CN101488031A - High-precision magnetic bearing axial control method based on interference observer - Google Patents
High-precision magnetic bearing axial control method based on interference observer Download PDFInfo
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Abstract
The invention provides a method for controlling axial direction of a high-precision magnetic bearing based on an interference observer. The method consists of a controller and the interference observer, wherein the interference observer comprises a Q filter and a rationalization generalized object inverse QGn<-1> part; the controller in a control system calculates according to displacement deviation to obtain basic control quantity so as to form a position closed loop control system; an interference value obtained by observation of the interference observer is negatively fed back into the basic control quantity to compensate exterior interference; and the formed current control quantity drives power amplification to realize high precision suspension of the magnetic bearing. The method leads differences caused by both exterior interference and objective parameter variation to be equivalent to a control input end, and introduces equivalent compensation into the control quantity to realize interference inhabitation. The method can carry out online observation and effective inhabitation against exterior interference which is not modeled or known, thereby improving control precision of suspension, and contributing to stability of the system.
Description
Technical Field
The invention discloses an axial control method of a magnetic bearing, relates to disturbance observation and suppression technology in high-precision control, is used for online observation and automatic suppression of external disturbance, and can be used for high-precision control and disturbance suppression of the magnetic bearing in a magnetic suspension control moment gyro system.
Background
A Control Moment Gyro (CMG) is a key execution mechanism for attitude Control of a spacecraft. High-speed magnetic bearing support in CMG is a key component, and usually has two modes of mechanical ball bearings and magnetic bearings. The magnetic suspension supporting mode solves the problems of abrasion and vibration caused by mechanical supporting, has the advantage of long service life, allows the rotating speed of the magnetic bearing to be greatly improved, and can obviously reduce the volume of the CMG on the premise of the same angular momentum. Meanwhile, the supporting precision of the magnetic bearing can be improved through active vibration control, and the magnetic bearing is supported at a relatively fixed position of the gyro room. However, magnetic levitation is a resilient supporting method with gaps, and the magnetic bearing has the disadvantage that transient or steady displacement is inevitably generated under the action of disturbance, which affects the precision of levitation. Therefore, the displacement disturbance response of the magnetic bearing must be minimized through disturbance compensation on the premise of keeping stability, so as to achieve the purpose of improving the suspension precision of the magnetic bearing. Disturbances affecting accuracy mainly take two forms, measurable and non-measurable. For measurable disturbances, feed forward compensation can be performed directly from the detected signal. For the disturbance which is not measurable and uncertain, the disturbance of the system needs to be observed on line, disturbance information is extracted, and then compensation is realized, so that the precision is improved.
At present, two main methods for high-precision control of a magnetic bearing are available, namely, optimizing a controller to minimize a disturbance response function, including a sliding mode variable structure control method and the like; and secondly, carrying out equivalent compensation on the disturbance, wherein the equivalent compensation comprises a feedforward control method. The sliding mode variable structure control method solves the interference caused by the unbalance of the system, can be very large in calculated amount, and limits the application in the actual system. The feedforward control method performs feedforward compensation by directly detecting signals, solves deterministic and measurable disturbance, and is compensation for modelable disturbance. The biggest problem of these methods is that no on-line observation and compensation is performed for the non-measurable and uncertain disturbances, such as carrier disturbance, external noise interference, etc., and no special disturbance suppression is performed, so that the disturbances affecting the accuracy cannot be suppressed. Meanwhile, the methods cannot analyze the disturbance situation in real time and lack corresponding disturbance recording and quantitative analysis means.
Disclosure of Invention
The technical problem of the invention is solved: the method for carrying out online observation and disturbance suppression on uncertain and unknown disturbance in high-precision control of the magnetic bearing is provided, so that the interference is effectively suppressed, and the suspension precision of the magnetic bearing is improved.
