A control method and device for a high-speed motor and electromagnetic bearing system

Abstract

The application belongs to the technical field and discloses a control method and equipment of a high-speed motor and an electromagnetic bearing system, the method comprising the following steps: selecting input variables and output variables of a fuzzy controller; fuzzifying the input variables and the output variables, determining a quantization factor, a basic domain and a fuzzy domain; defining fuzzy subsets and membership functions in the fuzzy domain of the input variables and the output variables; calculating the membership degrees through the membership functions; substituting the membership degrees into a fuzzy value formula to obtain fuzzy values of the output variables, obtaining accurate control amounts of the output variables through defuzzification; and outputting the accurate control amounts of the output variables to an electromagnetic bearing model for control. The method can effectively reduce the oscillation and vibration of the system, improve the stability of the overall system, and adapt to large disturbances or complex environments.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of active magnetic suspension bearings, and particularly relates to a control method and equipment for a high-speed motor and an electromagnetic bearing system. BACKGROUND

[0002] The combination of a high-speed motor and an electromagnetic bearing (AMB) is an important technical solution, especially in situations where high precision, speed and reliability are required. The magnetic suspension bearing system is an open-loop unstable system, so it needs to be controlled in a closed loop. However, there is strong nonlinearity, parameter uncertainty and external disturbance in the magnetic suspension bearing system, and the control system needs to overcome these factors to enable the magnetic suspension bearing to exert its various advantages.

[0003] A granted patent with the name of a fuzzy PID control optimization method for a magnetic suspension flywheel motor, with the patent number CN113009834B, includes the following steps: determining input variables, output variables and corresponding change ranges for a fuzzy PID controller according to a control model of the magnetic suspension flywheel motor; designing initial parameters of fuzzy rules; obtaining output quantities through fuzzy reasoning; processing the output displacement and speed as a function of the scaling factor parameter τ; obtaining the displacement and speed readings at the current time and the previous time, and updating the scaling factor parameter τ through the gradient descent formula. Although the patent application also uses a fuzzy PID control method, the patent application cannot adapt to the high-speed motor and electromagnetic bearing system. SUMMARY

[0004] In order to overcome the problems existing in the prior art, the purpose of the present application is to provide a control method and equipment for a high-speed motor and electromagnetic bearing system, which provides a simple solution through fuzzy PID, thereby reducing the oscillation and vibration phenomenon of the system and adapting to the nonlinear characteristics of the motor control system.

[0005] To achieve the above purpose, the technical scheme adopted by the present application is as follows:

[0006] In a first aspect, the present application provides a control method for a high-speed motor and electromagnetic bearing system, comprising the following steps:

[0007] Selecting input variables and output variables of the fuzzy controller;

[0008] Fuzzifying the input variables and output variables, determining the quantization factor, the basic universe and the fuzzy universe; defining fuzzy subsets and membership functions in the fuzzy universe of the input variables and output variables;

[0009] Calculating the membership degree through the membership function;

[0010] The membership degree is substituted into the fuzzy value formula to obtain the fuzzy value of the output variable, and through defuzzification, the accurate control amount of the output variable is obtained.

[0011] The accurate control amount of the output variable is output to the electromagnetic bearing model for control.

[0012] Optionally, the input variable of the fuzzy controller is a rotor vibration signal and its rate of change collected by an eddy current displacement sensor.

[0013] Optionally, the fuzzy domains of the input variable and the output variable are both [-6, 6].

[0014] Optionally, a Mamdani reasoning type fuzzy controller is used for fuzzy reasoning.

[0015] Optionally, a centroid method is used for defuzzification.

[0016] Optionally, the high-speed motor and electromagnetic bearing system comprises a high-speed magnetic suspension rotor model, an input end of the high-speed magnetic suspension rotor model is connected with an electromagnetic bearing model, an input end of the electromagnetic bearing model is connected with a power amplifier, and the output variable of the fuzzy controller is a power amplifier control signal.

