A control system for an upper and lower limb active and passive movement rehabilitation machine

Abstract

The present invention discloses a control system for an upper and lower limb active and passive movement rehabilitation machine, which includes a main control board. After the main control board collects the speed data of the DC motor, the AD value of the DC motor current sampling, the position data of the DC motor and the switch state information and performs calculations, the real-time speed and resistance data of the motor are obtained. Using the PID closed-loop feedback control algorithm, a PWM waveform is generated and applied to the motor through the H-bridge drive circuit; the SIMULINK is used to simulate the PID closed-loop feedback control algorithm to achieve precise control of the motor movement; the SIMULINK simulation model includes an upper limb control model, and the upper limb control model includes an upper limb training speed closed-loop, and the upper limb training speed closed-loop is used to control the passive mode. The present invention can perform rehabilitation training in the active mode, passive mode and active and passive mode. When the transfer condition is met, the automatic conversion between different movement modes is realized through the PID closed-loop feedback control algorithm, and the movement state of the DC motor is flexibly and precisely controlled.

Description

Technical Field

[0001] The present invention relates to a control system for an upper and lower limb active and passive motion rehabilitation machine, belonging to the technical field of control of upper and lower limb active and passive motion rehabilitation machines. Background Art

[0002] As a rehabilitation training device, the upper and lower limb motion rehabilitation machine adopts robot technology, is designed according to ergonomics, combines the theory of rehabilitation medicine, and is a rehabilitation trainer that uses an electric motor to drive a patient to perform circular motion training. It can perform separate training for the upper and lower limbs, and can achieve one-key free switching between the upper and lower limbs according to the needs of the patient. Its training interface is rich, with multiple built-in scenario interaction games. For different patients, the training method can be customized. After the training is completed, a training report is automatically generated, and the training report can be viewed and exported at any time. The purpose of this product is to improve joint range of motion, enhance muscle strength and endurance, improve balance and coordination ability, and improve overall motor function.

[0003] The existing upper and lower limb motion rehabilitation machines can control the operation of the electric motor according to the motion speed and resistance of the preset mode. However, when switching frequently between various motion modes, precise control of the electric motor cannot be achieved in real time; in the conventional training mode (passive mode), the patient is driven by the rehabilitation machine to perform training at a specific speed and resistance. The existing control method of the electric motor cannot achieve the active mode, that is, when the patient's force exceeds the threshold value, the training state cannot be changed, and flexible control of the motion state of the electric motor cannot be achieved.

[0004] In summary, it is obvious that the existing technology has inconveniences and defects in actual use, so it is necessary to improve it. Summary of the Invention

[0005] In view of the deficiencies in the background art, the present invention provides a control system for an upper and lower limb active and passive motion rehabilitation machine, which can perform rehabilitation training in the active mode, passive mode, and active and passive mode. When the transfer condition is met, automatic conversion between different motion modes is achieved through the PID closed-loop feedback control algorithm, and flexible and precise control of the motion state of the DC motor is realized.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions:

[0007] A control system for an upper and lower limb active and passive motion rehabilitation machine includes a main control board. After the main control board collects the speed data of the DC motor, the AD value of the DC motor current sampling, the position data of the DC motor, and the switch state information and performs calculations, the real-time speed and resistance data of the motor are obtained. Using the PID closed-loop feedback control algorithm, a PWM waveform is generated and acts on the motor through the H-bridge drive circuit;

[0008] The SIMULINK is used to simulate the PID closed-loop feedback control algorithm to achieve precise control of the motor movement;

[0009] The SIMULINK simulation model includes an upper limb control model. The upper limb control model includes an upper limb training speed closed-loop, and the upper limb training speed closed-loop is used to control the passive mode. The control process of the upper limb training speed closed-loop includes the following steps:

[0010] Step S1, assign 1 to the speed closed-loop enable terminal V_Enable_Upper and assign 0 to the current closed-loop enable terminal C_Enable_Upper;