The technical solution of the invention is as follows: a high-precision magnetic bearing axial control method based on a disturbance observer is disclosed, wherein a system for realizing the method comprises a frequency sweep circuit and digital control hardware, wherein the digital control hardware comprises an A/D module, a DSP module and an FPGA module; the frequency sweeping circuit superposes a sensor signal and an excitation signal and then transmits the superposed signals to the A/D module, the FPGA module receives digital quantity converted by the A/D module and then transmits the digital quantity to the DSP module, DSP module software comprises a disturbance observer algorithm and a controller K algorithm to calculate current control quantity, and then the current control quantity is transmitted to the FPGA module, and then the FPGA module converts the current control quantity into a PWM form to be output, and drives a power amplifier to generate electromagnetic force to act on the magnetic bearing, and the method specifically comprises the following steps:
(a) firstly, adding a frequency sweep circuit, respectively carrying out frequency sweep experiments on a power amplifier and a generalized controlled object including the power amplifier, acquiring parameters of the generalized controlled object, establishing an inverse Gn-1 transfer function of the generalized object, then removing a frequency sweep circuit part, and directly accessing the output of a sensor to an A/D module;
(b) initializing a K parameter of a disturbance observer and a controller in a DSP module, setting a sampling data storage space, and setting a sampling mode of an FPGA module as clock interrupt;
(c) the FPGA module controls the A/D module to sample to obtain sensor output and receives a digital quantity result obtained by conversion of the A/D module;
(d) the FPGA module sends the digital quantity to the DSP module, and displacement deviation corresponding to the input displacement value is calculated in the DSP module according to the given suspension center position;
(e) inputting displacement deviation values into a controller K in the DSP module, and calculating by the controller K through a controller algorithm to obtain basic control quantities;
(f) the interference observer in the DSP module consists of a Q filter and a physicochemical generalized object inverse QGn-1, and comprises two inputs of a current control quantity and a displacement quantity, wherein the current control quantity is input into the Q filter for calculation, the displacement quantity is input into the physicochemical generalized object inverse QGn-1 for calculation, and the calculation results of the current control quantity and the displacement quantity are subtracted to form an interference estimation quantity;
(g) and obtaining a current control quantity by utilizing the interference estimation quantity and the basic control quantity in the DSP module, then transmitting the current control quantity to the FPGA module, forming a PWM waveform in the FPGA module, controlling a power amplifier to generate electromagnetic force, and realizing high-precision stable suspension of the magnetic bearing.
Inverse G of the generalized object in said step (a)n -1The transfer function is:
wherein: k is a radical ofwIs the power amplifier coefficient, ksFor sensor sensitivity, m is the mass of the magnetic bearing, khIs the displacement stiffness, k, of the magnetic bearingiIs the current stiffness of the magnetic bearing.
The Q filter in the step (f) is a low-pass filter which has no zero point and has the number of poles which is one order higher than the order of the generalized controlled object, and the transfer function of the low-pass filter is as follows:
q(s) represents a laplacian transform form of the Q filter, s is a laplacian operator, τ is a Q filter parameter, and the Q filter cutoff frequency can be adjusted.
Inverse QG of physicochemical generalized object in the interference observer in the step (f)n -1Inverse G of generalized objectn -1Product with a Q filter.
The frequency sweeping circuit in the step (a) consists of an inverse adder and a primary inverter, wherein two inputs of the inverse adder are a sensor output and an excitation signal, and the excitation signal is a sine signal.
The principle of the invention is as follows: the difference caused by the external interference and the parameter change of the controlled object is equivalent to the control input end, namely the equivalent interference is observed, and the equivalent compensation is introduced in the control, so that the complete inhibition of the interference is realized. Meanwhile, model differences caused by parameter changes of the generalized controlled object are observed and fed back to the control input end, so that nonlinearity in a certain range is eliminated.
As shown in fig. 7, the transfer function between the input end u of the generalized controlled object and the output end y of the generalized controlled object can be obtained as follows:
from fig. 7, the transfer function between the input disturbance d and the generalized controlled object output y is obtained as follows:
where y(s) represents the laplacian transform form of the output y of the generalized controlled object, and s is the laplacian operator. D(s) represents the Laplace transform form of interference d, U(s) represents the Laplace transform form of input u of the generalized controlled object, G(s) represents the generalized controlled object, GnAnd(s) represents a nominal model of the generalized controlled object, namely the generalized object model adopted in the disturbance observer algorithm. Let the cut-off frequency of the low-pass filter Q(s) be fqWhen f is less than or equal to fqI.e. in the low frequency band, | Q (jw) | is approximately equal to 1, then Guy＝Gn，G dy0. Wherein G isuy≈GnEven if there is uncertainty in the model, i.e. G ≠ GnThe response of the actual object recognized by the disturbance observer is consistent with the response of the nominal model, namely the controller has certain robustness to parameter change of the generalized controlled object; gdyA disturbance observer of 0 indicates that it has full suppression capability for low frequency disturbances in the q(s) band.