[0017] In a second aspect, the application provides a control system of a high-speed motor and electromagnetic bearing system, comprising:

[0018] a range selection module for selecting input variables and output variables of a fuzzy controller;

[0019] a fuzzification processing module for fuzzifying the input variables and the output variables, determining a quantization factor, a basic domain and a fuzzy domain, and defining fuzzy subsets and membership functions in the fuzzy domain of the input variables and the output variables;

[0020] a first calculation module for calculating the membership degree through the membership function;

[0021] a second calculation module for substituting the membership degree into a fuzzy value formula to obtain the fuzzy value of the output variable, and through defuzzification, obtaining the accurate control amount of the output variable;

[0022] an output module for outputting the accurate control amount of the output variable to the electromagnetic bearing model for control.

[0023] In a third aspect, the application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the control method of the high-speed motor and electromagnetic bearing system when executing the computer program.

[0024] In a fourth aspect, the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the control method of the high-speed motor and the electromagnetic bearing system.

[0025] In a fifth aspect, the present application provides a computer program product comprising a computer readable medium, which contains computer readable program code, and the program code executes the control method of the high-speed motor and the electromagnetic bearing system.

[0026] Compared with the prior art, the present application has the following beneficial effects:

[0027] The present application provides a control method and device of a high-speed motor and an electromagnetic bearing system, which can well adapt to the nonlinear characteristics of the motor control system by using an intelligent control algorithm. The fuzzy PID control does not depend on an accurate mathematical model, which provides a simple solution for the motor control, especially in the case where the model is difficult to obtain or complex. The fuzzy PID control can effectively reduce the oscillation and vibration of the system, improve the stability of the overall system, and adapt to the case of large disturbance or complex environment. BRIEF DESCRIPTION OF DRAWINGS

[0028] The drawings described herein are for illustrative purposes only and are not intended to limit the scope of the present application in any way.

[0029] In the drawings:

[0030] Figure 1 is a principle block diagram of the high-speed motor and the electromagnetic bearing system of the present application;

[0031] Figure 2 is a diagram of a radial four-degree-of-freedom active electromagnetic bearing-rigid rotor system;

[0032] Figure 3 is a diagram of the membership function of the input and output variables of embodiment 1 of the present application;

[0033] Figure 4 is a characteristic surface diagram of the input and output variables of embodiment 1 of the present application;

[0034] Figure 5 is a rotor vibration x A direction displacement diagram of embodiment 1 of the present application;

[0035] Figure 6 is a rotor vibration x B direction displacement diagram of embodiment 1 of the present application;

[0036] Figure 7 is a rotor vibrationy A directional displacement map;

[0037] Figure 8 is the rotor vibration of embodiment 1 of the present invention y B directional displacement map. DETAILED DESCRIPTION

[0038] For those skilled in the technical field of the present technology, the technical solutions in the present invention will be better understood. The technical solutions in the embodiments of the present invention will be described clearly and completely below in combination with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present invention.

[0039] 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 belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0040] It should be noted that in the claims the reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unitary claim, several of the devices claimed in conjunction can be embodied by one and the same item of hardware. The word "first", "second", "third", etc. does not imply any order. These terms are used to name different elements.

[0041] Furthermore, the terms "first", "second", etc. are used herein only to describe different instances of an element and do not imply any order or sequence. The use of these terms is not meant to, nor does it, restrict the number of elements that can comprise the element. The term "plurality" is used herein to describe a number of elements that is greater than one. The term "set" is used herein to describe a number of elements that is greater than one.

[0042] The present invention will be described in detail below with reference to the drawings.

[0043] The present invention provides a control method of a high-speed motor and an electromagnetic bearing system, comprising the following steps:

[0044] Selecting input variables and output variables of the fuzzy controller;

[0045] Fuzzifying the input variables and the output variables, determining quantization factors, basic domains and fuzzy domains; defining fuzzy subsets and membership functions in the fuzzy domains of the input variables and the output variables;

[0046] Calculating the membership degrees through the membership functions;

[0047] Substituting the membership degrees into the fuzzy value formula to obtain the fuzzy value of the output variable, and obtaining the accurate control amount of the output variable through defuzzification;

[0048] Outputting the accurate control amount of the output variable to the electromagnetic bearing model for control.

