A RGV speed closed-loop control method and system based on fuzzy PID

Abstract

The present invention relates to a fuzzy PID-based RGV speed closed-loop control method, comprising: generating a driving S-type speed curve, whose horizontal and vertical coordinates are reference time and speed respectively; judging that the RGV actually starts to move according to the detected RGV displacement information, and continuing to the next step; generating a reference S-type speed curve, whose starting point of the horizontal coordinate is the actual start time of the RGV; calculating the error value between the instantaneous speed value on the reference S-type speed curve and the current actual movement speed of the collected RGV; inputting the error value into the function module of the fuzzy PID controller to obtain the output value; adding the output value of the fuzzy PID controller to the corresponding instantaneous speed value of the driving S-type speed curve to obtain the final speed value, and transmitting the final speed value signal to the frequency converter of the driving wheel motor of the RGV after limiting the amplitude. The present invention solves the problem of poor speed closed-loop control effect caused by system output hysteresis.

Description

Technical Field

[0001] The present invention relates to the technical field of RGV speed control, and in particular to a fuzzy PID-based RGV speed closed-loop control system and method. Background Art

[0002] Rail Guide Vehicle (RGV) has the characteristics of fast and stable operation, high reliability and low cost, and has been increasingly widely used in the field of modern automated logistics systems. RGV is an automated rail transportation equipment equipped with non-contact guidance devices such as electromagnetic or optical. The RGV system can be used as a peripheral device of a stereoscopic warehouse or as an independent system. RGV is one of the irreplaceable key equipment because of its large load capacity, safety, reliability and strong environmental adaptability. It is mostly used in fixed routes, heavy-load transfers and industrial production lines with complex environments.

[0003] In order to meet the stability requirements of material transportation equipment in industrial production, improve production efficiency under variable working distances, and increase the service life of transportation equipment, the speed setting of the RGV trolley usually adopts an S-shaped speed curve. However, in the actual working process of the RGV, only relying on the S-shaped speed curve to give the speed value to the inverter for speed control will result in poor resistance to disturbances in the system, making it difficult to meet the accuracy requirements of transportation work, and closed-loop control of the operating speed is required. Directly feedback the actual speed of the RGV through the encoder and input the S-shaped speed curve for traditional PID closed-loop control will not be ideal because the system has pure lag caused by the weight of the vehicle body, signal transmission, etc. Due to the ideal state of PID speed tracking, the real-time speed needs to be compared with the corresponding ideal speed, and the PID output is calculated through the error. However, the lag of the system output signal causes its speed to not correspond to the instant ideal speed provided by the S-shaped speed curve. The difference between the two speed curves caused by the lag becomes the main component of the speed error, rather than the various disturbances that the PID speed closed-loop system originally wanted to reduce and eliminate, which ultimately leads to speed tracking failure, and then leads to a significant error in the final displacement distance of the RGV. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a fuzzy PID-based RGV speed closed-loop control method and system, which solves the problem of poor speed closed-loop control effect caused by system output lag.

[0005] The technical solution adopted by the present invention is as follows:

[0006] A fuzzy PID-based RGV speed closed-loop control method comprises the following steps:

[0007] S1, generating a driving S-shaped speed curve, calculating intermediate parameters of the S-shaped speed curve according to expected operating parameters of the RGV and then generating the curve; the driving S-shaped speed curve uses reference time as the horizontal coordinate and speed value as the vertical coordinate;

[0008] S2, judging whether the RGV actually starts to move according to the detected RGV displacement information, if yes, go to step S3, otherwise continue judging;

[0009] S3, recording the time difference between the starting point of the abscissa of the driving S-shaped speed curve and the actual start of the RGV movement, and generating a reference S-shaped speed curve in the same manner based on the expected operating parameters, wherein the starting point of the abscissa of the reference S-shaped speed curve is the actual start of the RGV movement;

[0010] S4, subtract the instantaneous speed value on the reference S-shaped speed curve from the collected current actual movement speed of the RGV to obtain an error value;

[0011] The error value is input into the function module of the fuzzy PID controller according to the set time period, and the output value of the fuzzy PID controller is obtained as follows:

[0012] Δu x =K p *(e x -e x-1 )+K i *e x +K d *(e x -2*e x-1 +e x-2 )

[0013] Among them, Δu x is the output value of the fuzzy PID controller at time x, K p , K i , K d are the P, I, and D parameters of the fuzzy PID controller, respectively; e represents the input error value; the subscripts x, x-1, and x-2 represent the x moment, x-1 moment, and x-2 moment, respectively; and the difference between adjacent moments is the set time period;

[0014] S5. Add the output value of the fuzzy PID controller to the corresponding instantaneous speed value of the driving S-shaped speed curve to obtain a final speed value, and transmit the final speed value signal to the inverter of the driving wheel motor of the RGV after limiting the amplitude.

[0015] Further technical solutions are:

[0016] In steps S1 and S3, a subroutine preset in the PLC controller of the RGV is used to generate a corresponding S-shaped speed curve. During the generation of the S-shaped speed curve, the internal reference time of the subroutine is calculated by counting the constant interrupt time. The corresponding instantaneous speed value is calculated in the subroutine by the reference time value, and the voltage signal is output to the inverter of the drive wheel motor of the RGV through the analog output port after linear transformation.

[0017] In step S2, judging whether the RGV actually starts to move according to the detected RGV displacement information includes:

[0018] The encoder is used to collect RGV motion data at a constant time difference to obtain the actual movement distance of the RGV. The PLC controller uses the encoder's collection interruption time to calculate the real-time speed. When the RGV displacement and real-time speed are not zero, it is determined to have an actual speed.

[0019] In step S4, the function module first fuzzifies the input error value and the corresponding error value change rate using a membership function, performs fuzzy reasoning through a fuzzy rule table, and performs clarification operations through a centroid method to obtain a specific PID parameter change; then the calculated PID parameter change is added to the PID parameter standard value obtained by pre-adjusting the parameters, and the final PID output change is obtained through an incremental PID calculation formula, and is used as the output value of the fuzzy PID controller.

[0020] The expected operating parameters include expected RGV displacement, initial and final speeds, maximum speed, maximum acceleration, and maximum jerk.

[0021] A fuzzy PID based RGV speed closed-loop control system, comprising:

[0022] A driving S-type speed curve generating module is used to generate a driving S-type speed curve, calculate the intermediate parameters of the S-type speed curve according to the expected operating parameters of the RGV and then generate the curve; the driving S-type speed curve uses the reference time as the horizontal coordinate and the speed value as the vertical coordinate;

[0023] A detection module, which is used to determine whether the RGV actually starts to move according to the detected RGV displacement information, and if so, start the reference S-type speed curve generation module, otherwise continue to make a judgment;

[0024] A reference S-shaped speed curve generating module, which is used to record the time difference from the starting point of the horizontal coordinate of the driving S-shaped speed curve to the actual start of the movement of the RGV, and generate a reference S-shaped speed curve in the same way based on the expected operating parameters again, wherein the starting point of the horizontal coordinate of the reference S-shaped speed curve is the actual start of the movement of the RGV;

[0025] The fuzzy PID controller output value calculation module is used to obtain the error value by subtracting the instantaneous speed value on the reference S-shaped speed curve from the collected current actual movement speed of the RGV; the error value is input into the function module of the fuzzy PID controller according to the set time period, and the output value of the fuzzy PID controller is obtained as follows:

[0026] Δu x =K p *(e x -e x-1 )+K i *e x +K d *(e x -2*e x-1 +e x-2 )

[0027] Among them, Δu x is the output value of the fuzzy PID controller at time x, K p , K i , K d are the P, I, and D parameters of the fuzzy PID controller, respectively; e represents the input error value; the subscripts x, x-1, and x-2 represent the x moment, x-1 moment, and x-2 moment, respectively; and the difference between adjacent moments is the set time period;

[0028] The output module is used to add the output value of the fuzzy PID controller to the corresponding instantaneous speed value of the driving S-shaped speed curve to obtain a final speed value, and transmit the final speed value signal to the inverter of the driving wheel motor of the RGV after limiting the amplitude.

