CN106026835A - No-velocity sensor optimization method based on fuzzy control and sliding-mode observer - Google Patents

Abstract

The invention discloses a no-velocity sensor optimization method based on fuzzy control and a sliding-mode observer. The position and rotor speed of a motor rotor are detected through the sliding-mode observer which is prone to engineering implementation, and a fuzzy controller is adopted to replace a traditional PI velocity regulator. In a permanent magnet synchronous motor vector control system, due to the fact that the traditional PI regulator is obvious in time delay and low in adaptive ability, robustness of fuzzy control is high, influences of interference and parameter changes on the control effect are greatly weakened, the no-velocity sensor optimization method is particularly suitable for control over nonlinear, time varying and pure lag systems, fuzzy control is designed based on heuristic knowledge and language decision rules, it is beneficial for simulation of manual control processes and methods, the adaptive capacity of the control system is enhanced, a certain intelligence level is achieved, and the method is quite suitable for objects of which mathematical models are difficult to obtain, dynamic features are not mastered easily or changes are quite remarkable.

Description

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer

Technical field

The present invention relates to Speedless sensor velocity measuring technique field, be specifically related to one and observe based on fuzzy control and sliding formwork The Speedless sensor optimization method of device.

Background technology

Permagnetic synchronous motor (Permanent Magnet Synchronous Motor is called for short PMSM) has power density High, energy conversion efficiency high, speed adjustable range is wide, volume is little, the advantage such as lightweight, obtain extensively in the field such as industrial, civilian, military General application.

The control of permagnetic synchronous motor needs to obtain position and the velocity information of rotor, and current Application comparison is universal Position sensor includes the device such as photoelectric encoder, rotary transformer, and the use of these devices not only adds the body of system Amass and cost, reduce the reliability of system, also limit permagnetic synchronous motor application in particular circumstances, for solving machinery Many defects that sensor brings, the research of sensorless strategy technology has become study hotspot both domestic and external, and has achieved one Determine achievement, but there is also many problems.The most important thing is that there is presently no a kind of single sensorless technology can be applicable to Efficiently control motor at various operating conditions.In prior art, or it is applicable to low cruise, or is applicable to high-speed cruising, Or affected relatively big by the parameter of electric machine, amount of calculation is very big, structure is complicated, or stability is not fine.

During motor speed detects, there is a lot of insoluble shortcoming in mechanical pick-up device.As: special at some Under working environment (high temperature, high pressure), its precision of information provided is unworthy trusting；Use mechanical pick-up device to make motor control simultaneously The increase of system cost, difficult in maintenance etc..Additionally, because conventional PI controller the most all can have a problem that integration is satisfied With.So-called integration is saturated, and when referring to the deviation that system exists a direction, the integral element of PI controller constantly adds up, finally Arriving the amplitude limit value of controller, even if continuing integral action, controller output is constant, so occurring in that integration is saturated.It is once There is Reversal value in system, controller reverse integral, and controller output is gradually exited from saturation region, time of exiting and between integration The saturated degree of depth is relevant.But, in moving back the saturated time, still in amplitude limit value, the most easily there is regulation in controller output Delayed, cause poor system performance.

Summary of the invention

In order to overcome the rotor angle of existing permagnetic synchronous motor based on Speedless sensor, method for estimating rotating speed to deposit The problem that principle is complicated, computationally intensive and integration is saturated, specifically now propose one and there is relatively high dynamic performance and easily In a kind of based on fuzzy control and sliding mode observer the Speedless sensor optimization method of Project Realization, pass through fuzzy controller Adjust the proportion integral modulus of pi regulator, so that pi regulator can all have good moving in the velocity interval that motor is the widest Steady-state behaviour.

In order to reach foregoing invention purpose, solve the technical scheme that its technical problem used as follows:

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer, comprises the following steps:

Step 1: select d axle reference currentIt is 0, AC permanent magnet synchronous motor detection output three-phase current I_a、I_bAnd I_c；

Step 2: three-phase current I_a、I_bAnd I_cConverting through Clark, export under biphase static rectangular coordinate system alpha-beta is biphase Stator current i_αAnd i_β；

Step 3: biphase stator current i_αAnd i_βConverting through Park, export under biphase synchronous rotating frame d-q is biphase Electric current I_dAnd I_q；

Step 4: the estimated value of rotor speed will be estimated in sliding mode observerIt is multiplied by a constant and obtains the rotor of estimation Rotating speed n, and rotor speed n of estimation and actual rotor speed n* are carried out poor, difference is regulated by fuzzy controller PI Rear output q axle reference current

Step 5: by q axle reference currentWith the electric current I obtained in step 3_qIt is poor to carry out, and difference is defeated after being regulated by PI Go out q axle reference voltage

Step 6: by d axle reference currentWith the electric current I obtained in step 3_dIt is poor to carry out, and difference is defeated after being regulated by PI Go out d axle reference voltage

Step 7: by the q axle reference voltage of output in step 5With the d axle reference voltage of output in step 6Pass through Park inverse transformation, exports two phase control voltages under biphase static rectangular coordinate system alpha-betaWith

Step 8: by the biphase stator current i of gained in step 2_αAnd i_βWith two phase control voltages of gained in step 7WithInput sliding mode observer carries out estimation process in the lump, estimates the estimated value of rotor speedEstimated value with rotor-position

Step 9: by two phase control voltages of gained in step 7WithCarrying out space vector modulation, output PWM waveform is extremely Inverter, inverter inputs three-phase voltage U to permagnetic synchronous motor_a、U_bAnd U_c, thus control permagnetic synchronous motor.

Further, in step 4, following steps are specifically included:

Step 41: carry out obtaining accurately as difference operation with actual rotor speed set-point n* by rotor speed n of estimation Value e, exact value e are converted into digital quantity analog quantity after A/D changes and send into fuzzy controller；

Step 42: the digital quantity obtained in step 41 is exported exact value u after fuzzy controller Fuzzy Processing；

Step 43: the exact value u in step 42 is converted to analog quantity digital quantity after D/A changes, and exports q axle Reference current

Further, in step 42, following steps are specifically included:

Step 421: the digital quantity in step 41 is processed through fuzzy quantization, obtains a fuzzy value e；

Step 422: fuzzy value e is combined fuzzy control rule R composition rule by inference and carries out fuzzy decision, obtain mould Stick with paste controlled quentity controlled variable u, fuzzy value u=e*R；

Step 423: fuzzy value u is carried out de-fuzzy process, obtains exact value u.

