Self-adaptive fuzzy PID (Proportion Integration Differentiation) control disc type centrifugal machine rotating speed adjusting method and system

Abstract

The invention relates to the technical field of centrifugal machines, and particularly provides a self-adaptive fuzzy PID control disc type centrifugal machine rotating speed adjusting method and system, and the method comprises the steps: obtaining a rotating speed error, an error change rate, a load torque change rate and a friction coefficient variable quantity; a fuzzy inference engine is constructed based on a preset parameter self-adjustment rule base, and PID parameter adjustment amount is obtained with the rotating speed error, the error change rate, the load torque change rate and the friction coefficient change amount as input variables of the fuzzy inference engine; and the PID control parameters are corrected according to the PID parameter adjustment amount, and the rotating speed of the disc type centrifugal machine is adjusted in real time according to the PID control parameters. According to the method, the load torque change rate and the friction coefficient change quantity are introduced to serve as input of the fuzzy inference engine, the load torque change rate serves as a disturbance feed-forward item, the working condition adaptability can be enhanced, and the defects that PID parameters are fixed, variable working conditions are difficult to adapt, and overshoot or slow response is likely to be caused in traditional PID control are overcome.

Description

Technical Field

[0001] This invention relates to the field of centrifuge technology, and more specifically, to an adaptive fuzzy PID control method and system for adjusting the speed of a disc centrifuge. Background Technology

[0002] Disc centrifuges are a type of sedimentation centrifuge, also known as disc centrifuges. They are mainly used for solid-liquid or liquid-liquid separation of materials that are difficult to separate, such as suspensions and emulsions. They are widely used in more than ten industries, including mineral oil purification, dairy product defatting, vegetable oil refining, and pharmaceutical purification. Their core structure consists of a vertical rotating drum and an internal stack of conical discs. The centrifugal force field accelerates sedimentation, achieving a separation factor of 4000-10000. They can process particles of 0.001-100 microns and materials with a solid phase concentration of less than 25%.

[0003] Disc separators are characterized by high-speed rotating discs, material stratification between discs, large rotational inertia of the drum, high separation factor, and sensitivity to vibration. These characteristics determine the criticality of speed control: it must respond quickly while avoiding overshoot that could lead to vibration.

[0004] Generally, the traditional method for regulating the speed of a disc centrifuge uses a PID controller. However, traditional PID control has the drawbacks of fixed PID parameters and difficulty in adapting to changing operating conditions. It is prone to overshoot or slow response, which can endanger dynamic balance and lead to a decrease in separation efficiency. Summary of the Invention

[0005] Based on this, in order to better regulate the speed of a disc centrifuge, this invention provides an adaptive fuzzy PID control method and system for regulating the speed of a disc centrifuge. By introducing real-time observation of load torque and friction coefficient as fuzzy inputs, it can enhance the adaptability to operating conditions. The specific technical solution is as follows: An adaptive fuzzy PID control method for speed regulation of a disc centrifuge includes the following steps: Obtain the speed error, error change rate, load torque change rate, and friction coefficient change; A fuzzy inference engine is constructed based on a preset parameter self-adjustment rule base. The speed error, error change rate, load torque change rate, and friction coefficient change are used as input variables of the fuzzy inference engine to obtain the PID parameter adjustment amount. The PID control parameters are adjusted based on the PID parameter adjustment amount, and the speed of the disc centrifuge is adjusted in real time based on the PID control parameters.

[0006] The proposed disc centrifuge speed regulation method introduces the load torque change rate and friction coefficient change as inputs to the fuzzy inference engine, and uses the load torque change rate as a disturbance feedforward term. This enhances the adaptability to operating conditions and overcomes the shortcomings of traditional PID control, such as fixed PID parameters, difficulty in adapting to changing operating conditions, and easy overshoot or slow response.

[0007] Preferably, the specific method for obtaining the change in the coefficient of friction includes the following steps: Real-time acquisition of centrifuge actual speed and motor output torque; obtaining centrifuge speed change rate based on centrifuge actual speed. Obtain the moment of inertia of the rotor system, and obtain the inertial term based on the centrifuge speed change rate and the moment of inertia of the rotor system; Obtain the load torque observation value, and obtain the torque residual based on the motor output torque, inertia term, and load torque observation value; Integrate the product of the torque residual and the actual speed of the centrifuge to obtain an estimated value of the friction coefficient, and obtain the change in friction coefficient based on the estimated value.