[0011] Step S2, perform Operation 1: Multiply the difference between the target speed V_Desired_Upper and the real-time speed Velocity_Upper by the speed loop enable terminal V_Enable_Upper;

[0012] Step S3, perform Operation 2: Multiply the operation result of Operation 1 by the speed proportionality coefficient VP_Upper;

[0013] Step S4, perform Operation 3: Multiply the operation result of Operation 1 by the speed integral coefficient VI_Upper, and then perform discrete integration on the result;

[0014] Step S5, sum the results of Operation 2 and Operation 3, multiply the summed result by the speed closed-loop enable terminal V_Enable_Upper, then pass it through an adder, and after performing limit processing on the operation result, transfer the data to the output terminal PWM_Out_Upper; The output terminal PWM_Out_Upper generates PWM pulses, which act on the upper limb DC motor through the H-bridge drive circuit, making the rotation speed of the upper limb DC motor closer to the target speed;

[0015] Step S6, loop and repeat Steps S2 - S5. Finally, when the difference between the target speed V_Desired_Upper and the real-time speed Velocity_Upper is approximately 0, the loop ends, and the upper limb DC motor runs at the target speed.

[0016] Furthermore, the upper limb control model also includes an upper limb training current closed-loop. The upper limb training current closed-loop is used to control the active mode. The control process of the upper limb training current closed-loop includes the following steps:

[0017] Step T1, assign 1 to the current closed-loop enable terminal C_Enable_Upper and assign 0 to the speed closed-loop enable terminal V_Enable_Upper;

[0018] Step T2, perform Operation 1: Multiply the difference between the target current C_Desired_Upper and the real-time current Current_Upper by the current loop enable terminal C_Enable_Upper;

[0019] Step T3, perform Operation 2: Multiply the operation result of Operation 1 by the current proportionality coefficient CP_Upper;

[0020] Step T4, perform Operation 3: Multiply the operation result of Operation 1 by the current integral coefficient CI_Upper, and then perform discrete integration on the result;

[0021] Step T5, sum the results of Operation 2 and Operation 3, multiply the summed result by the current loop enable terminal C_Enable_Upper, then pass it through an adder, and after performing limit processing on the operation result, transfer the data to the output terminal PWM_Out_Upper. The output terminal PWM_Out_Upper generates a PWM pulse, which acts on the upper limb DC motor through the H-bridge drive circuit, making the current for the motor operation closer to the target current;

[0022] Step T6, loop and repeat Steps T2 - T5. Eventually, when the difference between the target current C_Desired_Upper and the real-time current Current_Upper is approximately 0, the loop ends, and the upper limb DC motor operates according to the target current.

[0023] Furthermore, the SIMULINK simulation model is divided into two parts: the upper limb control model and the lower limb control model, which are respectively used to control upper limb training and lower limb training, and their control methods are the same.

[0024] Furthermore, the main control board receives information such as the speed data of the DC motor, the AD value of the DC motor current sampling, the DC motor position data, and the switch state through a closed-loop circuit. The closed-loop circuit includes an optoelectronic incremental encoder processing circuit, a current detection sensing control circuit, and a motor drive circuit.

[0025] Furthermore, the incremental encoder feeds back the speed data of the DC motor to the main control board through the optoelectronic incremental encoder processing circuit, the H-bridge drive circuit feeds back the AD value of the DC motor current sampling to the main control board through the current detection sensing control circuit, and the Hall sensor feeds back the DC motor position data and the switch state to the main control board through the motor drive circuit.

[0026] Furthermore, the control system also includes a state machine. The state machine detects the real-time speed value, real-time resistance value, and the state input by external variables during the operation of the DC motor, and controls the operation of the DC motor through state variable update and switching, so as to switch the rehabilitation machine between different operation modes.