[0029] The beneficial effects of the present invention are as follows:

[0030] The present invention uses a preset S-shaped speed curve to set the driving speed and PID reference speed, and forms a speed closed-loop control of the RGV by feedback of the RGV movement speed through the encoder, which solves the problem of reference speed curve misalignment caused by system output lag and the poor tracking problem caused by it, stabilizes the RGV running speed and thus improves the RGV displacement accuracy. Compared with open-loop control, the displacement error is reduced by 92.9%, realizing speed closed-loop control, greatly improving the movement effect, and meeting the actual production needs.

[0031] The present invention generates a reference speed curve based on the actual movement of the RGV, and does not need to manually re-set the speed curve generation start time due to changes in cargo weight, etc. It provides a relatively stable speed closed-loop control method that can be widely used when the equipment is loaded with different cargoes and is subject to different interferences, ensuring the RGV running speed control accuracy.

[0032] Other features and advantages of the present invention will be set forth in the following description or may be learned by practicing the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 Schematic diagram of the process of the embodiment of the present invention.

[0034] Figure 2 It is a schematic diagram of the structure of RGV according to an embodiment of the present invention.

[0035] Figure 3 This is a control logic diagram of an RGV speed closed-loop control system based on fuzzy PID according to an embodiment of the present invention.

[0036] Figure 4 This is a simulation result diagram of fuzzy PID control using a simulation tool according to an embodiment of the present invention.

[0037] Figure 5 This is a diagram of the actual output of a system using open-loop control during a simulation experiment of an embodiment of the present invention.

[0038] Figure 6 This is a diagram of the actual output of a system using closed-loop control during a simulation experiment of an embodiment of the present invention.

[0039] In the figure: 1. PLC controller; 2. Frequency converter; 3. Encoder; 4. Driving wheel motor. DETAILED DESCRIPTION

[0040] The specific implementation of the present invention is described below with reference to the accompanying drawings.

[0041] A fuzzy PID based RGV speed closed-loop control method of this embodiment is shown in FIG. Figure 2 , the RGV of this embodiment includes an RGV body and a drive control system, and the drive control system includes a PLC controller 1, a drive wheel motor 4, an encoder 3, and a frequency converter 2. The incremental encoder 3 is installed on the drive wheel axle of the RGV body to collect data on the RGV displacement. The encoder 3 is connected to the PLC controller 1 to transmit data to the PLC controller. The PLC controller 1 is connected to the frequency converter 2, and the frequency converter 2 receives the instruction of the PLC controller by receiving the voltage signal output by the analog output module of the PLC controller. The frequency converter 2 is connected to the drive wheel motor 4 (three-phase asynchronous motor) and controls the motor according to the control logic to control the running speed of the RGV. Specifically, the feedback of the speed comes from the encoder 3, which is input through the high-speed pulse counter port of the PLC, and the instantaneous speed is calculated by the returned signal through the formula. The PLC controller 1 uses fuzzy PID to process the error between the reference speed and the actual movement speed to obtain the final speed control value, and outputs a voltage signal to the frequency converter 2 that controls the drive wheel motor 4 through the analog output module, thereby providing a specific speed signal.

[0042] The control method specifically comprises the following steps:

[0043] See also Figure 1 The method of this embodiment specifically includes the following steps:

[0044] S1. Generate a driving S-shaped speed curve. Calculate intermediate parameters of the S-shaped speed curve according to expected operating parameters of the RGV and then generate the curve. The driving S-shaped speed curve uses reference time as the horizontal coordinate and speed value as the vertical coordinate.

[0045] Specifically, a subroutine set in the PLC controller is used to generate a corresponding S-shaped speed curve. During the generation of the S-shaped speed curve, the internal reference time of the subroutine is calculated by counting the constant interrupt time. The corresponding instantaneous speed value is calculated in the subroutine through the reference time value, and the voltage signal is output to the inverter of the RGV drive motor through the analog output port after linear transformation.

[0046] The expected operating parameters include expected RGV displacement, initial and final speeds, maximum speed, maximum acceleration, and maximum jerk.

[0047] S2. According to the detected RGV displacement information, determine whether the RGV actually starts to move. If yes, go to step S3; otherwise, continue to determine.