[0049] The intelligent control algorithm is adopted, and the nonlinear characteristics of the motor control system can be well adapted. The fuzzy PID control does not depend on an accurate mathematical model, and provides a simple solution. The fuzzy PID control can effectively reduce the oscillation and vibration phenomenon of the system, and improve the stability of the overall system.

[0050] Example 1

[0051] Proportional Integral Derivative (PID) as a classic control method, because of its simple structure, easy to realize and convenient parameter adjustment, is widely used in various control systems. PID obtains accurate control action through accurate proportional-integral-derivative operation, and acts on the magnetic suspension bearing to achieve stable suspension effect, thereby realizing optimization of system performance. PID is usually used as a main controller in active magnetic bearing-rigid rotor system to ensure system stability.

[0052] Fuzzy Logic Control (FLC) is a computer digital control technology based on fuzzy set theory, fuzzy language variables and fuzzy logic reasoning. The implementation of fuzzy control mainly includes fuzzification, knowledge base, logical judgment and defuzzification. Fuzzy logic control regards the controlled system as a "black box", and the controller learns the system characteristics according to the response of the input and output, and adjusts the controller parameters in real time according to the control target, which is very suitable for complex nonlinear system control.

[0053] When the controlled object has uncertain factors or the model parameters change greatly, the PID control effect has certain limitations, and the parameter setting process and the principles followed are not clear, and many times it is debugged by experience. Simple PID control cannot meet the increasingly complex application requirements. Adding fuzzy control on the basis of traditional PID control can be used to realize active control of active magnetic bearing-rigid rotor system.

[0054] Step 1, analyze the composition of active magnetic bearing-rigid rotor system, and establish a model for four-degree-of-freedom active magnetic bearing-rigid rotor system;

[0055] Figure 2 For a typical radial four-degree-of-freedom active magnetic bearing-rigid rotor system.

[0056] When the real-time position of the rotor deviates from the target position, the controller will accept the real-time position signal of the rotor returned by the displacement sensor, and send a control signal according to the set algorithm, which is amplified by the power amplifier to drive the electromagnetic bearing, adjust the size of the electromagnetic force, and thus real-time correct the position of the rotor, so that it can be stably suspended at the ideal position.

[0057] In Figure 2 , the relevant planes and coordinate systems are defined. Assuming that the center planes of the two end AMBs-A and AMBs-B are and , respectively. The center of mass of the balanced rotor is C Due to symmetry, the center of mass C must be located on the geometric center line of the rotor, passing through point to make a plane parallel to the center planes of the two end AMBs and , The plane intersects the geometric center line of the stator at point. The distance from the point to the center planes of the two end AMBs and is l a and l b , and the distance between the planes and is . A fixed coordinate system is established, wherein, the x-axis is the rotation axis, , and form a right-hand system. Then the motion state of the rotor can be described by the translational displacement of the center of mass of the rotor in the and directions x , y and the angular displacement of the rotor around the and axes , .

[0058] By using rotor dynamics theory, the differential equations of AMBs-rigid rotor system during acceleration process can be obtained as:

[0059] Equation 1

[0060] In Equation 1, is the rotor mass; and J are the moments of inertia of the rotor about and about or axes, respectively; and are the unbalance mass and eccentricity, respectively; are the electromagnetic forces of the two AMBs in and directions, respectively.

[0061]

[0062] Equation 2

[0063] In Equation 2, , , are the generalized mass matrix, gyroscopic matrix and force arm coefficient matrix of the system, respectively; is the acceleration vector; is the velocity vector; are the electromagnetic force vectors of the radial AMBs at A and B ends in x and y directions, respectively; is the generalized unbalance vector of the system.

[0064] wherein the generalized mass matrix and gyroscopic matrix of the rotor system are

[0065] ,

[0066] wherein, is the rotor mass; and are the moments of inertia of the rotor about z and about x or y axes, respectively.

[0067] The force arm coefficient matrix of the rotor system and the generalized unbalance vector of the system are

[0068]

[0069]

[0070] wherein, and is the force arm coefficient; and are the unbalance mass and eccentricity, respectively.

[0071] A and B end radial AMBs generate electromagnetic force vectors in x and y directions, respectively, as

[0072]

[0073] where, are the electromagnetic forces of the two AMBs in x and y directions, respectively.