Further, in step 8, following steps are specifically included:

Step 81: by two phase control voltages in step 7WithElectric current estimation is obtained after SMO optimized algorithm calculates ValueWith

Step 82: by electric current estimated valueWithWith the biphase stator current i in step 2_αAnd i_βIt is poor to carry out, and obtains α β Current error value on axleWith

Step 83: by current error valueWithCounter electromotive force e is obtained after switch function computing_αAnd e_β；

Step 84: on the one hand, counter electromotive force e_αAnd e_βSend back in step 81, join in the calculating of SMO optimized algorithm；Separately On the one hand, counter electromotive force e_αAnd e_βThe counter electromotive force estimated value of sliding mode observer estimation is obtained by low pass filterWith

Step 85: the counter electromotive force estimated value of sliding mode observer estimationWithRotor speed is obtained by turn count Estimated value

Step 86: the counter electromotive force estimated value of sliding mode observer estimationWithRotor-position is obtained not by position estimation Estimated value before compensation

Step 87: by phase place is carried out lag compensation, draw phase compensation amount

Step 88: the estimated value before the rotor-position in step 86 is not compensatedWith the phase compensation amount in step 87Sue for peace, obtain the estimated value of rotor-position

As an embodiment, in step 81, specifically include following steps:

First, AC permanent magnet synchronous motor mathematical model in biphase static rectangular coordinate system alpha-beta is set up:

$\stackrel{\·}{i_{\mathrm{\α}}}=-\frac{R_S}{L_S}{i}_{\mathrm{\α}}-\frac{1}{L_S}{e}_{\mathrm{\α}}+\frac{u_{\mathrm{\α}}^{*}}{L_S}---\left(1\right)$

$\stackrel{\·}{i_{\mathrm{\β}}}=-\frac{R_S}{L_S}{i}_{\mathrm{\β}}-\frac{1}{L_S}{e}_{\mathrm{\β}}+\frac{u_{\mathrm{\β}}^{*}}{L_S}---\left(2\right)$

Wherein,For electric current i current value i on α axle_αDerivative,For electric current i current value i on β axle_βLead Number, R_SFor stator winding resistance, Ls is equivalent inductance, e_αFor sliding mode observer counter electromotive force on α axle, e_βObserve for sliding formwork Device counter electromotive force on β axle,For voltage U voltage estimated value on α axle,Estimate for voltage U voltage on β axle Value；

Secondly, counter electromotive force equation is substituted into:

e_α=-ψ_fω_rsinθ (3)

e_β=ψ_fω_rcosθ (4)

Wherein, ψ_fThe magnetic linkage produced for permanent magnet on rotor, ω_rFor synchronous rotational speed, θ is rotor angle location；

Furthermore, AC permanent magnet synchronous motor SMO in biphase static rectangular coordinate system alpha-beta optimizes accounting equation and is:

$\stackrel{\·}{\widehat{i_{\mathrm{\α}}}}=-\frac{R_S}{L_S}\widehat{i_{\mathrm{\α}}}+\frac{u_{\mathrm{\α}}^{*}}{L_S}-\frac{k}{L_S}sign(\widehat{i_{\mathrm{\α}}}-i_{\mathrm{\α}})---\left(5\right)$

$\stackrel{\·}{\widehat{i_{\mathrm{\β}}}}=-\frac{R_S}{L_S}\widehat{i_{\mathrm{\β}}}+\frac{u_{\mathrm{\β}}^{*}}{L_S}-\frac{k}{L_S}sign(\widehat{i_{\mathrm{\β}}}-i_{\mathrm{\β}})---\left(6\right)$

Wherein,It is respectively i_α、i_βEstimated value, k is sliding formwork handoff gain；

Finally, by the above-mentioned current estimation error equation that obtains:

$\stackrel{\·}{\widetilde{i_{\mathrm{\α}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\α}}}+\frac{e_{\mathrm{\α}}}{L_s}-\frac{k}{L_s}sign\left(\widetilde{i_{\mathrm{\α}}}\right)---\left(7\right)$

$\stackrel{\·}{\widetilde{i_{\mathrm{\β}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\β}}}+\frac{e_{\mathrm{\β}}}{L_s}-\frac{k}{L_s}sign\left(\widetilde{i_{\mathrm{\β}}}\right)---\left(8\right)$

Wherein,For the current error value on α axle,For the current error value on β axle.

As an embodiment, in step 82, current error valueWithAccounting equation be:

$\widetilde{i_{\mathrm{\α}}}={\hat{i}}_{\mathrm{\α}}-i_{\mathrm{\α}}---\left(9\right)$

$\widetilde{i_{\mathrm{\β}}}={\hat{i}}_{\mathrm{\β}}-i_{\mathrm{\β}}---\left(10\right)$

Wherein,And i_αFor the current error value on α axle, electric current estimated value and current value,And i_βFor β axle On current error value, electric current estimated value and current value.

As an embodiment, in a step 83, counter electromotive force e_αAnd e_βCalculating process comprise the following steps respectively:

First, choose sign switch function and carry out switch function computing, it may be assumed that

$sign=\left\{\begin{array}{cc}1& x>0\\ -1& x<0\end{array}\right.---\left(11\right)$

Secondly, liapunov function is chosen:

To V derivation, work as k > max (| e_α|,|e_β|) time, thenV ＞ 0, is known by Lyapunov theorem of stability, electric current Sliding mode observer is stable, and choosing current error is sliding formwork diverter surface, then, when entering sliding mode, haveWithTime,

$e_{\mathrm{\&alpha;}}=ksign\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(12\right)$

$e_{\mathrm{\&beta;}}=ksign\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(13\right)$

Wherein, e_αAnd e_βFor the counter electromotive force of sliding mode observer,For the current error value on α axle,For the electric current on β axle Error amount, k is sliding formwork handoff gain.

