METHOD FOR CONSTRUCTING ACTIVE MAGNETIC BEARING CONTROLLER BASED ON LOOK-UP TABLE METHOD

Abstract

A method for constructing an active magnetic bearing controller based on a look-up table method includes: building finite element models of an active magnetic bearing to obtain two universal Kriging prediction models in X-axis and Y-axis directions about actual suspension forces being in association with actual displacement eccentricities and actual control currents in the X-axis and Y-axis directions of the active magnetic bearing based on a universal Kriging model; creating two model state tables in the X-axis and Y-axis directions about the actual suspension forces being in association with the actual displacement eccentricities and the actual control currents to construct two look-up table modules with the two built-in model state tables, respectively; and constructing an active magnetic bearing controller by using two fuzzy adaptive PID controllers, two amplifier modules in the X-axis and Y-axis directions, the two look-up table modules, and two measurement modules in the X-axis and Y-axis directions.

Claims

1. A method for constructing an active magnetic bearing controller based on a look-up table method, comprising the following steps: step (1): building finite element models of an active magnetic bearing, and. obtaining, by using the finite element models and based on a general universal Kriging model, two universal Kriging prediction models about actual suspension forces {circumflex over (F)}.sub.x, {circumflex over (F)}.sub.y being in association with actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 and actual control currents î.sub.x, î.sub.y in X-axis and Y-axis directions; step (2): creating, based on the two universal Kriging prediction models, two model state tables about the actual suspension forces {circumflex over (F)}.sub.x, {circumflex over (F)}.sub.y being in association with the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 and the actual control currents î.sub.x, î.sub.y to construct two corresponding look-up table modules with the two model state tables being built in, respectively; and step (3): constructing an active; magnetic bearing controller by using two fuzzy adaptive proportional-integral-derivative (PID) controllers, two amplifier modules, two look-up table modules, and two measurement modules in the X-axis and Y-axis directions, wherein the fuzzy adaptive PID controller, the amplifier module, and the look-up table module in the X-axis direction are connected in series and then connected to an input end of the active magnetic bearing; the fuzzy adaptive PID controller, the amplifier module, and the look-up table module in the Y-axis direction are connected in series and then connected to the input end of the active magnetic bearing; the two measurement modules in the X-axis and Y-axis directions measure the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 of the active magnetic bearing in the X-axis and Y-axis directions, respectively; the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 are input into the two corresponding look-up table modules, respectively; reference displacements x*, y* in the X-axis and Y-axis directions are subtracted from the corresponding actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 to obtain displacement errors e.sub.x, e.sub.y, respectively; initial control currents I.sub.x0, I.sub.y0 are obtained through the corresponding fuzzy adaptive PID controllers by using the displacement errors e.sub.x, e.sub.y, and actual control currents î.sub.x, î.sub.y are obtained through the corresponding amplifier modules by using the initial control currents I.sub.x0, I.sub.y0, respectively; the actual control currents î.sub.x, î.sub.y are input into the corresponding look-up table modules, and the two look-up table modules output the corresponding actual suspension forces {circumflex over (F)}.sub.x, {circumflex over (F)}.sub.y to the active magnetic bearing.

