Vibration compensation controller with neural network band-pass filters for bearingless permanent magnet synchronous motor

The controller comprises a displacement controller and a rotating speed controller. The displacement controller includes a vibration force compensation control module and a dead-time vibration compensation module. The vibration force compensation control module receives actual displacements and a rotor mechanical angle and outputs corresponding vibration compensation forces. The vibration force compensation control module comprises a first neural network band-pass filter, a second neural network band-pass filter, a third PID controller, and a fourth PID controller. The dead-time vibration compensation module receives a rotor electrical angle and an actual quadrature-direct axis currents and an actual direct axis current and outputs a quadrature-direct axis compensation voltages and a direct axis compensation voltage. The dead-time vibration compensation module consists of a third neural network band-pass filter in a direct axis direction, a fourth neural network band-pass filter in a quadrature axis direction, a sixth PI controller, and a seventh PI controller.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a 371 of international application of PCT application serial no. PCT/CN2021/082326, filed on Mar. 23, 2021, which claims the priority benefit of China application no. 202110195977.3, filed on Feb. 22, 2021. The entirety of each of the above mentioned patent applications is hereby incorporated by reference herein and made a part of this specification.

TECHNICAL FIELD

The present invention relates to the field of control of a bearingless motor, and in particular, to compensation control for vibration of a bearingless permanent magnet synchronous motor by using dead-time compensation control and rotor eccentricity control technologies for the bearingless permanent magnet synchronous motor.

BACKGROUND

Bearingless permanent magnet synchronous motors are a new type of special motors that have high speed and high precision and require no lubrication. Their application prospects in aerospace, chemical manufacturing, semiconductor industry, and other fields in need of special environments increasingly grow. The bearingless permanent magnet synchronous motor is used as a rotary drive motor. Due to problems such as material unevenness, processing errors, and assembly errors, a certain degree of rotor mass eccentricity inevitably exists and a centrifugal excitation force at the same frequency as a rotation speed is produced when the motor is in rotation. Meanwhile, in a control process of the bearingless permanent magnet synchronous motor, a dead time must be set to avoid a short circuit between upper and lower bridge arms of an inverter. The introduction of the dead time causes an increase in current harmonics, and the amplitude of an unbalanced force is further increased, which results in unbalanced vibration of a rotor and affects suspension control precision of the rotor.

Regarding control for unbalanced vibration of the rotor in the bearingless permanent magnet synchronous motor, compensation control is mainly performed against unbalanced vibration caused by rotor mass eccentricity in the prior art, while unbalanced vibration caused by a dead-time effect is rarely concerned. Chinese Patent Publication No. CN104659990A discloses a method for extracting an unbalanced vibration displacement of a bearingless motor through adaptive filtering, which paves the way for the primary condition of vibration compensation control of a bearingless motor. Chinese Patent Publication No. CN105048913A discloses a current compensation-based unbalanced vibration control system for a bearingless asynchronous motor, wherein compensation control for suspension vibration is realized by adjusting a compensation current. However, in these solutions, the vibration compensation control of the bearingless motor mainly focuses on detection and compensation for vibration caused by eccentricity and does not concern vibration caused by the dead-time effect. To improve the control precision of the unbalanced vibration displacement of the bearingless permanent magnet synchronous motor, compensation not only needs to be made for a rotor eccentricity displacement caused by rotor mass eccentricity, but also needs to be made for unbalanced vibration of the rotor caused by the dead-time effect, which is critical to the implementation of high-precision control of the bearingless permanent magnet synchronous motor.

SUMMARY

An objective of the present invention is to provide a vibration compensation controller with neural network band-pass filters for a bearingless permanent magnet synchronous motor. The controller performs vibration compensation to suppress vibration of the bearingless permanent magnet synchronous motor, thereby solving the problem in the prior art that compensation is only made for vibration caused by rotor mass eccentricity and vibration caused by a dead-time effect is ignored in the vibration compensation control of the bearingless permanent magnet synchronous motor. Therefore, stable suspension and efficient operation of a rotor of the motor are realized, the control precision of the motor is improved, and better application in an electric drive system is achieved.

