, in the force/position hybrid control system proposed in this embodiment, the FSR sensor 2 is mounted on the five-finger abdomen of the prosthetic hand 1, the ADXL345 module 3 is mounted on each finger joint of the prosthetic hand, and the number of the ADXL345 modules 3 can be adjusted accordingly according to the number of different prosthetic hand drivers in order to ensure accurate control of different prosthetic hands. In general, the number of ADXL345 modules 3 is consistent with the number of prosthetic hand drivers. In terms of circuit implementation, in order to ensure electrical safety and reliability of the system, a design method of separating the main board from the driving board is adopted. The design can effectively reduce interference and electromagnetic coupling in a circuit and ensure the stability of signal transmission among the modules.
As shown in fig. 2, the force feedback module mainly comprises an FSR sensor 2 and a voltage conversion module located on a motherboard, and the voltage conversion module adopts a resistor voltage division mode to realize linear voltage-resistor conversion of the FSR sensor, thereby realizing pressure measurement. The position feedback module mainly comprises an ADXL345 module 3 and an analog switch module positioned on the main board. Because ADXL345 module 3 is I 2 C equipment with only one address, the analog switch module is mainly used for controlling the selection of a plurality of ADXL345 modules 3, and ensuring the normal operation of data transmission. The control module is positioned on the main board and is used as a core computing unit of the system and is responsible for collecting, analyzing, processing and transmitting signals from the force feedback module and the position feedback module and generating corresponding control instructions to drive the artificial hand to act.
The driving module in this embodiment is a driving board, and is used as an execution unit of the system to convert the instruction generated by the control module into a specific motor action, so as to adjust the motion of each joint of the prosthetic hand, so as to complete the designated task.
To sum up, the fingertip pressure signal of the prosthetic hand of the present embodiment is obtained by a film pressure sensor (Thin Film Pressure Sensor, FSR) mounted on the abdomen of the five fingers of the prosthetic hand. The position information of each joint of the prosthetic hand is obtained through a three-axis acceleration sensor ADXL345 module which is arranged on each knuckle of the five fingers. The main board is used for collecting, processing and calculating two signals, communicating with the upper computer and generating control signals for driving the motor. The drive plate is used for controlling and driving the motor of the prosthetic hand. For the whole control method, the controller based on the force/bit mixed fuzzy control has a double-ring structure, and comprises an external force control ring and an internal position control ring. The external force control loop is realized by using an impedance model according to the inverse kinematics of the prosthetic hand, and the damping and the rigidity of the impedance model are calculated by using a fuzzy control algorithm, so that the damping and the rigidity can be self-adjusted in real time according to different contact environments. The internal position control loop is implemented by using an MFC controller based on ULM, and all the characteristics and uncertainties of the system are integrated into one unknown item, so that the complexity of the controller design is greatly reduced. And the time lag estimator is used for estimating the value of the unknown item, and the introduction of the time lag estimator also reduces the requirement on accurate model parameters.
Example two
The embodiment provides a prosthetic hand control method based on force/position mixed fuzzy control, which comprises the following steps:
The external force control loop (also called external force control loop) is implemented using an impedance model based on the inverse kinematics of the prosthetic hand. The model is used for simulating mechanical characteristics required in the interaction process of the prosthetic hand and an external object, dynamically adjusting the force applied by the prosthetic hand in the gripping process, converting the force control into position control and combining the position control with an internal position control loop. Wherein the damping and stiffness of the impedance model are calculated using a fuzzy control algorithm.
An internal position control loop (also referred to as an internal position control loop) is implemented using a ULM-based MFC controller, integrating all the characteristics and uncertainties of the system into one unknown term, and using a time-lag estimator to estimate the value of the unknown term.
As shown in fig. 3, the external force control loop dynamically adjusts the force distribution of the prosthetic hand by continuously monitoring the contact state of the prosthetic hand with the object. First, the FSR sensor located on the prosthetic finger tip will collect real-time force feedback data.
Using this data and the desired force set manually or otherwise obtained, the desired impedance characteristics are calculated from the fuzzy control algorithm and input into the impedance model. Then, the impedance model generates a position change instruction corresponding to the target interaction force. And finally, combining the position information of the gripping object, and converting the position information into bending angle information of each joint of the prosthetic hand through an inverse kinematics model of the prosthetic hand. In this way, the force control is successfully converted into position control, ensuring that the prosthetic hand can interact with the object in a compliant and stable manner.
