CN104184382B - Method for observing speed of permanent magnet motor - Google Patents

Method for observing speed of permanent magnet motor Download PDF

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CN104184382B
CN104184382B CN201410393609.XA CN201410393609A CN104184382B CN 104184382 B CN104184382 B CN 104184382B CN 201410393609 A CN201410393609 A CN 201410393609A CN 104184382 B CN104184382 B CN 104184382B
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observer
kalman
motor
speed
rotating speed
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CN104184382A (en
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史婷娜
王铮
夏长亮
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天津大学
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Abstract

The invention discloses a method for observing the speed of a permanent magnet motor, and relates to the field of speed observation and speed control for motors. The method comprises the steps of combining the rotor position acquired by an absolute type encoder with three parts of a designed kalman observer, observing the rotating speed of a rotor and a load torque of the motor, and using the observed rotating speed as feedback signals of a rotating speed ring of a permanent magnet synchronous motor control system; regarding the suddenly changed load torque of a permanent magnet synchronous motor as a system disturbance variable, using the motor load torque observed by the constructed kalman observer as feed-forward signals of a current loop, and constructing a feed-forward control system; acquiring the switching sequence of an inverter through a current controller and a space vector pulse width modulation method, then acquiring three-phase voltage inputting into the permanent magnet synchronous motor, and finally enabling the permanent magnet motor to rotate by a certain rotating speed. The method disclosed by the invention adopts the load torque acquired by the adaptive kalman observer, thereby being capable of timely reflecting load variation conditions of the system, carrying out feed-forward control on the estimated load torque, and being capable of improving an accurate tracking ability for the rotating speed.

Description

A kind of magneto speed observation procedure

Technical field

The present invention relates to motor speed observation and speed controlling field, more particularly, to a kind of magneto speed observation side Method.

Background technology

For permagnetic synchronous motor (PMSM) servosystem, the rotor-position of motor and rotating speed are closed loop control systems Requisite feedback quantity in system.In traditional location measurement method, position signalling is many to be obtained by optical encoder.Light Learn encoder and be generally divided into incremental encoder, absolute type encoder and hybrid encoder.Wherein, absolute type encoder energy Enough directly obtain the binary coding of rotor absolute position, each position has unique binary coding.Compile compared to other Code device, absolute type encoder has obvious advantage at aspects such as capacity of resisting disturbance, stationkeeping abilities, thus sets in high-accuracy mechanical The place such as standby has obtained many applications.

The reason such as non-ideal being made due to quantizing noise and optical encoder itself, by turning that optical encoder records There is measurement noise in sub- position, thus certain error be there is also by the calculated rotating speed of rotor position information.Additionally, passing The encoder of system tests the speed computational methods, such as:The speed-measuring methods such as measured frequency method, measuring period method, are all based on derivative algorithms solution and turn The meansigma methodss of speed, so cause rotating speed value of calculation to there is error and delay, thus have impact on permanent magnet synchronous electric to a certain extent The dynamic and static performance of machine servo system.In order to reduce the problem that traditional speed-measuring method exists, generally adopt wave digital lowpass filter To suppress noise, but conventional lowpass filter cannot realize the purpose suppressing noise and reducing time delay simultaneously.

In order to solve the shortcoming of traditional speed-measuring method, the method that scholars propose multiple observation rotating speeds, such as nonlinear riew Survey device, sliding mode observer etc..System, in the case of low cruise, is not each sampling period to calculate rotating speed, in order to true Protect within each sampling period rotating speed can real-time update, can be using adaptive speed observer, instantaneous velocity observer, complete Dimension or Reduced-Order State Observer are observed and carry out motor control to the rotating speed of magneto, rotor-position etc., but these Method depends on the accurate mathematical model of motor, and systematic function is vulnerable to Parameters variation and the impact of various uncertain factor, makes Obtain its application limited.Because the measurement noise of encoder can be counted as white Gaussian noise, Kalman (Kalman) filtering algorithm As the optimal effectiveness method of estimation in a kind of minimum variance meaning, it using recurrence method directly to random noise disturbance at Reason, and have less dependency to model, therefore, obtain relatively broad application in terms of system speed observation.However, by Need to carry out many experiments to noise parameter in traditional Kalman filter algorithm, just can have preferable observation effect, so, Work efficiency undoubtedly can be reduced, therefore, seek a kind of method solving or substitute this problem urgently important.