2. The method for constructing the active magnetic bearing controller based on the look-up table method according to claim 1, wherein in step (1), N levels of control currents and M levels of displacement eccentricities are selected for finite element simulation to obtain N*M finite element models; the control currents, the displacement eccentricities, and the corresponding suspension forces of the N*M finite element models in the X-axis and Y-axis directions are collected; the control currents and the displacement eccentricities in the X-axis and Y-axis directions of each of the finite element models are used as an independent variable x and the corresponding suspension forces are used as a dependent variable ŷ(x), and the independent variable x and the dependent variable ŷ(x) are substituted into a general universal Kriging model ŷ(x)=F(β, x)+z(x) to obtain two universal Kriging prediction models {circumflex over (F)}.sub.x(î.sub.x, {circumflex over (x)}.sub.0)=F.sub.1({circumflex over (β)}, î.sub.x, {circumflex over (x)}.sub.0)+z.sub.1(î.sub.x, {circumflex over (x)}.sub.0) and {circumflex over (F)}.sub.y(î.sub.y, ŷ.sub.0)=F.sub.1({circumflex over (β)}, î.sub.y, ŷ.sub.0)+z.sub.1(î.sub.y, ŷ.sub.0) through fitting, wherein F(β, x), F.sub.1({circumflex over (β)}, î.sub.x, {circumflex over (x)}.sub.0), and F.sub.1({circumflex over (β)}, î.sub.y, ŷ.sub.0) are regression models, z(x), z.sub.1(î.sub.x, {circumflex over (x)}.sub.0), and z.sub.1(î.sub.y, ŷ.sub.0) are error terms, β is a regression coefficient of the general universal Kriging model, and {circumflex over (β)} is a regression coefficient of the universal Kriging prediction model.

3. The method for constructing the active magnetic bearing controller based on the look-up table method according to claim 2, wherein the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 start from 0 and are sampled at an interval of 0.01 mm, the actual control currents î.sub.x, î.sub.y start from 0 and are sampled at an interval of 0.1 A, sampled values of the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 and the actual control currents î.sub.x, î.sub.y are substituted into the corresponding universal Kriging prediction models to calculate the actual suspension forces {circumflex over (F)}.sub.x, {circumflex over (F)}.sub.y, to create the corresponding two model state tables.

4. The method for constructing the active magnetic bearing controller based on the look-up table method according to claim 3, wherein first rows of the two model state tables are about the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 and first columns of the two model state tables are about the actual control currents î.sub.x, î.sub.y, respectively; and each of the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 and each of the actual control currents î.sub.x, î.sub.y are corresponding to one of the actual suspension forces {circumflex over (F)}.sub.x, {circumflex over (F)}.sub.y.

5. The method for constructing the active magnetic bearing controller based on the look-up table method according to claim 3, wherein as for data of the actual displacement eccentricities and the actual control currents that are not the sampled values, the corresponding actual suspension forces are calculated through interpolation.

6. The method for constructing the active magnetic bearing controller based on the look-up table method according to claim 1, wherein the fuzzy adaptive PID controller in step (3) consists of a fuzzy inference system, a proportional term, an integral term, and a derivative term; the displacement errors e.sub.x, e.sub.y and first-order derivatives ė.sub.x, ė.sub.y thereof are input into the corresponding fuzzy inference systems, and each of the fuzzy inference systems outputs a proportional modification coefficient CP, an integral modification coefficient CI, and a derivative modification coefficient CD; the proportional modification coefficient CP, the integral modification coefficient CI, and the derivative modification coefficient CD are respectively multiplied by a corresponding proportional coefficient KP, integral coefficient KI, and derivative coefficient KD to obtain a modified proportional term, integral term, and derivative term; a summation operation is performed on outputs of the modified proportional term, integral term, and derivative term based on the displacement errors e.sub.x, e.sub.y to obtain the initial control currents I.sub.x0, I.sub.y0.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0018] FIG. 1 is a block diagram of a fuzzy adaptive PID controller;

[0019] FIG. 2 is a block diagram of a common PID controller; and

[0020] FIG. 3 is a structural block diagram of an active magnetic bearing controller constructed by using a method of the present invention.

