Electric elevator control system and control method for cabinet

Abstract

The invention belongs to the technical field of cabinets, and particularly relates to an electric lifter control system and method for a cabinet, and the system comprises a control panel, a lifting mechanism, a lifting motor, a load sensor, an encoder, a limiting sensor and a controller with a built-in fuzzy PI D module. The system comprises a control panel, a lifting mechanism, a motor, a load sensor, an encoder, a limiting sensor and a controller with a built-in fuzzy PI D module. Load, speed and limiting signals are collected in real time, a controller generates a closed-loop control signal containing a fuzzy PI D speed regulation instruction and a limiting stop instruction, and the motor power is dynamically regulated. The method is characterized in that the fuzzy PI D algorithm is adopted to optimize PI D parameters in real time, high-precision speed regulation (the position error is smaller than or equal to 0.5 mm, and the speed fluctuation is smaller than 3%) and rapid overload protection are achieved, the position memory and load self-adaption functions are achieved, the problem of unstable operation caused by load change is effectively solved, and safety and control precision are remarkably improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of cabinets, and particularly relates to a cabinet electric lift control system and a control method. BACKGROUND

[0002] With the increasing demand for space utilization and convenience of modern home kitchens, the combination design of cabinets and electric lifts is increasingly popular, which is used for driving a lifting basket, a storage rack or an electric appliance in a hanging cabinet, a corner cabinet or a high cabinet to realize easy access to articles and improve use convenience and comfort. The existing cabinet electric lift control system is usually composed of a direct current or alternating current motor, a transmission mechanism (a screw rod, a rack, a chain, etc.), a lifting actuator, a basic microcontroller (MCU), a physical button or a simple touch screen control panel and possible mechanical or simple electronic limit switches. After a user sends an ascending / descending instruction through the panel, the controller outputs a preset fixed duty ratio PWM signal to drive the motor until a stop signal is received or a physical limit switch is triggered to stop; speed control depends on a fixed voltage / PWM setting value, and position control is realized by simple stop through preset encoder counting points or time control.

[0003] However, this simple structure and extensive control technical solution has significant defects, and the core problem lies in the lack of real-time perception and dynamic response capability to load changes. The system is generally not equipped with an effective load sensor, and the controller cannot know the actual weight of the articles on the lifting mechanism and its changes, and can only rely on preset fixed control parameters (such as fixed PWM parameters) to run. This leads to: 1) unstable operation: excessive driving force when empty / under load, causing start / stop impact, overshoot, oscillation and noise; insufficient driving force when heavy load / rapid load change, resulting in speed drop, start difficulty and even "slip" sliding, and the severe shaking caused by rapid load change seriously affects user experience and mechanical life. 2) weak safety mechanism: overload protection mainly depends on slow-responding (hundreds of milliseconds) circuit overcurrent protection or mechanical strength, which cannot effectively intervene before the motor is blocked or the structure is damaged.

[0004] In summary, the existing cabinet lifting control system cannot effectively perceive and adapt to load changes, resulting in unstable operation. SUMMARY

[0005] The first application purpose of the application is to solve the problem of instability of the cabinet electric lift control system, and provide a cabinet electric lift control system.

[0006] To achieve the above application purposes, the application adopts the following technical solutions:

[0007] A control system for an electric lift for a kitchen cabinet includes a control panel, a lifting mechanism, a lifting motor, a load sensor, an encoder, and a controller. The control panel generates and sends user input commands; the lifting mechanism enables the cabinet to lift; the lifting motor drives the lifting mechanism; the load sensor generates a load signal based on load changes; the encoder generates a speed signal based on changes in the position and speed of the lifting mechanism; a limit sensor monitors positioning information and generates a limit signal; the controller includes a fuzzy PID module; the controller's signal input is connected to the control panel, load sensor, and encoder, and its signal output is connected to the lifting motor. It receives signals and generates control commands based on these signals to control the system's operation. The control commands include initial control commands and closed-loop control commands. The closed-loop control commands include speed adjustment commands, which are dynamically generated by the fuzzy PID module based on the received load and speed signals. The controller controls the lifting motor's power through the closed-loop control commands, thereby adjusting the lifting speed of the lifting mechanism.