When f is more than or equal to fqThat is, in the high frequency band, | Q (jw) | is assumed to be ≈ 0, then Guy＝G，Gdy＝G。GuyG explains the interference viewThe detector has no effect on the perturbation of the object parameters. GdyG illustrates that due to the low-pass filtering effect of the disturbance observer, there is no suppression effect on the disturbance in the q(s) high band, and the transfer function of the system based on the disturbance observer remains the transfer function of the original system.
From the above analysis, the key step of designing the high-precision magnetic bearing axial control method based on the disturbance observer is the Q filter, and if the Q filter has an ideal low-pass filter form, the above analysis performance is completely achieved, but the ideal low-pass filter is physically unrealizable. Therefore, designing the form and cut-off frequency of the Q filter determines the dynamic performance of the entire disturbance observer. Meanwhile, the suppression capability of the interference and the robustness of the interference observer need to be considered, and the following constraint conditions exist:
(1) the order of the Q(s) filter satisfies Q Gn -1(s) regular, physically realizable. Namely, the relative order of the q(s) filter is required to be greater than or equal to that of the generalized controlled object model g(s), and the q(s) filter is not too high, and increasing the order of the filter causes uncertain marginal effect, which actually reduces the robust stability of the control system of the q(s) filter near the peak value. The amount of calculation of the controller is also increased, which is disadvantageous to real-time control. Therefore, a low-pass filter without zero points and with the number of poles higher than the order of the generalized controlled object by one order is selected.
(2) The wider the frequency band of the Q(s) filter, the stronger the ability of suppressing the external interference of the system, but the larger the gain of the high frequency band, the worse the robust stability, and the increased sensitivity to the measurement noise; conversely, the narrower the frequency band, the better the robustness and stability, the less sensitive the measurement noise, and the weaker the suppression capability of external interference. Reference may be made to q(s) formula of the form:
wherein, <math> <mrow> <msub> <mi>α</mi> <mi>k</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mi>N</mi> <mo>!</mo> </mrow> <mrow> <mrow> <mo>(</mo> <mi>N</mi> <mo>-</mo> <mi>k</mi> <mo>)</mo> </mrow> <mo>!</mo> <mi>k</mi> <mo>!</mo> </mrow> </mfrac> </mrow></math>
is a coefficient, N is the order of the denominator, M is the order of the numerator, and N-M is the relative order.
As can be seen from the interference transfer function analysis, in an ideal case, if the transfer function of the generalized controlled object is consistent with the nominal model, the analysis has an ideal result, but in the case of modeling error perturbation and external interference, an error necessarily exists between the actual system and the nominal model. The actual parameters of the generalized object can be obtained through a sweep frequency experiment of the system, and a relatively accurate nominal model is established. And in the implementation of the residual model error in the disturbance observer, converting the residual model error to a control signal end, equivalently converting the residual model error into external disturbance, and compensating.
The invention is used on the premise that an accurate nominal model is established through a frequency sweep experiment to obtain model parameters, and the frequency sweep is obtained by a frequency response curve of a single-input single-output system, so that the frequency sweep can be realized on an axial single channel of the magnetic bearing, and the application range of the radial coupled multi-channel axial control system in the single channel is limited by using a frequency sweep method.
In conclusion, the high-precision magnetic bearing axial control method based on the disturbance observer can perform online observation on uncertain and unknown external disturbances, effectively suppress the disturbances, and achieve the purpose of high-precision control.
Compared with the prior art, the scheme of the invention has the main advantages that:
(1) due to the adoption of the algorithm of the interference observer, observation and inhibition of unmoldable and uncertain disturbance are realized, and the axial control precision of the magnetic bearing is improved;
(2) the online observation and suppression of disturbance are realized through the disturbance observer, the calculation amount of the algorithm is small, the calculation time is short, the field realization is easy, and the debugging process is flexible;
(3) external interference of various different frequency bands can be effectively inhibited by changing the cut-off frequency of the Q filter in the interference observer;
(4) the interference observer part of the invention has independence, and the observed interference magnitude value realizes recording and quantitative analysis, thereby expanding the application range.
