Intelligent induction sliding door system

Abstract

The invention discloses an intelligent induction sliding door system, which belongs to the field of sliding doors and comprises a door frame, a pair of symmetrically arranged door bodies, a sliding door machine, a fuzzy PID (Proportion Integration Differentiation) controller, a counterweight mechanism and a power supply module, the door frame is fixed to a wall, a horizontal rail is arranged on the inner side of the door frame, and the door body is slidably connected with the rail through pulleys. Interlayers with inward openings are arranged on the two sides of the door frame, and the door body is contained in the interlayer on the corresponding side when being opened. The sliding door machine is fixed to the top of a door frame, a sliding door motor is arranged in the sliding door machine and connected with a power module through a motor driver, a torque sensor is arranged at the output end of the sliding door motor, and the fuzzy PID controller is installed in the sliding door machine and electrically connected with the motor driver and the torque sensor. The counterweight mechanisms are symmetrically arranged on the two sides, close to the wall body, of the interlayer, one ends of the counterweight mechanisms are fixedly connected with the top of the door body, the fuzzy PID controller dynamically adjusts output of the sliding door motor and the counterweight mechanisms, the gravity center position of the door body is adjusted in real time through the counterweight mechanisms, and stable starting and stopping are achieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of sliding doors, and more specifically, relates to an intelligent induction sliding door system. Background Art

[0002] As a common type of automatic door, sliding doors are widely used in places such as shopping malls, hotels, office buildings, etc. In the traditional sliding door, the center of gravity is unstable during the opening and closing of the door body, resulting in vibrations or even shakes, causing harm and loss of the door body's lifespan. Existing sliding doors with adjustable door body center of gravity are for fixed adjustment or are applied in the case of automatic door closing, and cannot be applied to the daily life of door body opening and closing. The existing sliding doors have the following deficiencies:

[0003] Poor balance: The fixed mechanical counterweight or the elastic coefficient of the spring is fixed, making it difficult to adapt to changes in the door body weight, wind pressure and other external interferences, resulting in unstable operation of the door body, and even phenomena such as jamming and shaking;

[0004] Low degree of intelligence: Traditional sliding doors lack intelligent induction and control systems, and cannot automatically adjust operating parameters according to environmental changes, with poor adaptability;

[0005] High energy consumption: The motor of the traditional sliding door is always in a working state, consuming electrical energy even when there is no personnel passing through, resulting in energy waste.

[0006] Therefore, there is a need for a sliding door that can intelligently sense the external environment, automatically adjust operating parameters according to the environment, achieve dynamic balance of door body opening and closing, and is energy-saving and environmentally friendly. Summary of the Invention

[0007] The technical problem to be solved by the present invention is to provide an intelligent induction sliding door system, which can meet the requirements of intelligent induction of the external environment by the sliding door and automatic adjustment of operating parameters to achieve dynamic balance of door body opening and closing.

[0008] An intelligent induction sliding door system of the present invention includes a door frame, a pair of symmetrically arranged door bodies, a sliding door machine, a fuzzy PID controller, a counterweight mechanism and a power supply module; the door frame is fixed to the wall, and a horizontal track is provided inside; the door body is slidably connected to the track through a pulley; on both sides of the door frame, there are inwardly opening interlayers, and when the door body is opened, it is received into the corresponding side interlayer; the sliding door machine is fixed on the top of the door frame, and a sliding door motor is provided inside it. The sliding door motor is connected to the power supply module through a motor driver, a torque sensor is provided at the output end of the sliding door motor, the fuzzy PID controller is installed in the sliding door machine and is electrically connected to the motor driver and the torque sensor, the counterweight mechanism is symmetrically arranged on both sides of the interlayer close to the wall and one end is fixedly connected to the top of the door body, and an induction device is provided on the outer side of the door body.