The vibration compensation controller with neural network band-pass filters for a bearingless permanent magnet synchronous motor provided by the present invention adopts the following technical solution. The controller comprises a displacement controller and a rotating speed controller. The displacement controller includes a vibration force compensation control module and a dead-time vibration compensation module.

The vibration force compensation control module receives, as input, actual displacements x, y in x and y directions and a rotor mechanical angle θmand outputs corresponding vibration compensation forces Fxhand Fyh. The vibration force compensation control module comprises a first neural network band-pass filter, a second neural network band-pass filter, a third proportional-integral-derivative (PID) controller, and a fourth PID controller. The first neural network band-pass filter receives, as input, the actual displacement x in the x direction and the rotor mechanical angle θmand outputs a vibration displacement {circumflex over (x)}. A difference between a specified value 0 and the vibration displacement {circumflex over (x)} is input to the third PID controller, and the third PID controller outputs the vibration compensation force Fxh. The second neural network band-pass filter receives, as input, the actual displacement y in the y direction and the rotor mechanical angle θmand outputs a vibration displacement ŷ. A difference between the specified value 0 and the vibration displacement ŷ is input to the fourth PID controller, and the fourth PID controller outputs the vibration compensation force Fyh. A sum of the vibration compensation force Fxhand a specified force value Fxof a suspension winding in the x direction is input to a force/current conversion module, a sum of the vibration compensation force Fyhand a specified force value Fyof the suspension winding in the y direction is input to the force/current conversion module, and the current conversion module obtains a specified quadrature axis current value i*Bqand a specified direct axis current value i*Bd.

The dead-time vibration compensation module receives, as input, a rotor electrical angle θe, and an actual quadrature axis current iBq, and an actual direct axis current iBdand outputs a quadrature axis compensation voltage uBqhand a direct axis compensation voltage uBdh. The dead-time vibration compensation module comprises a third neural network band-pass filter in a direct axis direction, a fourth neural network band-pass filter in a quadrature axis direction, a sixth proportional-integral (PI) controller, and a seventh PI controller. The third neural network band-pass filter receives, as input, the actual current iBdin the direct axis direction and 6 times of the rotor electrical angle θeand obtains a harmonic current îBdin the direct axis direction. A difference between the specified value 0 and the harmonic current îBdis input to the sixth PI controller, and the sixth PI controller obtains the direct axis compensation voltage uBdh. A sum of a control voltage uBdin the direct axis direction and the direct axis compensation voltage uBdhserves as a direct axis command voltage u*Bd. The fourth neural network band-pass filter receives, as input, the actual current iBqin the quadrature axis direction and 6 times of the rotor electrical angle θeand obtains a harmonic current ÎBqin the direct axis direction. A difference between the specified value 0 and the harmonic current ÎBqis input to the seventh PI controller, and the seventh PI controller obtains the quadrature axis compensation voltage uBqh. A sum of a control voltage uBqin the quadrature axis direction and the quadrature axis compensation voltage uBqhserves as a quadrature axis command voltage u*Bq.

The present invention has the following beneficial effects:

1) By adopting dead-time vibration compensation control, the present invention not only compensates for the dead time, but also effectively suppresses vibration during the operation of the bearingless permanent magnet synchronous motor, thereby improving the suspension control precision.

2) The neural network band-pass filters adopted by the present invention have simple working principles and concise calculation processes and can obtain required signals according to real-time speeds of the motor.

3) The present invention adopts the PI controllers to regulate vibration. The controllers have simple principles, their coefficients can be adjusted conveniently, and they have strong robustness.