Content of the invention

The invention provides a kind of magneto speed observation procedure, present invention, avoiding the differential in traditional speed-measuring method Process and filtering, make up the measurement error of the absolute type encoder of finite accuracy, thus improve motor speed to control system The control accuracy of system and Immunity Performance, described below:

A kind of magneto speed observation procedure, the method comprising the steps of:

The rotor-position that absolute type encoder is obtained is combined with three parts of designed kalman observer, sees Measure rotor speed and the load torque values of motor, using the rotating speed observed as control system for permanent-magnet synchronous motor der Geschwindigkeitkreis Feedback signal;

The load torque that permagnetic synchronous motor is mutated regards system interference amount as, is seen using constructed kalman observer The electric motor load torque surveyed, as the feed-forward signal of electric current loop, builds feedforward control system;

Obtain the switching sequence of inverter by current controller and space vector width pulse modulation method, and then acquisition is passed through The three-phase voltage of permagnetic synchronous motor, finally makes magneto with certain rotational speed.

Three parts of described designed kalman observer are specially:

1) by coefficient square based on durface mounted permanent magnet synchronous motor mathematical model is obtained to the design of Kalman's observer Battle array;

2) part is observed according to Kalman's observer, devise the alternative manner of Kalman observer;

3) according to measurement noise self adaptation part, the computational methods of measurement noise are devised.

Described it is specially based on the coefficient matrix of durface mounted permanent magnet synchronous motor mathematical model:

In formula, J is rotary inertia;F is friction torque coefficient;KTFor motor torque coefficient;TsFor the sampling period.

Described part is observed according to Kalman's observer, the alternative manner devising Kalman observer is specially:

The alternative manner of Kalman observer is

In formula, and x (k | k) it is kth TsThe posterior estimate of moment state variable;P (k | k) it is kth TsMoment error covariance Posterior estimate;X (k | k-1) it is kth TsEstimated value is tested before the state variable in moment;P (k | k-1) it is respectively kth TsMoment Estimated value is tested before error covariance;I is unit matrix;K (k), err (k) are kth TsThe Kalman gain in moment and tested The residual error of signal.

Described according to measurement noise self adaptation part, the computational methods devising measurement noise are specially:

Wherein, k is kth time sampling, TsFor the sampling period, ω (k | k-1) test discreet value for before kth moment state variable, Δ is quantization error.

The beneficial effect of technical scheme that the present invention provides is:

(1) present invention be directed to speed error during magneto low cruise and filter delay problem it is proposed that a kind of from Adapt to Kalman's observer, compared to traditional speed-measuring method, adaptive Kalman observer proposed by the invention becomes in rotating speed In the case of change, can more accurately realize the identification of rotor-position, and realize the quick tracking of rotating speed.

(2) PMSM can be entered using the rotor-position and rotating speed of adaptive Kalman observer proposed by the present invention identification Row closed loop control well, and there is the less fluctuation of speed, reduce the fluctuation of q shaft current during startup simultaneously.

(3) adaptive Kalman observer can promptly and accurately identifying motor dynamic change when rotating speed so that system tool There is dynamic responding speed faster.

(4) the load change feelings of system can be reflected in time using the load torque that adaptive Kalman observer obtains Condition, the load torque estimated is carried out the feedforward, it is possible to increase the accurate ability of tracking of rotating speed.

Brief description

Fig. 1 is permagnetic synchronous motor Feedforward-feedback control block diagram;

Fig. 2 measures figure for rotor-position signal, and Fig. 2 (a) is signal measurement figure during motor low cruise;Fig. 2 (b) is electricity Signal measurement figure during machine high-speed cruising;

Fig. 3 is the flow chart of Kalman observer;

Fig. 4 is permagnetic synchronous motor Feedforward-feedback control simplified block diagram;

Fig. 5 is the experimental waveform under cycle overlay method, and Fig. 5 (a) calculates rotating speed n for cycle overlay method3And iqWaveform;Fig. 5 B () is enlarged drawing when starting;

Fig. 6 is the experimental waveform under Adaptive Kalman observer, and Fig. 6 (a) estimates rotating speed for KalmaniqWith's Waveform;Fig. 6 (b) is enlarged drawing when starting;

Fig. 7 is that the observer of the present invention adds experimental waveform under feedforward controller, and Fig. 7 (a) estimates rotating speed for Kalman iqWithWaveform;Fig. 7 (b) is enlarged drawing when starting.