[0008] This invention solves the technical problem of unstable operation caused by the inability to dynamically adjust the existing cabinet lifting system when the load changes, through the coordinated work of the fuzzy PID control module, load sensor, and encoder. The system monitors the motor current in real time and converts it into a load signal. The speed signal is obtained through the encoder, and the controller calculates the speed in real time through differential operation of the speed signal. The fuzzy PID module dynamically adjusts the PID parameters (Kp, Ki, Kd) according to the load error and speed error to achieve precise control of the lifting speed. When an overload or limit signal is detected, the controller immediately issues an emergency stop command. This solution achieves three major technical effects: (1) Improved safety, with an overload response time of <50ms, and dual protection with the limit sensor; (2) Improved control accuracy, with a position error of ≤0.5mm and speed fluctuation of <3%; (3) Enhanced intelligence, with adaptive load capability, and automatic maintenance of stable operation when the load changes.

[0009] Furthermore, the user input commands include commands to ascend, descend, stop, and remember a position. This invention provides a position memory function, allowing users to easily select the lowest suitable position for the electric lift during installation or adjustment, thus enabling more comfortable use of the electric lift.

[0010] Furthermore, the control panel is equipped with at least one of a touch control unit, a voice control unit, and a wireless communication unit.

[0011] Furthermore, limit sensors are used to monitor positioning information and generate limit signals. The lifting mechanism has an upper limit position and a lower limit position. The limit sensors are photoelectric sensors, two of which correspond to the upper limit position and the lower limit position, respectively. This solution monitors the lifting mechanism reaching its highest and lowest positions through limit sensor signals, forming a dual protection mechanism with software limit (encoder position judgment) to prevent single-point failure from causing malfunctions.

[0012] Furthermore, the lifting motor is a permanent magnet DC geared motor with a maximum output torque of 10 N·m, and the load sensor is a current sensor installed on the lifting motor.

[0013] Another objective of this invention is to provide a control method for an electric lift for cabinets, based on the electric lift control system for cabinets according to claims 1-5, and comprising the following steps: a control panel generates and sends user input commands; a controller generates control commands based on the user input commands, wherein the control commands are original control commands; the control system performs any action of rising, falling, stopping, or position memorization under the control of the original control commands; a load sensor and an encoder generate load signals and speed signals in real time; the controller dynamically generates PID dynamic parameters through the load signals and speed signals, and generates speed adjustment commands based on the PID dynamic parameters; the system adjusts the operating speed of the lifting mechanism under the control of the speed adjustment commands; a limit sensor monitors whether the lifting mechanism has risen / fallen to the correct position and generates limit signals; the controller generates stop commands based on the limit signals.

[0014] The control method for an electric lift mechanism for kitchen cabinets provided by this invention has the following technical advantages: It monitors load, position, and speed signals in real time using load sensors and encoders, and dynamically adjusts PID parameters using a fuzzy PID control algorithm, enabling the system to adapt to load changes and maintain stable operation of the lifting mechanism, effectively preventing jitter or loss of control caused by sudden load changes; it employs closed-loop control to achieve high-precision speed regulation, allowing the operating speed to quickly converge to the set value, while achieving ±1mm-level precise positioning through position memory; the system is equipped with multiple safety protection mechanisms, including electronic limit protection and overload protection, immediately stopping operation when extreme positions or overloads are detected, ensuring safe use; it supports multiple control methods such as touch, voice, and remote control, offering flexible and convenient operation; and it reduces energy consumption and operating noise through optimized control algorithms, achieving energy-saving and quiet operation. This invention significantly improves the control accuracy, safety, and user experience of kitchen cabinet lifting systems.

[0015] Furthermore, the system presets load setpoints and speed setpoints, and initial PID parameter values ​​K (Kp0, Ki0, Kd). The fuzzy control module includes a fuzzy controller and a PID controller. The module's output of PID dynamic parameters includes the following steps: the fuzzy controller receives the load signal from the load sensor and the speed signal from the encoder in real time, and converts them into real-time load values ​​and real-time speed values; the load error value is obtained by comparing the load setpoints and the real-time load values, using the formula e2 = M. set -M actual The load error change rate is obtained by comparing the load setpoint with the real-time load value, and the formula is e. 2c =de2 / dt; The speed error value is obtained by comparing the speed setpoint with the real-time speed value, and the formula is e = V set -V actual The rate of change of speed error is obtained by comparing the speed setpoint with the real-time speed value, and the formula is e. c =de / dt; change e, e 2c , e, e c As input variables, the fuzzy algorithm is used to obtain the dynamic adjustment amount ΔK of the PID parameters; the dynamic parameters of the PID are calculated by using the dynamic adjustment amount ΔK and the initial PID parameter value K0, and the formula is K=ΔK+K0.