The internal position control loop monitors and adjusts the real-time position of the joint of the prosthetic hand, and is matched with the external force control loop to realize accurate control of the prosthetic hand. Firstly, an ADXL345 module arranged on the prosthetic hand acquires position information of each joint of the prosthetic hand in real time. The position feedback data from the prosthetic hand and the angle information from the internal force control loop via inverse kinematics are then input into the ULM-based MFC controller. And simultaneously calculating the value of the unknown item of the system in the MFC controller by using the time lag estimator. And finally, outputting the result of the MFC controller to the prosthetic hand, and realizing the closed-loop control of the prosthetic hand.
One possible way of establishing a rectangular coordinate system for a prosthetic finger is shown in fig. 4. The external force control loop is used to track the interaction force f d of the prosthetic finger tip with the gripping object. Assuming that the five fingertips as the end effectors are flexible, the prosthetic hand output force f e on the gripping object can be expressed as an impedance model:
Wherein B f and K f represent damping and stiffness, respectively, of the prosthetic hand system and Z f represents compression displacement of the tips of the five fingers. If a Kelvin-Voigt model is used, the force between the five fingertips and the gripping object f i can be expressed as:
wherein B i and K i are the damping and stiffness, respectively, of the gripping object. The reference trajectory along the z-axis of the prosthetic hand is represented by:
Zr＝Zd+Zf(3)
Where Z d is the desired trajectory along the Z-axis.
Next, the desired force f d and the actual contact force f e are blurred by using the fuzzy control theory, and a dual-input four-output fuzzy controller is established.
First, the variable is blurred. Let the expected force f d be [ f dmin,fdmax ], define the fuzzy set of f d as { NB, NS, ZO, PS, PB }, the actual contact force f e be [ f emin,femax ], define the fuzzy set of f e as { NB, NS, ZO, PS, PB }, and the control amount U of the system have basic definition fields [ -6,6], and the fuzzy set as { NB, NS, ZO, PS, PB }.
NB, NS, ZO, PS, PB respectively represent negative big, negative small, zero, positive small and positive big, and represent membership in fuzzy control.
And selecting different membership functions for the system according to the intensity of the force. For example, for minimum and maximum forces, a triangular membership function may be selected, and for medium magnitude forces, a trapezoidal membership function may be selected.
Next, a fuzzy rule control table is created. And B f,Kf,Bi,Ki is changed along with the parameter (f d,fe) to be a fuzzy inference rule, so that a deterministic relationship between a fuzzy control input variable and a system control quantity U is obtained, and the deterministic relationship is shown in the following formulas (5) - (8).
Finally, deblurring, setting the true adjustment range ([ B fmin,Bfmax],[Kfmin,Kfmax],[Bimin,Bimax],[Kimin,Kimax ]) of the output variable (B f,Kf,Bi,Ki):
X d is the desired trajectory of the finger along the X-axis, and the internal position control loop is used to track the reference trajectory (Z r,Xd) to achieve a hybrid control of force and position. Firstly, in order to reduce the difficulty of the controller, the dynamics equation of the prosthetic hand is converted into a super local model ULM:
where α is a constant, x represents the rotation angle of each joint of the prosthetic hand, u represents the torque of each motor, and F is an unknown term, including all dynamic characteristics and uncertainty terms of the system. Defining a tracking error:
e=x-xd (10)
In practical control tasks, the system parameters are often unknown or inaccurate, which makes the value of F very difficult, and therefore, an estimator needs to be designed to estimate the value of F:
Wherein, the Is an estimate of F and delta represents a small time delay. The delay estimator estimates the value of F at time t by the value of F at time t-delta. If delta is small enough, the estimation error of the delay estimator for F can be very small.
Example III
A prosthetic hand system based on force/position hybrid fuzzy control, comprising:
the artificial hand body comprises a palm platform, a plurality of finger structures are arranged on the palm platform, each finger structure is provided with a plurality of joints, and each joint is provided with a driving module;
The force feedback module comprises a plurality of finger tip parts which are respectively arranged on the finger structures and used for acquiring the contact pressure of the corresponding finger tips;
The position feedback module comprises a plurality of positions which are respectively arranged at each joint and used for acquiring the motion information of each joint, calculating the buckling/stretching angle and the adduction/abduction angle of the corresponding joint according to the motion information and determining the position information of each joint;
The control module is connected with the force feedback module and the position feedback module, and is used for dynamically adjusting the force applied by the prosthetic hand in the grasping process by utilizing the impedance model according to the contact pressure of each fingertip, converting the force control instruction into a position control instruction, combining the position control instruction and the position information of each joint to obtain a final control signal, and sending the final control signal to the corresponding driving module.
In some embodiments, the control module is configured to perform the steps of the control method provided in embodiment two.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which do not require the inventive effort by those skilled in the art, are intended to be included within the scope of the present invention.