4) In the vibration compensation control of the bearingless permanent magnet synchronous motor, generally only the vibration caused by eccentricity is considered and compensation control is implemented, while the vibration caused by the dead-time effect is not concerned, which affects the entire suspension control precision. To achieve higher suspension control precision of the bearingless permanent magnet synchronous motor, the present invention not only performs analysis and compensation for vibration caused by eccentricity, but also performs compensation control for vibration caused by the dead-time effect, thereby effectively improving the suspension control precision.

DESCRIPTION OF THE EMBODIMENTS

The specific ideas and implementation steps of the present invention are illustrated below.

Referring toFIG.1, the vibration compensation controller with neural network band-pass filters for a bearingless permanent magnet synchronous motor of the present invention comprises a displacement controller1and a rotating speed controller2. Output ends of the displacement controller1and the rotating speed controller2are connected to a bearingless permanent magnet synchronous motor3, so as to control the bearingless permanent magnet synchronous motor3.

As shown inFIG.2, the rotating speed controller2adopts double closed-loop control of speed and current, and comprises a first PI controller21, a second PI controller22, a third PI controller23, a first coordinate transformation module24, a second coordinate transformation module25, a first SVPWM inverter26, a coder27, and a speed calculation module28. An output end of the coder27is connected to the speed calculation module28. The coder27collects speed pulse signals from a rotating shaft of the bearingless permanent magnet synchronous motor3, performs an accumulate operation, and inputs an accumulation result ΔP into the speed calculation module28. The speed calculation module28calculates an actual rotor speed n of the motor, and the speed n is calculated by the following formula:

wherein Tsis an interrupt cycle of the rotating speed controller2and Leis the number of lines of the coder.

A difference between the calculated actual speed n and a specified speed value n* serves as a speed error, and the error is input to the first PI controller21. The first PI controller21makes adjustment to obtain a specified quadrature axis current value i*Mqof a torque winding. Meanwhile, a current sensor collects torque currents i2Aand i2Cof the two-phase torque winding of the bearingless permanent magnet synchronous motor3, and inputs the torque currents i2Aand i2Cto the second coordinate transformation module25. The second coordinate transformation module25is configured for performing Clarke transform and Park transform. The second coordinate transformation module25transforms i2Aand i2Cinto an actual quadrature axis current value iMqof the torque winding and an actual direct axis current value iMdof the torque winding in a rotating reference frame. An error between the specified quadrature axis current value i*Mqthe torque winding and the actual quadrature axis current value iMqof the torque winding is input to the second PI controller22to obtain a specified quadrature axis voltage value u*Mqof the torque winding. When a specified direct axis current value of the torque winding is i*Md=0, an error between i*Mdand the actual direct axis current value iMdof the torque winding is input to the third PI controller23to obtain a specified direct axis voltage value u*Mdof the torque winding. Output ends of the second PI controller22and the third PI controller23are both connected to an input end of the first coordinate transformation module24. The first coordinate transformation module24is configured for performing inverse Park transform, through which the specified quadrature axis voltage value u*Mqof the torque winding and the specified direct axis voltage value u*Mdof the torque winding can be transformed into voltages uMαand uMβof the torque winding in a stationary reference frame. An output end of the first coordinate transformation module24is sequentially connected in series with the first SVPWM inverter26and the bearingless permanent magnet synchronous motor3. The first coordinate transformation module24inputs the voltages uMαand uMβto the first SVPWM inverter26. An output of the first SVPWM inverter26is connected to an input of the bearingless permanent magnet synchronous motor3. The first SVPWM inverter26obtains three-phase input voltages u2A, u2B, and u2Cof the bearingless permanent magnet synchronous motor3.