Specific embodiment

For making the object, technical solutions and advantages of the present invention clearer, below embodiment of the present invention is made further Ground describes in detail.

A kind of magneto speed observation procedure, this method carries out rotating speed using the rotor-position that absolute type encoder records And load torque estimates, and controlled using rotating speed, current double closed-loop, outer shroud is der Geschwindigkeitkreis, feedback signal is to estimate rotating speed, adopts Ratio and integral controller, abbreviation PI controller, internal ring is electric current loop, and using PI controller, estimating load torque is feedforward letter Number, using feedforward controller;The motor speed measurement based on adaptive Kalman observer of present invention design is by three part groups Become, a part is Kalman's observer modeled segments, and a part is Kalman's observer observation part, another part is that measurement is made an uproar Sound self adaptation part, this three parts collective effect obtains speed feedback signal and the load torque feed-forward signal of system, the method Concrete operation step described below:

The present invention devises the permagnetic synchronous motor Feedforward-feedback control system based on Adaptive Kalman observer, such as Shown in Fig. 1.In figure, permagnetic synchronous motor adopts id=0 rotating speed, the vector control strategy of current double closed-loop, and using limited The absolute type encoder of precision is accurately observed to rotor-position, rotating speed and load torque with adaptive Kalman observer, And using the signal of observation as the feedback signal of der Geschwindigkeitkreis and load torque interference compensation signal.

To control from the analysis of absolute type encoder range rate error, the design of Adaptive Kalman observer, rotating speed PI below The design of link, the design of feedforward compensation link, current controller, space vector pulse width modulation, inverter and PMSM, experiment knot Fruit is analyzed eight aspects and is described further.

1st, absolute type encoder range rate error analysis

The code-disc of n position absolute type encoder is on the donut of circular glass or plastics, depicts n circle and uniformly divides The printing opacity of cloth and light tight alternate groove, the value of adjacent code channel is according to certain rule arrangement, any one radial position Only unique 2 scale codings correspond to therewith, and binary coding scope is 0~2n-1.N position absolute type encoder is corresponding Resolution is 1/2n, be equivalent to n position absolute type encoder and be melted into 2 by discrete for the circumference of 2 π radnIndividual differ as 2 pi/2snThe one of rad The position signalling of series.

Fig. 2 (a) and Fig. 2 (b) is respectively under low speed and high-speed case, continuous rotor-position signal, absolute type encoder The position signalling picking out and the position signalling being obtained through digital signal processor (DSP) sampling by absolute type encoder output Curve chart.For the ease of analysis it is assumed that rotating speed is the steady state value more than zero.

In figure, k is sampling number, k=1,2 ...;θ is rotor-position;θ (m) is the rotor-position of the m time reading of DSP, m =1,2 ...;For the derivative of rotor-position, i.e. rotational speed omega;TsSampling period for controller;T1_actualFor absolute encoding The double time interval picking out new rotor-position of device;T1For the double time interval reading new rotor-position of DSP.

As seen from Figure 2, when rotor-position variable quantity is equal to its quantization error Δ=2 pi/2nDuring rad, absolute type is compiled Code device can obtain the rotor-position of discretization in time, but only when next sampled signal arrives, new rotor-position is Can be read by DSP.This has resulted in exists between the position signalling that the position signalling that absolute type encoder picks out and DSP read Measurement error.When sampling instant just occur before encoder picks out new rotor-position at that moment when, measurement occurs Error is maximum, and its value is quantization error Δ=2 pi/2nrad;And work as sampling instant and just occur to pick out new turning in encoder During sub- position, measurement error is minimum, and its value is 0.