DETAILED DESCRIP HON OF THE EMBODIMENTS

[0021] In the present invention, firstly, finite element models of an active magnetic bearing are built. Two universal Kriging prediction models in X-axis and Y-axis directions about actual suspension forces {circumflex over (F)}.sub.x, {circumflex over (F)}.sub.y being in association with actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 and actual control currents î.sub.x, î.sub.y in the X-axis and Y-axis directions of the active magnetic bearing are obtained by using the finite element models of the active magnetic bearing. Two model state tables in the X-axis and Y-axis directions about the actual suspension forces {circumflex over (F)}.sub.x, {circumflex over (F)}.sub.y being in association with the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 and the actual control currents î.sub.x, î.sub.y are created. Based on the two model state tables, two look-up table modules with the two model state tables being built in are constructed, respectively. Two fuzzy adaptive PID controllers in the X-axis and Y-axis directions are constructed. Finally, the two fuzzy adaptive PM controllers, two corresponding amplifier modules in the X-axis and Y-axis directions, the two look-up table modules, and two corresponding measurement modules in the X-axis and Y-axis directions are used together to constitute an active magnetic bearing controller, which implements accurate control of the active magnetic bearing. The specific method is as follows:

[0022] Dimension parameters of an active magnetic bearing to be controlled are measured, finite element models of the active magnetic bearing are built in finite element software, and performance parameters of the active magnetic bearing are obtained through simulation. On the premise of unsaturated magnetic field strength, N levels of control currents and M levels of displacement eccentricities are selected for finite element simulation to obtain N*M finite element models, wherein N and M are selected according to the control currents, an air gap range, and the fineness of the models required. Then, data about the control currents in the X-axis and Y-axis directions, the displacement eccentricities in the X-axis and Y-axis directions, and the corresponding suspension forces in the X-axis and Y-axis directions of the N*M finite element models are collected. The control currents and the displacement eccentricities in the X-axis and Y-axis directions of each model are a measured independent variable, and the corresponding suspension forces in the X-axis and Y-axis directions are a dependent variable. The present invention is described below by taking the X-axis direction as an example, and the implementation in the Y-axis direction is the same as that in the X-axis direction:

[0023] Data about the control currents {i.sub.11, i.sub.12, . . . , i.sub.NM}, the displacement eccentricities {x.sub.11, x.sub.12, . . . , x.sub.NM}, and the corresponding suspension forces {F.sub.11, F.sub.12, . . . , F.sub.NM} in the X-axis direction of the N*M finite element models are collected. The control currents {i.sub.11, i.sub.12, . . . , i.sub.NM} and the displacement eccentricities {x.sub.11, x.sub.12, . . . , x.sub.NM} of each of the finite element models are a measured independent variable, and the suspension forces {F.sub.11, F.sub.12, . . . , F.sub.NM} are a dependent variable. The independent variable can be expressed as X.sub.ij=[i.sub.ij, x.sub.ij].sup.T, and the dependent variable can be expressed as Y.sub.ij=F.sub.ij, wherein i=1, 2, . . . , and j=1, 2, . . . , M.

[0024] The general universal Kriging model is expressed as:

ŷ(x)=F(β, x)+z(x)   (1)

wherein ŷ(x) is a final result value, that is, a dependent variable; F(β, x) is a regression model, wherein β is a regression coefficient and x is an independent variable of the universal Kriging model; z(x) is an error term in normal distribution with a mean of 0 and a variance of σ.sub.z.sup.2, wherein the variance σ.sub.z.sup.2 is selected according to specific applications and will influence the accuracy of an approximate model. The regression model F(β, x) is expressed as:

F(β, x)=β.sub.1f.sub.1(x)+ . . . +β.sub.pf.sub.p(x)=f(x).sup.Tβ  (2)

wherein β.sub.1, β.sub.2, . . . , β.sub.p are regression coefficients of each order and f.sub.p(x) is a p-order approximate model.