[0008] Preferably, the specific method for correcting the PID control parameters based on the PID parameter adjustment includes the following steps: Obtain the proportional reference gain and the proportional gain adjustment amount; The proportional base gain is corrected based on the proportional gain adjustment to obtain the PID proportional gain.

[0009] Preferably, the specific method for correcting the PID control parameters based on the PID parameter adjustment amount further includes the following steps: Obtain the integral reference gain and the integral gain adjustment amount; Integral saturation suppression is applied to the integral reference gain based on the rotational speed error; The integral reference gain for integral saturation suppression is corrected based on the integral gain adjustment to compensate for the phase lag caused by viscosity abrupt changes, thereby obtaining the PID integral gain.

[0010] Preferably, the specific method for correcting the PID control parameters based on the PID parameter adjustment amount further includes the following steps: Obtain the differential reference gain and the differential gain adjustment amount; The differential gain adjustment is corrected based on the absolute value of the load torque change rate so that the correction to the differential reference gain decreases as the disturbance increases.

[0011] Preferably, the disc centrifuge speed adjustment method further includes the following steps: Obtain the yield strength, density, and inner-outer diameter difference of the disc material; The upper limit of safe rotation speed is determined based on the yield strength of the disc material, the density of the disc material, and the difference between the inner and outer diameters of the disc.

[0012] Preferably, the disc centrifuge speed adjustment method further includes the following steps: Obtain the rate of change of the load torque observation; When the rate of change of the load torque observation is greater than the first preset torque threshold and the duration is greater than the first time threshold, and the rate of change of the speed is less than the first preset speed threshold and the duration is greater than the second time threshold, it is determined that the load is abnormal due to disk scaling.

[0013] An adaptive fuzzy PID control disc centrifuge speed regulation system, used to implement the aforementioned adaptive fuzzy PID control disc centrifuge speed regulation method, includes: The parameter acquisition module is used to acquire speed error, error change rate, load torque change rate, and friction coefficient change. A fuzzy inference engine is used to obtain PID parameter adjustment values ​​by taking speed error, error change rate, load torque change rate, and friction coefficient change as input variables. The control module is used to correct the PID control parameters based on the PID parameter adjustment amount, and to adjust the speed of the disc centrifuge in real time based on the PID control parameters.

[0014] Preferably, the parameter acquisition module includes: The speed change rate acquisition unit is used to collect the actual speed of the centrifuge and the output torque of the motor in real time, and to obtain the speed change rate of the centrifuge based on the actual speed of the centrifuge. The inertia term acquisition unit is used to acquire the rotational inertia of the rotor system, and to acquire the inertia term based on the centrifuge speed change rate and the rotational inertia of the rotor system. The torque residual acquisition unit is used to acquire the load torque observation value and obtain the torque residual based on the motor output torque, inertia term and load torque observation value; The change acquisition unit is used to integrate the product of the torque residual and the actual speed of the centrifuge to obtain an estimated value of the friction coefficient, and to obtain the change in the friction coefficient based on the estimated value of the friction coefficient.

[0015] Preferably, the change in the coefficient of friction is expressed as ; in, The values ​​are, in order, the motor output torque, the rotor system moment of inertia, the centrifuge actual speed, and the observed load torque. Represents the inertial term. Represents torque residual. Represents the adaptive gain coefficient. This represents the estimated value of the friction coefficient. Attached Figure Description

[0016] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0017] Figure 1 This is a schematic diagram of the overall process of an adaptive fuzzy PID control method for adjusting the speed of a disc centrifuge according to an embodiment of the present invention. Figure 2 This is a flowchart illustrating a specific method for obtaining the change in friction coefficient in one embodiment of the present invention; Figure 3 This is one of the flowcharts illustrating a specific method for correcting PID control parameters based on PID parameter adjustment amounts in one embodiment of the present invention. Figure 4 This is a second flowchart illustrating a specific method for correcting PID control parameters based on PID parameter adjustment amounts in one embodiment of the present invention. Figure 5 This is a third flowchart illustrating a specific method for correcting PID control parameters based on PID parameter adjustment amounts in one embodiment of the present invention. Figure 6 This is a schematic diagram of the overall process of an adaptive fuzzy PID control method for adjusting the speed of a disc centrifuge, according to another embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to its embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the scope of protection of the invention.