[0074] The linearized electromagnetic force of AMBs in the differential drive mode can be expressed as

[0075] Equation 3

[0076] In Equation 3, is the current stiffness coefficient matrix of AMBs; is the displacement stiffness coefficient matrix of AMBs; is the displacement vector at the sensor position; is the electromagnetic force matrix when the rotor is in the balanced position; is the control current vector; the control current vector will be determined by the control strategy.

[0077] Step 2: Analyze the influence of the fuzzy PID controller on the stability of the rotor system, analyze the working principle of the fuzzy PID controller in the active magnetic bearing-high speed motor and electromagnetic bearing system, and design the fuzzy control of the electromagnetic bearing-rigid rotor system.

[0078] AMBs-high speed motor and electromagnetic bearing system itself is an unstable strong nonlinear system, and its mathematical model is not easy to accurately obtain, therefore, as a classical nonlinear control method, fuzzy control can be used to realize the active control of AMBs-high speed motor and electromagnetic bearing system.

[0079] The realization of fuzzy control mainly includes fuzzification, knowledge base, logical judgment and defuzzification, and its working principle in AMBs-high speed motor and electromagnetic bearing system is: taking the rotor vibration information and vibration rate as input signals, fuzzifying them to obtain fuzzy quantities, obtaining fuzzy sets through fuzzy reasoning, then defuzzifying them into clear quantities of control power amplifier current size, and then realizing the active control of AMBs-high speed motor and electromagnetic bearing system, as shown in Figure 1 .

[0080] At present, the control strategies of AMBs-rigid rotor system are simply divided into two kinds, one is the traditional fixed parameter PID controller, the most common one is PID control; the other is the variable parameter controller with strong robustness, including fuzzy PID control, sliding mode control, robust controller.

[0081] Firstly, the range of PID parameters is studied under the stable operation of the system.

[0082] The transfer function of the controlled object of AMBs-rigid rotor system is expressed as:

[0083]

[0084] where, is the transfer function of the controlled object; is the rotor mass; is the current stiffness coefficient, is the displacement stiffness coefficient.

[0085] The closed-loop transfer function of AMBs-rigid rotor system under PID control is:

[0086]

[0087] where, is the transfer function of the closed-loop controller; is the transfer function of the controlled object; is the rotor mass; is the current stiffness coefficient, is the displacement stiffness coefficient; , , are the proportional, integral and derivative link coefficients respectively.

[0088] Therefore, the characteristic equation of the system is obtained as:

[0089]

[0090] where, is the rotor mass; , , are the proportional, integral and derivative link coefficients respectively; is the current stiffness coefficient, is the displacement stiffness coefficient;

[0091] According to Routh criterion, the sufficient and necessary condition for system stability is:

[0092]

[0093] where, M is the mass of the rotor; , , Kp, Ki and Kd are the proportional, integral and derivative coefficients, respectively; Kt is the current stiffness coefficient, Kd is the displacement stiffness coefficient;

[0094] The range of PID parameters for stabilizing the AMBs-rigid rotor system is obtained.

[0095] Step 3, the range of fuzzy PID parameters for stabilizing the AMBs-rigid rotor system is studied, and then the stability of the system under the control of the fixed parameter PID parameters is studied;

[0096] The design steps of the fuzzy control in the AMBs-high speed motor and electromagnetic bearing system are as follows:

[0097] 1) The input variables and the output variable of the fuzzy controller are selected.

[0098] For the active electromagnetic bearing-rigid rotor system, the input variables of the fuzzy controller are the rotor vibration signals collected by the eddy current displacement sensor x a and the change rate thereof, and the output variable is the power amplifier control signal.

[0099] 2) The input variables and the output variable are fuzzified, and the quantization factor, the basic domain and the fuzzy domain are determined. According to the change range of the output voltage of the eddy current displacement sensor corresponding to the change range of the rotor vibration displacement, the basic domain of the rotor vibration signal and the change rate of the rotor vibration and the corresponding quantization factor are determined.

[0100] The fuzzy domain of the input variables E and R and the output variable U are all [-6, 6].