As an embodiment, in step 84, counter electromotive force estimated valueWithCalculating process include:

Using low pass filter, discontinuous switching signal is converted to the continuous signal of equivalence, corresponding computing formula is such as Under:

${\hat{e}}_{\mathrm{\&alpha;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&alpha;}}---\left(14\right)$

${\hat{e}}_{\mathrm{\&beta;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&beta;}}---\left(15\right)$

Wherein,WithFor the counter electromotive force estimated value of sliding mode observer estimation, ω_cFor the cut-off frequency of low pass filter, S is Laplace operator, e_αAnd e_βCounter electromotive force for sliding mode observer.

As an embodiment, in step 85, the estimated value of rotor speed is tried to achieve by below equation:

$\widehat{\mathrm{\&omega;}}=\frac{\sqrt{{\widehat{e_{\mathrm{\&alpha;}}}}^2+{\widehat{e_{\mathrm{\&beta;}}}}^2}}{{\mathrm{\&psi;}}_f}---\left(16\right)$

Wherein,For rotor speed estimated value,WithFor the counter electromotive force of sliding mode observer estimation, ψ_fFor on rotor forever The magnetic linkage that magnet produces.

As an embodiment, in step 86, the estimated value of rotor-position is tried to achieve by below equation:

$\widehat{{\mathrm{\&theta;}}_c}=-\arctan \left(\frac{\widehat{e_{\mathrm{\&alpha;}}}}{\widehat{e_{\mathrm{\&beta;}}}}\right)---\left(17\right)$

Wherein,For the estimated value of rotor-position,WithCounter electromotive force for sliding mode observer estimation.

As an embodiment, in step 87, due to the use of low pass filter, its phase place has certain hysteresis quality, Phase place must be carried out lag compensation, its phase compensation amount is:

$\mathrm{\&Delta;}\widehat{{\mathrm{\&theta;}}_c}=-\arctan \left(\frac{{\mathrm{\&omega;}}_c}{\mathrm{\&omega;}}\right)---\left(18\right)$

Wherein,It is the phase compensation amount of rotor-position, rotating speed when ω is stable state, ω_cCutoff frequency for low pass filter Rate.

Due to the fact that the above technical scheme of employing, be allowed to compared with prior art, have the following advantages that and actively imitate Really:

1, a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention to system disturbance, The uncertain factors such as Parameter Perturbation have robustness, therefore can preferably realize the control without sensor of permagnetic synchronous motor System；

2, the sliding mode observer designed by the present invention is in the case of rotating speed sudden change and load changing, can be the most accurate in time The true rotating speed following the tracks of motor and corner change, have precise control high, and dynamic property is good, the feature of strong robustness, and And designed sliding mode observer implements the most more convenient on hardware and software, there is certain practicality；

3, the present invention is by using sliding mode observer to realize state estimation, significantly improves the estimation of rotor-position and speed Degree of accuracy；

4, present invention application fuzzy controller adjusts the proportion integral modulus of pi regulator, makes PI self-adaptive regulator at electricity Good dynamic steady-state behaviour is had, so that observer can suppress the rotor of detection when low speed in the velocity interval that machine is the widest The but small oscillations of position angle, reduces the Phase delay of its angle during high speed, improve the accuracy of detection of rotor-position；

The impact controlling effect is significantly reduced by 5, the strong robustness of fuzzy control of the present invention, interference and Parameters variation, Being particularly suitable for the control of non-linear, time-varying and dead-time system, fuzzy control is based on suggestive knowledge and language decision-making Rule design, this is conducive to simulating manually operated process and method, strengthens the adaptation ability of control system, has certain Those mathematical modeies are difficult to obtain by level of intelligence, and the object that dynamic characteristic is difficult to grasp or change highly significant is the most applicable；

6, the present invention have that low cost, control algolithm be simple, rotating speed and the estimated speed of position and precision advantages of higher.

Accompanying drawing explanation

In order to be illustrated more clearly that the technical scheme of the embodiment of the present invention, required use in embodiment being described below Accompanying drawing be briefly described.It is clear that the accompanying drawing in describing below is only some embodiments of the present invention, for ability From the point of view of field technique personnel, on the premise of not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.Attached In figure:

Fig. 1 is that in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention, sliding formwork becomes The motor process figure of structural control system；

Fig. 2 is Fuzzy Control in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention Device structure chart processed；

Fig. 3 is that in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention, sliding formwork is seen Survey device structure chart；

Fig. 4 is the bulk flow of a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention Cheng Tu；

Fig. 5 is the step in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention The particular flow sheet of 4；

Fig. 6 is the step in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention The particular flow sheet of 42；

Fig. 7 is the step in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention The particular flow sheet of 8；

Fig. 8 is corresponding to a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention System emulation figure；

Fig. 9 is the person in servitude of e in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention Membership fuction figure；

Figure 10 is de in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention Membership function figure；

Figure 11 is du in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention Membership function figure；

Figure 12 is a kind of Speedless sensor optimization method medium velocity based on fuzzy control and sliding mode observer of the present invention Simulation waveform during sudden change；

Figure 13 is torque in a kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer of the present invention Simulation waveform during sudden change.

Detailed description of the invention

Below with reference to the accompanying drawing of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete description And discussion, it is clear that a part of example of the only present invention as described herein, is not whole examples, based on the present invention In embodiment, the every other enforcement that those of ordinary skill in the art are obtained on the premise of not making creative work Example, broadly falls into protection scope of the present invention.

See Fig. 1, the situation that consideration is general now in patent of the present invention, there is diverter surface s (x)=s (x₁, x₂,…,x_n)=0, it is by x=f (x) (x ∈ Rⁿ) state space of this system is divided into upper and lower two parts s>0 and s<0.Such as figure Shown in 1, diverter surface has the motor point of 3 kinds of situations.Point A is usual point, and when arriving near diverter surface s=0, motion is brought out into the open More some A and mistake；Point B is starting point, and when arriving near diverter surface s=0, a B is left from diverter surface both sides in motor point；Point C is Terminating point, when arriving near diverter surface s=0, motor point levels off to a C from diverter surface both sides.