As shown inFIG.3, the displacement controller1adopts double closed-loop control of displacement and current, and comprises a first PID controller11, a second PID controller12, a vibration force compensation module5, a force/current conversion module13, a fourth PI controller14, a fifth PI controller15, a dead-time vibration compensation module6, a third coordinate transformation module16, an angle calculation module17, a second SVPWM inverter90, a fourth coordinate transformation module91, a displacement calculation module92, and the coder27. A displacement sensor collects and inputs a rotor position of the bearingless permanent magnet synchronous motor3to the displacement calculation module92. The displacement calculation module92converts a collected displacement signal into actual displacements in x and y directions, obtains a displacement error as a difference between the actual displacement x in the x direction and a specified value x* and inputs the error to the first PID controller11. The first PID controller11makes adjustment to obtain a specified force value Fxof a suspension winding in the x direction. The displacement calculation module92obtains a displacement error as a difference between the actual displacement y in the y direction and a specified value y* and inputs the error to the second PID controller82. The second PID controller12makes adjustment to obtain a specified force value Fyof the suspension winding in the y direction.

The output end of the coder27is further connected to the angle calculation module17. A pulse signal output by the coder27is input to the angle calculation module17to obtain a rotor mechanical angle θm. The rotor mechanical angle at a moment k is calculated as follows:

θm(k)=θm(k-1)+60⁢Δ⁢P9.55Le(2)
wherein ΔP is the accumulation result of pulses output by the coder27.

Output ends of the angle calculation module17and the displacement calculation module92are both connected to an input end of the vibration force compensation control module5. The rotor mechanical angle θmoutput by the angle calculation module17and the actual rotor displacements x, y output by the displacement calculation module92are input to the vibration force compensation control module5to obtain compensation forces Fxhand Fyh.

As shown inFIG.4, the vibration force compensation control module5comprises a first neural network band-pass filter51, a second neural network band-pass filter53, a third PID controller52, and a fourth PID controller54. The first neural network band-pass filter51receives the displacement in the x direction and the rotor mechanical angle θmand outputs a vibration displacement signal {circumflex over (x)}.FIG.6shows the specific structure of the first neural network band-pass filter51in the x direction, which includes a first weight adjustment module5. A difference between the actual displacement x and the vibration displacement {circumflex over (x)} output by the first neural network band-pass filter51serves as an error signal ex. The error signal exand sine and cosine values of the rotor mechanical angle θmare input to the first weight adjustment module55to obtain updated weights ωx_1and ωx_2in the x direction. The vibration displacement {circumflex over (x)} output by the first neural network band-pass filter51at the moment k is calculated by the following formula:
{circumflex over (x)}(k)=ωx_1(k)·cos θm(k)+ωx_2(k)·sin θm(k)  (3).

The weights ωx_1and ωx_2are calculated by the following formulas:

wherein exis a component in the x direction after harmonics are filtered out; ωx_1and ωx_2are updated weights in the x direction; μ1is a step factor.

Therefore, the vibration displacement {circumflex over (x)} in the x direction is obtained. As shown inFIG.4, a displacement difference between a specified value 0 and the vibration displacement {circumflex over (x)} is input to the third PID controller52, and the third PID controller52makes adjustment to obtain the vibration compensation force Fxh.

The second neural network band-pass filter53is identical to the first neural network band-pass filter51in structure and principle. Likewise, the displacement in the y direction and the rotor mechanical angle θmare input to the second neural network band-pass filter53.FIG.7shows the specific structure of the second neural network band-pass filter53in the y direction. A difference between the actual displacement y and a vibration displacement ŷ output by the second neural network band-pass filter53serves as an error signal ey. The error signal eyand the sine and cosine values of the rotor mechanical angle θmare input to a second weight adjustment module56to obtain updated weights ωy_1and ωy_2in the y direction. The vibration displacement signal ŷ output by the second neural network band-pass filter53at the moment k is calculated by the following formula:
ŷ(k)=ωy_1(k)·cos θm(k)+ωy_2(k)·sin θm(k)  (5).

The weights ωy_1and ωy_2are calculated by the following formulas:

wherein eyis a component in the y direction after harmonics are filtered out; ωy_1and ωy_2are updated weights in the y direction; μ1is the step factor.