[0101] In the actual active electromagnetic bearing-rigid rotor system, the change range of the rotor vibration signal x a is ±0.3 mm, and the change range of the output voltage of the eddy current displacement sensor is 6 V, so the basic domain of x a is [-0.003, 0.003], and the corresponding quantization factor is k 1=2000; the basic domain of the change rate of the rotor vibration r xa is [-0.003, 0.003], and the corresponding quantization factor is k 2=2000; the output variable is the power amplifier current, and the fuzzy variable domain thereof is selected as [-6, 6].

[0102] 3) Define fuzzy subsets and membership functions in the fuzzy universe of input and output variables.

[0103] The fuzzy subsets of input and output variables are both selected as 7, i.e. PB (positive big), PM (positive medium), PS (positive small), ZO (zero), NS (negative small), NM (negative medium) and NB (negative big), and triangular membership functions are selected to define them.

[0104] 4) Fuzzy control rules

[0105] The proper fuzzy control rules determine the control performance of the active magnetic bearing-rigid rotor system. According to the expert experience and theoretical analysis, the relationship between the input and output variables of the fuzzy controller is obtained. For example, when the rotor vibration x a is much smaller than the reference position r xa , the corresponding error signal E is PB (positive big), and the control variable corresponds to the maximum value to ensure that the rotor position quickly approaches the reference position; when the rotor vibration x a is much larger than the reference position r a , the control variable corresponds to the minimum value. As the rotor vibration decreases, the vibration error signal E is PS (positive small), at which time the output should not be too large in order to accelerate the rotor to a stable speed, so the output variable is PS (positive small). The control rule table shown in Table 1 can be obtained according to the above method in other control processes. In addition, Figure 3 and Figure 4 the membership function graphs of the input and output variables and their characteristic surface graphs are given.

[0106] Table 1

[0107]

[0108] In Table 1, E is the rotor vibration error, R is the rotor vibration error rate, PB, PM, PS, ZO, NS, NM and NB describe the state level of the input and output variables of the fuzzy controller, representing positive big, positive medium, positive small, zero, negative small, negative medium and negative big, respectively.

[0109] 5) Fuzzy reasoning and defuzzification

[0110] The Mamdani reasoning type fuzzy controller is adopted, such as the rotor vibration error E and its rate of change R .The fuzzy values of E and R are 3 and -3, respectively, and E and R belong to (PS, PM) and (NM, NS), respectively. Therefore, the fuzzy rules for the two input variables are as follows according to Table 1:

[0111] Rule 1: If E is PS and R is NM, then U o is NS

[0112] Rule 2: If E is PS and R is NS, then U o is ZO

[0113] Rule 3: If E is PM and R is NM, then U o is ZO

[0114] Rule 4: If E is PM and R is NS, then U o is PM

[0115] The fuzzy values of E and R can be calculated by Mamdani reasoning as follows: U U 1 is:

[0116] Equation 4

[0117] Equation 5

[0118] where "min" and "max" represent the minimum and maximum values, respectively; represents the fuzzy value of E in Rule ; U is an input or output variable; and U1 is the fuzzy output value of U. i Equation 6 U

[0119] For example, Rule 1 is used to explain Equation (6). When the input E = 3, according to the membership function of E, the membership degree of the fuzzy language variable PS is 0.5, i.e. E

[0120] Equation 7

[0121] When R =-3, according to the membership function of R, the membership degree of the fuzzy language variable NM is also 0.5, i.e. R

[0122] ​​​​​ Formula 7

[0123] In combination with formula (4), formula (6) and formula (7), it is known that the fuzzy value of the fuzzy output under the condition of rule 1 is: U

[0124] Formula 8

[0125] The accurate control amount of the power amplifier current is obtained by the barycentric method.

[0126] Embodiment 2

[0127] As shown in Figure 1 , a high-speed motor and an electromagnetic bearing system used in this embodiment are shown. In the fuzzy controller, the error E, the error rate R and the output Δ k p of the fuzzy controller are fuzzified. k d k i

[0128] According to the established fuzzy control rule table, the fuzzy relationship equation is solved by the fuzzy reasoning of the fuzzy input variables E and R after the minimum operation, and the fuzzy output quantity Ui of the system is obtained. The accurate output quantity within the range of the output fuzzy domain is obtained by the defuzzification of the weighted average method, and then the accurate output quantity within the range of the output fuzzy domain is converted into the actual output control quantity by the scale transformation, and then the actual output control quantity is converted into the control current by the power amplifier, and the current of the coil on the electromagnet is adjusted in real time, so that the rotor is stably suspended.