In sliding moding structure, terminating point has special meaning, and what meaning starting point and usual point do not have substantially. When being all terminating point in a certain section of region on diverter surface, the motor point when, and will be at this once trend towards this region Move in region.Now, this region is called " sliding mode " district i.e. " sliding formwork " district, and the system motion in this region is called " sliding formwork Motion ".

With reference to Fig. 4, the invention discloses a kind of Speedless sensor optimization side based on fuzzy control and sliding mode observer Method, comprises the following steps:

Step 1: select d axle reference currentIt is 0, AC permanent magnet synchronous motor detection output three-phase current I_a、I_bAnd I_c；

Step 2: three-phase current I_a、I_bAnd I_cConverting through Clark, export under biphase static rectangular coordinate system alpha-beta is biphase Stator current i_αAnd i_β；

Step 3: biphase stator current i_αAnd i_βConverting through Park, export under biphase synchronous rotating frame d-q is biphase Electric current I_dAnd I_q；

Step 4: the estimated value of rotor speed will be estimated in sliding mode observerBe multiplied by a constant obtain estimation rotor turn Speed n, and rotor speed n of estimation and actual rotor speed n* are carried out poor, after difference passes through fuzzy controller PI regulation Output q axle reference current

Step 5: by q axle reference currentWith the electric current I obtained in step 3_qIt is poor to carry out, and difference is defeated after being regulated by PI Go out q axle reference voltage

Step 6: by d axle reference currentWith the electric current I obtained in step 3_dIt is poor to carry out, and difference is defeated after being regulated by PI Go out d axle reference voltage

Step 7: by the q axle reference voltage of output in step 5With the d axle reference voltage of output in step 6Pass through Park inverse transformation, exports two phase control voltages under biphase static rectangular coordinate system alpha-betaWith

Step 8: by the biphase stator current i of gained in step 2_αAnd i_βWith two phase control voltages of gained in step 7WithInput sliding mode observer carries out estimation process in the lump, estimates the estimated value of rotor speedEstimated value with rotor-position

Step 9: by two phase control voltages of gained in step 7WithCarrying out space vector modulation, output PWM waveform is extremely Inverter, inverter inputs three-phase voltage U to permagnetic synchronous motor_a、U_bAnd U_c, thus control permagnetic synchronous motor.

In step 2, by three-phase current I_a、I_bAnd I_cConvert through Clark, export under biphase static rectangular coordinate system alpha-beta Biphase stator current i_αAnd i_βThe reduction formula being specifically related to is as follows:

$\left[\begin{array}{c}{i}_{\mathrm{\&alpha;}}\\ i_{\mathrm{\&beta;}}\end{array}\right]=\frac{2}{3}\left[\begin{array}{ccc}1& -1/2& -1/2\\ 0& \sqrt{3}/2& -\sqrt{3}/2\end{array}\right]\left[\begin{array}{c}{i}_a\\ i_b\\ i_c\end{array}\right]$

In step 3, by biphase stator current i_αAnd i_βConvert through Park, export under biphase synchronous rotating frame d-q Biphase current I_dAnd I_qThe reduction formula being specifically related to is as follows:

$\left[\begin{array}{c}{I}_d\\ I_q\end{array}\right]=\left[\begin{array}{cc}\cos \widehat{\mathrm{\&theta;}}& \sin \widehat{\mathrm{\&theta;}}\\ -\sin \widehat{\mathrm{\&theta;}}& \cos \widehat{\mathrm{\&theta;}}\end{array}\right]\left[\begin{array}{c}{i}_{\mathrm{\&alpha;}}\\ i_{\mathrm{\&beta;}}\end{array}\right]$

Wherein,Rotor angle for estimation.

In step 4, the estimated value of rotor speed is estimatedAnd the relation between rotor speed n of estimation is:

$n=\frac{60\widehat{\mathrm{\&omega;}}}{2\mathrm{\&pi;}}=9.55\widehat{\mathrm{\&omega;}}$

That is, described constant is 9.55.

Fig. 2 is Fuzzy control system block diagram in the present invention, and set-point is actual given speed, with the speed of SMO feedback Differing from, obtained the difference i.e. exact value e of speed, exact value e is converted into digital quantity through A/D converter analog quantity, sends into Fuzzy controller, exports exact value u, exact value u after fuzzy controller processes and is converted to through D/A converter digital quantity Analog quantity.

Wherein the control law of fuzzy controller is realized by the program of computer, it is achieved the process of a step FUZZY ALGORITHMS FOR CONTROL It is: microcomputer sampling obtains the exact value of control target, then this amount is compared with set-point and obtains error signal e；General choosing Error signal e, as an input quantity of fuzzy controller, carries out fuzzy quantization the precise volume of e and becomes fuzzy quantity, error e Fuzzy quantity can represent with corresponding fuzzy language；Thus obtain subset e of the fuzzy language set of error e (actually One fuzzy vector)；Mould is carried out again by fuzzy vector e and fuzzy control rule R (fuzzy relation) composition rule by inference Sticking with paste decision-making, obtaining fuzzy control quantity u is u=e R.

In formula, u is a fuzzy quantity；In order to apply to be accurately controlled to controlled device (PMSM), in addition it is also necessary to by fuzzy quantity u Carry out de-fuzzy process and be converted to precise volume: after obtaining precise figures amount, become accurate analog quantity through digital-to-analogue conversion and give Actuator (includes pi regulator, Park inverse transformation and space vector modulation SVPWM), and controlled device carries out a step control； Then, carry out second time and sample, complete second step control, so circulation and go down, be achieved that the fuzzy control of controlled device.