Therefore, the vibration displacement signal ŷ in the y direction is obtained. As shown inFIG.4, a displacement difference between the specified value 0 and the vibration displacement signal ŷ is input to the fourth PID controller54, and the fourth PID controller54makes adjustment to obtain the vibration compensation force Fyh.

A sum of the force Fxin the x direction output by the first PID controller11and the vibration compensation force Fxhin the x direction output by the vibration force compensation module5and a sum of the force Fyin the y direction output by the second PID controller12and the vibration compensation force Fyhin the y direction output by the vibration force compensation module5are input to the force/current conversion module13to obtain a specified quadrature axis current value i*Bqand a specified direct axis current value i*Bdof the suspension winding.

Differences between the obtained a specified quadrature axis current value i*Bq, and a specified direct axis current value i*Bdand an actual quadrature axis current value iBq, an actual direct axis current value iBdof the suspension winding are obtained respectively. The current sensor collects currents i1Aand i1Cof the two-phase suspension winding of the bearingless permanent magnet synchronous motor3and inputs the collected currents to the fourth coordinate transformation module91. The fourth coordinate transformation module91is configured for performing Clarke transform and Park transform. The fourth coordinate transformation module91processes i1Aand i1Cto obtain the actual quadrature axis current iBqand the actual direct axis current iBdof the suspension winding. The difference between i*Bqand iBqis input to the fifth PI controller15to obtain a quadrature axis control voltage uBqof the suspension winding. The difference between i*Bdand iBdis input to the fourth PI controller14to obtain a direct axis control voltage uBdof the suspension winding.

A rotor electrical angle θe, the actual quadrature axis current value iBqof the suspension winding, and the actual direct axis current value iBdof the suspension winding are input to the dead-time vibration compensation module6to obtain compensation voltages uBqhand uBdh. The angle calculation module17processes the pulse signal, collected by the coder27, of the bearingless permanent magnet synchronous motor3to obtain the rotor electrical angle θe, which is calculated as follows:
θe(k)=PMθm(k)  (7)

wherein θm(k) is the rotor mechanical angle at the moment k according to the formula (2) and PMis the number of pole-pairs of the torque winding.

The obtained rotor electrical angle θeand the actual quadrature axis current value iBqand the actual direct axis current value iBdare input to the dead-time vibration compensation module6. The dead-time vibration compensation module6comprises a third neural network band-pass filter61in the direct axis direction, a fourth neural network band-pass filter63in the quadrature axis direction, a sixth PI controller62, and a seventh PI controller64. In the dead-time vibration compensation module6, compensations in the direct axis direction and the quadrature axis direction are shown inFIG.5. The current iBdin the direct axis direction and 6 times of the rotor electrical angle θeare input to the third neural network band-pass filter61in the direct axis direction to obtain a harmonic current signal îBdin the direct axis direction.FIG.8is a schematic diagram of the internal structure of the third neural network band-pass filter61in the direct axis direction, which includes a third weight adjustment module65. InFIG.8, a difference between the current iBdin the direct axis direction and the harmonic current signal îBdoutput by the third neural network band-pass filter61serves as an error signal eBd; the error signal eBdand sine and cosine values of 6 times of the rotor electrical angle θeare input to the third weight adjustment module65to obtain updated weights ωd6_1and ωd6_2in the direct axis direction. The harmonic current îBdoutput by the third neural network band-pass filter61at the moment k is calculated by the following formula:
îBd(k)=ωd6_1(k)·cos 6θe(k)+ωd6_2(k)·sin 6θe(k)  (8).

The weights ωd6_1and ωd6_2are calculated by the following formulas:

wherein eBdis a component in the direct axis direction after harmonics are filtered out; ωd6_1and ωd6_2are updated sixth-harmonic weights in the direct axis direction; μ2is a step factor.