[0129] In this embodiment, the characteristics of the rotor system based on fuzzy PID control are verified by simulation, and the influence of AMBs-high-speed motor and electromagnetic bearing system stability is verified.

[0130] The MATLAB / Simulink function is used for dynamic simulation of the system, and the influence of the fuzzy PID controller on the translational and conical modalities of the active magnetic bearing (AMBs)-rotor system is studied, and the feasibility of the algorithm is verified.

[0131] In the simulink environment, the fuzzy PID controller is built, the rotor vibration information and the vibration rate are taken as input signals, the fuzzy quantity is obtained by fuzzification, the fuzzy set is obtained by fuzzy reasoning, and then it is converted into accurate control quantity by defuzzification, so as to adjust the proportional value Δ k p , the integral value Δ k i and the differential value Δ k d ​​​As the system output, the AMBs-high speed motor and electromagnetic bearing system is actively controlled to verify the optimization effect of the control algorithm.

[0132] The rotor vibration of the AMBs-rigid rotor system in this embodiment x A The direction displacement simulation diagram is shown in Figure 5 , wherein the maximum displacement under the PID and fuzzy PID control is 1.5950 and 1.4333 respectively, and the rotor vibration y A The direction displacement simulation diagram is shown in Figure 6 , wherein the maximum displacement under the PID and fuzzy PID control is 1.5925 and 1.4315 respectively, and the rotor vibration x B The direction displacement simulation diagram is shown in Figure 7 , wherein the maximum displacement under the PID and fuzzy PID control is 1.6672 and 1.4870 respectively, and the rotor vibration y B The direction displacement simulation diagram is shown in Figure 8 , wherein the maximum displacement under the PID and fuzzy PID control is 1.6699 and 1.4888 respectively, and it can be seen that the effect of the fuzzy PID control on optimizing the rotor stability is very obvious.

[0133] Embodiment 3

[0134] Based on the method of embodiment 1, a control system of a high speed motor and electromagnetic bearing system is disclosed, comprising:

[0135] a range selection module for selecting the input variable and the output variable of the fuzzy controller;

[0136] a fuzzification processing module for fuzzifying the input variable and the output variable, determining the quantization factor, the basic universe and the fuzzy universe; defining the fuzzy subsets and the membership functions in the fuzzy universe of the input variable and the output variable;

[0137] a first calculation module for calculating the membership degree through the membership function;

[0138] a second calculation module for substituting the membership degree into the fuzzy value formula to obtain the fuzzy value of the output variable, and obtaining the accurate control amount of the output variable through defuzzification;

[0139] an output module for outputting the accurate control amount of the output variable to the electromagnetic bearing model for control.

[0140] Embodiment 4

[0141] The embodiment aims to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the control method of the high-speed motor and the electromagnetic bearing system when executing the computer program.

[0142] Embodiment 5

[0143] The embodiment aims to provide a computer readable storage medium, which stores a computer program, and the computer program implements the control method of the high-speed motor and the electromagnetic bearing system when executed by a processor.

[0144] Embodiment 6

[0145] The embodiment aims to provide a computer program product comprising a computer readable medium, and the computer readable medium comprises computer readable program code, and the program code implements the control method of the high-speed motor and the electromagnetic bearing system.

[0146] The steps and methods involved in the above embodiments 3, 4, 5 and 6 correspond to embodiment 1, and the specific embodiments can refer to the relevant description part of embodiment 1.