[0027] Further, the operation modes include an active mode, a passive mode, a main - passive mode, a spasm mode, and a fault mode;

[0028] The state machine compares the currently received motion parameters, i.e., the real - time speed value, the real - time resistance value, and the state input by an external variable, with the currently selected operation mode. When the current motion parameters do not match the currently selected operation mode, it automatically identifies the change in the motion state, automatically terminates the current state, and switches to the next operation mode by updating the state variable.

[0029] Further, in the training mode of the active mode, the DC motor is controlled by current closed - loop control. In the training mode of the passive mode, the DC motor is controlled by speed closed - loop control. In the main - passive mode, when the patient exerts little or no force, the state machine performs passive - mode training according to the current motion parameters. When the force exerted by the patient reaches the set threshold value, the state machine automatically switches to the active mode;

[0030] In the active mode, passive mode, or main - passive mode, the state machine controls the increase and decrease of the DC motor speed and the increase and decrease of the resistance.

[0031] After the present invention adopts the above - mentioned technical solutions, compared with the prior art, it has the following advantages:

[0032] 1. The SIMULINK is used to simulate the PID closed - loop feedback control algorithm. The motor parameters are adjusted in real time through the analysis of the simulation curve, performance testing, and user experience, so as to achieve precise control of the motion of the DC motor. The upper - limb control model is a double - loop simulation model, including an upper - limb training speed closed - loop and an upper - limb training current closed - loop. Among them, the upper - limb training speed closed - loop is used to achieve the passive mode, and the upper - limb training current closed - loop is used to achieve the active mode. In the main - passive mode, the active mode and the passive mode can be automatically switched when the conditions are met.

[0033] 2. The state machine can compare the currently received motion parameters with the currently selected operation mode. When the current motion parameters do not match the currently selected operation mode, it automatically identifies the change in the motion state, automatically terminates the current state, and switches to the next operation mode by updating the state variable. It is more intelligent in application, does not require the operator to stop, is safer and more reliable, and is convenient for training.

[0034] The present invention will be described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 is the functional block diagram of the control system of the present invention;

[0036] Figure 2 is the logical operation diagram of the upper - limb control model in the present invention;

[0037] Figure 3 It is the working flow chart of the state machine in the present invention. Specific embodiments

[0038] For a clearer understanding of the technical features, objectives and effects of the present invention, the specific embodiments of the present invention will now be described with reference to the accompanying drawings.

[0039] The upper and lower limb movement rehabilitation machine consists of an upper limb trainer, an upper limb handle, a lower limb trainer, a foot pedal, a lower limb guide (including a calf bracket), a foot pedal quick locking device, an operation display panel and a control system.

[0040] As Figure 1 shown, the control system of the upper and lower limb movement rehabilitation machine provided by the present invention includes a main control board. The main control board receives information such as the speed data of the DC motor, the AD value of the DC motor current sampling, the position data of the DC motor and the switch state through a closed-loop circuit. The closed-loop circuit includes an optical incremental encoder processing circuit, a current detection sensing control circuit and a motor drive circuit.

[0041] Among them, the incremental encoder feeds back the speed data of the DC motor to the main control board through the optical incremental encoder processing circuit. The H-bridge drive circuit feeds back the AD value of the DC motor current sampling to the main control board through the current detection sensing control circuit. The Hall sensor feeds back the position data and switch state of the DC motor to the main control board through the motor drive circuit.

[0042] After the main control board collects information such as the speed data of the DC motor, the AD value of the DC motor current sampling, the position data of the DC motor and the switch state and performs calculations, it obtains the real-time speed and resistance data of the DC motor. Using the PID closed-loop feedback control algorithm, it generates a PWM waveform, which acts on the DC motor through the H-bridge drive circuit to achieve precise control of the DC motor.

[0043] The present invention uses SIMULINK to simulate the PID closed-loop feedback control algorithm, and adjusts the motor parameters in real time through the analysis of the simulation curve, performance test and user experience to achieve precise control of the motor movement.