In the present embodiment, in conjunction with Fig. 2 and Fig. 5, in step 4, following steps are specifically included:

Step 41: carry out obtaining accurately as difference operation with actual rotor speed set-point n* by rotor speed n of estimation Value e, exact value e are converted into digital quantity analog quantity after A/D changes and send into fuzzy controller；

Step 42: the digital quantity obtained in step 41 is exported exact value u after fuzzy controller Fuzzy Processing；

Step 43: the exact value u in step 42 is converted to analog quantity digital quantity after D/A changes, and exports q axle Reference current

Further, in conjunction with Fig. 2 and Fig. 6, in step 42, following steps are specifically included:

Step 421: the digital quantity in step 41 is processed through fuzzy quantization, obtains a fuzzy value e；

Step 422: fuzzy value e is combined fuzzy control rule R composition rule by inference and carries out fuzzy decision, obtain mould Stick with paste controlled quentity controlled variable u, fuzzy value u=e*R；

Step 423: fuzzy value u is carried out de-fuzzy process, obtains exact value u.

In step 7, by the q axle reference voltage of output in step 5With the d axle reference voltage of output in step 6Warp Cross Park inverse transformation, export two phase control voltages under biphase static rectangular coordinate system alpha-betaWithIt is specifically related to following conversion Formula:

$\left[\begin{array}{c}{u}_{\mathrm{\&alpha;}}^{*}\\ u_{\mathrm{\&beta;}}^{*}\end{array}\right]\left[\begin{array}{cc}\cos \widehat{\mathrm{\&theta;}}& -\sin \widehat{\mathrm{\&theta;}}\\ \sin \widehat{\mathrm{\&theta;}}& \cos \widehat{\mathrm{\&theta;}}\end{array}\right]\left[\begin{array}{c}{u}_d^{*}\\ u_q^{*}\end{array}\right]$

Wherein,Rotor angle for estimation.

Further, in conjunction with Fig. 3 and Fig. 7, in step 8, following steps are specifically included:

Step 81: by two phase control voltages in step 7WithElectric current estimation is obtained after SMO optimized algorithm calculates ValueWith

Step 82: by electric current estimated valueWithWith the biphase stator current i in step 2_αAnd i_βIt is poor to carry out, and obtains α β axle On current error valueWith

Step 83: by current error valueWithCounter electromotive force e is obtained after switch function computing_αAnd e_β；

Step 84: on the one hand, counter electromotive force e_αAnd e_βSend back in step 81, join in the calculating of SMO optimized algorithm；Separately On the one hand, counter electromotive force e_αAnd e_βThe counter electromotive force estimated value of sliding mode observer estimation is obtained by low pass filterWith

Step 85: the counter electromotive force estimated value of sliding mode observer estimationWithRotor speed is obtained by turn count Estimated value

Step 86: the counter electromotive force estimated value of sliding mode observer estimationWithRotor-position is obtained not by position estimation Estimated value before compensation

Step 87: by phase place is carried out lag compensation, draw phase compensation amount

Step 88: the estimated value before the rotor-position in step 86 is not compensatedWith the phase compensation amount in step 87Sue for peace, obtain the estimated value of rotor-position

As an embodiment, in step 81, specifically include following steps:

First, AC permanent magnet synchronous motor mathematical model in biphase static rectangular coordinate system alpha-beta is set up:

$\stackrel{\&CenterDot;}{i_{\mathrm{\&alpha;}}}=-\frac{R_S}{L_S}{i}_{\mathrm{\&alpha;}}-\frac{1}{L_S}{e}_{\mathrm{\&alpha;}}+\frac{u_{\mathrm{\&alpha;}}^{*}}{L_S}---\left(1\right)$

$\stackrel{\&CenterDot;}{i_{\mathrm{\&beta;}}}=-\frac{R_S}{L_S}{i}_{\mathrm{\&beta;}}-\frac{1}{L_S}{e}_{\mathrm{\&beta;}}+\frac{u_{\mathrm{\&beta;}}^{*}}{L_S}---\left(2\right)$

Wherein,For electric current i current value i on α axle_αDerivative,For electric current i current value i on β axle_βLead Number, R_SFor stator winding resistance, Ls is equivalent inductance, e_αFor sliding mode observer counter electromotive force on α axle, e_βObserve for sliding formwork Device counter electromotive force on β axle,For voltage U voltage estimated value on α axle,Estimate for voltage U voltage on β axle Value；

Secondly, counter electromotive force equation is substituted into:

e_α=-ψ_fω_rsinθ (3)

e_β=ψ_fω_rcosθ (4)

Wherein, ψ_fThe magnetic linkage produced for permanent magnet on rotor, ω_rFor synchronous rotational speed, θ is rotor angle location；

Furthermore, AC permanent magnet synchronous motor SMO in biphase static rectangular coordinate system alpha-beta optimizes accounting equation and is:

$\stackrel{\&CenterDot;}{\widehat{i_{\mathrm{\&alpha;}}}}=-\frac{R_S}{L_S}\widehat{i_{\mathrm{\&alpha;}}}+\frac{u_{\mathrm{\&alpha;}}^{*}}{L_S}-\frac{k}{L_S}sign(\widehat{i_{\mathrm{\&alpha;}}}-i_{\mathrm{\&alpha;}})---\left(5\right)$

$\stackrel{\&CenterDot;}{\widehat{i_{\mathrm{\&beta;}}}}=-\frac{R_S}{L_S}\widehat{i_{\mathrm{\&beta;}}}+\frac{u_{\mathrm{\&beta;}}^{*}}{L_S}-\frac{k}{L_S}sign(\widehat{i_{\mathrm{\&beta;}}}-i_{\mathrm{\&beta;}})---\left(6\right)$

Wherein,It is respectively i_α、i_βEstimated value, k is sliding formwork handoff gain；

Finally, by the above-mentioned current estimation error equation that obtains:

$\stackrel{\&CenterDot;}{\widetilde{i_{\mathrm{\&alpha;}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\&alpha;}}}+\frac{e_{\mathrm{\&alpha;}}}{L_s}-\frac{k}{L_s}sign\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(7\right)$

$\stackrel{\&CenterDot;}{\widetilde{i_{\mathrm{\&beta;}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\&beta;}}}+\frac{e_{\mathrm{\&beta;}}}{L_s}-\frac{k}{L_s}sign\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(8\right)$

Wherein,For the current error value on α axle,For the current error value on β axle.