[0147] Those skilled in the art of the present technology should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can be in the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0148] The present application is described with reference to flowcharts and / or block diagrams according to the method, device (system), and computer program product of the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to produce a machine, so that the instructions executed by the computer or other programmable data processing devices produce a device that implements the functions specified in the flowcharts and / or block diagrams. Figure 1 The device that implements the functions specified in one flow or multiple flows and / or blocks Figure 1 The device that implements the functions specified in one flow or multiple flows and / or blocks

[0149] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instructions which implement the flow Figure 1 The functions specified in the flow or flows and / or blocks Figure 1 The functions specified in the flow or flows and / or blocks

[0150] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flow Figure 1 The functions specified in the flow or flows and / or blocks Figure 1 The functions specified in the flow or flows and / or blocks

[0151] The working modes or control modes involved in the above embodiments are conventional working modes or control modes in the art unless otherwise specified.

[0152] Although the preferred embodiments of the present application have been described, those skilled in the art who understand the basic inventive concept can make additional changes and modifications to the embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application but not to limit the present application. Other modifications or equivalent replacements to the technical solutions of the present application made by those skilled in the art should be covered in the scope of the claims of the present application as long as they do not depart from the spirit and scope of the present application.

Claims

1. A control method for a high-speed motor and electromagnetic bearing system, characterized in that, Includes the following steps: Select the input and output variables of the fuzzy controller; the input variable of the fuzzy controller is the rotor vibration signal and its rate of change collected by the eddy current displacement sensor; The Mamdani inference-type fuzzy controller is used for fuzzy inference, and the input and output variables are fuzzified to determine the quantization factor, the basic universe of discourse, and the fuzzy universe of discourse. Define fuzzy subsets and membership functions in the fuzzy universes of the input and output variables; select 7 fuzzy subsets for both input and output variables, namely PB positive large, PM positive medium, PS positive small, ZO zero, NS negative small, NM negative medium, and NB negative large, and define them using triangular membership functions. ； Rotor vibration error is E， Its rate of change R； The control rules are as follows: The membership degree is calculated using the membership function. Substituting the membership degree into the fuzzy value formula yields the fuzzy value of the output variable, and the centroid method is used for defuzzification. By defuzzifying, the precise control quantity of the output variable is obtained; The precise control values ​​of the output variables are output to the electromagnetic bearing model for control. The fuzzy universe of discourse for both the input and output variables is [-6, 6]. The high-speed motor and electromagnetic bearing system includes a high-speed magnetic levitation rotor model, the input of which is connected to an electromagnetic bearing model, the input of which is connected to a power amplifier, and the output variable of the fuzzy controller is the power amplifier control signal.

2. A control system for a high-speed motor and electromagnetic bearing system, characterized in that, The high-speed motor and electromagnetic bearing system includes a high-speed magnetic levitation rotor model, the input of which is connected to an electromagnetic bearing model, and the input of which is connected to a power amplifier. The output variable of the fuzzy controller is the power amplifier control signal. The control system includes: The range selection module is used to select the input and output variables of the fuzzy controller; the input variables of the fuzzy controller are the rotor vibration signal and its rate of change collected by the eddy current displacement sensor. The fuzzification module is used for fuzzy inference using a Mamdani inference-type fuzzy controller. It fuzzifies the input and output variables, determining the quantization factor, basic universe of discourse, and fuzzy universe of discourse. Fuzzy subsets and membership functions are defined within the fuzzy universes of discourse for both input and output variables. Seven fuzzy subsets are selected for both input and output variables: PB (positive large), PM (positive medium), PS (positive small), ZO (zero), NS (negative small), NM (negative medium), and NB (negative large), and triangular membership functions are used to define them. ； Rotor vibration error is E， Its rate of change R； The control rules are as follows: The fuzzy universe of discourse for both the input and output variables is [-6, 6]. The first calculation module is used to calculate the membership degree through the membership function; The second calculation module is used to substitute the membership degree into the fuzzy value formula to obtain the fuzzy value of the output variable, and to perform defuzzification using the centroid method; through defuzzification, the precise control quantity of the output variable is obtained; The output module is used to output the precise control quantity of the output variable to the electromagnetic bearing model for control.

3. An electronic device, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the control method of the high-speed motor and electromagnetic bearing system of claim 1.

4. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the control method of the high-speed motor and electromagnetic bearing system of claim 1.

5. A computer program product comprising a computer-readable medium, characterized in that, The computer-readable medium contains computer-readable program code that executes the control method of the high-speed motor and electromagnetic bearing system of claim 1.

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