[0044] The SIMULINK simulation model is divided into two parts: an upper limb control model and a lower limb control model, which are used to control upper limb training and lower limb training respectively. The control methods of the two are the same. Now, the upper limb control model will be taken as an example for description:

[0045] The upper limb control model is a double-loop simulation model, including an upper limb training speed closed-loop and an upper limb training current closed-loop. Among them, the upper limb training speed closed-loop is used to control the passive mode, and the upper limb training current closed-loop is used to control the active mode. When the rehabilitation machine is working, it will only control the motor operation through one of the upper limb training speed closed-loop or the upper limb training current closed-loop according to the need.

[0046] For example Figure 2 , the control process of the upper limb training speed closed-loop includes the following steps:

[0047] Step S1, assign the speed closed-loop enable terminal V_Enable_Upper to 1 and the current closed-loop enable terminal C_Enable_Upper to 0; make the upper limb control model control the motor only through the upper limb training speed closed-loop to control the passive mode.

[0048] Step S2, perform operation 1: Multiply the difference between the target speed V_Desired_Upper and the real-time speed Velocity_Upper by the speed loop enable terminal V_Enable_Upper.

[0049] Step S3, perform operation 2: Multiply the operation result of operation 1 by the speed proportionality coefficient VP_Upper.

[0050] Step S4, perform operation 3: Multiply the operation result of operation 1 by the speed integral coefficient VI_Upper, and then perform discrete integration on the result.

[0051] Step S5, sum the results of operation 2 and operation 3, multiply the summed result by the speed closed-loop enable terminal V_Enable_Upper, then pass through an adder, and after performing limit processing on the operation result, transfer the data to the output terminal PWM_Out_Upper. The output terminal PWM_Out_Upper generates a PWM pulse, which acts on the upper limb DC motor through the H-bridge drive circuit, making the rotation speed of the motor closer to the target speed and reducing the difference between the target speed V_Desired_Upper and the real-time speed Velocity_Upper.

[0052] Step S6, loop and repeat steps S2 - S5. Finally, when the difference between the target speed V_Desired_Upper and the real-time speed Velocity_Upper is approximately 0, the loop ends, and the upper limb DC motor runs at the target speed.

[0053] The control process of the upper limb training current closed-loop includes the following steps:

[0054] Step T1, assign the current closed-loop enable terminal C_Enable_Upper to 1 and the speed closed-loop enable terminal V_Enable_Upper to 0; enable the upper limb control model to control the motor only through the upper limb training current closed-loop to control the active mode.

[0055] Step T2, perform Operation 1: Multiply the difference between the target current C_Desired_Upper and the real-time current Current_Upper by the current loop enable terminal C_Enable_Upper.

[0056] Step T3, perform Operation 2: Multiply the operation result of Operation 1 by the current proportionality coefficient CP_Upper.

[0057] Step T4, perform Operation 3: Multiply the operation result of Operation 1 by the current integral coefficient CI_Upper, and then perform discrete integration on the result.

[0058] Step T5, sum the results of Operation 2 and Operation 3, multiply the summed result by the current loop enable terminal C_Enable_Upper, then pass through an adder, and after limiting the operation result, transfer the data to the output terminal PWM_Out_Upper. The output terminal PWM_Out_Upper generates PWM pulses, which act on the upper limb DC motor through the H-bridge drive circuit, making the current of the motor operation closer to the target current and reducing the difference between the target current C_Desired_Upper and the real-time current Current_Upper.

[0059] Step T6, loop and repeat Steps T2 - T5. Finally, when the difference between the target current C_Desired_Upper and the real-time current Current_Upper is approximately 0, the loop ends, and the upper limb DC motor operates according to the target current, thereby controlling the upper limb DC motor to output the target resistance.

[0060] The lower limb control model is also a double-loop simulation model. Since the control methods for upper limb training and lower limb training are the same, the control processes of the lower limb training speed closed-loop and the lower limb training current closed-loop are not described herein again.