[0019] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly attached to the other element or there may be an intervening element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or there may be an intervening element. The terms "vertical," "horizontal," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible implementation.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0021] In this invention, "first" and "second" do not represent a specific quantity or order, but are merely used to distinguish names.

[0022] Before describing the specific embodiments of the present invention, a brief introduction to the prior art will be given first.

[0023] A disc centrifuge is an analytical instrument that separates liquid phases from solid phases or liquid phases of different densities through centrifugal force generated by high-speed rotation. Its core component is a stack of discs inside a rotating drum. As the suspension passes through the gaps between the discs, solid particles settle and separate under centrifugal force. Specifically, a disc centrifuge is a vertical centrifuge, with the drum mounted on a vertical shaft and driven at high speed by an electric motor via a transmission device. Inside the drum is a set of interlocking disc-shaped components—discs—with very small gaps between them. The suspension (or emulsion) is added to the drum through a feed pipe located at the center. As the suspension (or emulsion) flows through the gaps between the discs, solid particles (or droplets) settle onto the discs under centrifugal force, forming sediment (or a liquid layer). The sediment slides along the disc surface, detaches from the discs, and accumulates at the largest diameter part inside the drum. The separated liquid is discharged from the drum through the outlet. The discs shorten the settling distance of solid particles (or droplets) and increase the settling area of ​​the drum. The installation of discs in the drum greatly improves the production capacity of the separator. The solids accumulated in the drum are manually removed after the separator is stopped, or discharged from the drum through the slag discharge mechanism without stopping the machine.

[0024] The disc stacking structure of disc centrifuges results in a much higher inertia than ordinary centrifuges. With its large rotational inertia, changes in material viscosity can cause dynamic fluctuations in the coefficient of viscous friction, leading to nonlinear friction. Furthermore, fluctuations in feed flow rate, changes in material density, and disc scaling can all cause sudden changes in load torque, reducing the accuracy of its speed control.

[0025] To better regulate the speed of a disc centrifuge, this invention provides an adaptive fuzzy PID control method and system for regulating the speed of a disc centrifuge. By introducing real-time observation of load torque and friction coefficient as fuzzy inputs, it can enhance the adaptability to operating conditions.

[0026] like Figure 1 As shown, an adaptive fuzzy PID control method for adjusting the speed of a disc centrifuge according to an embodiment of the present invention includes the following steps: S1, obtains the speed error, error change rate, load torque change rate, and friction coefficient change.

[0027] As a preferred technical solution, such as Figure 2 As shown, the specific method for obtaining the change in friction coefficient includes the following steps: S11 collects the actual speed of the centrifuge and the output torque of the motor in real time, and obtains the centrifuge speed change rate based on the actual speed of the centrifuge.

[0028] The motor output torque is calculated by multiplying the motor current by the torque constant.

[0029] S12, obtain the rotational inertia of the rotor system, and obtain the inertial term based on the centrifuge speed change rate and the rotational inertia of the rotor system.

[0030] S13, obtain the load torque observation value, and obtain the torque residual based on the motor output torque, inertia term and load torque observation value.

[0031] The observed load torque can be estimated using an extended Kalman filter.

[0032] S14, integrate the product of the torque residual and the actual speed of the centrifuge to obtain an estimated value of the friction coefficient, and obtain the change in friction coefficient based on the estimated value of the friction coefficient.

[0033] For example, the change in the coefficient of friction is expressed as ;in, The values ​​are, in order, the motor output torque, the rotor system moment of inertia, the centrifuge actual speed, and the observed load torque. Represents the inertial term. Represents torque residual. Represents the adaptive gain coefficient. This represents the estimated value of the friction coefficient.

[0034] Specifically, the change in the friction coefficient reflects the viscous damping caused by changes in material viscosity, and is dynamically updated to adapt to varying operating conditions. An adaptive gain coefficient is used to control the convergence speed of the friction estimate, balancing response speed and stability. The rotor system's moment of inertia is determined by the disc structure, and the centrifuge speed change rate can be obtained through encoder differential calculation or an acceleration observer.