By Fig. 2 (a) as can be seen that when system low cruise, rotor-position signal change is slow, absolute type encoder is even Continuous time interval T picking out new rotor-position twice1_actualMore than sampling time Ts, i.e. the fixing sampling period, now DSP Double time interval T reading new rotor-position1More than Ts;By Fig. 2 (b) as can be seen that when system high-speed runs, turning Sub- position signalling change is rapid, T1_actual<Ts, now T1=Ts.

The rotor-position signal derivation that DSP is read, you can obtain tach signal.Traditional speed-measuring method such as Euler test the speed Method, variable period velocimetry and cycle overlap velocimetry all obtain rotating speed using the method that difference coefficient forward approximately to replace derivative.On State three kinds of algorithms and only after DSP continuously reads new rotor-position signal, just calculate rotating speed, be not within each sampling period All calculate rotating speed, therefore, the speed-measuring method based on above-mentioned algorithm unavoidably has larger speed error and delay of testing the speed.

2nd, the design of Adaptive Kalman observer

1) by coefficient square based on durface mounted permanent magnet synchronous motor mathematical model is obtained to the design of Kalman's observer Battle array;

Voltage equation under synchronous rotating frame (d-q) for the durface mounted permanent magnet synchronous motor is

Wherein, ω is the mechanical angular velocity of motor;D axle is rotor magnetic pole axis, q axle advanced 90 degree of spaces of d axle counterclockwise Electrical angle, this d-q coordinate system is spatially rotated therefore referred to as synchronously rotating reference frame with electromechanics angular velocity omega together with rotor System;ud、uq、id、iq、Ld、LqIt is respectively motor d, q shaft voltage, electric current and stator inductance, and Ld=Lq;P is number of pole-pairs;RsIt is fixed Sub- resistance;ψfFor rotor flux.

Motor movement equation is

In formula, J is rotary inertia;F is friction torque coefficient;KTFor motor torque coefficient;TLFor load torque, testing the speed One controlling tests the speed, and the cycle is interior it is believed that load torque is definite value, that is,

Wherein, this step is specially:Discretization is carried out to the equation of motion of permagnetic synchronous motor, following karr can be designed Graceful observer:

In formula, k represents sampling number;X=[θ ω TL]TFor state variable;U=[iq] it is control signal;Y=[θ] is It is observed signal;W is system noise, the impact that the system parameter error of representative is brought;R is measurement noise, including encoder Other noises in quantization error and measurement process and interference;θ is motor rotor position;ω is the mechanical angular velocity of motor; iqFor motor q shaft current;TLFor load torque, it is believed that load torque is definite value, that is, within a cycle of testing the speed of control of testing the speed The derivative of load torqueCoefficient matrix is

In formula, TsFor the sampling period.

It is generally acknowledged that w (k) and r (k) is stable white Gaussian noise, its meansigma methods is zero, and the variance matrix of noise meets

In formula, Q and R is diagonal matrix, due to being observed signal y=[θ] herein, therefore error r and observational variance R= [R (k)] is first order matrix.

2) part is observed according to Kalman's observer, devise the alternative manner of Kalman observer;

Wherein, the alternative manner of Kalman observer is

In formula, and x (k | k) it is kth TsThe posterior estimate of moment state variable;P (k | k) it is kth TsMoment error covariance Posterior estimate;X (k | k-1) it is kth TsEstimated value is tested before the state variable in moment;P (k | k-1) it is respectively kth TsMoment Estimated value is tested before error covariance;I is unit matrix;K (k), err (k) are kth TsThe Kalman gain in moment and tested The residual error of signal, its value can be updated by following formula:

Wherein, y (k | k-1) is kth TsThe measured signal estimated value in moment, can be seen that survey by above recurrence formula Amount noise variance R (k) impact Kalman gain K (k), and then the correction feelings to x (k | k) for the err (k) and x (k | k-1) can be affected Condition.

In traditional Kalman observer, system noise variance Q (k) and measurement noise variance R (k) are all gathered by examination Method, come to determine, needs multigroup repeatability to attempt.After system reaches and stablizes, gain matrix K (k) convergence of Kalman observer For definite value matrix, in each sampling instant, err (k) is identical to the correcting rate of x (k | k-1) for that is, traditional Kalman observer. In rotating speed mutation or load torque mutation, K (k) still keeps constant, and this results in traditional Kalman observer cannot be according to tool Body rotating speed is carrying out rational parameter regulation, and then cannot carry out optimal predictor to rotating speed.