[0061] As Figure 3 , the control system further includes a state machine. A state machine refers to a strategy defined in the state machine model on how to determine the transition to the next state based on the current state and input. A state machine is a mathematical model used to describe the behavior of an object in different states and the state transition rules.

[0062] The state machine used in the present invention mainly detects the real-time speed value, real-time resistance value and the state of external variable input during the operation of the DC motor, and controls the operation of the DC motor by updating and switching state variables, so as to enable the rehabilitation machine to switch between different operation modes. The operation modes include active mode, passive mode, active-passive mode, spasm mode and fault mode.

[0063] The state machine can compare the currently received motion parameters, i.e., the real-time speed value, real-time resistance value and the state of external variable input, with the currently selected operation mode. When the current motion parameters do not match the currently selected operation mode, it can automatically identify the change in the motion state, automatically terminate the current state, and switch to the next operation mode by updating the state variables. It is more intelligent in application, does not require the operator to stop, is safer and more reliable, and is convenient for training.

[0064] In the training mode of the active mode, the DC motor is controlled by the upper limb (or lower limb) training current closed loop. In the training mode of the passive mode, the DC motor is controlled by the upper limb (or lower limb) training speed closed loop. In the active-passive mode, when the patient exerts little or no force, the state machine performs passive mode training according to the current motion parameters. When the patient's exerted force reaches the set threshold value, the state machine will automatically switch to the active mode. That is to say, in the active-passive mode, the state machine automatically switches between the active mode and the passive mode according to the patient's exerted force. In a certain motion mode, when the conditions are met (i.e., the current motion parameters do not match the currently selected operation mode), the operation mode is automatically switched by the state machine. In addition, in the active mode, passive mode or active-passive mode, the control of speed increase and decrease, and resistance increase and decrease is also achieved through the control of the state machine.

[0065] The above is an example of the best implementation mode of the present invention, and the parts not described in detail are the common general knowledge of those of ordinary skill in the art. The protection scope of the present invention shall be subject to the content of the claims, and any equivalent transformation based on the technical inspiration of the present invention is also within the protection scope of the present invention.

Claims

1. A control system for an upper and lower limb active and passive exercise rehabilitation machine, characterized in that: It includes a main control board, which collects the speed data of the DC motor, the current sampling AD value of the DC motor, the position data of the DC motor and the switch status information, and obtains the real-time speed and resistance data of the motor after calculation, and uses the PID closed-loop feedback control algorithm to generate a PWM waveform, which acts on the motor through an H-bridge drive circuit; SIMULINK is used to simulate the PID closed-loop feedback control algorithm to achieve precise control of the motor motion; The SIMULINK simulation model includes an upper limb control model, which includes an upper limb training speed closed loop. The upper limb training speed closed loop is used to control the passive mode. The control process of the upper limb training speed closed loop includes the following steps: Step S1, assigning a value of 1 to the speed closed-loop enable terminal V_Enable_Upper and a value of 0 to the current closed-loop enable terminal C_Enable_Upper; Step S2, perform operation 1: multiply the difference between the target speed V_Desired_Upper and the real-time speed Velocity_Upper by the speed loop enable terminal V_Enable_Upper; Step S3, executing operation 2: multiplying the result of operation 1 by the speed proportional coefficient VP_Upper; Step S4, perform operation three: multiply the result of operation one by the speed integral coefficient VI_Upper, and then perform discrete integration on the result; Step S5, summing the results of operation 2 and operation 3, multiplying the summed result by the speed closed-loop enable terminal V_Enable_Upper, passing through an adder, and limiting the operation result before transmitting the data to the output terminal PWM_Out_Upper; the output terminal PWM_Out_Upper generates a PWM pulse, which acts on the upper limb DC motor through the H-bridge drive circuit, so that the speed of the upper limb DC motor is further close to the target speed; Step S6, repeating steps S2-S5 in a loop, and finally when the difference between the target speed V_Desired_Upper and the real-time speed Velocity_Upper is approximately 0, the loop ends, and the upper limb DC motor runs at the target speed; The upper limb control model also includes an upper limb training current closed loop, which is used to control the active mode. The control process of the upper limb training current closed loop includes the following steps: Step T1, assigning the current closed-loop enable terminal C_Enable_Upper to 1, and assigning the speed closed-loop enable terminal V_Enable_Upper to 0; Step T2, perform operation 1: multiply the difference between the target current C_Desired_Upper and the real-time current Current_Upper by the current loop enable terminal C_Enable_Upper; Step T3, perform operation 2: multiply the result of operation 1 by the current proportional coefficient CP_Upper; Step T4, perform operation three: multiply the result of operation one by the current integral coefficient CI_Upper, and then perform discrete integration on the result; Step T5, summing the results of operation 2 and operation 3, multiplying the summed result by the current loop enable terminal C_Enable_Upper, passing through an adder, and limiting the operation result, and then transmitting the data to the output terminal PWM_Out_Upper. The output terminal PWM_Out_Upper generates a PWM pulse, which acts on the upper limb DC motor through the H-bridge drive circuit, so that the current of the upper limb DC motor is closer to the target current; Step T6, repeat steps T2-T5 in a loop, and finally when the difference between the target current C_Desired_Upper and the real-time current Current_Upper is approximately 0, the loop ends and the upper limb DC motor runs according to the target current.