Claims (7)
1. A prosthetic hand system based on force/position hybrid fuzzy control, comprising:
the artificial hand body comprises a palm platform, a plurality of finger structures are arranged on the palm platform, each finger structure is provided with a plurality of joints, and each joint is provided with a driving module;
The force feedback module comprises a plurality of finger tip parts which are respectively arranged on the finger structures and used for acquiring the contact pressure of the corresponding finger tips;
The position feedback module comprises a plurality of positions which are respectively arranged at each joint and used for acquiring the motion information of each joint, calculating the buckling/stretching angle and the adduction/abduction angle of the corresponding joint according to the motion information and determining the position information of each joint;
The control module is connected with the force feedback module and the position feedback module, is used for dynamically adjusting the force applied by the prosthetic hand in the process of grasping by utilizing an impedance model according to the contact pressure of each fingertip, converting the force control instruction into a position control instruction, combining the position control instruction and the position information of each joint to obtain a final control signal, and transmitting the final control signal to the corresponding driving module;
The fuzzy controller is configured to fuzzify the expected force f d and the actual contact force f e by utilizing a fuzzy control theory, and defuzzify the system control quantity by using the change relation of the damping B f, the rigidity K f, the damping B i and the rigidity K i of the grasping object, the expected force f d and the actual contact force f e of the prosthetic hand system as a fuzzy reasoning rule to obtain the deterministic relation between the fuzzy control input variable f d,fe and the system control quantity B f、 Kf、Bi and K i;
The control module comprises an internal position control loop, wherein the internal position control loop is configured to take position information of each joint of the prosthetic hand body and bending angle information of an external force control loop as input, obtain a final control signal by using a model-free controller, calculate the value of an unknown item in the model-free controller by using a time lag estimator, and output the final control signal to the prosthetic hand body to realize closed loop control;
The driving module is used for controlling and driving the motor of the prosthetic hand, receiving the signals from the control module, and converting the signals into specific motor driving instructions so as to ensure that all parts of the prosthetic hand can operate in a coordinated manner.
2. The prosthetic hand system based on force/position mixed fuzzy control of claim 1, wherein the force feedback module comprises a film pressure sensor, the film pressure sensor is connected with a voltage conversion module, and the voltage conversion module is used for carrying out linear voltage-resistance conversion of the film pressure sensor by adopting a resistance voltage division mode so as to realize measurement of contact pressure.
3. The prosthetic hand system based on force/position hybrid fuzzy control of claim 1, wherein said position feedback module comprises a tri-axis acceleration sensor module connected to an analog switch module for controlling the selection of each tri-axis acceleration sensor module.
4. The prosthetic hand system based on force/position hybrid fuzzy control of claim 1, wherein each joint is driven by a motor, said driving module is connected to the motor for converting the final control signal generated by the control module into a corresponding motor action to adjust the motion of the corresponding joint of the prosthetic hand to accomplish the specified task.
5. A prosthetic hand control method based on force/position mixed fuzzy control, characterized in that a prosthetic hand system based on force/position mixed fuzzy control according to claim 1 is utilized, comprising the following steps:
acquiring contact pressure of each fingertip;
acquiring motion information of each joint, calculating buckling/stretching angles and adduction/abduction angles of the corresponding joints according to the motion information, and determining position information of each joint;
and dynamically adjusting the force applied by the prosthetic hand in the process of grasping by using an impedance model according to the contact pressure of each fingertip, converting the force control instruction into a position control instruction, and combining the position control instruction and the position information of each joint to obtain a final control signal.
6. The prosthetic hand control method according to claim 5, wherein the process of dynamically adjusting the force applied by the prosthetic hand during the grasping process using the impedance model according to the contact pressure of each fingertip and converting the force control command into the position control command comprises:
And comparing the contact pressure of each fingertip with a preset or acquired expected force, calculating an ideal impedance characteristic by using a fuzzy controller, generating a position change instruction corresponding to the target interaction force according to the impedance characteristic by using an impedance model, combining the position information of the grasping object, and converting the position change instruction into bending angle information of each joint of the prosthetic hand by using an inverse kinematics model of the prosthetic hand.
7. The prosthetic hand control method based on force/bit mixed fuzzy control according to claim 5, wherein the process of combining the position control command and the position information of each joint to obtain the final control signal comprises:
The position information of each joint of the prosthetic hand body and the bending angle information of the external force control ring are taken as input, a final control signal is obtained by using the model-free controller, the value of an unknown item in the model-free controller is calculated by using the time lag estimator, and the final control signal is output to the prosthetic hand body to realize closed loop control.
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