3) according to measurement noise self adaptation part, the computational methods of measurement noise are devised;

At low speeds, DSP may not read new rotor-position in each sampling, now T1>Ts.In present sample In the cycle, when DSP does not export new rotor-position, there is relatively large measurement error in the position signalling that sampling obtains, that is, think The position signalling that this time sampling obtains is incredible, and being manually set measurement noise is Rw, RwFor one larger on the occasion of now blocking Gain K is less for Germania, approximates 0, from formula (5) first formula, the observed result x of Kalman (k | k) can be partial to x (k | k- 1), ignore measured value y (k), do not carry out estimating the correction of position using the rotor-position that DSP reads, but conduct is estimated Device carries out estimating of rotor-position and rotating speed.

In current sample period, when DSP has read new rotor-position, the measurement error of the position signalling now obtaining is relatively Little, its maximum is The rotating speed estimated for Kalman observer.Because measurement error is as random Variable, with TsUncorrelated, you can to think measurement error in 0~emaxIn the range of be equal-probability distribution, the distribution of measurement error is close Degree is inversely proportional to constant interval, then the excursion of measurement error e (t), anticipation error and distribution density are respectively

In formula, e (t) is measurement error value;E [e (t)] is expected error value;F (e, t) is measurement error distribution density.

Can be obtained by formula (7), in current sample period, when DSP reads new rotor-position, measurement noise RtFor

The discrete form of above formula is

Using the calculated R of formula (8)tWhen can reflect under different rotating speeds that DSP reads new rotor-position exactly, Measurement noise between the position signalling being obtained and actual rotor position, by this RtCalculated K can utilize err (k) X (k | k-1) is corrected, obtains accurate x (k | k), now Kalman observer as a state observer to state Variable is observed.

To sum up analysis understands, the Adaptive Kalman observer being constructed is carried out to state variable in each sampling instant Estimate, but only when DSP reads new rotor-position, just carry out the correction of state variable.Then Kalman observer is pre- Estimate the sampling period T that the cycle is fixations, the error correction period interval time T that read new rotor-position double with DSP1Phase Deng.

Measurement noise variance yields R (k) of Adaptive Kalman observer is

Wherein, θ (k) is kth TsThe rotor-position that moment digital signal processor obtains;Rt(k) and RwValue condition such as Under:When digital signal processor (DSP) obtains new rotor-position, the rotor-position recording is relatively accurate, and Kalman observes Device is corrected to predicted state amount using the rotor-position reading, and Kalman's observer enters to quantity of state as state observer Row observation, now the maximum of measurement error is The rotating speed estimated for Kalman observer, now Measurement noise is Rt(k):

Wherein, k is kth time sampling, TsFor the sampling period, ω (k | k-1) test discreet value for before kth moment state variable, Δ is quantization error.

If DSP does not obtain new rotor-position, the rotor position error recording is larger, and the rotor-position now obtaining is by mistake Difference is larger, and the position signalling that is, this time sampling obtains is insincere, and now measurement noise is set as a higher value Rw, now Kalman Gain K is less, approximates 0, iterative from state, and the observed result x of Kalman (k | k) can be partial to x (k | k-1), and Ignore measured value y (k), do not carry out estimating the correction of position using the rotor-position that DSP reads, but carry out as prediction device The estimating of rotor-position and rotating speed.The calculating process of Kalman observer is as shown in Figure 3.

3. the design of rotating speed PI controlling unit

Combined with three parts of designed kalman observer using the rotor-position that absolute type encoder obtains, can So that rotor speed and the load torque values of motor quick and precisely must be observed, using the rotating speed observed as permagnetic synchronous motor control The feedback signal of the der Geschwindigkeitkreis of system processed, can improve the dynamic and static state performance of system.