[0025] The independent variable X.sub.ij and the dependent variable of the finite element models are used to respectively substitute x and ŷ(x) in the formula (1) of the general universal Kriging model. A universal Kriging prediction model in the X-axis direction about the actual suspension forces {circumflex over (F)}.sub.x being in association with the actual displacement eccentricities {circumflex over (x)}.sub.0 and the actual control currents î.sub.x in the X-axis direction of the active magnetic bearing can be obtained through fitting and is specifically expressed as:

{circumflex over (F)}.sub.x(î.sub.x, {circumflex over (x)}.sub.0)=F.sub.1({circumflex over (β)}, î.sub.x, {circumflex over (x)}.sub.0)+z.sub.1(î.sub.x, {circumflex over (x)}.sub.0)   (3)

wherein {circumflex over (β)} is a regression coefficient of the built universal Kriging prediction model, and z.sub.1(î.sub.x, {circumflex over (x)}.sub.0) is an error term about the actual control currents î.sub.x and the actual displacement eccentricities {circumflex over (x)}.sub.0 in the X-axis direction.

[0026] Similarly, the universal Kriging prediction model in the Y-axis direction is obtained as follows:

{circumflex over (F)}.sub.y(î.sub.y, ŷ.sub.0)=F.sub.1({circumflex over (β)}, î.sub.y, ŷ.sub.0)+z.sub.1(î.sub.y, ŷ.sub.0),

wherein F.sub.1({circumflex over (β)}, î.sub.y, ŷ.sub.0) is a regression model of the built universal Kriging prediction model, and z.sub.1(î.sub.y, ŷ.sub.0) is an error term about the actual control currents î.sub.y and the actual displacement eccentricities ŷ.sub.0 in the Y-axis direction.

[0027] Two model state tables about the actual suspension forces {circumflex over (F)}.sub.x, {circumflex over (F)}.sub.y being in association with the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 and the actual control currents î.sub.x, î.sub.y are created according to the obtained two universal Kriging prediction models in the X-axis and Y-axis directions, respectively. Specifically, a model state table 1 about the actual suspension forces {circumflex over (F)}.sub.x being in association with the actual displacement eccentricities {circumflex over (x)}.sub.0 and the actual control currents î.sub.x in the X-axis direction is built, and a model state table 2 about the actual suspension forces {circumflex over (F)}.sub.y being in association with the actual displacement eccentricities ŷ.sub.0 and the actual control currents î.sub.y in the Y-axis direction is built:

TABLE-US-00001 TABLE 1 Actual displacement eccentricities/control currents in the X-axis direction 0 0.01 0.02 0.03 . . . x.sub.max 0 F.sub.11 F.sub.12 F.sub.13 F.sub.14 . . . F.sub.1a 0.1 F.sub.21 F.sub.22 F.sub.23 F.sub.24 . . . F.sub.2a 0.2 F.sub.31 F.sub.32 F.sub.33 F.sub.34 . . . F.sub.3a 0.3 F.sub.41 F.sub.42 F.sub.43 F.sub.44 . . . F.sub.4a i.sub.max F.sub.b1 F.sub.b2 F.sub.b3 F.sub.b4 . . . F.sub.ba

TABLE-US-00002 TABLE 2 Actual displacement eccentricities/control currents in the Y-axis direction 0 0.01 0.02 0.03 . . . y.sub.max 0 F′.sub.11 F′.sub.12 F′.sub.13 F′.sub.14 . . . F′.sub.1a 0.1 F′.sub.21 F′.sub.22 F′.sub.23 F′.sub.24 . . . F′.sub.2a 0.2 F′.sub.31 F′.sub.32 F′.sub.33 F′.sub.34 . . . F′.sub.3a 0.3 F′.sub.41 F′.sub.42 F′.sub.43 F′.sub.44 . . . F′.sub.4a i.sub.ymax F′.sub.b1 F′.sub.b2 F′.sub.b3 F′.sub.b4 . . . F′.sub.ba