[0009] As a further improvement of the present invention, the counterweight mechanism includes a counterweight block, a chain, a ball screw, a sprocket, a counterweight motor and an encoder; the ball screw is vertically fixed in the interlayer, the counterweight block is connected to the ball screw through a nut pair, the sprocket is fixed at the top of the door frame, one end of the chain is connected to the counterweight block, and the other end is fixed to the top of the door body after passing around the sprocket. The input end of the counterweight motor is directly connected to the power module through a motor driver, the output end is directly connected to the ball screw, and an encoder is provided at the output end. The encoder is electrically connected to the fuzzy PID controller and is used to real-time feedback the position of the counterweight block and the rotation speed of the counterweight motor. The fuzzy PID controller dynamically adjusts the outputs of the sliding door motor and the counterweight mechanism according to the feedback data of the torque sensor and the encoder, and real-time adjusts the center of gravity position of the door body through the counterweight mechanism to achieve smooth start and stop.

[0010] As a further improvement of the present invention, it further includes a memory, which is built in the sliding door machine and electrically connected to the fuzzy PID controller. The memory stores a fuzzy rule base, PID parameters and historical operation data, and is used to dynamically optimize the control algorithm, provide data support for the fuzzy PID controller, and process non-linear and uncertain problems through the fuzzy rule base to enhance the adaptability and robustness of the system.

[0011] Required input variables: e(t) is the error signal, which is the difference between the actual position and the target position of the door body, Δe is the change rate of the error, ΔW is the change in the door body counterweight, and the change value of the door body load detected by the weighing sensor;

[0012] Output quantities: Kp is the proportional coefficient, Ki is the integral coefficient, Kd is the differential coefficient, and u(t) is the control output.

[0013] The proportional coefficient Kp dynamically adjusts the fuzzy rule base as follows

[0014]

[0015] The parameters in the above table are: Negative Big (NB), Negative Medium (NM), Negative Small (NS), Zero (Z0), Positive Small (PS), Positive Medium (PM), Positive Big (PB).

[0016] The fuzzy set of the change in the door body counterweight ΔW: Light (L), Medium (M), Heavy (H).

[0017] Set thresholds for the variables e(t), Δe(t), and ΔW, convert the measured values of the input variables e(t), Δe(t), and ΔW into membership degrees of the fuzzy set, calculate the output membership degree corresponding to each rule according to the fuzzy rule base, and finally convert the fuzzy output into specific PID parameter values through the weighted average method.

[0018] Finally, according to the fuzzy PID controller output formula

[0019] u(t) = Kp·e(t) + Ki∫e(t)dt + Kd·dtde(t)

[0020] Calculate the control output u(t).

[0021] As a further improvement of the present invention, a weighing sensor is provided at the lower end of the door body, and an accelerometer is provided at the center of the top. The weighing sensor detects the load distribution of the door body in real time, and the accelerometer monitors the acceleration and vibration state of the door body. Both are connected to the fuzzy PID controller to provide real-time parameters for the fuzzy PID controller to dynamically adjust the opening and closing parameters of the door body.

[0022] As a further improvement of the present invention, the counterweight mechanism further includes a tensioning assembly. The tensioning assembly includes a tensioning wheel and a tensioning spring. The tensioning wheel is installed on the side wall of the door frame through a bracket, and the chain bypasses the tensioning wheel to form a closed loop. The two ends of the tensioning spring are respectively connected to the bracket and the door frame, and are used to automatically adjust the chain tension; when the counterweight moves and causes the chain to be tightened, the tensioning spring is compressed and the tensioning wheel moves back to guide the movement of the chain to reduce chain wear; when the counterweight moves and causes the chain to be loose, the tensioning spring stretches and the tensioning wheel presses against the chain to maintain the chain tension and prevent the chain from loosening and slipping, resulting in the ineffective transmission of the pulling force of the counterweight to the door body.

[0023] As a further improvement of the present invention, the sensing device is at least one of an infrared sensor, a microwave sensor or a pressure sensor, and is installed on the outer edge of the door body to detect obstacle or human approach signals.