4. the design of feedforward compensation link

In traditional rotating speed, the double PI feedback control system of electric current, in the case of load changing, rotating speed PI controls motor Device cannot be realized following the tracks of the purpose of rotating speed and opposing load disturbance simultaneously.For the problems referred to above, the load torque that PMSM is mutated Regard system interference amount as, by the use of constructed kalman observer observation electric motor load torque as electric current loop feedforward letter Number, build feedforward control system.Fig. 4 is PMSM Feedforward-feedback control simplified block diagram.

In figure, Gw、GFIt is respectively rotating speed PI controller, feedforward controller transmission function;GIFor system internal ring transmission function, It is approximately the proportional component that proportionality coefficient is 1;GT、GMFor motor model parameter.From motor movement equation

From the figure 3, it may be seen that rotating speed with the transmission function of load torque is

In order to reduce the impact to system rotating speed for the load torque interference, G should be madeF=GT=1.Due to loading the feedforward Device is worked to PMSM system with rotating speed PI controller simultaneously, therefore, GFValue should choose near 1 it is ensured that feedforward control Under device processed and rotating speed PI controller dual function, rotating speed control effect reaches most preferably.By GFAnd the observation of Kalman observer is negative Set torque, as PMSM system feedforward compensation link, is combined with speed feedback link, constitutes PMSM Feedforward-feedback control system System.

5. current controller

Current controller adopts traditional PI controller, and wherein, the set-point of q shaft current controller is rotating speed PI controller The output valve of output valve and front deaf controller value preset, its value of feedback is the electromagnetic torque of motor;The giving of d shaft current controller Definite value is id=0, its value of feedback is motor d shaft current.

6. space vector pulse width modulation

Space vector pulse width modulation strategy (SVPWM) to be modulated using seven sections of traditional methods, the input voltage of SVPWM It is to be obtained after anti-PARK coordinate transform by the magnitude of voltage of d axle and q axle, wherein, d axle and q shaft voltage value are respectively corresponding electricity The output valve of stream controller, 6 groups of height pulses of its SVPWM output are the on off sequence of inverter.

7. inverter and PMSM

Pulse train using SVPWM output is controlled to the switch of inverter, obtains the three-phase voltage of PMSM, PMSM Rotor rotated with certain rotating speed under the driving of three-phase voltage.

8. interpretation

Fig. 5 and Fig. 6 is respectively using the cycle overlay method in traditional velocimetry and self adaptation proposed by the invention Kalman observer gained rotating speed carries out the experimental waveform of closed loop control;Fig. 7 is that the Adaptive Kalman that the present invention is designed is seen Survey the experimental waveform that device acquired results carry out Feedforward-feedback control.

T be can be seen that by Fig. 5 (b) and Fig. 6 (b)1Moment motor starts to start, iqRapid rising, the cycle, overlay method was in t2 , there is time delay after 7ms in moment ability measuring rotating speed;And when being controlled using this paper observer, it is possible to achieve the accurate control of motor System, and there is the less fluctuation of speed and response speed faster;From Fig. 6 and Fig. 7, when motor load is mutated, adaptive Answer Kalman observer can realize accurately estimating of load torque in about 200ms;And after adopting Feedforward-feedback control, bear When carrying mutation, the fluctuation of speed is less.

It will be appreciated by those skilled in the art that accompanying drawing is the schematic diagram of a preferred embodiment, the embodiments of the present invention Sequence number is for illustration only, does not represent the quality of embodiment.

The foregoing is only presently preferred embodiments of the present invention, not in order to limit the present invention, all spirit in the present invention and Within principle, any modification, equivalent substitution and improvement made etc., should be included within the scope of the present invention.

Claims (3)