[0035] The output torque of a motor is generally equal to the sum of the inertial torque, frictional resistance, and load resistance. When the actual motor output torque deviates from the theoretical requirement, the equation can be kept constant by dynamically adjusting the estimated friction coefficient. Here, separating the load disturbance, i.e., the observed load torque, from the friction estimation avoids misjudgment of the friction coefficient caused by sudden changes in material flow.

[0036] For adaptive gain coefficients, to ensure Lyapunov stability, the following conditions generally need to be met. ,in, Indicates the maximum permissible speed, recommended. , This is the rated speed.

[0037] When ω is high, the integral gain increases, which can quickly track changes in viscosity; when ω is low, integral saturation is suppressed, which can prevent overcompensation.

[0038] In summary, the nonlinear damping torque caused by changes in material viscosity can be offset by the aforementioned friction coefficient change function, significantly improving the control robustness of the disc centrifuge under varying material conditions.

[0039] S2. A fuzzy inference engine is constructed based on a preset parameter self-adjustment rule base. The speed error, error change rate, load torque change rate, and friction coefficient change are used as input variables of the fuzzy inference engine to obtain the PID parameter adjustment amount.

[0040] Load torque variation rate Specifically, the load torque observation value can be understood as the load torque caused by material resistance, disc fouling, etc., and the load torque change rate serves as a quantitative indicator of the dynamic trend of the disturbance.

[0041] Conventional PID controllers rely solely on error feedback for adjustment, resulting in a response lag behind sudden load changes, such as step changes in feed flow. This invention, by injecting the load torque change rate as a feedforward signal into the controller, generates a compensating torque in advance. This torque can counteract disturbances before the speed error increases significantly.

[0042] Compensating torque .in, The feedforward gain is generally obtained based on the ratio of the rotor system's moment of inertia to the motor's torque constant (rotor system moment of inertia / motor torque constant).

[0043] S3 corrects the PID control parameters based on the PID parameter adjustment amount and adjusts the speed of the disc centrifuge in real time based on the PID control parameters.

[0044] For the fuzzy inference engine, its membership function can be Gaussian to accommodate nonlinear mappings. For example, a preset self-adjusting rule base for parameters includes: IF Zhengda AND Zhengda THEN (Increase anti-interference capabilities in advance) IF Negative small AND Negative THEN (Suppressing oscillations caused by sudden changes in viscosity) in, These represent the proportional gain adjustment, integral gain adjustment, and derivative gain adjustment, respectively, while H and M represent the specific PID parameter adjustment values. These represent the rotational speed error and the rate of change of error, respectively. .

[0045] In summary, the proposed disc centrifuge speed regulation method, by introducing the load torque change rate and friction coefficient change as inputs to the fuzzy inference engine and using the load torque change rate as a disturbance feedforward term, can enhance the adaptability to operating conditions and overcome the shortcomings of traditional PID control, such as fixed PID parameters, difficulty in adapting to changing operating conditions, and easy overshoot or slow response.

[0046] In one embodiment, such as Figure 3 As shown, the specific method for correcting PID control parameters based on PID parameter adjustments includes the following steps: S31, Obtain the proportional reference gain and proportional gain adjustment amount .

[0047] S32 corrects the proportional base gain based on the proportional gain adjustment to obtain the PID proportional gain.

[0048] For example, the final PID proportional gain .in, This represents the proportional gain weighting coefficient, typically between 0.3 and 0.5. Too large a value leads to oscillation, while too small a value results in a sluggish response. The proportional reference gain is used to provide basic stiffness and resist steady-state disturbances. Used to dynamically enhance anti-disturbance capabilities based on fuzzy rules.

[0049] like Figure 4 As shown, the specific method for correcting PID control parameters based on PID parameter adjustments also includes the following steps: S33, Obtain the integral reference gain and integral gain adjustment .

[0050] S34, perform integral saturation suppression on the integral reference gain based on the rotational speed error.

[0051] S35 corrects the integral reference gain for integral saturation suppression based on the integral gain adjustment to compensate for the phase lag caused by viscosity abrupt changes and obtain the PID integral gain.