[0024] As a further improvement of the present invention, a disturbance observer module is provided in the fuzzy PID controller for estimating and compensating external disturbances in real time. Based on the door body dynamics model, a disturbance estimation model is constructed to estimate the external disturbance d in real time. The disturbance estimation formula is

[0025] d = M·a - F 电机 -F 负载

[0026] where M is the mass of the door body, a is the acceleration detected by the accelerometer, and F 电机 is the output force of the sliding door motor, which can be obtained by the PID controller after the torque sensor detects the torque, and F 负载 is the load force detected by the weighing sensor.

[0027] Disturbance compensation mechanism: The estimated disturbance d is used as a feedforward compensation term and superimposed on the fuzzy PID control output. The formula is

[0028] u = u PID + d

[0029] where u PID is the fuzzy PID control output and u is the final control quantity.

[0030] As a further improvement of the present invention, an energy recovery module and an energy storage device are provided inside the fuzzy PID controller. The energy storage device selects a super capacitor and is used to recover energy during the deceleration or braking process of the door body. The energy recovery logic is that when the accelerometer detects negative acceleration or the torque sensor detects a sudden change in load, the fuzzy PID controller determines that the door body enters the deceleration or braking state, the motor driver cuts off the drive current, the translation door motor stops outputting mechanical energy, the door body continues to move by inertia, the internal circuit of the motor driver switches to the rectification mode, the translation door motor is switched from the motor state to the generator state, and the full-bridge rectification circuit converts the alternating current generated by the translation door motor into direct current. The motor rotor continues to rotate under the action of inertia, cuts the magnetic field lines to generate an induced electromotive force, and the induced current outputs direct current through the rectification circuit and is stored in the super capacitor. According to the energy consumption demand of the system, the ratio of energy recovery and release is dynamically adjusted to improve the overall energy efficiency.

[0031] Compared with the prior art, the beneficial effects of the present invention are as follows: The fuzzy PID controller dynamically adjusts the rotation speed and torque of the translation door motor and the counterweight motor according to the feedback data of the encoder, the weighing sensor and the accelerometer, so that the center of gravity of the door body is matched with the position of the counterweight block in real time, realizing smooth start and stop; The weighing sensor detects the load distribution of the door body in real time, and the accelerometer monitors the acceleration and vibration state of the door body. Both are connected to the fuzzy PID controller and provide real-time parameters for the fuzzy PID controller to dynamically adjust the opening and closing parameters of the door body, improving the adaptability of the translation door; The counterweight mechanism also includes a tensioning component, which automatically adjusts the chain tension to prevent the chain from loosening and slipping, resulting in the ineffective transmission of the pulling force of the counterweight block to the door body; The sensing device is at least one of an infrared sensor, a microwave sensor or a pressure sensor, and is installed on the outer edge of the door body to detect the approach signal of obstacles or human bodies; A disturbance observer module is provided inside the fuzzy PID controller to estimate and compensate external disturbances in real time; An energy recovery module is provided inside the fuzzy PID controller to recover energy during the deceleration or braking process of the door body, saving energy and protecting the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 is a structural schematic diagram of the present invention;

[0033] Figure 2 is a structural schematic diagram of the single-sided door body of the present invention;

[0034] Figure 3 is a structural schematic diagram of the fuzzy PID controller and the memory of the present invention;

[0035] Figure 4 is of the present invention Figure 3 regional enlarged view;

[0036] Figure 5 is a flowchart of the operation logic of the present invention;

[0037] Figure 6 This is the operation logic flowchart of the disturbance observer of the present invention;

[0038] Figure 7 This is the operation logic flowchart of the energy recovery of the present invention.