Therefore, the harmonic current signal îBdin the direct axis direction is obtained. As shown inFIG.5, a difference between the specified value 0 and the harmonic current signal îBdis input to the sixth PI controller62, and the sixth PI controller62makes adjustment to obtain the direct axis compensation voltage uBdh.

The fourth neural network band-pass filter63in the quadrature axis direction is identical to the third neural network band-pass filter61in structure. Likewise, the current iBqin the quadrature axis direction and 6 times of the rotor electrical angle θeare input to the fourth neural network band-pass filter63in the quadrature axis direction to obtain a harmonic current signal îBqin the direct axis direction.FIG.9is a schematic diagram of the internal structure of the fourth neural network band-pass filter63in the quadrature axis direction, which includes a fourth weight adjustment module66. InFIG.9, a difference between the current iBqin the quadrature axis direction and the harmonic current signal îBqoutput by the fourth neural network band-pass filter63serves as a current error signal eBq; the current error signal eBqand the sine and cosine values of 6 times of the rotor electrical angle θeare input to the fourth weight adjustment module66to obtain updated weights ωg6_1and ωq6_2in the direct axis direction. The harmonic current îBqoutput by the fourth neural network band-pass filter63at the moment k is calculated by the following formula:
îBq(k)=ωq6_1(k)·cos 6θe(k)+ωq6_2(k)·sin 6θe(k)  (10).

The weights ωd6_1and ωd6_2are calculated by the following formulas:

wherein eBqis a component in the quadrature axis direction after harmonics are filtered out; ωg6_1and ωq6_2are updated sixth-harmonic weights in the quadrature axis direction; μ2is the step factor.

Therefore, the harmonic current signal îBqin the direct axis direction is obtained. As shown inFIG.5, a difference between the specified value 0 and the harmonic current signal îBqis input to the seventh PI controller64, and the seventh PI controller64makes adjustment to obtain the quadrature axis compensation voltage uBqh.

A sum of the direct axis voltage uBdoutput by the fourth PI controller14and the direct axis compensation voltage uBdhoutput by the dead-time vibration compensation module serves as a direct axis command voltage u*Bd. A sum of the quadrature axis voltage uBqoutput by the fifth PI controller15and the quadrature axis compensation voltage uBqhoutput by the dead-time vibration compensation module serves as a quadrature axis command voltage u*Bq. The obtained u*Bdand u*Bqare input to the third coordinate transformation module16. The third coordinate transformation module16is configured for performing inverse Park transform. The third coordinate transformation module16processes u*Bdand u*Bqto obtain voltages uBαand uBβof the suspension winding in the stationary reference frame.

The voltages uBαand uBβof the suspension winding are input to the second SVPWM inverter90. An output of the second SVPWM inverter90is connected to the input of the bearingless permanent magnet synchronous motor3. The second SVPWM inverter90obtains three-phase input voltages u1A, u1B, u1Cof the bearingless permanent magnet synchronous motor3.

FIG.10is a schematic block diagram of the overall structure of the motor vibration compensation controller according to the present invention. Closed-loop control of speed and vibration compensation control are realized through design of the displacement controller1, the rotating speed controller2, and the modules therein as well as parameter adjustment of closed-loop regulators for speed and position. The rotating speed controller2performs speed regulation and control by using a commonly used vector control method with a direct axis command current of 0. The displacement controller1completes vector control through displacement adjustment, so that the rotor of the bearingless permanent magnet synchronous motor3maintains stable operation. The vibration force compensation module5performs compensation control on the eccentricity vibration signal in the displacement signals. Meanwhile, the dead-time vibration compensation control module6compensates for high-order harmonic signals in the current caused by the dead-time effect, thereby achieving more precise vibration compensation control.

The present invention can be implemented based on the above descriptions. Other changes and modifications made by persons skilled in the art without departing from the spirit and protection scope of the present invention still fall within the protection scope of the present invention.