[0028] Taking Table 1 as an example, the first row is about the actual displacement eccentricities {circumflex over (x)}.sub.0 in the X-axis direction, and the first column is about the actual control currents î.sub.x. The actual displacement eccentricities {circumflex over (x)}.sub.0 start from 0 to the maximum eccentricity x.sub.max and are sampled at an interval of 0.01 mm; meanwhile, the actual control currents î.sub.x start from 0 and are sampled at an interval of 0.1 A. The sampled values of the actual displacement eccentricities {circumflex over (x)}.sub.0 and the actual control currents î.sub.x are substituted into the formula (3) to calculate the actual suspension forces {circumflex over (F)}.sub.x associated with the sampled values, and the model state table 1 is created accordingly. Therefore, each of the actual displacement eccentricities {circumflex over (x)}.sub.0 and each of the actual control currents î.sub.x are corresponding to one of the actual suspension forces {circumflex over (F)}.sub.x, as shown by F.sub.11 to F.sub.ba in Table 1, wherein x.sub.max is a maximum displacement in the X-axis direction and i.sub.max is a maximum control current. Taking Table 1 as an example, when the actual displacement eccentricity is 0.01 mm and the actual control current is 0.1 A, the actual suspension force is F.sub.22; and when the actual displacement eccentricity is 0.03 mm and the actual control current is 0.2 A, the actual suspension force is F.sub.34. In Table 1, b and a are respectively the number of the sampled actual displacement eccentricities and the number of the sampled actual control currents. Similarly, in Table 2, the actual suspension forces are F′.sub.11 to F′.sub.ba, y.sub.max is a maximum displacement in the Y-axis direction, and i.sub.ymax is a maximum control current in the Y-axis direction. Similarly, in Table 2, the first row is about the actual displacement eccentricities ŷ.sub.0 in the Y-axis direction, and the first column is about the actual control currents î.sub.y. The sampling mode is the same as that in the X-axis direction. The sampled values of the actual displacement eccentricities ŷ.sub.0 and the actual control currents î.sub.y are substituted into the formula (3) to calculate the actual suspension forces {circumflex over (F)}.sub.y associated with the sampled values, and the model state table 2 is created accordingly.

[0029] As for data of the actual displacement eccentricities and the actual control currents that are not sampled values, the corresponding actual suspension forces are calculated through interpolation. Taking the X-axis direction as an example, when the actual displacement eccentricity is x.sub.0 and the actual control current is i.sub.0, the positions of x.sub.0 and i.sub.0 in Table I. need to be determined first. Assume that the displacement eccentricity of {x.sub.0, i.sub.0} falls between the sampled values x.sub.1 and x.sub.2, the control current falls between the sampled values i.sub.1 and i.sub.2, x.sub.1 and x.sub.2 satisfy x.sub.1+0.01 mm=x.sub.2, i.sub.1 and i.sub.2 satisfy i.sub.1+0.1 A=i.sub.2, and x.sub.1, x.sub.2, i.sub.1, and i.sub.2 are all sampled displacements and currents. At this time, the actual suspension force corresponding to the sampled values {x.sub.1, i.sub.1} is F.sub.c,d, the actual suspension force corresponding to {x.sub.1, i.sub.2} is F.sub.c,d+1, the actual suspension force corresponding to {x.sub.2, i.sub.1} is F.sub.c+1,d, and the actual suspension force corresponding to {x.sub.2, i.sub.2} is F.sub.c+1,d+1, wherein c and d are the row number and the column number of the sampled values {x.sub.1, i.sub.1} in Table 1. Then, the actual suspension force corresponding to {k.sub.0, i.sub.0} can be calculated as:

[00001]$F_{x_0\text{/}{i}_0}=\left(\frac{\left(x_2-x_0\right)}{0.01}*F_{c,d+1}+\frac{-\left(x_1-x_0\right)}{0.01}*F_{c,d}\right)*\frac{i_0-i_1}{0.1}+\left(\frac{\left(x_2-x_0\right)}{0.01}*F_{c+1,d+1}+\frac{-\left(x_1-x_0\right)}{0.01}*F_{c+1,d}\right)*\frac{i_2-i_0}{0.1}.$