Drawings
FIG. 1 is a schematic block diagram of a system implemented by the method of the present invention;
FIG. 2 is a schematic circuit diagram of the A/D module of FIG. 1;
FIG. 3 is a schematic circuit diagram of a hardware portion of the DSP block of FIG. 1;
FIG. 4 is a schematic circuit diagram of the FPGA module of FIG. 1;
FIG. 5 is a flow chart of an implementation of the method of the present invention;
FIG. 6 is a schematic diagram of the frequency sweep circuit of FIG. 1;
FIG. 7 is a functional block diagram of the present invention;
FIG. 8 is a flow chart of the disturbance observer algorithm of the present invention.
Detailed Description
As shown in fig. 1, the system for implementing the method of the present invention includes a frequency sweep circuit 5 and digital control hardware 6, wherein the digital control hardware 6 includes an a/D module 8, a DSP module 9 and an FPGA module 7; the sweep frequency circuit 5 superposes an output signal and an excitation signal of the sensor 4 and then transmits the superposed signals to the A/D module 8, the FPGA module 7 receives digital quantity converted by the A/D module 8 and then transmits the digital quantity to the DSP module 9, the DSP module 9 calculates by adopting an interference observer algorithm to obtain current control quantity and then transmits the current control quantity to the FPGA module 7, and then the FPGA module 7 converts the current control quantity into a PWM form to be output, and drives the power amplifier 2 to generate electromagnetic force to act on the magnetic bearing, so that the suspension function is realized.
Fig. 2 shows a schematic diagram of the a/D module 8 of the present invention, and the a/D module 8 is used for collecting displacement values and converting the displacement values into digital values. The A/D module 8 adopts an AD7938 chip of TI company, the precision of the chip is 12 bits, the chip is output in parallel, and 8 channels can sample simultaneously. AD7938 single channel sampling rate is: 25M/(17 x 8) ═ 183.8235KHz, can satisfy the requirement of the required sampling rate (10KHz) of bearing control. The output voltage of the AD chip is adjustable, the output high level is 3.3V, and a level conversion circuit required when the AD chip is connected with the FPGA module 7 can be omitted.
As shown in fig. 3 and 4, the DSP module 9 and the FPGA module 7 of the present invention are main control chips of a digital control hardware part. The FPGA module 7 is used as a main control system to control the A/D module 8 to process external signals, the external signals are sent into the DSP module 9 through the bus to be operated, and the operation result is sent back to the FPGA module 7 through the bus to form a PWM signal to drive the power amplifier.
The hardware part of the DSP module 8 adopts TMS320VC33 chip of TI company, the dominant frequency can reach 150MHz at most, the word length is 32 bits, the extension precision is 40 bits, the instruction fetching and the data reading can be carried out simultaneously by separate program bus, data bus and DMA bus, the synchronous serial port is integrated, and the high-speed communication between DSPs can be realized.
The hardware part of the FPGA module 7 selects a Spartan-3 series XC3S400 chip of Xilinx, the chip integrates 40 ten thousand gates to meet the requirement of managing and controlling resources required by peripherals, the power supply voltage of an I/O port of the chip is 3.3V, the power supply voltage of a kernel is 1.2V, and the power consumption is low. And the download modes of main serial, main parallel and JTAG are supported, and the debugging is flexible and convenient.
As shown in fig. 5, the method for controlling the axial direction of the magnetic bearing with high precision based on the disturbance observer of the present invention comprises the following steps:
the method comprises the following steps: respectively carrying out frequency sweep experiments on the power amplifier 2 and the generalized controlled object 1 including the power amplifier by using the frequency sweep circuit 5, obtaining parameters of the generalized controlled object, and establishing inverse G of the generalized objectn -1The transfer function is removed, then the frequency sweeping circuit 5 is removed, and the sensor 4 is directly connected to the A/D module 8;
according to the principle of the invention, the design of the method depends on whether the parameters of the generalized controlled object are accurate or not, so before the method is used, a frequency sweeping experiment must be carried out on the generalized controlled object to obtain the actual parameters of the object model.