[0048] Specifically, judging whether the RGV actually starts to move according to the detected RGV displacement information includes:

[0049] The encoder is used to collect RGV motion data at a constant time difference to obtain the actual movement distance of the RGV. The PLC controller uses the collection interruption time of the drive wheel motor encoder to calculate the real-time speed. When the RGV displacement and real-time speed are not zero, it is judged to have actual speed.

[0050] Among them, the PLC program is designed with encoder feedback interruption to continuously return data at a constant time difference.

[0051] S3. Record the time difference from the starting point of the horizontal coordinate of the driving S-shaped speed curve to the actual start of the movement of the RGV, and generate a reference S-shaped speed curve in the same way based on the expected operating parameters again, wherein the starting point of the horizontal coordinate of the reference S-shaped speed curve is the actual start of the movement of the RGV.

[0052] Specifically, the subroutine used by S1 is also called to generate the reference S-type speed curve, and the starting point (time zero) of the reference abscissa of the reference S-type speed curve is changed, and the delay starting from the internal reference time in the driving S-type speed curve subroutine is the time difference between the start time of the driving S-type speed curve and the actual movement of RGV. The reference S-type speed curve is used for reference by fuzzy PID.

[0053] The method for generating the S-shaped speed curve in this embodiment can adopt the solution disclosed in the prior art, which will not be described in detail.

[0054] S4, subtract the instantaneous speed value on the reference S-shaped speed curve from the collected current actual movement speed of the RGV to obtain an error value;

[0055] The error value calculated in real time is input into the function module of the fuzzy PID controller according to the set time period. The function module first fuzzifies the input error value and the corresponding error value change rate using the membership function, performs fuzzy reasoning through the fuzzy rule table, and performs clarification operation through the center of gravity method to obtain the specific PID parameter change; then the calculated PID parameter change is added to the PID parameter standard value obtained by pre-adjustment, and the final PID output change is obtained through the incremental PID calculation formula, and it is used as the output value of the fuzzy PID controller.

[0056] The output value of the fuzzy PID controller is obtained as follows:

[0057] Δu x =K p *(e x -e x-1 )+K i *e x +K d *(e x -2*e x-1 +e x-2 )

[0058] Among them, Δu x is the output value of the fuzzy PID controller at time x, K p , K i , K d are the P, I, and D parameters of the fuzzy PID controller respectively, e represents the input error value, the subscripts x, x-1, and x-2 represent the x moment, x-1 moment, and x-2 moment respectively, and the difference between adjacent moments is the set time period.

[0059] Specifically, the instantaneous speed of the reference S-shaped speed curve and the actual movement speed of the RGV fed back by the encoder are calculated through a subtraction calculation instruction to obtain an error value and save it as a real number.

[0060] Specifically, the PLC is set with a loop interrupt for fuzzy PID, and the error value is input into the fuzzy PID function block for subsequent calculation according to a fixed time. The membership function and fuzzy control rule table required for fuzzy PID are pre-designed in the PLC.

[0061] S5, add the output value of the fuzzy PID controller to the instantaneous speed value corresponding to the driving S-shaped speed curve to obtain the final speed value, limit the final speed value signal and transmit it to the inverter of the RGV drive motor, and control the three-phase asynchronous motor through the inverter. See the control system structure Figure 3 . Figure 3 In the example, the given speed is the instantaneous speed value corresponding to the S-shaped speed curve.

[0062] The following is an experimental example in which a simulation is performed according to the method of this embodiment to verify the effectiveness of this embodiment.

[0063] Simulation experiment:

[0064] Use Simulink to build a simulation system based on fuzzy PID control; according to the actual situation, set a sine signal with an amplitude of 0.8 and a frequency of 1 radian per second as the simulation speed input; the basic values ​​of the three parameters P, I, and D are set to 12, 5, and -5, and the delay time is 0.2 seconds. The system has a random disturbance with a mean of 0 and a variance of 0.015. The simulation results are as follows Figure 4 As shown. The green line in the figure represents the difference between the reference S-shaped speed curve and the actual output speed of the system, the orange line represents the driving S-shaped speed curve, the yellow line represents the actual output speed of the system, and the blue line represents the reference S-shaped speed curve whose start time is determined according to the system delay, which has made a delayed translation compared to the driving reference curve. It can be seen that the system output speed can track the speed curve well under this method, and the overall speed consistency is high and smooth. The improvement of speed control directly ensures that the operation displacement of RGV meets the needs of actual industrial production.