[0052] For example, the final PID integral gain .in, This is the integral gain weighting coefficient, used to control the attenuation slope; the default value is 0.05. (Denominator) In this process, the larger the error, the smaller the integral gain, in order to suppress integral saturation. Used to compensate for phase hysteresis caused by sudden changes in viscosity.

[0053] like Figure 5As shown, the specific method for correcting PID control parameters based on PID parameter adjustments also includes the following steps: S36, Obtain the differential reference gain and differential gain adjustment .

[0054] S37, the differential gain adjustment is corrected based on the absolute value of the load torque change rate so that the correction to the differential reference gain decreases as the disturbance increases.

[0055] For example, the final PID derivative gain Here, the auto-ignition exponential function is used. When the absolute value of the load torque change rate increases, When the load torque rate of change is approximately zero, the differential gain is reduced to avoid amplification of high-frequency noise. The fundamental differential gain is retained when the absolute value of the load torque rate of change is approximately zero. .

[0056] Generally speaking, when the final PID proportional gain When this occurs, an alarm is triggered to prevent mechanical overload caused by abnormal parameters.

[0057] In summary, by using the proportional term to enhance dynamic stiffness, the integral term to resist nonlinear saturation, and the differential term to adapt to disturbances, the contradiction between speed and stability of the disc centrifuge under varying operating conditions is resolved. In actual deployment, it can be combined with a real-time monitoring system such as vibration sensors and current sampling, and the weighting coefficients α, β, and γ can be dynamically adjusted to achieve optimal control throughout the entire life cycle.

[0058] In one embodiment, such as Figure 6 As shown, the disc centrifuge speed adjustment method further includes the following steps: S4, obtain the disc material yield strength, disc material density, and the difference between the inner and outer diameters of the disc.

[0059] S5, based on the yield strength of the disc material Disc material density and the difference between the inner and outer diameters of the disc Obtain the safe maximum rotation speed.

[0060] For the yield strength of the disc material, high-temperature compensation can be performed. Specifically, the yield strength of the disc material at the standard temperature is first obtained. Then according to the formula Where T represents the real-time temperature.

[0061] The disc centrifuge speed adjustment method further includes the following steps: obtaining the load torque observation value change rate; when the load torque observation value change rate is greater than a first preset torque threshold and the duration is greater than a first time threshold, and the speed change rate is less than a first preset speed threshold and the duration is greater than a second time threshold, it is determined that the load is abnormal due to disc scaling.

[0062] For example, the upper limit of safe speed. Where g is the acceleration due to gravity.

[0063] When the rate of change of the load torque observation is greater than 50 N·m / s and the duration is greater than 5 seconds, and the rate of change of the speed... If the speed is 20 rpm / s for more than 3 seconds, it is determined that the abnormal load is caused by disk scaling. At this time, an alarm can be triggered, and the actual operating speed can be switched to the upper limit of the safe speed to avoid excessive rotor stress.

[0064] When the actual operating speed exceeds 1.5 times the upper limit of the safe speed, the power source should be immediately cut off and the hydraulic brake should be activated to achieve emergency braking.

[0065] An embodiment of the present invention also provides an adaptive fuzzy PID control disc centrifuge speed regulation system, used to implement the adaptive fuzzy PID control disc centrifuge speed regulation method, which includes a parameter acquisition module, a fuzzy inference engine and a control module.

[0066] The parameter acquisition module is used to acquire the speed error, error change rate, load torque change rate, and friction coefficient change; the fuzzy inference engine is used to acquire the PID parameter adjustment amount by using the speed error, error change rate, load torque change rate, and friction coefficient change amount as input variables; the control module is used to correct the PID control parameters according to the PID parameter adjustment amount and adjust the speed of the disc centrifuge in real time according to the PID control parameters.

[0067] The parameter acquisition module includes a speed change rate acquisition unit, an inertia term acquisition unit, a torque residual acquisition unit, and a change quantity acquisition unit.

[0068] The speed change rate acquisition unit is used to collect the actual speed of the centrifuge and the output torque of the motor in real time, and obtain the speed change rate of the centrifuge based on the actual speed of the centrifuge; the inertia term acquisition unit is used to obtain the rotational inertia of the rotor system, and obtain the inertia term based on the speed change rate of the centrifuge and the rotational inertia of the rotor system.