As shown in fig. 6, is a frequency sweep circuit 5 incorporated in the present invention. As shown in FIG. 1, A, B, C, D is an electrical connection point for testing different links. A. B, C, D represent four test points in the closed loop control system, respectively: the point A is the value of the displacement sensor after conditioning, the point B is the input signal value of the controller, the point C is the digital control quantity output, and the point D is the current magnitude.
Adopting Agilent35670A dynamic analyzer to perform frequency sweep experiment on power amplifier link, as shown in FIG. 1, inputting sweep excitation signal and sensor signal into inverse adder composed of operational amplifier, and passing through first-stage inverter composed of operational amplifierAfter the operation, the signal becomes an output signal and is transmitted to the A/D module port. The operational amplifier is TL084 from TI company. The input end of the dynamic analyzer is connected to the point C in fig. 7, namely the digital quantity output of the controller, and the output end of the dynamic analyzer is connected to the point D in fig. 7, namely the current quantity value output by the power amplifier. The excitation signal added at the excitation end is VPeak value＝40mV，VBiasingAnd (3) obtaining a frequency sweep curve of the power amplifier according to the frequency sweep of the sinusoidal signal of 0V, wherein the frequency of the sinusoidal signal is from 0.1Hz to 2kHz when the frequency sweep is carried out. The theoretical formula of the power amplifier is shown as follows:
Gw＝kwgwLPF
wherein k iswIs the power amplifier DC amplification factor, gwLPFIs a power amplifier low-pass filter function. Obtaining an analytical expression of an actual model after fitting the sweep frequency curve, and comparing the analytical expression with a theoretical formula to obtain an actual kwThe parameter values.
And performing a frequency sweep experiment on the generalized controlled object 1 including the power amplifier 2 by adopting the same method, wherein the input end outputs a point C in the digital control quantity, and the output end outputs a point A in the sensor, so as to obtain an analytical expression of the generalized controlled object. According to the formula:
to find a generalized senseInverse G of the objectn -1(s), wherein r: k is a radical ofsFor sensor sensitivity, m is the mass of the magnetic bearing, khIs the displacement stiffness, k, of the magnetic bearingiIs the current stiffness, k, of the magnetic bearingwIs the power amplification coefficient, and adopts the measured parameters.
In establishing inverse G of generalized objectn -1After the transfer function, in order to ensure that the system is not interfered by other signals, the frequency sweeping circuit part must be removed, and the sensor is directly connected to the A/D module to form an independent closed-loop system for operation.
Step two: initializing parameters of a disturbance observer 11 and a controller K in the DSP module in the control method, setting a storage space of sampling data, and setting a sampling mode of the FPGA module 7 as clock interrupt.
The initialized parameters include parameters in PID control of the controller K, parameters of the Q filter 12 used in the disturbance observer obtained by the sweep experiment and the physicochemical generalized object QG n -113, and the like, specifically comprising: (a) the initialized parameters of the controller K10 include: setting suspension center position parameters of the magnetic bearing, wherein the values of the suspension center position parameters are half of the positions at two ends of the magnetic bearing and are used as center positions; the proportional, integral and differential parameters of the controller have preset values; the time constant of the controller, its value is identical to sampling time; the control variable memory locations of the controller are initialized to zero. (b) The parameters of the initialized Q-filter 12 include: a set Q filter cut-off frequency, the value of which is set to 20Hz, which is the minimum cut-off frequency; the filter parameters calculated according to the cut-off frequency are the corresponding multiplication coefficients for input and output obtained according to the transfer function and the cut-off frequency of the Q filter; the storage unit for the input quantity and the output quantity in the Q filter is initialized to zero. (c) Initialized physicochemical generalized object inverse QGn -1The parameters of 13 include: the input and output multiplication weight parameter is obtained by calculating the value of the input and output multiplication weight parameter according to the cut-off frequency of the Q filter; the storage locations for the input and output quantities are initialized to zero. Sampling time of A/D module 8Is 7kHz, the memory space opened up in the controller K10 is mapped into distributed ROM inside the FPGA module 7.
