Control system of upper and lower limb active and passive movement rehabilitation machine

Abstract

The invention discloses a control system of an upper and lower limb active and passive motion rehabilitation machine, which comprises a main control board, the main control board acquires speed data of a direct current motor, a current sampling AD value of the direct current motor, position data of the direct current motor and on-off state information and calculates the speed data, the current sampling AD value, the position data and the on-off state information to obtain real-time speed and resistance data of the motor, and a PID closed-loop feedback control algorithm is utilized to control the real-time speed and resistance data of the motor. A PWM waveform is generated and acts on the motor through an H-bridge driving circuit; sIMULINK is adopted to simulate a PID closed-loop feedback control algorithm, and precise control over motor motion is achieved; the SIMULINK simulation model comprises an upper limb control model, the upper limb control model comprises an upper limb training speed closed loop, and the upper limb training speed closed loop is used for controlling a passive mode. Automatic switching among different motion modes is realized through a PID closed loop feedback control algorithm, and flexible and accurate control of the motion state of the direct current motor is realized.

Description

Technical Field

[0001] The invention relates to a control system of 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 exercise rehabilitation machine adopts robot technology, is designed according to ergonomics, and combines rehabilitation medicine theory. It uses motors to drive patients to perform circular motions. It can perform separate training for upper and lower limbs, and can realize one-button free switching of upper and lower limbs according to patient needs. It has a rich training interface, built-in multiple scenario interactive games, and customized training methods for different patients. After the training, a training report is automatically generated, which can be viewed and exported at any time. The purpose of this product is to improve joint mobility, enhance muscle strength and endurance, improve balance and coordination, and improve overall motor function.

[0003] The upper and lower limb exercise rehabilitation machines in the prior art can control the operation of the motor according to the movement speed and resistance of the preset mode. However, it is impossible to accurately control the motor in real time when frequently switching between various exercise modes; in the conventional training mode (passive mode), the patient is trained at a specific speed and resistance under the drive of the rehabilitation machine. The existing motor control method cannot achieve the passive mode, that is, when the patient's force exceeds the threshold value, the training state cannot be changed, and the movement state of the motor cannot be flexibly controlled.

[0004] In summary, the prior art obviously has inconveniences and defects in practical use, so it is necessary to improve it. Summary of the invention

[0005] In view of the deficiencies in the background technology, 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 active mode, passive mode and active and passive mode. When the transfer conditions are met, automatic conversion between different motion modes is achieved through a PID closed-loop feedback control algorithm, thereby achieving flexible and precise control of the motion state of a DC motor.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions: A control system for an upper and lower limb active and passive motion rehabilitation machine, comprising a main control board, which collects speed data of a DC motor, a DC motor current sampling AD value, a DC motor position data and switch state information, and obtains real-time speed and resistance data of the motor after calculation, and generates a PWM waveform by using a PID closed-loop feedback control algorithm, and 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.

[0007] Furthermore, 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, sum the results of operation 2 and operation 3, multiply the summed result by the current loop enable terminal C_Enable_Upper, pass through an adder, and after the operation result is limited, the data is transmitted to the output terminal PWM_Out_Upper, and 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 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.

[0008] Furthermore, 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, and the control methods of the two are the same.

[0009] Furthermore, the main control board receives information such as speed data of the DC motor, current sampling AD value of the DC motor, position data of the DC motor and switch status 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.

[0010] Furthermore, 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.

[0011] Furthermore, the control system also includes a state machine, which detects the real-time speed value, real-time resistance value and 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.

[0012] Further, 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.

[0013] Furthermore, in the active mode training mode, the DC motor is controlled by a current closed loop, and in the passive mode 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, and 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.

[0014] After adopting the above technical solution, the present invention has the following advantages compared with the prior art: 1. SIMULINK is used to simulate the PID closed-loop feedback control algorithm. The motor parameters are adjusted in real time through simulation curve analysis, performance testing and user experience to achieve precise control of the DC motor movement. The upper limb control model is a dual-loop simulation model, including an upper limb training speed closed loop and an upper limb training current closed loop. 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 active and passive modes, the active mode and the passive mode can be automatically switched when the conditions are met.

[0015] 2. The state machine can compare the received current motion parameters with the currently selected operating mode. When the current motion parameters do not match the currently selected operating mode, it 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. The application is more intelligent, does not require the operator to stop, is safer and more reliable, and is convenient for training.

[0016] The present invention is described in detail below with reference to the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a functional block diagram of the control system of the present invention; Figure 2 It is a logic operation diagram of the upper limb control model in the present invention; Figure 3 It is a working flow chart of the state machine in the present invention. DETAILED DESCRIPTION

[0018] In order to have a clearer understanding of the technical features, purposes and effects of the present invention, specific embodiments of the present invention are now described with reference to the accompanying drawings.

[0019] The upper and lower limb exercise 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 support), a foot pedal quick locking device, an operation display panel and a control system.

[0020] like Figure 1As shown, the control system of the upper and lower limb exercise rehabilitation machine provided by the present invention includes a main control board, which receives information such as 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 through a closed-loop circuit. The closed-loop circuit includes a photoelectric incremental encoder processing circuit, a current detection sensor control circuit and a motor drive circuit.