[0065] Figure 5 and Figure 6 The speed and displacement curves obtained in the actual experiment are obtained by using PLC Recorder software to collect data in the PLC in real time. The preset RGV travel distance is 6.00 meters. Figure 5 When the closed-loop system of this embodiment is not used for open-loop control, the final displacement is 6.14 meters, with an error of 0.14 meters, indicating that the RGV cannot move strictly according to the set S-shaped speed curve during driving. Figure 6When the speed closed-loop system of this embodiment is used for control, the final travel distance is 5.99 meters, with an error of 0.01 meters, and the displacement error is reduced by 92.9%. This shows that the speed closed-loop control system of this embodiment enables the RGV to move according to the preset S-shaped speed curve during long-term operation, improves the speed control effect and ultimately affects the running displacement of the RGV, meets the needs of actual industrial production, and solves the problem of difficulty in speed closed-loop control caused by system delay.

[0066] This embodiment also provides a fuzzy PID-based RGV speed closed-loop control system, including:

[0067] A driving S-type speed curve generating module is used to generate a driving S-type speed curve, calculate the intermediate parameters of the S-type speed curve according to the expected operating parameters of the RGV and then generate the curve; the driving S-type speed curve uses the reference time as the horizontal coordinate and the speed value as the vertical coordinate;

[0068] A detection module, which is used to determine whether the RGV actually starts to move according to the detected RGV displacement information, and if so, start the reference S-type speed curve generation module, otherwise continue to make a judgment;

[0069] A reference S-shaped speed curve generating module, which is used to record the time difference from the starting point of the horizontal coordinate of the driving S-shaped speed curve to the actual start of the movement of the RGV, and generate a reference S-shaped speed curve in the same way based on the expected operating parameters again, wherein the starting point of the horizontal coordinate of the reference S-shaped speed curve is the actual start of the movement of the RGV;

[0070] The fuzzy PID controller output value calculation module is used to obtain the error value by subtracting the instantaneous speed value on the reference S-shaped speed curve from the collected current actual movement speed of the RGV; the error value calculated in real time is input into the function module of the fuzzy PID controller according to the set time period, and the output value of the fuzzy PID controller is obtained as follows:

[0071] Δu x =K p *(e x -e x-1 )+K i *e x +K d *(e x -2*e x-1 +e x-2 )

[0072] Among them, Δu x is the output value of the fuzzy PID controller at time x, K p , K i , K dare the P, I, and D parameters of the fuzzy PID controller, respectively; e represents the input error value; the subscripts x, x-1, and x-2 represent the x moment, x-1 moment, and x-2 moment, respectively; and the difference between adjacent moments is the set time period;

[0073] The output module is used to add the output value of the fuzzy PID controller to the corresponding instantaneous speed value of the driving S-shaped speed curve to obtain a final speed value, and transmit the final speed value signal to the frequency converter of the RGV drive motor after limiting the amplitude.

[0074] Those skilled in the art can understand that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention is described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions recorded in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A fuzzy PID based RGV speed closed-loop control method, characterized in that: The following steps are involved: S1, generating a driving S-shaped speed curve, calculating intermediate parameters of the S-shaped speed curve according to expected operating parameters of the RGV and then generating the curve; the driving S-shaped speed curve uses reference time as the horizontal coordinate and speed value as the vertical coordinate; S2, judging whether the RGV actually starts to move according to the detected RGV displacement information, if yes, go to step S3, otherwise continue judging; S3, recording the time difference between the starting point of the abscissa of the driving S-shaped speed curve and the actual start of the RGV movement, and generating a reference S-shaped speed curve in the same manner based on the expected operating parameters, wherein the starting point of the abscissa of the reference S-shaped speed curve is the actual start of the RGV movement; S4, subtract the instantaneous speed value on the reference S-shaped speed curve from the collected current actual movement speed of the RGV to obtain an error value; The error value is input into the function module of the fuzzy PID controller according to the set time period, and the output value of the fuzzy PID controller is obtained as follows: Δu x =K p *(and x -and x-1 )+K i *and x +K d *(and x -2*e x-1 +and x-2 ) Among them, Δu x is the output value of the fuzzy PID controller at time x, K p , K i , K d are the P, I, and D parameters of the fuzzy PID controller, respectively; e represents the input error value; the subscripts x, x-1, and x-2 represent the x moment, x-1 moment, and x-2 moment, respectively; and the difference between adjacent moments is the set time period; S5. Add the output value of the fuzzy PID controller to the corresponding instantaneous speed value of the driving S-shaped speed curve to obtain a final speed value, and transmit the final speed value signal to the inverter of the driving wheel motor of the RGV after limiting the amplitude.