Step three: the FPGA module 7 controls the A/D module 8 to sample to obtain the displacement output by the sensor 4, and the displacement is converted into digital quantity to be input into the DSP module 9 of the hardware controller; the A/D module 8 and the FPGA module 7 adopt the design of the digital control hardware.
Step four: the FPGA module 7 transmits the digital quantity to the DSP module 9, and the DSP module 9 calculates the input displacement quantity value according to the given suspension center position to obtain the corresponding displacement deviation value; the suspension position given in the DSP module 9 is the center position of the magnetic bearing, and before system debugging, non-floating is adopted, the positions of both ends acquired by the a/D module 8 are halved as the center position, and the direction is determined such that if the direction is above the center position, the displacement deviation amount is a positive value, otherwise, it is a negative value.
Step five: the input displacement deviation amount is calculated in a DSP module 9 by adopting a controller K algorithm to obtain a basic control amount; the algorithm of the controller K uses a decentralized PID control algorithm, and the transfer function is as follows:
wherein, KpIs a proportionality coefficient, TiAs an integral coefficient, TDIs a differential coefficient, TfIs a differential ringAnd (4) saving the time constant of the added inertia link, wherein T is the sampling period.
Step six: the interference observer algorithm in the DSP module 9 has two inputs, the current control quantity is input into a Q filter for calculation, and the displacement quantity is input into a physicochemical generalized object inverse QGn -1Calculating, subtracting the calculation results of the two to obtain an interference estimation quantity;
FIG. 7 is a schematic block diagram of a disturbance observer according to the present invention, where y is the output of the generalized controlled object, d is the disturbance, u is the input of the generalized controlled object, G(s) represents the generalized controlled object, Gn(s) a nominal model of the generalized controlled object, i.e. the generalized object model used in the disturbance observer algorithm, the disturbance observer is used for disturbance observation and compensation of the system, and the output of the actual object G(s) caused by external disturbance is added to Gn -1And(s) reproducing the sum of the disturbance and the error signal, subtracting the error signal, observing the disturbance quantity, introducing equivalent compensation in the control input, and eliminating the disturbance. It can be seen from the principle analysis that the key of the present invention is to find the nominal model G based on the magnetic bearing systemnAnd realization of Gn -1(s) Q filter. The nominal model G is obtained by previous frequency sweep experimentsnNext, a suitable Q filter is selected and a disturbance observer algorithm is implemented.
According to the principle of the invention, the order of the generalized controlled object is 2 orders, and the relative order of the selected Q filter must be greater than or equal to 2 orders, so a general formula is selected, where N is 3, M is 0, and the relative order is N-M is 3, so that the requirement of the relative order is met, and a good robust performance index is ensured, as shown in the following formula:
where τ is the Q filter parameter, the Q filter cutoff frequency can be adjusted. In the implementation process, the cut-off frequency of the low-pass filter can be adjusted according to the interference characteristic, the range of the cut-off frequency is 20Hz to 1630Hz, and the corresponding tau is 0.004 to 0.00005.
Inverse QG of physicochemical generalized objectn -1The form of the Q filter 12 selected in 13 is identical to the Q filter 12 described above, and the parameters are the same. Inverse G of generalized objectn -1I.e. the transfer function obtained in the step one, namely the inverse QG of the physicochemical generalized objectn -1(s) transfer function is the inverse G of the generalized objectn -1(s) and Q(s) of the Q filter, as shown by:
fig. 8 is a flowchart of the disturbance observer algorithm according to the present invention. The designed transfer function is discretized by a backward difference method, a forward difference method, a Tustin transformation method or a pre-correction Tustin transformation method. The invention adopts backward difference method to compile corresponding algorithm. In the implementation of the interference observer algorithm, firstly, parameters used by the algorithm are initialized according to a set cut-off frequency, the inverse input of a physicochemical generalized object is a displacement value of an axial sensor, and a result is obtained through calculation; then, the input of the Q filter is axial control quantity, and a corresponding result is obtained through calculation; and subtracting the two results to obtain an interference estimation value observed by the interference observer, adding the interference estimation value into the control quantity in a negative feedback manner, and performing equivalent compensation on external disturbance to realize high-precision control of the magnetic bearing.