[0039] Explanation of the reference numerals in the figure:

[0040] Door frame 1; door body 2; weighing sensor 21; accelerometer 22; sliding door machine 3; sliding door motor 31; torque sensor 32; fuzzy PID controller 4; memory 5; counterweight mechanism 6; counterweight block 61; chain 62; ball screw 63; sprocket 64; counterweight motor 65; encoder 66; tensioning pulley 67; tension spring 68; power supply 7; motor driver 8; induction device 9. Detailed implementation manner

[0041] Specific embodiment 1: Please refer to Figures 1-7 , the present invention relates to an intelligent induction sliding door system, including a door frame 1, a pair of symmetrically arranged door bodies 2, a sliding door machine 3, a fuzzy PID controller 4, a counterweight mechanism 6 and a power supply module 7; the door frame 1 is fixed to the wall, and a horizontal track is provided inside. The door body 2 is slidably connected to the track through a pulley; sandwich layers with inward openings are provided on both sides of the door frame 1, and the door body 2 is received into the corresponding side sandwich layer when opened; the sliding door machine 3 is fixed on the top of the door frame 1, and a sliding door motor 31 is provided inside it. The sliding door motor 31 is connected to the power supply module 7 through a motor driver 8. A torque sensor 32 is provided at the output end of the sliding door motor 31. The fuzzy PID controller 4 is installed in the sliding door machine 3 and is electrically connected to the motor driver 8 and the torque sensor 32. The counterweight mechanism 6 is symmetrically arranged on both sides of the sandwich layer close to the wall and one end is fixedly connected to the top of the door body 2. The fuzzy PID controller 4 dynamically adjusts the sliding door motor 31 and the counterweight mechanism according to the feedback data, so that the center of gravity of the door body 2 is matched with the position of the counterweight mechanism 6 in real time, realizing smooth start and stop.

[0042] In a further embodiment, as Figure 2 shown, the counterweight mechanism 6 includes a counterweight block 61, a chain 62, a ball screw 63, a sprocket 64, a counterweight motor 65 and an encoder 66; the ball screw 63 is vertically fixed in the sandwich layer, the counterweight block 61 is connected to the ball screw 63 through a nut pair, the sprocket 64 is fixed to the top end of the door frame 1, one end of the chain 62 is connected to the counterweight block 61, and the other end passes around the sprocket 64 and is fixed to the top of the door body 2. The input end of the counterweight motor 65 is directly connected to the power supply module 7 through a motor driver 8, the output end is directly connected to the ball screw 63, and an encoder 66 is provided at the output end. The encoder 66 is electrically connected to the fuzzy PID controller 4 for real-time feedback of the position of the counterweight block 61 and the rotation speed of the counterweight motor 65.

[0043] In a further embodiment, as Figure 3 shown, it further includes a memory 5. The memory 5 is built into the sliding door machine 3 and is electrically connected to the fuzzy PID controller 4. The memory 5 stores a fuzzy rule base, PID parameters, and historical operation data, and is used to dynamically optimize the control algorithm to provide data support for the fuzzy PID controller 4.

[0044] In a further embodiment, as Figure 2 shown, a weighing sensor 21 is provided at the lower end of the door body 2, and an accelerometer 22 is provided at the center of the top. The weighing sensor 21 detects the load distribution of the door body in real time, and the accelerometer 22 monitors the acceleration and vibration state of the door body. Both are connected to the fuzzy PID controller 4 to provide real-time parameters for the fuzzy PID controller to dynamically adjust the opening and closing parameters of the door body 2.

[0045] In a further embodiment, as Figure 2 and Figure 4 shown, the counterweight mechanism 6 further includes a tensioning assembly. The tensioning assembly includes a tensioning wheel 67 and a tensioning spring 68. The tensioning wheel 67 is installed on the side wall of the door frame 1 through a bracket. The chain 62 bypasses the tensioning wheel 67 to form a closed loop. Both ends of the tensioning spring 68 are respectively connected to the bracket and the door frame 1, and are used to automatically adjust the tension of the chain 62. When the movement of the counterweight 61 causes the chain 62 to be tightened, the tensioning spring 68 is compressed, and the tensioning wheel 67 moves back to guide the movement of the chain 67 to reduce the wear of the chain 67. When the movement of the counterweight 61 causes the chain 62 to be slack, the tensioning spring 68 stretches, and the tensioning wheel 67 presses against the chain 62 to maintain the tension of the chain 67 and prevent the chain 67 from slipping due to slack, resulting in the ineffective transmission of the pulling force of the counterweight 61 to the door body 2.