[0016] Furthermore, the lifting motor is connected to the lifting mechanism via a transmission mechanism, and the motor torque constant is set to Kt, and the system friction torque is τ. fric The gravitational acceleration is g, and the equivalent radius of the transmission mechanism is r; the load signal is a current signal, and the controller obtains the real-time current value I of the drive motor through the current signal, and obtains the real-time load value based on the current data, using the formula:

[0017] Furthermore, the speed signal is a pulse signal, the change in the number of encoder pulses per unit time is set as ΔPPR, the sampling time interval is Δt, the pulse-to-displacement conversion coefficient is CPM, and the cumulative number of pulses during the running time is ∑ i PPR i The resolution is PPR a The system, with a lead of P, implements position memory through the following steps: receiving a position memory command, acquiring the velocity signal of the current position, and calculating the real-time velocity value using the velocity signal, as shown in the formula. The position value is calculated using real-time velocity, resolution, and cumulative pulse count, using the following formula:

[0018] Furthermore, the speed control command is a PWM signal, and the step of the controller generating the speed control command based on the PID parameters includes: the PID controller receiving the PID dynamic parameters generated by the fuzzy controller; calculating the PWM duty cycle based on the PID parameters and outputting the PWM signal. Attached Figure Description

[0019] Figure 1 This is the principle of the invention. Figure 1 ;

[0020] Figure 2 This is a system block diagram of the present invention;

[0021] Figure 3 This is the principle of the invention. Figure 2 ;

[0022] Figure 4 This is a flowchart of the present invention; Detailed Implementation

[0023] The technical solution of the present invention will be further described below with reference to the accompanying drawings:

[0024] Example 1:

[0025] A control system for an electric lift for a kitchen cabinet includes a control panel, a lifting mechanism, a lifting motor, a load sensor, an encoder, a limit sensor, and a controller. The control panel generates and sends user input commands; the lifting mechanism enables the cabinet to lift; the lifting motor drives the lifting mechanism; the load sensor generates a load signal based on load changes; and generates a speed signal based on changes in the position and speed of the lifting mechanism. The limit sensor monitors positioning information and generates limit signals. The controller includes a fuzzy PID module. The controller's signal input terminal is connected to the control panel, load sensor, encoder, and limit sensor, and its signal output terminal is connected to the lifting motor. It receives signals and generates control commands based on these signals to control the system. The control commands include initial control commands and closed-loop control commands. The closed-loop control commands include speed adjustment commands and stop commands. The speed adjustment commands are dynamically generated by the fuzzy PID module based on the received load and speed signals, and the stop commands are generated based on the limit signals.

[0026] This invention solves the technical problem of unstable operation caused by the inability to dynamically adjust the existing cabinet lifting system when the load changes, through the coordinated work of the fuzzy PID control module, load sensor, encoder, and limit sensor. The system monitors the motor current in real time and converts it into a load signal. The speed signal is obtained through the encoder, and the controller calculates the speed in real time through differential operation of the speed signal. The fuzzy PID module dynamically adjusts the PID parameters (Kp, Ki, Kd) according to the load error and speed error to achieve precise control of the lifting speed. When an overload or limit signal is detected, the controller immediately issues an emergency stop command. This solution achieves three major technical effects: (1) Improved safety, with an overload response time of <50ms and dual protection with the limit sensor; (2) Improved control accuracy, with a position error of ≤0.5mm and speed fluctuation of <3%; (3) Enhanced intelligence, with position memory function and adaptive load capability, automatically maintaining stable operation when the load changes.

[0027] Furthermore, the user input commands include commands to go up, go down, stop, and remember the position.

[0028] Furthermore, the control panel is equipped with at least one of a touch control unit, a voice control unit, and a wireless communication unit.

[0029] Furthermore, the lifting mechanism has an upward limit position and a downward limit position, and the limit sensor is a photoelectric sensor, of which two are provided, each corresponding to the upward limit position and the downward limit position respectively.

[0030] Furthermore, the lifting motor is a permanent magnet DC geared motor with a maximum output torque of 10 N·m, and the load sensor is a current sensor installed on the lifting motor.