[0021] Among them, 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.

[0022] The main control board collects the speed data of the DC motor, the current sampling AD value of the DC motor, the position data of the DC motor, the switch status and other information, and after calculation, obtains the real-time speed and resistance data of the DC motor. The PID closed-loop feedback control algorithm is used to generate a PWM waveform, which is applied to the DC motor through the H-bridge drive circuit to achieve precise control of the DC motor.

[0023] The present invention adopts SIMULINK to simulate the PID closed-loop feedback control algorithm, and adjusts the motor parameters in real time through simulation curve analysis, performance testing and user experience to achieve precise control of the motor movement.

[0024] The SIMULINK simulation model is divided into two parts: the upper limb control model and the 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 let's take the upper limb control model as an example to explain: The upper limb control model is a dual-loop simulation model, including an upper limb training speed closed loop and an upper limb training current closed loop. 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 as needed.

[0025] like Figure 2 ,The closed-loop control process of upper limb training speed 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; enabling the upper limb control model to control the passive mode only through the upper limb training speed closed-loop control motor.

[0026] Step S2, performing operation 1: multiplying 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.

[0027] Step S3, executing operation 2: multiplying the operation result of operation 1 by the speed proportional coefficient VP_Upper.

[0028] Step S4, executing operation three: multiplying the result of operation one by the speed integral coefficient VI_Upper, and then performing discrete integration on the result.

[0029] 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, and then pass through an adder, and after the operation result is limited, the data is transmitted 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 motor speed is closer to the target speed, and the difference between the target speed V_Desired_Upper and the real-time speed Velocity_Upper becomes smaller.

[0030] 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.

[0031] 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 the speed closed-loop enable terminal V_Enable_Upper to 0; the upper limb control model controls the active mode only by controlling the motor through the upper limb training current closed-loop.

[0032] Step T2, performing operation 1: multiplying 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.

[0033] Step T3, executing operation 2: multiplying the operation result of operation 1 by the current proportional coefficient CP_Upper.

[0034] Step T4, executing operation three: multiplying the operation result of operation one by the current integral coefficient CI_Upper, and then performing discrete integration on the result.

[0035] Step T5, sum the results of operation 2 and operation 3, multiply the summed result by the current loop enable terminal C_Enable_Upper, and then pass through an adder, and after the operation result is limited, the data is transmitted 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 motor is closer to the target current, and the difference between the target current C_Desired_Upper and the real-time current Current_Upper becomes smaller.

[0036] 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, thereby controlling the upper limb DC motor to output the target resistance.

[0037] The lower limb control model is also a dual-loop simulation model. Since the control methods of upper limb training and lower limb training are the same, the control process of the lower limb training speed closed loop and the lower limb training current closed loop will not be repeated here.

[0038] like Figure 3 The control system also includes a state machine, which refers to a strategy in the state machine model that defines how to decide how to transition to the next state based on the current state and input. The state machine is a mathematical model used to describe the behavior of an object in different states and state transition rules.

[0039] 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 fed back during the operation of the DC motor, and controls the operation of the DC motor by updating and switching the state variables, so that the rehabilitation machine switches between different operation modes. The operation modes include active mode, passive mode, active and passive mode, spasm mode and fault mode.

[0040] The state machine can compare the received current motion parameters, i.e., real-time speed value, real-time resistance value, and the state of 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 motion state, automatically terminates the current state, and switches to the next operating mode by updating the state variables. The application is more intelligent, does not require the operator to stop, is safer and more reliable, and is convenient for training.

[0041] In the active training mode, the DC motor is controlled by the upper limb (or lower limb) training current closed loop. In the passive training mode, the DC motor is controlled by the upper limb (or lower limb) training 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 other words, in the active and passive modes, the state machine automatically switches between the active mode and the passive mode according to the patient's force. In a certain motion mode, when the conditions are met (that is, the current motion parameters do not match the currently selected operating mode), the operating mode is automatically converted through the state machine. In addition, in the active mode, passive mode or active and passive mode, the speed addition and subtraction, and the resistance addition and subtraction control are also realized through the state machine control.

[0042] The above is an example of the best implementation of the present invention, and the parts not described in detail are common knowledge of ordinary technicians in the field. The protection scope of the present invention shall be based on the content of the claims, and any equivalent transformation based on the technical enlightenment 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 motion 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.

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 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.

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 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.

4. 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 information such as the speed data of the DC motor, the DC motor current sampling AD value, the DC motor position data and the switch status through a closed-loop circuit. The closed-loop circuit includes a photoelectric incremental encoder processing circuit, a current detection sensor control circuit and a motor drive circuit.

5. The control system of the upper and lower limb active and passive motion rehabilitation machine as claimed in claim 4, 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.

6. 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.

7. The control system of the upper and lower limb active and passive motion rehabilitation machine as claimed in claim 6, 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.

8. The control system of the upper and lower limb active and passive motion rehabilitation machine as claimed in claim 7, 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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