[0069] The torque residual acquisition unit is used to acquire the load torque observation value and obtain the torque residual based on the motor output torque, inertia term and load torque observation value; the change acquisition unit is used to integrate the product of torque residual and centrifuge actual speed to obtain the friction coefficient estimate and obtain the friction coefficient change based on the friction coefficient estimate.

[0070] For example, the change in the coefficient of friction is expressed as ;in, The values ​​are, in order, the motor output torque, the rotor system moment of inertia, the centrifuge actual speed, and the observed load torque. Represents the inertial term. Represents torque residual. Represents the adaptive gain coefficient. This represents the estimated value of the friction coefficient.

[0071] For adaptive gain coefficients, to ensure Lyapunov stability, the following conditions generally need to be met. ,in, Indicates the maximum permissible speed, recommended. , This is the rated speed.

[0072] When ω is high, the integral gain increases, which can quickly track changes in viscosity; when ω is low, integral saturation is suppressed, which can prevent overcompensation.

[0073] For the fuzzy inference engine, its membership function can be Gaussian to accommodate nonlinear mappings. For example, a preset self-adjusting rule base for parameters includes: Rule 1: IF Zhengda AND Zhengda THEN (Increase immunity to interference in advance), for example, IF Zhengda AND Zhengda THEN In this way, the proportional gain can be enhanced to resist disturbances before the speed drops further.

[0074] Rule 2: IF Negative small AND Negative THEN (Suppressing oscillations caused by sudden viscosity changes), for example, IF Negative small AND Negative THEN Thus, as viscosity decreases, system damping decreases, and resonance can be avoided by suppressing the differential term.

[0075] Other preset parameter self-adjustment rules can be set with reference to control targets such as error slowing down, significantly weakening differential vibration prevention when viscosity drops sharply, strengthening full gain when the speed is seriously low and continues to deteriorate, and suppressing reverse full gain when the speed is seriously high and continues to deteriorate. These will not be elaborated on here.

[0076] in, These represent the proportional gain adjustment, integral gain adjustment, and derivative gain adjustment, respectively, while H and M represent the specific PID parameter adjustment values. These represent the rotational speed error and the rate of change of error, respectively. .

[0077] The input space is divided into 125 regions (5 language values ​​× 5 variables) to ensure full coverage of operating conditions: ={Negative large, negative small, zero, positive small, positive large} ={Negative large, negative small, zero, positive small, positive large} ={Negative large, negative small, zero, positive small, positive large} ={Negative large, negative small, zero, positive small, positive large} for The scope and control effects are shown in the table below:

[0078] In summary, the disc centrifuge speed regulation system, by introducing the load torque change rate and friction coefficient change as inputs to the fuzzy inference engine and using the load torque change rate as a disturbance feedforward term, can enhance the adaptability to operating conditions and overcome the defects of traditional PID control, such as fixed PID parameters, difficulty in adapting to changing operating conditions, and easy overshoot or slow response.

[0079] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0080] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this invention patent should be determined by the appended claims.

Claims

1. A method for speed regulation of a disc centrifuge using adaptive fuzzy PID control, characterized in that, The method for adjusting the speed of the disc centrifuge includes the following steps: Obtain the speed error, error change rate, load torque change rate, and friction coefficient change; A fuzzy inference engine is constructed based on a preset parameter self-adjustment rule base. The speed error, error change rate, load torque change rate, and friction coefficient change are used as input variables of the fuzzy inference engine to obtain the PID parameter adjustment amount. The PID control parameters are adjusted based on the PID parameter adjustment amount, and the speed of the disc centrifuge is adjusted in real time based on the PID control parameters.

2. The method for adjusting the speed of a disc centrifuge using adaptive fuzzy PID control as described in claim 1, characterized in that, The specific method for obtaining the change in the coefficient of friction includes the following steps: Real-time acquisition of centrifuge actual speed and motor output torque; obtaining centrifuge speed change rate based on centrifuge actual speed. Obtain the moment of inertia of the rotor system, and obtain the inertial term based on the centrifuge speed change rate and the moment of inertia of the rotor system; Obtain the load torque observation value, and obtain the torque residual based on the motor output torque, inertia term, and load torque observation value; Integrate the product of the torque residual and the actual speed of the centrifuge to obtain an estimated value of the friction coefficient, and obtain the change in friction coefficient based on the estimated value.