[0046] In a further embodiment, as Figure 2 shown, a sensing device 9 is provided on the outer side of the door body 2. The sensing device 9 is at least one of an infrared sensor, a microwave sensor, or a pressure sensor, and is installed on the outer edge of the door body 2 for detecting an obstacle or a human approach signal.

[0047] In a further embodiment, as Figure 6 shown, a disturbance observer module is provided in the fuzzy PID controller 4 for estimating and compensating external disturbances in real time. Based on the door body dynamics model, a disturbance estimation model is constructed to estimate the external disturbance d in real time. The disturbance estimation formula is

[0048] d = M·a - F 电机 -F 负载

[0049] where M is the mass of the door body 2, a is the acceleration detected by the accelerometer 22, and F 电机 is the output force of the sliding door motor 31. After the torque sensor 32 detects the torque and transmits it to the PID controller for calculation, F 负载is the load force detected by the load cell 21.

[0050] Disturbance compensation mechanism: The estimated disturbance d is used as a feed-forward compensation term and superimposed on the output of the fuzzy PID control. The formula is:

[0051] u = u PID + d

[0052] where u PID is the output of the fuzzy PID control, and u is the final control quantity.

[0053] In a further embodiment, as Figure 7 shown, the fuzzy PID controller 4 is provided with an energy recovery module and an energy storage device. The energy storage device selects a super capacitor, which is used to recover energy during the deceleration or braking process of the door body. The energy recovery logic is: when the accelerometer 22 detects a negative acceleration or the torque sensor 32 detects a load mutation, the fuzzy PID controller 4 determines that the door body 2 enters the deceleration or braking state, the motor driver 8 cuts off the drive current, the translational door motor 31 stops outputting mechanical energy, the door body 2 continues to move by inertia, the internal circuit of the motor driver 8 switches to the rectification mode, the translational door motor 31 is switched from the motor state to the generator state, the full-bridge rectification circuit converts the alternating current generated by the translational door motor 31 into direct current, the motor rotor continues to rotate under the action of inertia, cuts the magnetic field lines to generate an induced electromotive force, the induced current outputs direct current through the rectification circuit, stores it in the super capacitor, and dynamically adjusts the ratio of energy recovery and release according to the system energy consumption demand to improve the overall energy efficiency.

[0054] In a further embodiment, the dynamic optimization based on the fuzzy PID control algorithm

[0055] The initial parameters of the fuzzy rule base are as follows:

[0056] Kp = 1.0, Ki = 0.1, Kd = 0.01

[0057] Convert the measured values of the input variables e(t), Δe(t), and ΔW into the membership degrees of the fuzzy sets:

[0058] The error e(t) = 8 cm, the membership degree of positive large (PB) is 0.8, and the membership degree of positive small (PS) is 0.2; the error change rate Δe(t) = 4 cm / s; the membership degree of positive large (PB) is 0.7, and the membership degree of positive small (PS) is 0.3; the change in the counterweight of the door body 2 ΔW = light (L); the membership degree of light (L) is 1.0, and the membership degree of medium (M) is 0.0.

[0059] According to the fuzzy rule base, calculate the output membership degree corresponding to each rule:

[0060] Rule 1: If e(t) is positive big (PB), Δe(t) is positive big (PB), and ΔW is light (L), then Kp is big (B), Ki is small (S), and Kd is big (B);

[0061] Input membership degree μ PB (e) = 0.8, μ PB (Δe) = 0.7, (Δ) = 1.0μ L (ΔW) = 1.0;

[0062] Rule strength μ 规则1 = min(0.8, 0.7, 1.0) = 0.7;

[0063] Output membership degree μ Kp＝B = 0.7, μ Ki＝S = 0.7, μ Kd＝B = 0.7.

[0064] Convert the fuzzy output to specific PID parameter values through the weighted average method:

[0065] For Kp: The typical value of big (B) is 2.0, and the membership degree is 0.7. The typical value of medium (M) is 1.0, and the membership degree is 0.3. The typical value of small (S) is 0.5, and the membership degree is 0.0.