2. The control system of the upper and lower limb active and passive motion rehabilitation machine as claimed in claim 1, characterized in that: The SIMULINK simulation model is divided into two parts: upper limb control model and lower limb control model, which are used to control upper limb training and lower limb training respectively. The control methods of the two are the same.

3. The control system of the upper and lower limb active and passive motion rehabilitation machine as claimed in claim 1, characterized in that: The main control board receives the speed data of the DC motor, the DC motor current sampling AD value, the DC motor position data and the switch status information through a closed-loop circuit, and the closed-loop circuit includes a photoelectric incremental encoder processing circuit, a current detection sensor control circuit and a motor drive circuit.

4. The control system of the upper and lower limb active and passive motion rehabilitation machine as claimed in claim 3, characterized in that: The incremental encoder feeds back the speed data of the DC motor to the main control board through the photoelectric incremental encoder processing circuit, the H-bridge drive circuit feeds back the DC motor current sampling AD value to the main control board through the current detection sensor control circuit, and the Hall sensor feeds back the DC motor position data and switch status to the main control board through the motor drive circuit.

5. The control system of the upper and lower limb active and passive motion rehabilitation machine as claimed in claim 1, characterized in that: The control system also includes a state machine, which detects the real-time speed value, real-time resistance value and the state of external variable input fed back during the operation of the DC motor, and controls the operation of the DC motor by updating and switching the state variables, thereby switching the rehabilitation machine between different operating modes.

6. The control system of the upper and lower limb active and passive motion rehabilitation machine as claimed in claim 5, characterized in that: The operation modes include active mode, passive mode, active-passive mode, spastic mode and fault mode; The state machine compares the received current motion parameters, i.e., the real-time speed value, the real-time resistance value, and the state of the external variable input with the currently selected operating mode. When the current motion parameters do not match the currently selected operating mode, the state machine automatically identifies the change in the motion state, automatically terminates the current state, and switches to the next operating mode by updating the state variables.

7. The control system of the upper and lower limb active and passive motion rehabilitation machine as claimed in claim 6, characterized in that: In the active training mode, the DC motor is controlled by a current closed loop. In the passive training mode, the DC motor is controlled by a speed closed loop. In the active and passive modes, when the patient exerts little or no force, the state machine performs passive mode training according to the current motion parameters. When the patient's force reaches the set threshold value, the state machine automatically switches to the active mode. In active mode, passive mode or active-passive mode, the speed increase and decrease and resistance increase and decrease of the DC motor are controlled by the state machine.

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