As an embodiment, in step 82, current error valueWithAccounting equation be:

$\widetilde{i_{\mathrm{\&alpha;}}}={\hat{i}}_{\mathrm{\&alpha;}}-i_{\mathrm{\&alpha;}}---\left(9\right)$

$\widetilde{i_{\mathrm{\&beta;}}}={\hat{i}}_{\mathrm{\&beta;}}-i_{\mathrm{\&beta;}}---\left(10\right)$

Wherein,And i_αFor the current error value on α axle, electric current estimated value and current value,And i_βFor β axle On current error value, electric current estimated value and current value.

As an embodiment, in a step 83, counter electromotive force e_αAnd e_βCalculating process comprise the following steps respectively:

First, choose sign switch function and carry out switch function computing, it may be assumed that

$sign=\left\{\begin{array}{cc}1& x>0\\ -1& x<0\end{array}\right.---\left(11\right)$

Secondly, liapunov function is chosen:

To V derivation, work as k > max (| e_α|,|e_β|) time, thenV ＞ 0, is known by Lyapunov theorem of stability, electric current Sliding mode observer is stable, and choosing current error is sliding formwork diverter surface, then, when entering sliding mode, have WithTime,

$e_{\mathrm{\&alpha;}}=ksign\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(12\right)$

$e_{\mathrm{\&beta;}}=ksign\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(13\right)$

Wherein, e_αAnd e_βFor the counter electromotive force of sliding mode observer,For the current error value on α axle,For the electric current on β axle Error amount, k is sliding formwork handoff gain.

As an embodiment, in step 84, counter electromotive force estimated valueWithCalculating process include:

Using low pass filter, discontinuous switching signal is converted to the continuous signal of equivalence, corresponding computing formula is such as Under:

${\hat{e}}_{\mathrm{\&alpha;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&alpha;}}---\left(14\right)$

${\hat{e}}_{\mathrm{\&beta;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&beta;}}---\left(15\right)$

Wherein,WithFor the counter electromotive force estimated value of sliding mode observer estimation, ω_cFor the cut-off frequency of low pass filter, S is Laplace operator, e_αAnd e_βCounter electromotive force for sliding mode observer.

As an embodiment, in step 85, the estimated value of rotor speed is tried to achieve by below equation:

$\widehat{\mathrm{\&omega;}}=\frac{\sqrt{{\widehat{e_{\mathrm{\&alpha;}}}}^2+{\widehat{e_{\mathrm{\&beta;}}}}^2}}{{\mathrm{\&psi;}}_f}---\left(16\right)$

Wherein,For rotor speed estimated value,WithFor the counter electromotive force of sliding mode observer estimation, ψ_fFor on rotor forever The magnetic linkage that magnet produces.

As an embodiment, in step 86, the estimated value of rotor-position is tried to achieve by below equation:

$\widehat{{\mathrm{\&theta;}}_c}=-\arctan \left(\frac{\widehat{e_{\mathrm{\&alpha;}}}}{\widehat{e_{\mathrm{\&beta;}}}}\right)---\left(17\right)$

Wherein,For the estimated value of rotor-position,WithCounter electromotive force for sliding mode observer estimation.

As an embodiment, in step 87, due to the use of low pass filter, its phase place has certain hysteresis quality, Phase place must be carried out lag compensation, its phase compensation amount is:

$\mathrm{\&Delta;}\widehat{{\mathrm{\&theta;}}_c}=-\arctan \left(\frac{{\mathrm{\&omega;}}_c}{\mathrm{\&omega;}}\right)---\left(18\right)$

Wherein,It is the phase compensation amount of rotor-position, rotating speed when ω is stable state, ω_cCutoff frequency for low pass filter Rate.

The domain of all fuzzy sets of Fig. 9, Figure 10 and Figure 11 elects [-1,1] as.Balance control accuracy and calculating complexity Spending, fuzzy set daughter element elects 7 as, respectively NL, NM, NS, ZO, PS, PM, PL.Quantizing factor K_e、K_iSelection, in reality It is considered as the situation of change of performance requirement and e and de, chooses rational range of accommodation.Assume the domain scope of e and de respectively For [-m, m] and [-n, n], wherein meetThe selection triangle of membership function and trapezoidal membership function, Because selecting triangle and trapezoidal membership function controller to have preferable performance comparatively speaking.Reasoning is conciliate blur method and is selected MAMDANI fuzzy reasoning and center of gravity ambiguity solution method.

Fuzzy rule base is normally based on the control rule sets of expertise or procedural knowledge generation and closes.For permanent-magnet synchronous Motor speed regulation system, the fuzzy controller of design is for speed controlling, so controlling rule to be also based on speed responsive process.

If<0, now speed tends to set-point, it should give less controller output for e>0, de；

If e < 0, de < 0, speed overshoot now occurs, it should as early as possible by controller Reducing overshoot；

If e<0, de>0, now suppression plays a role, and speed returns set-point, and controller output should be less；

If e > 0, de > 0, now speed Tracking is not upper given, and controller should give bigger output.

Fig. 8, Figure 12 and Figure 13 are system emulation schematic diagram and the simulation experiment result.Substitute with Fuzzy PI Speed actuator Traditional PI speed regulator, and set up the sliding formwork gain of Fuzzy PI Speed actuator sliding mode observer and the pass of estimation counter electromotive force System accelerates system response time, derived calculating corner and the formula of rotating speed, constructs phantom.Simulation result shows, Designed PI type Fuzzy sliding mode observer, in the case of rotating speed sudden change and load changing, can be followed the tracks of electronic fast and accurately The rotating speed of machine and corner change, and when torque suddenlys change, Fuzzy PI Speed actuator is relative to traditional PI actuator torque pulsation Little, there is precise control high, dynamic property is good, the feature of strong robustness, and designed PI type Fuzzy sliding mode observer without It is all very convenient that opinion implements on hardware system and software system, has certain practical value.