[0066] Kp = (2.0 × 0.7 + 1.0 × 0.3 + 0.5 × 0.0) / (0.7 + 0.3 + 0.0) = 1.7.

[0067] For Ki: The typical value of small (S) is 0.01, and the membership degree is 0.7; the typical value of medium (M) is 0.05, and the membership degree is 0.3; the typical value of big (B) is 0.1, and the membership degree is 0.0.

[0068] Ki = (0.01 × 0.7 + 0.05 × 0.3 + 0.1 × 0.0) / (0.7 + 0.3 + 0.0) = 0.022.

[0069] For Kd: The typical value of big (B) is 0.01, and the membership degree is 0.7; the typical value of medium (M) is 0.005, and the membership degree is 0.3; the typical value of small (S) is 0.001, and the membership degree is 0.0.

[0070] Kd = (0.01 × 0.7 + 0.005 × 0.3 + 0.001 × 0.0) / (0.7 + 0.3 + 0.0) = 0.0085.

[0071] Final PID parameters:

[0072] Kp = 1.7, Ki = 0.022, Kd = 0.0085

[0073] According to the PID control formula, calculate the control output u(t):

[0074]

[0075] Substitute the above parameters into the formula, and based on the actual value of the adjustment error e(t) received by the PID controller after the change, obtain the final control output, and timely adjust the position of the counterweight 61 and the output power of the sliding door motor 31.

[0076] When the error e is positive and large and the error change rate Δe is positive and large, then Kp increases to 1.5, Ki decreases to 0.05, and Kd increases to 0.02; when the error e is negative and small and the error change rate Δe is negative and small, then Kp decreases to 0.8, Ki increases to 0.2, and Kd decreases to 0.005, ensuring that the door body 2 moves smoothly during the opening and closing processes, and avoiding jitter or impact.

[0077] When the door body is opened, the sensing device 9 detects a signal of a person approaching or an obstacle, and sends a start command to the fuzzy PID controller 4. The fuzzy PID controller 4 calls the initialization parameters in the memory 5. The sliding door motor 31 receives the control signal through the motor driver 32 and starts to drive the door body 2 to move along the track. The torque sensor 33 detects the output torque of the sliding door motor 31 in real time to ensure a smooth start;

[0078] The counterweight motor 65 receives the signal from the fuzzy PID controller 4, drives the ball screw 63 to rotate, drives the counterweight 61 to move in the vertical direction, and the chain 62 transmits the counterweight force to the top of the door body 2 through the sprocket 64 to offset the center-of-gravity shift of the door body 2. The tension pulley 67 and the tension spring 68 ensure that the chain 62 is always taut to avoid slack;

[0079] The load cells 21 monitor the load distribution at both ends of the door body 2 in real time. The accelerometer 22 captures the motion acceleration and abnormal vibration of the door body 2. The encoder 66 feeds back the precise position of the counterweight 61 and the rotational speed of the counterweight motor 65. The fuzzy PID controller 4 integrates the multi-sensor data, outputs a control signal to the motor driver 32, and dynamically adjusts the opening and closing speed of the door body 2;

[0080] Based on the dynamic model, the disturbance observer estimates the external disturbance in real time through d = M·a - F 电机 -F 负载 and superimposes it on the control output to suppress vibration. The door body 2 moves smoothly along the track, the counterweight 61 dynamically adjusts the center of gravity to ensure the smooth operation of the door body 2. The accelerometer 22 monitors the vibration, and the disturbance observer suppresses the external interference.

Claims

1. An intelligent induction sliding door system, characterized in that: The invention comprises a door frame (1), a pair of symmetrically arranged door bodies (2), a sliding door machine (3), a fuzzy PID controller (4), a counterweight mechanism (6), a power module (7) and a motor driver (8); the door frame (1) is fixed to a wall, a horizontal track is arranged on the inner side, and the door body (2) is slidably connected to the track via a pulley; both sides of the door frame (1) are provided with interlayers opening inwards, and the door body (2) is received into the interlayers on the corresponding sides when it is opened; the sliding door machine (3) is fixed to the top of the door frame (1), a sliding door motor (31) is arranged inside the interlayer, the sliding door motor (31) is connected to the power module (7) via the motor driver (8), a torque sensor (32) is arranged at the output end of the sliding door motor (31), the fuzzy PID controller (4) is installed in the sliding door machine (3), and is electrically connected to the motor driver (8) and the torque sensor (32); the counterweight mechanism (6) is symmetrically arranged on both sides of the interlayer close to the wall, and one end is fixedly connected to the top of the door body (2).