[0030] For example, when the actual displacement eccentricity is 0.025 mm and the actual control current is 0.25 A, the corresponding suspension force can be calculated according to data in Table 1 as follows:

[00002]$F_{0.025\text{/}0.25}=\left(\frac{\left(0.03-0.025\right)}{0.01}*F_{24}+\frac{-\left(0.02-0.025\right)}{0.01}*F_{23}\right)*\frac{0.25-0.2}{0.1}+\left(\frac{\left(0.03-0.025\right)}{0.01}*F_{34}+\frac{-\left(0.02-0.025\right)}{0.01}*F_{33}\right)*\frac{0.3-0.25}{0.1}.$

[0031] Similarly, as for data of the actual displacement eccentricities and the actual control currents in the Y-axis direction that are not sampled values, the corresponding actual suspension forces are calculated through interpolation in the same way.

[0032] Two look-up table modules are constructed, wherein the model state table 1 and the model state Table 2 are respectively built in the look-up table module in the X-axis direction and the look-up table module in the Y-axis direction.

[0033] A fuzzy adaptive PID controller shown in FIG. 1 is constructed. Since changes of input currents and displacements of the active magnetic bearing may cause certain errors in the models, a common controller cannot make adjustments according to the models, and thus the present invention adopts a fuzzy adaptive PID controller for control. FIG. 2 is a structural block diagram of an existing common PID controller, which mainly consists of a proportional term, an integral term, and a derivative term. The proportional term is directly composed of a proportional coefficient KP, the integral term is directly composed of an integral coefficient KI and an integral module ∫, and the derivative term is directly composed of a derivative coefficient KD and a derivative module d/dt. A summation operation, denoted by Σ, is performed on the three terms to obtain a final output. FIG. 1 shows the fuzzy adaptive PID controller in the X-axis direction that is constructed by the present invention and consists of a fuzzy inference system, a proportional term, an integral term, and a derivative term. Compared with the existing common PID controller shown in FIG. 2, improvements have been made in the controller in FIG. 1, and the fuzzy inference system is employed in addition to the proportional term, the integral term, and the derivative term in the PID controller in FIG. 2. Taking the fuzzy adaptive PID controller in the X-axis direction as an example, displacement errors e.sub.x in the X-axis direction and first-order derivatives ė.sub.x thereof are input into the fuzzy inference system, and the fuzzy inference system calculates according to the displacement errors e.sub.x and the first-order derivatives ė.sub.x to output a proportional modification coefficient CP, an integral modification coefficient CI, and a derivative modification coefficient CD. The proportional modification coefficient CP, the integral modification coefficient CI, and the derivative modification coefficient CD are respectively multiplied by the corresponding proportional coefficient KP, integral coefficient KI, and derivative coefficient KD to obtain the modified proportional coefficient, the modified integral coefficient, and the modified derivative coefficient, which are expressed as:

[00003]$\begin{array}{cc}\{\begin{array}{c}{K}_p^{*}=\mathrm{CP}*\mathrm{KP}\\ K_I^{*}=\mathrm{CI}*\mathrm{KI}\\ K_D^{*}=\mathrm{CD}*\mathrm{KD}.\end{array}& \left(5\right)\end{array}$

A summation operation, denoted by Σ, is performed on the modified proportional term, integral term, and derivative term to obtain a final output. That is, initial control currents I.sub.x0 output in the X-axis direction can be accurately controlled through the modified proportional term, integral term, and derivative term based on the displacement errors e.sub.x.

[0034] According to the influence of parameter adjustment on the output performance of the system, the modification coefficients CP, CI, CD are adjusted based on the following principles: When e.sub.x is large, K*.sub.p is increased, K*.sub.D is decreased, and K*.sub.I is kept moderate through the modification coefficients to improve the response speed of the system and meanwhile prevent excessive overshoot. When e.sub.x is moderate, K*.sub.p and K*.sub.I are kept small while K*.sub.D is kept moderate through the modification coefficients to reduce the overshoot and meanwhile enable the system to respond quickly. When e.sub.x is small, K*.sub.p and K*.sub.I are increased while K*.sub.D is kept moderate through the modification coefficients to ensure good stability of the system, avoid system oscillation, and enhance the anti-interference performance of the system.