The above, the only present invention preferably detailed description of the invention, but protection scope of the present invention is not limited thereto, Any those familiar with the art in the technical scope that the invention discloses, the change that can readily occur in or replacement, All should contain within protection scope of the present invention.Therefore, protection scope of the present invention should be with scope of the claims It is as the criterion.

Claims (11)

1. a Speedless sensor optimization method based on fuzzy control and sliding mode observer, it is characterised in that include following Step:

Step 1: select d axle reference currentIt is 0, AC permanent magnet synchronous motor detection output three-phase current I_a、I_bAnd I_c；

Step 2: three-phase current I_a、I_bAnd I_cConvert through Clark, export the biphase stator under biphase static rectangular coordinate system alpha-beta Electric current i_αAnd i_β；

Step 3: biphase stator current i_αAnd i_βConvert through Park, export the biphase current under biphase synchronous rotating frame d-q I_dAnd I_q；

Step 4: the estimated value of rotor speed will be estimated in sliding mode observerIt is multiplied by a constant and obtains rotor speed n of estimation, And rotor speed n of estimation and actual rotor speed n* being carried out poor, difference is by output q after fuzzy controller PI regulation Axle reference current

Step 5: by q axle reference currentWith the electric current I obtained in step 3_qIt is poor to carry out, and difference exports q axle after being regulated by PI Reference voltage

Step 6: by d axle reference currentWith the electric current I obtained in step 3_dIt is poor to carry out, and difference exports d axle after being regulated by PI Reference voltage

Step 7: by the q axle reference voltage of output in step 5With the d axle reference voltage of output in step 6Through Park contravariant Change, export two phase control voltages under biphase static rectangular coordinate system alpha-betaWith

Step 8: by the biphase stator current i of gained in step 2_αAnd i_βWith two phase control voltages of gained in step 7WithOne And input sliding mode observer and carry out estimation process, estimate the estimated value of rotor speedEstimated value with rotor-position

Step 9: by two phase control voltages of gained in step 7WithCarrying out space vector modulation, output PWM waveform is to inversion Device, inverter inputs three-phase voltage U to permagnetic synchronous motor_a、U_bAnd U_c, thus control permagnetic synchronous motor.

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer the most according to claim 1, It is characterized in that, in step 4, specifically include following steps:

Step 41: carry out obtaining exact value e as difference operation with actual rotor speed set-point n* by rotor speed n of estimation, Exact value e is converted into digital quantity analog quantity after A/D changes and sends into fuzzy controller；

Step 42: the digital quantity obtained in step 41 is exported exact value u after fuzzy controller Fuzzy Processing；

Step 43: the exact value u in step 42 is converted to analog quantity digital quantity after D/A changes, and exports q axle reference Electric current

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer the most according to claim 2, It is characterized in that, in step 42, specifically include following steps:

Step 421: the digital quantity in step 41 is processed through fuzzy quantization, obtains a fuzzy value e；

Step 422: fuzzy value e is combined fuzzy control rule R composition rule by inference and carries out fuzzy decision, obtain Fuzzy Control Amount u processed, fuzzy value u=e*R；

Step 423: fuzzy value u is carried out de-fuzzy process, obtains exact value u.

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer the most according to claim 1, It is characterized in that, in step 8, specifically include following steps:

Step 81: by two phase control voltages in step 7WithElectric current estimated value is obtained after SMO optimized algorithm calculates With

Step 82: by electric current estimated valueWithWith the biphase stator current i in step 2_αAnd i_βIt is poor to carry out, and obtains on α β axle Current error valueWith

Step 83: by current error valueWithCounter electromotive force e is obtained after switch function computing_αAnd e_β；

Step 84: on the one hand, counter electromotive force e_αAnd e_βSend back in step 81, join in the calculating of SMO optimized algorithm；The opposing party Face, counter electromotive force e_αAnd e_βThe counter electromotive force estimated value of sliding mode observer estimation is obtained by low pass filterWith

Step 85: the counter electromotive force estimated value of sliding mode observer estimationWithThe estimation of rotor speed is obtained by turn count Value

Step 86: the counter electromotive force estimated value of sliding mode observer estimationWithObtain rotor-position by position estimation not compensate Front estimated value

Step 87: by phase place is carried out lag compensation, draw phase compensation amount

Step 88: the estimated value before the rotor-position in step 86 is not compensatedWith the phase compensation amount in step 87Enter Row summation, obtains the estimated value of rotor-position

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer the most according to claim 4, It is characterized in that, in step 81, specifically include following steps:

First, AC permanent magnet synchronous motor mathematical model in biphase static rectangular coordinate system alpha-beta is set up:

$\stackrel{\&CenterDot;}{i_{\mathrm{\&alpha;}}}=-\frac{R_S}{L_S}{i}_{\mathrm{\&alpha;}}-\frac{1}{L_S}{e}_{\mathrm{\&alpha;}}+\frac{u_{\mathrm{\&alpha;}}^{*}}{L_S}---\left(1\right)$

$\stackrel{\&CenterDot;}{i_{\mathrm{\&beta;}}}=-\frac{R_S}{L_S}{i}_{\mathrm{\&beta;}}-\frac{1}{L_S}{e}_{\mathrm{\&beta;}}+\frac{u_{\mathrm{\&beta;}}^{*}}{L_S}---\left(2\right)$

Wherein,For electric current i current value i on α axle_αDerivative,For electric current i current value i on β axle_βDerivative, R_S For stator winding resistance, Ls is equivalent inductance, e_αFor sliding mode observer counter electromotive force on α axle, e_βFor sliding mode observer at β Counter electromotive force on axle,For voltage U voltage estimated value on α axle,For voltage U voltage estimated value on β axle；

Secondly, counter electromotive force equation is substituted into:

e_α=-ψ_fω_rsinθ (3)

e_β=ψ_fω_rcosθ (4)

Wherein, ψ_fThe magnetic linkage produced for permanent magnet on rotor, ω_rFor synchronous rotational speed, θ is rotor angle location；