2. The intelligent induction sliding door system according to claim 1, characterized in that: The counterweight mechanism (6) comprises a counterweight block (61), a chain (62), a ball screw (63), a sprocket (64) and a counterweight motor (65); the ball screw (63) is vertically fixed to the interlayer, the counterweight block (61) is connected to the ball screw (63) through a nut pair, the sprocket (64) is fixed to the top of the door frame (1), one end of the chain (62) is connected to the counterweight block (61), and the other end is fixed to the top of the door body (2) after passing through the sprocket (64); the input end of the counterweight motor (65) is directly connected to the power module (7) through the motor driver (8), and the output end is directly connected to the ball screw (63), and the output end is provided with an encoder (66), and the encoder (66) is electrically connected to the fuzzy PID controller (4) for real-time feedback of the position of the counterweight block (61) and the rotation speed of the counterweight motor (65).

3. The intelligent induction sliding door system according to claim 1, characterized in that: It also includes a memory (5), which is built into the sliding door machine (3) and electrically connected to the fuzzy PID controller (4), and the memory (5) stores a fuzzy rule base, PID parameters and historical operation data for dynamic optimization of the control algorithm.

4. The intelligent induction sliding door system according to claim 1, characterized in that: A weighing sensor (21) is provided at the lower end of the door body (2), and an accelerometer (22) is provided at the top center. The weighing sensor (21) detects the load distribution of the door body in real time, and the accelerometer (22) monitors the acceleration and vibration state of the door body. Both are connected to a fuzzy PID controller (4) for adjusting the movement parameters of the door body (2).

5. The intelligent induction sliding door system according to claim 2, characterized in that: The counterweight mechanism (6) also includes a tensioning assembly, which includes a tensioning wheel (67) and a tensioning spring (68). The tensioning wheel (67) is installed on the side wall of the door frame (1) through a bracket. The chain (62) passes around the tensioning wheel (67) to form a closed loop. The two ends of the tensioning spring (68) are respectively connected to the bracket and the door frame (1) for automatically adjusting the tension of the chain (62).

6. The intelligent induction sliding door system according to claim 1, characterized in that: A sensing device (9) is provided on the outside of the door body (2); the sensing device (9) is at least one of an infrared sensor, a microwave sensor or a pressure sensor, and is installed on the outside edge of the door body (2).

7. The intelligent induction sliding door system according to claim 1, characterized in that: The fuzzy PID controller (4) is provided with a disturbance observer module, which constructs a disturbance estimation model based on the dynamic model of the door body (2) to estimate the external disturbance d in real time; the disturbance estimation formula is: d=M·a-F 电机 -F 负载 Where M is the mass of the door body (2), a is the acceleration detected by the accelerometer (22), and F 电机 is the output force of the sliding door motor (31), and the torque is detected by the torque sensor (32) and transmitted to the PID controller for calculation. 负载 It is the load force detected by the weighing sensor (21). Disturbance compensation mechanism: The estimated disturbance d is used as a feedforward compensation term and added to the fuzzy PID control output. The formula is: u=u PID +d where u PID is the fuzzy PID control output, and u is the final control quantity.

8. The intelligent induction sliding door system according to claim 1, characterized in that: An energy recovery module and an energy storage device are provided in the fuzzy PID controller (4). The energy storage device is a super capacitor. The energy recovery logic is that when it is detected that the door body is decelerating or braking, the sliding door motor (31) is switched to a power generation mode through the motor driver (8) to convert mechanical energy into electrical energy.

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