[0031] Example 2:

[0032] This invention discloses a control method for an electric lift for kitchen cabinets, based on the electric lift control system for kitchen cabinets according to claims 1-5, and includes the following steps: a control panel generates and sends user input commands; a controller generates control commands based on the user input commands, the control commands being original control commands; the control system performs any action such as rising, falling, stopping, or position memorization under the control of the original control commands; a load sensor and an encoder generate load signals and speed signals in real time; the controller dynamically generates PID dynamic parameters based on the load signals and speed signals, and generates speed adjustment commands based on the PID dynamic parameters; the system adjusts the operating speed of the lifting mechanism under the control of the speed adjustment commands; a limit sensor monitors whether the lifting mechanism has risen / fallen to the correct position and generates limit signals; the controller generates stop commands based on the limit signals.

[0033] The aforementioned module controller includes a fuzzy control database, which stores experimentally optimized fuzzy rules (IF-THEN rules). These fuzzy rules are used to describe the logical relationship between input variables (such as error and error rate of change) and output variables (PID parameter increments ΔKp, ΔKi, and ΔKd).

[0034] Furthermore, the system presets load setpoints and speed setpoints, and initial PID parameter values ​​K (Kp0, Ki0, Kd). The fuzzy control module includes a fuzzy controller and a PID controller. The module's output of PID dynamic parameters includes the following steps: the fuzzy controller receives the load signal from the load sensor and the speed signal from the encoder in real time, and converts them into real-time load values ​​and real-time speed values; the load error value is obtained by comparing the load setpoints and the real-time load values, using the formula e2 = M. set -M actual The load error change rate is obtained by comparing the load setpoint with the real-time load value, and the formula is e. 2c =de2 / dt; The speed error value is obtained by comparing the speed setpoint with the real-time speed value, and the formula is e = V set -V actual The rate of change of speed error is obtained by comparing the speed setpoint with the real-time speed value, and the formula is e. 2v =de / dt; change e2, e 2c , e, e c As the output variable, it is substituted into the fuzzy algorithm to obtain the dynamic adjustment amount ΔK; the dynamic parameters of the PID are calculated by using the dynamic adjustment amount ΔK and the initial PID parameter value K0, and the formula is K=ΔK+K0.

[0035] via e2, e 2c , e, e c The specific steps to obtain the dynamic adjustment amount ΔK include:

[0036] The system has a predefined set of linguistic variables. The values ​​of load error, load error change rate, speed error, and speed error change rate are converted into specific linguistic variables on the fuzzy domain through quantization and membership functions, respectively, thereby obtaining a combination of linguistic variables of four different linguistic variables. The combination of linguistic variables is input into the fuzzy database, and the adjustment amount of PID parameters is generated according to the rules of the fuzzy database.

[0037] More specifically, the system performs the following operations on the load error value, load error change rate, speed error value, and speed error change rate using a predefined set of language variables:

[0038] (1) Quantization mapping: scaling the values ​​of each parameter to a unified fuzzy domain (e.g., [-6,6]);

[0039] For example: Map the real-time load value e2 and the real-time speed value e to the universe of discourse [-6, 6], where the universe of discourse mapping value for e2 is x_M and the universe of discourse mapping value for the real-time speed value e is x_V.

[0040] x_M = (e^2 / 15) × 12 - 6,

[0041] x_v = (e / 120) × 12 - 6;

[0042] (2) Fuzzification: The membership degree of each parameter value to all linguistic variables is calculated through the membership function, generating four membership degree distribution sets. For example, the membership function is used to convert the linguistic variables into {NB, Nm, NS, ZO, PS, PM, PB}, that is, {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}, to obtain combinations of linguistic variables such as {positive small, negative large, positive medium, positive small} (i.e., membership degree distribution sets). For example, if x_M is 0 and x_v is 1.5, then the linguistic variable of the real-time load value e2 is positive medium, and the linguistic variable of the real-time speed value e is positive small.

[0043] (3) Rule triggering: Input the membership distribution set into the fuzzy rule base, match the combination of linguistic variables specified in the IF part of each rule (such as e_M is PM AND e_{Mc} is NS...), and calculate the rule triggering strength;

[0044] (4) Generate adjustment amount: Based on the trigger strength, the PID parameter adjustment amount, ΔK (including ΔKp, ΔKi, ΔKd), is weighted and synthesized.