3. The method for adjusting the speed of a disc centrifuge using adaptive fuzzy PID control as described in claim 2, characterized in that, The specific method for correcting PID control parameters based on PID parameter adjustments includes the following steps: Obtain the proportional reference gain and the proportional gain adjustment amount; The proportional base gain is corrected based on the proportional gain adjustment to obtain the PID proportional gain.

4. The method for adjusting the speed of a disc centrifuge using adaptive fuzzy PID control as described in claim 3, characterized in that, The specific method for correcting PID control parameters based on PID parameter adjustments also includes the following steps: Obtain the integral reference gain and the integral gain adjustment amount; Integral saturation suppression is applied to the integral reference gain based on the rotational speed error; The integral reference gain for integral saturation suppression is corrected based on the integral gain adjustment to compensate for the phase lag caused by viscosity abrupt changes, thereby obtaining the PID integral gain.

5. The method for adjusting the speed of a disc centrifuge using adaptive fuzzy PID control as described in claim 4, characterized in that, The specific method for correcting PID control parameters based on PID parameter adjustments also includes the following steps: Obtain the differential reference gain and the differential gain adjustment amount; The differential gain adjustment is corrected based on the absolute value of the load torque change rate so that the correction to the differential reference gain decreases as the disturbance increases.

6. The method for adjusting the speed of a disc centrifuge using adaptive fuzzy PID control as described in claim 5, characterized in that, The disc centrifuge speed adjustment method further includes the following steps: Obtain the yield strength, density, and inner-outer diameter difference of the disc material; The upper limit of safe rotation speed is determined based on the yield strength of the disc material, the density of the disc material, and the difference between the inner and outer diameters of the disc.

7. The method for adjusting the speed of a disc centrifuge using adaptive fuzzy PID control as described in claim 6, characterized in that, The disc centrifuge speed adjustment method further includes the following steps: Obtain the rate of change of the load torque observation; When the rate of change of the load torque observation is greater than the first preset torque threshold and the duration is greater than the first time threshold, and the rate of change of the speed is less than the first preset speed threshold and the duration is greater than the second time threshold, it is determined that the load is abnormal due to disk scaling.

8. An adaptive fuzzy PID control disc centrifuge speed regulation system, used to implement the adaptive fuzzy PID control disc centrifuge speed regulation method as described in any one of claims 1-7, characterized in that, The disc centrifuge speed regulation system includes: The parameter acquisition module is used to acquire speed error, error change rate, load torque change rate, and friction coefficient change. A fuzzy inference engine is used to obtain PID parameter adjustment values ​​by taking speed error, error change rate, load torque change rate, and friction coefficient change as input variables. The control module is used to correct the PID control parameters based on the PID parameter adjustment amount, and to adjust the speed of the disc centrifuge in real time based on the PID control parameters.

9. The adaptive fuzzy PID control speed regulation system for a disc centrifuge as described in claim 8, characterized in that, The parameter acquisition module includes: The speed change rate acquisition unit is used to collect the actual speed of the centrifuge and the output torque of the motor in real time, and to obtain the speed change rate of the centrifuge based on the actual speed of the centrifuge. The inertia term acquisition unit is used to acquire the rotational inertia of the rotor system, and to acquire the inertia term based on the centrifuge speed change rate and the rotational inertia of the rotor system. The torque residual acquisition unit is used to acquire the load torque observation value and obtain the torque residual based on the motor output torque, inertia term and load torque observation value; The change acquisition unit is used to integrate the product of the torque residual and the actual speed of the centrifuge to obtain an estimated value of the friction coefficient, and to obtain the change in the friction coefficient based on the estimated value of the friction coefficient.

10. The adaptive fuzzy PID control speed regulation system for a disc centrifuge as described in claim 9, characterized in that, The change in the friction coefficient is expressed as ; in, The values ​​are, in order, the motor output torque, the rotor system moment of inertia, the centrifuge actual speed, and the observed load torque. Represents the inertial term. Represents torque residual. Represents the adaptive gain coefficient. This represents the estimated value of the friction coefficient.

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