2. The fuzzy PID based RGV speed closed-loop control method according to claim 1 is characterized in that: In steps S1 and S3, a subroutine preset in the PLC controller of the RGV is used to generate a corresponding S-shaped speed curve. During the generation of the S-shaped speed curve, the internal reference time of the subroutine is calculated by counting the constant interrupt time. The corresponding instantaneous speed value is calculated in the subroutine by the reference time value, and the voltage signal is output to the inverter of the drive wheel motor of the RGV through the analog output port after linear transformation.

3. The fuzzy PID based RGV speed closed-loop control method according to claim 2 is characterized in that: In step S2, judging whether the RGV actually starts to move according to the detected RGV displacement information includes: The encoder is used to collect RGV motion data at a constant time difference to obtain the actual movement distance of the RGV. The PLC controller uses the encoder's acquisition interrupt time to calculate the real-time speed. When the RGV displacement and real-time speed are not zero, it is judged to have actual speed.

4. The fuzzy PID based RGV speed closed-loop control method according to claim 1 is characterized in that: In step S4, the function module first fuzzifies the input error value and the corresponding error value change rate using a membership function, performs fuzzy reasoning through a fuzzy rule table, and performs clarification operations through a centroid method to obtain a specific PID parameter change; then the calculated PID parameter change is added to the PID parameter standard value obtained by pre-adjusting the parameters, and the final PID output change is obtained through an incremental PID calculation formula, and is used as the output value of the fuzzy PID controller.

5. The fuzzy PID based RGV speed closed-loop control method according to claim 1 is characterized in that: The expected operating parameters include expected RGV displacement, initial and final speeds, maximum speed, maximum acceleration, and maximum jerk.

6. A fuzzy PID based RGV speed closed loop control system, characterized in that: include: A driving S-type speed curve generating module is used to generate a driving S-type speed curve, calculate the intermediate parameters of the S-type speed curve according to the expected operating parameters of the RGV and then generate the curve; the driving S-type speed curve uses the reference time as the horizontal coordinate and the speed value as the vertical coordinate; A detection module, which is used to determine whether the RGV actually starts to move according to the detected RGV displacement information, and if so, start the reference S-type speed curve generation module, otherwise continue to make a judgment; A reference S-shaped speed curve generating module, which is used to record the time difference from the starting point of the horizontal coordinate of the driving S-shaped speed curve to the actual start of the movement of the RGV, and generate a reference S-shaped speed curve in the same way based on the expected operating parameters again, wherein the starting point of the horizontal coordinate of the reference S-shaped speed curve is the actual start of the movement of the RGV; The fuzzy PID controller output value calculation module is used to obtain the error value by subtracting the instantaneous speed value on the reference S-shaped speed curve from the collected current actual movement speed of the RGV; the error value is input into the function module of the fuzzy PID controller according to the set time period, and the output value of the fuzzy PID controller is obtained as follows: Δu x =K p *(and x -and x-1 )+K i *and x +K d *(and x -2*e x-1 +and x-2 ) Among them, Δu x is the output value of the fuzzy PID controller at time x, K p , K i , K d are the P, I, and D parameters of the fuzzy PID controller, respectively; e represents the input error value; the subscripts x, x-1, and x-2 represent the x moment, x-1 moment, and x-2 moment, respectively; and the difference between adjacent moments is the set time period; The output module is used to add the output value of the fuzzy PID controller to the corresponding instantaneous speed value of the driving S-shaped speed curve to obtain a final speed value, and transmit the final speed value signal to the inverter of the driving wheel motor of the RGV after limiting the amplitude.

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