[0045] Furthermore, the lifting motor is connected to the lifting mechanism via a transmission mechanism, and the motor torque constant is set to Kt, and the system friction torque is τ. fric The gravitational acceleration is g, and the equivalent radius of the transmission mechanism is r; the load signal is a current signal, and the controller obtains the real-time current value I of the drive motor through the current signal, and obtains the real-time load value based on the current data, using the formula:

[0046] Furthermore, the speed signal is a pulse signal, the change in the number of encoder pulses per unit time is set as ΔPPR, the sampling time interval is Δt, the pulse-to-displacement conversion coefficient is CPM, and the cumulative number of pulses during the running time is ∑ i PPR i The resolution is PPR a The system, with a lead of P, implements position memory through the following steps: receiving a position memory command, acquiring the velocity signal of the current position, and calculating the real-time velocity value using the velocity signal, as shown in the formula. The position value is calculated using real-time velocity, resolution, and cumulative pulse count, using the following formula:

[0047] The fuzzy controller processes the signal according to the following steps:

[0048] b) Convert the variables into linguistic variables {NB, Nm, NS, ZO, PS, PM, PB} through membership functions, i.e., {negative large, negative medium, negative small, zero, positive small, positive medium, positive large}.

[0049] c) Output the PID parameter increments ΔKp, ΔKi, and ΔKd based on the fuzzy rule database.

[0050] Furthermore, the membership functions of the linguistic variables are trigonal, where the membership function of ZO ranges from [-1, 1], and the membership function of PB ranges from [-6, 6].

[0051] Furthermore, the fuzzy rule database contains at least one of the following rules: IF x_M is PM AND x_Vis NS THENΔKp is PS,ΔKi is NB,ΔKd is ZO.

[0052] It should be noted that the initial PID parameter value KO is obtained through multiple iterations to approximate the optimal kp, ki, and kd values ​​under the current conditions. It is generally set based on the unloaded state of the elevator. This set of values ​​is adjusted during the testing process, and the final initial PID parameter value KO used is obtained through testing. The initial value will be recorded after actual operation and generally remains unchanged. It is updated when the electric elevator is working, but it will revert to the original initial value after the electric elevator stops. It will only change if manually modified.

[0053] Furthermore, the speed control command is a PWM signal, and the step of the controller generating the speed control command based on the PID parameters includes: the PID controller receiving the PID dynamic parameters generated by the fuzzy controller; calculating the PWM duty cycle based on the PID parameters and outputting the PWM signal.

[0054] The control method for an electric lift mechanism for kitchen cabinets provided by this invention has the following technical advantages: It monitors load, position, and speed signals in real time using load sensors and encoders, and dynamically adjusts PID parameters using a fuzzy PID control algorithm, enabling the system to adapt to load changes and maintain stable operation of the lifting mechanism, effectively preventing jitter or loss of control caused by sudden load changes; it employs closed-loop control to achieve high-precision speed regulation, allowing the operating speed to quickly converge to the set value, while achieving ±1mm-level precise positioning through position memory; the system is equipped with multiple safety protection mechanisms, including electronic limit protection and overload protection, immediately stopping operation when extreme positions or overloads are detected, ensuring safe use; it supports multiple control methods such as touch, voice, and remote control, offering flexible and convenient operation; and it reduces energy consumption and operating noise through optimized control algorithms, achieving energy-saving and quiet operation. This invention significantly improves the control accuracy, safety, and user experience of kitchen cabinet lifting systems.

[0055] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. Based on the disclosure and teachings of the above specification, those skilled in the art can make changes and modifications to the above embodiments. Therefore, this invention is not limited to the specific embodiments disclosed and described above, and some modifications and changes to this invention should also fall within the protection scope of the claims of this invention. Furthermore, although some specific terms are used in this specification, these terms are only for convenience of explanation and do not constitute any limitation on this invention.

Claims

1. A control system for an electric lift for a cabinet, characterized in that, include: Control panel, used to generate and send user input commands; The lifting mechanism is used to enable the cabinet to be lifted or lowered. A lifting motor is used to drive the lifting mechanism; The load sensor generates a load signal based on changes in load. The encoder generates speed signals based on changes in the position and speed of the lifting mechanism. The controller has a built-in fuzzy PID module. The signal input terminal of the controller is connected to the control panel, load sensor, and encoder, and the signal output terminal is connected to the lifting motor. It receives signals and generates control commands based on the received signals to control the operation of the system. The control commands include original control commands and closed-loop control commands. The closed-loop control commands include speed adjustment commands. The speed adjustment commands are dynamically generated by the fuzzy PID module based on the received load and speed signals. The controller controls the working power of the lifting motor through the closed-loop control commands.