[0035] Similarly, the fuzzy adaptive PID controller in the Y-axis direction is constructed in the same way as the fuzzy adaptive PID controller in the X-axis direction. Displacement errors e.sub.y in the Y-axis direction and first-order derivatives ė.sub.y thereof are input into the corresponding fuzzy inference system in the Y-axis direction, and the fuzzy inference system outputs a proportional modification coefficient CP, an integral modification coefficient CI, and a derivative modification coefficient CD. The proportional modification coefficient CP, the integral modification coefficient CI, and the derivative modification coefficient CD are respectively multiplied by the corresponding proportional coefficient KP, integral coefficient KI, and derivative coefficient KD to obtain the modified proportional term, integral term, and derivative term. A summation operation is performed on the outputs of the modified proportional term, integral term, and derivative term based on the displacement errors e.sub.y to obtain initial control currents I.sub.y0 in the Y-axis direction.

[0036] An active magnetic bearing controller shown in FIG. 3 is constructed. The active magnetic bearing controller consists of two fuzzy adaptive PID controllers, two amplifier modules, two look-up table modules, and two measurement modules in the X-axis and Y-axis directions, and is connected to an input end of the active magnetic bearing to implement control of the active magnetic bearing. The fuzzy adaptive PID controller, the amplifier module, and the look-up table module in the X-axis direction are connected in series and then connected to the input end of the active magnetic bearing. The fuzzy adaptive PID controller, the amplifier module, and the look-up table module in the Y-axis direction are connected in series and then connected to the input end of the active magnetic bearing. The two measurement modules in the X-axis and Y-axis directions measure, through displacement sensors, the actual displacement eccentricities {circumflex over (x)}.sub.0, ŷ.sub.0 in the X-axis and Y-axis directions of the active magnetic bearing, respectively. The actual displacement eccentricities {circumflex over (x)}.sub.0 in the X-axis direction are input into the look-up table module in the X-axis direction, and the actual displacement eccentricities ŷ.sub.0 in the Y-axis direction are input into the look-up table module in the Y-axis direction. The reference displacements x* are subtracted from the actual displacement eccentricities {circumflex over (x)}.sub.0 to obtain the displacement errors e.sub.x in the X-axis direction. The initial control currents I.sub.x0 are obtained through the fuzzy adaptive PID controller in the X-axis direction by using the displacement errors e.sub.x, and the actual control currents î.sub.x are obtained through the amplifier module in the X-axis direction. The actual control currents î.sub.x are input into the look-up table module in the X-axis direction, and the look-up table module in the X-axis direction obtains the actual suspension forces {circumflex over (F)}.sub.x according to data in the model state table 1. Similarly, the reference displacements y* are subtracted from the actual displacement eccentricities ŷ.sub.0 to obtain the displacement errors e.sub.y in the Y-axis direction. The initial control currents I.sub.y0 are obtained through the fuzzy adaptive HD controller in the Y-axis direction by using the displacement errors e.sub.y, and the actual control currents î.sub.y are obtained through the amplifier module in the Y-axis direction. The actual control currents î.sub.y are input into the look-up table module in the Y-axis direction, and the look-up table module in the Y-axis direction obtains the actual suspension forces {circumflex over (F)}.sub.y according to data in the model state table 2 and outputs the actual suspension forces {circumflex over (F)}.sub.y to the active magnetic bearing. That is, the look-up table modules in the X-axis and Y-axis directions respectively output the corresponding actual suspension forces {circumflex over (F)}.sub.x, {circumflex over (F)}.sub.y to the active magnetic bearing, to implement control of the active magnetic bearing in the X-axis and Y-axis directions.