1. a kind of permanent magnet synchronous electric motor speed observation procedure is it is characterised in that the method comprising the steps of:
The rotor-position that absolute type encoder is obtained is combined with three parts of designed kalman observer, observes Rotor speed and the load torque values of motor, the rotating speed observed is anti-as the der Geschwindigkeitkreis of control system for permanent-magnet synchronous motor Feedback signal;
The load torque that permagnetic synchronous motor is mutated regards system interference amount as, is observed using constructed kalman observer Electric motor load torque, as the feed-forward signal of electric current loop, builds feedforward control system;
Obtain the switching sequence of inverter by current controller and space vector width pulse modulation method, and then acquisition is passed through permanent magnetism The three-phase voltage of synchronous motor, finally makes permagnetic synchronous motor with certain rotational speed;
Three parts of described designed kalman observer are specially:
1) by coefficient matrix based on durface mounted permanent magnet synchronous motor mathematical model is obtained to the design of Kalman's observer;
2) part is observed according to Kalman's observer, devise the alternative manner of Kalman observer;
3) according to measurement noise self adaptation part, the computational methods of measurement noise are devised;
Wherein, described according to measurement noise self adaptation part, the computational methods devising measurement noise are specially:
R t ( k ) = m i n { ( &omega; ( k | k - 1 ) T s ) 2 12 , &Delta; 2 12 }
Wherein, k is kth time sampling, TsFor the sampling period, and ω (k | k-1) test discreet value for before kth moment state variable, Δ is amount Change error.
2. a kind of permanent magnet synchronous electric motor speed observation procedure according to claim 1 it is characterised in that described based on Surface Mount The coefficient matrix of formula permagnetic synchronous motor mathematical model is specially:
A = 1 T s 0 0 1 - f J T s - T s J 0 0 1 ; B = 0 T s K T J 0 ; C = 1 0 0
In formula, J is rotary inertia;F is friction torque coefficient;KTFor motor torque coefficient;TsFor the sampling period.
3. a kind of permanent magnet synchronous electric motor speed observation procedure according to claim 1 it is characterised in that described according to karr Part observed by graceful observer, and the alternative manner devising Kalman observer is specially:
The alternative manner of Kalman observer is
x ( k | k ) = x ( k | k - 1 ) + K ( k ) e r r ( k ) P ( k | k ) = ( I - K ( k ) C ) P ( k | k - 1 )
In formula, and x (k | k) it is kth TsThe posterior estimate of moment state variable;P (k | k) it is kth TsAfter moment error covariance Test estimated value;X (k | k-1) it is kth TsEstimated value is tested before the state variable in moment;P (k | k-1) it is respectively kth TsMoment error Estimated value is tested before covariance;I is unit matrix;K (k), err (k) are kth TsThe Kalman gain in moment and measured signal Residual error.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110858758A (en) * 2018-08-23 2020-03-03 深圳市优必选科技有限公司 Motor speed estimation method and device, and motor control method and system

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104950806B (en) * 2015-06-18 2017-07-28 南京航空航天大学 A kind of Machine Tool Feeding System feed forward control method based on GMDH data mining algorithms
CN105356823A (en) * 2015-10-30 2016-02-24 中国兵器工业集团第二O二研究所 Load torque observation and compensation method for servo system
CN105915144B (en) * 2016-05-16 2018-08-03 南京航空航天大学 A kind of permanent magnet synchronous motor rotary speed tracing control method
CN106533291A (en) * 2016-08-31 2017-03-22 东菱技术有限公司 Inertia identification and load torque observation-based speed loop response improvement method
CN109061537B (en) * 2018-08-23 2019-07-16 重庆大学 Electric vehicle lithium ion battery sensor fault diagnosis method based on observer
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101800505A (en) * 2010-03-12 2010-08-11 北京航空航天大学 Method for controlling rotary speed of magnetically suspended flywheel
CN102176653A (en) * 2011-01-19 2011-09-07 哈尔滨工业大学 Method for observing rotary speed of induction motor of Kalman filter with index fading factor
CN103684178A (en) * 2013-12-17 2014-03-26 清华大学 Rotating speed filtering device and filtering method of PMSM

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101800505A (en) * 2010-03-12 2010-08-11 北京航空航天大学 Method for controlling rotary speed of magnetically suspended flywheel
CN102176653A (en) * 2011-01-19 2011-09-07 哈尔滨工业大学 Method for observing rotary speed of induction motor of Kalman filter with index fading factor
CN103684178A (en) * 2013-12-17 2014-03-26 清华大学 Rotating speed filtering device and filtering method of PMSM

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
基于扰动观测器和卡尔曼滤波器的永磁直线同步电机扰动抑制;杨俊友等;《组合机床与自动化加工技术》;20130630(第6期);第2节,第3节 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110858758A (en) * 2018-08-23 2020-03-03 深圳市优必选科技有限公司 Motor speed estimation method and device, and motor control method and system

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