2. The control system according to claim 1, characterized in that, The user input commands include commands to go up, go down, stop, and remember the position.

3. The control system according to claim 1, characterized in that: The control panel is equipped with at least one of the following: a touch control unit, a voice control unit, and a wireless communication unit.

4. The control system according to claim 1, which is mounted on a cabinet, further includes a limit sensor for monitoring positioning information and generating a limit signal; The lifting mechanism has an upward limit position and a downward limit position. The limit sensor is a photoelectric sensor, which has two sensors, and they correspond to the upward limit position and the downward limit position respectively.

5. The control system according to claim 4, characterized in that: The lifting motor is a permanent magnet DC geared motor with a maximum output torque of 10 N·m, and the load sensor is a current sensor installed on the lifting motor.

6. A control method for an electric lift for a kitchen cabinet, characterized in that, The control system for the electric lift for cabinets according to claims 1-5 includes the following steps: The control panel generates and sends user input commands, and the controller generates control commands based on the user input commands. These control commands are the original control commands. The load sensor and encoder generate load signals, speed signals and speed signals in real time; The controller dynamically generates PID dynamic parameters based on load signals, speed signals, and speed signals, and generates speed regulation commands based on the PID dynamic parameters. The system adjusts the operating speed of the lifting mechanism under the control of the speed regulation commands. The limit sensor monitors whether the lifting mechanism has risen / fallen to the correct position and generates a limit signal; The controller generates a stop command based on the limit signal.

7. The processing method according to claim 6, characterized in that: The system has preset load setting values ​​and speed setting values, and initial PID parameter values ​​K (Kp0, Ki0, Kd). The fuzzy control module includes a fuzzy controller and a PID controller. The module outputs PID dynamic parameters by controlling the module, which includes the following steps: The fuzzy controller receives the load signal from the load sensor and the speed signal from the encoder in real time, and converts them into real-time load value and real-time speed value. The load error value is obtained by comparing the load setpoint with the real-time load value. The formula is e2 = M. set -M actual ; The load error change rate is obtained by comparing the load setpoint and the real-time load value, and the formula is e. 2c =de2 / dt; The speed error value is obtained by comparing the speed setpoint with the real-time speed value. The formula is e = V set -V actual ; The rate of change of speed error is obtained by comparing the speed setpoint with the real-time speed value, and the formula is e. c =de / dt; e2, e 2c , e, e c As input variables, they are substituted into the fuzzy algorithm to obtain the dynamic adjustment of the PID parameters; The dynamic parameters of the PID are calculated by using the dynamic adjustment amount ΔK and the initial PID parameter value K0, and the formula is K=ΔK+K0.

8. The processing method according to claim 6, characterized in that, The lifting motor is connected to the lifting mechanism via a transmission mechanism. The motor torque constant is set to Kt, and the system friction torque is set to τ. fric The gravitational acceleration is g, and the equivalent radius of the transmission mechanism is r; the load signal is a current signal, and the controller obtains the real-time current value I of the drive motor through the current signal, and obtains the real-time load value based on the current data, using the formula:

9. The processing method according to claim 6, characterized in that: The control system performs any action such as rising, falling, stopping, or position memorization under the control of the original control command. The speed signal is a pulse signal. The change in the number of encoder pulses per unit time is set as ΔPPR, the sampling time interval is Δt, the pulse-to-displacement conversion coefficient is CPM, and the cumulative number of pulses during the running time is ∑ i PPR i The resolution is PPR a The system, with a lead of P, implements position memory through the following steps: Receive location memory command, Collect the velocity signal at the current location. The real-time velocity value is obtained by calculating the velocity signal using the following formula: The position value is calculated using real-time velocity, resolution, and cumulative pulse count, using the following formula:

10. The processing method according to claim 6, characterized in that: The speed control command is a PWM signal. The steps of the controller generating the speed control command based on the PID dynamic parameters include: the PID controller receiving the PID dynamic parameters generated by the fuzzy controller; calculating the PWM duty cycle based on the PID parameters and outputting the PWM signal.

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