Step seven: the current control quantity is obtained by utilizing the interference estimation quantity and the basic control quantity in the DSP module 9, then the current control quantity is transmitted to the FPGA module 7, a PWM waveform is formed in the FPGA module 7, and a power amplifier is controlled to drive an electromagnet to generate electromagnetic force, so that the high-precision stable suspension of the magnetic bearing is realized.
In conclusion, the invention can effectively control the suspension stability of the magnetic bearing and compensate the interference of the external unknown and unmodeled disturbance on the axial magnetic bearing. Through the comparison and calculation between the control quantity and the displacement quantity, the disturbance on the system is solved, and the disturbance is restrained by adding negative feedback into the system. Meanwhile, an oscilloscope or a spectrum analyzer can be used for carrying out dynamic analysis on the observed disturbance, and the disturbance condition of the magnetic bearing is quantitatively solved. In the process of using the disturbance observer, disturbance of different frequency bands can be effectively inhibited by adjusting the cut-off frequency of the Q filter, and the flexibility of system debugging is enhanced. The method has the advantage of remarkably improving the suspension precision of the magnetic suspension axial magnetic bearing.
Those skilled in the art will appreciate that the invention may be practiced without these specific details.
Claims (5)
1. A high-precision magnetic bearing axial control method based on a disturbance observer is characterized by comprising the following steps:
(a) firstly, adding a frequency sweep circuit, respectively carrying out frequency sweep experiments on a power amplifier and a generalized controlled object including the power amplifier, acquiring parameters of the generalized controlled object, establishing an inverse Gn-1 transfer function of the generalized object, then removing a frequency sweep circuit part, and directly accessing the output of a sensor to an A/D module;
(b) initializing a K parameter of a disturbance observer and a controller in a DSP module, setting a sampling data storage space, and setting a sampling mode of an FPGA module as clock interrupt;
(c) the FPGA module controls the A/D module to sample to obtain sensor output and receives a digital quantity result obtained by conversion of the A/D module;
(d) the FPGA module sends the digital quantity to the DSP module, and displacement deviation corresponding to the input displacement value is calculated in the DSP module according to the given suspension center position;
(e) inputting displacement deviation values into a controller K in the DSP module, and calculating by the controller K through a controller algorithm to obtain basic control quantities;
(f) the interference observer in the DSP module consists of a Q filter and a physicochemical generalized object inverse QGn-1, and comprises two inputs of a current control quantity and a displacement quantity, wherein the current control quantity is input into the Q filter for calculation, the displacement quantity is input into the physicochemical generalized object inverse QGn-1 for calculation, and the calculation results of the current control quantity and the displacement quantity are subtracted to form an interference estimation quantity;
(g) and obtaining a current control quantity by utilizing the interference estimation quantity and the basic control quantity in the DSP module, then transmitting the current control quantity to the FPGA module, forming a PWM waveform in the FPGA module, controlling a power amplifier to generate electromagnetic force, and realizing high-precision stable suspension of the magnetic bearing.
2. The disturbance observer-based high precision magnetic bearing axial control method of claim 1, wherein: inverse G of the generalized object in said step (a)n -1The transfer function is:
wherein: k is a radical ofwIs the power amplifier coefficient, ksFor sensor sensitivity, m is the mass of the magnetic bearing, khIs the displacement stiffness, k, of the magnetic bearingiIs the current stiffness of the magnetic bearing.
3. The disturbance observer-based high precision magnetic bearing axial control method of claim 1, wherein: the Q filter in the step (f) is a low-pass filter which has no zero point and has the number of poles which is one order higher than the order of the generalized controlled object, and the transfer function of the low-pass filter is as follows:
q(s) represents a laplacian transform form of the Q filter, s is a laplacian operator, τ is a Q filter parameter, and the Q filter cutoff frequency can be adjusted.
4. The disturbance observer-based high precision magnetic bearing axial control method of claim 1, wherein: inverse QG of physicochemical generalized object in the interference observer in the step (f)n -1Inverse G of generalized objectn -1And Q filteringThe product of the multipliers.
5. The disturbance observer-based high precision magnetic bearing axial control method of claim 1, wherein: the frequency sweeping circuit in the step (a) consists of an inverse adder and a primary inverter, wherein two inputs of the inverse adder are a sensor output and an excitation signal, and the excitation signal is a sine signal.
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