Furthermore, AC permanent magnet synchronous motor SMO in biphase static rectangular coordinate system alpha-beta optimizes accounting equation and is:

$\stackrel{\&CenterDot;}{\widehat{i_{\mathrm{\&alpha;}}}}=-\frac{R_S}{L_S}\widehat{i_{\mathrm{\&alpha;}}}+\frac{u_{\mathrm{\&alpha;}}^{*}}{L_S}-\frac{k}{L_S}sign(\widehat{i_{\mathrm{\&alpha;}}}-i_{\mathrm{\&alpha;}})---\left(5\right)$

$\stackrel{\&CenterDot;}{\widehat{i_{\mathrm{\&beta;}}}}=-\frac{R_S}{L_S}\widehat{i_{\mathrm{\&beta;}}}+\frac{u_{\mathrm{\&beta;}}^{*}}{L_S}-\frac{k}{L_S}sign(\widehat{i_{\mathrm{\&beta;}}}-i_{\mathrm{\&beta;}})---\left(6\right)$

Wherein,It is respectively i_α、i_βEstimated value, k is sliding formwork handoff gain；

Finally, by the above-mentioned current estimation error equation that obtains:

$\stackrel{\&CenterDot;}{\widetilde{i_{\mathrm{\&alpha;}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\&alpha;}}}+\frac{e_{\mathrm{\&alpha;}}}{L_s}-\frac{k}{L_s}sign\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(7\right)$

$\stackrel{\&CenterDot;}{\widetilde{i_{\mathrm{\&beta;}}}}=-\frac{R_s}{L_s}\widetilde{i_{\mathrm{\&beta;}}}+\frac{e_{\mathrm{\&beta;}}}{L_s}-\frac{k}{L_s}sign\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(8\right)$

Wherein,For the current error value on α axle,For the current error value on β axle.

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer the most according to claim 4, It is characterized in that, in step 82, current error valueWithAccounting equation be:

$\widetilde{i_{\mathrm{\&alpha;}}}={\hat{i}}_{\mathrm{\&alpha;}}-i_{\mathrm{\&alpha;}}---\left(9\right)$

$\widetilde{i_{\mathrm{\&beta;}}}={\hat{i}}_{\mathrm{\&beta;}}-i_{\mathrm{\&beta;}}---\left(10\right)$

Wherein,And i_αFor the current error value on α axle, electric current estimated value and current value,And i_βFor the electricity on β axle Stream error value, electric current estimated value and current value.

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer the most according to claim 4, It is characterized in that, in a step 83, counter electromotive force e_αAnd e_βCalculating process comprise the following steps respectively:

First, choose sign switch function and carry out switch function computing, it may be assumed that

$sign=\left\{\begin{array}{cc}1& x>0\\ -1& x<0\end{array}\right.---\left(11\right)$

Secondly, liapunov function is chosen:

To V derivation, work as k > max (| e_α|,|e_β|) time, thenV ＞ 0, is known by Lyapunov theorem of stability, electric current sliding formwork Observer is stable, and choosing current error is sliding formwork diverter surface, then, when entering sliding mode, haveWithTime,

$e_{\mathrm{\&alpha;}}=ksign\left(\widetilde{i_{\mathrm{\&alpha;}}}\right)---\left(12\right)$

$e_{\mathrm{\&beta;}}=ksign\left(\widetilde{i_{\mathrm{\&beta;}}}\right)---\left(13\right)$

Wherein, e_αAnd e_βFor the counter electromotive force of sliding mode observer,For the current error value on α axle,For the current error on β axle Value, k is sliding formwork handoff gain.

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer the most according to claim 4, It is characterized in that, in step 84, counter electromotive force estimated valueWithCalculating process include:

Using low pass filter, discontinuous switching signal is converted to the continuous signal of equivalence, corresponding computing formula is as follows:

${\hat{e}}_{\mathrm{\&alpha;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&alpha;}}---\left(14\right)$

${\hat{e}}_{\mathrm{\&beta;}}=\frac{{\mathrm{\&omega;}}_c}{s+{\mathrm{\&omega;}}_c}{e}_{\mathrm{\&beta;}}---\left(15\right)$

Wherein,WithFor the counter electromotive force estimated value of sliding mode observer estimation, ω_cFor the cut-off frequency of low pass filter, s is Laplace operator, e_αAnd e_βCounter electromotive force for sliding mode observer.

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer the most according to claim 4, It is characterized in that, in step 85, the estimated value of rotor speed is tried to achieve by below equation:

$\widehat{\mathrm{\&omega;}}=\frac{\sqrt{{\widehat{e_{\mathrm{\&alpha;}}}}^2+{\widehat{e_{\mathrm{\&beta;}}}}^2}}{{\mathrm{\&psi;}}_f}---\left(16\right)$

Wherein,For rotor speed estimated value,WithFor the counter electromotive force of sliding mode observer estimation, ψ_fFor permanent magnet on rotor The magnetic linkage produced.

A kind of Speedless sensor optimization method based on fuzzy control and sliding mode observer the most according to claim 4, It is characterized in that, in step 86, the estimated value of rotor-position is tried to achieve by below equation:

$\widehat{{\mathrm{\&theta;}}_c}=-\arctan \left(\frac{\widehat{e_{\mathrm{\&alpha;}}}}{\widehat{e_{\mathrm{\&beta;}}}}\right)---\left(17\right)$

Wherein,For the estimated value of rotor-position,WithCounter electromotive force for sliding mode observer estimation.

11. a kind of Speedless sensor optimization methods based on fuzzy control and sliding mode observer according to claim 4, It is characterized in that, in step 87, due to the use of low pass filter, its phase place has certain hysteresis quality, must enter phase place Row lag compensation, its phase compensation amount is:

$\mathrm{\&Delta;}\widehat{{\mathrm{\&theta;}}_c}=-\arctan \left(\frac{{\mathrm{\&omega;}}_c}{\mathrm{\&omega;}}\right)---\left(18\right)$

Wherein,It is the phase compensation amount of rotor-position, rotating speed when ω is stable state, ω_cCut-off frequency for low pass filter.