CN203057059U - Permanent magnet synchronous motor combination control system based on fuzzy sliding mode and neural network - Google Patents
Permanent magnet synchronous motor combination control system based on fuzzy sliding mode and neural network Download PDFInfo
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- CN203057059U CN203057059U CN2012204340371U CN201220434037U CN203057059U CN 203057059 U CN203057059 U CN 203057059U CN 2012204340371 U CN2012204340371 U CN 2012204340371U CN 201220434037 U CN201220434037 U CN 201220434037U CN 203057059 U CN203057059 U CN 203057059U
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Abstract
The utility model discloses a permanent magnet synchronous motor combination control system based on a fuzzy sliding mode and a neural network, comprising a rotating speed control outer ring and a current control inner ring; a control unit in the rotating speed control outer ring employs a composite control module; the composite control module comprises a fuzzy sliding mode control module and a neural network control module which are combined through two weighting factors lambda n and lambda f. The permanent magnet synchronous motor combination control system combines the advantages of fuzzy sliding mode control and neural network control, realizes the advantages of strong robustness and high stability of a permanent magnet synchronous motor control system, raises stability precision and reaches the purposes of control rapidity and strong capability of load disturbance resistance.
Description
Technical field
The utility model relates to a kind of alternating current machine drive technology field, is specifically related to a kind of multiplex control system based on permanent magnet synchronous motor vector control system.
Background technology
Since first automobile was born in the world in 1886, automobile was with its application more and more widely that has obtained in aspect of social life in the combination property advantage of aspects such as delivery power, convenience, comfortableness and cost performance.When but automobile brings convenient, the comfortable modern life of people, also be unable to escape the responsibility of destroying biological environment and the resource that consumes petroleum in a large number.The clean energy resource automobile of Development of New Generation becomes inexorable trend.Take all factors into consideration factors such as energy-saving and emission-reduction potentiality, technology maturity and product price, electric automobile becomes one of best solution of new-energy automobile.The electric vehicle engineering development of China is more or less the same with countries in the world, and under the background of financial crisis in 2009, China is developed the good opportunity of electric automobile cause especially, and electric automobile will become a kind of trend of development of automobile and inevitable.
Power-driven system is the heart of pure electric automobile, and the quality of its control effect directly affects the quality of electric automobile whole performance.Electric automobile is different from the general industry field to the requirement of drive motors, mainly comprises following several respects: (1) high power density; (2) good speed adjusting performance can be realized accurate torque control; (3) high efficiency is to improve continual mileage; (4) adapt to bad working environment (high low temperature, vibration); (5) the special package design of small size and adaptation interior space; (6) high reliability and cost performance.Volume is little, in light weight, moment of inertia is light, power density is high, efficient is high and export advantages such as torque is big and permagnetic synchronous motor has, become a motor the most competitive in the used for electric vehicle drive motors, generally use on mixed power electric car in Japan and Europe.Simultaneously, China contains abundant rare earth resources, and along with continuing to bring out of novel permanent magnetic material, the cost of permanent magnetic material is expected to reduce, thereby magneto is occupying absolute advantage in price especially than other class motors.
Permagnetic synchronous motor have close coupling, the time become, characteristics such as non-linear, in order to realize high performance governing system, make system possess good dynamic and static performance, and variation and external disturbance to parameter have insensitivity, crucial effects is being brought into play in the correct selection of control strategy, good control strategy not only can remedy the deficiency on the hardware designs, and can further improve the combination property of system.1971, the engineer F.Blaschke of Siemens proposed vector control theory, made the theoretical acquisition of AC Motor Control qualitative leap.At the control object of this close coupling of alternating current machine, adopt the modern control theory of parameter reconstruct to come decoupling zero, carry out the vector conversion, copy the DC speed regulation principle, make the dynamic and static performance of Alternating Current Governor System reach the level of DC speed regulation.Generally adopt the control strategy of breakdown torque current ratio further permagnetic synchronous motor to be carried out the linearisation decoupling zero for internal permanent magnet synchronous motor.At present, permanent magnet synchronous motor vector control system generally adopts speed and current double closed-loop control method, and the control major part of speed is utilized traditional PID controller, though the traditional PID control principle is simple, robustness, good stability, but rapidity and anti-jamming capacity are very limited.
Summary of the invention
The utility model purpose is at the deficiencies in the prior art, a kind of permagnetic synchronous motor multiplex control system based on fuzzy sliding formwork and neural net is provided, the utility model has both the advantage of fuzzy sliding mode tracking control and ANN Control, realize strong robustness, the high stability of control system for permanent-magnet synchronous motor, and the raising stable state accuracy reaches the rapidity of control and strong anti-load disturbance ability
In order to solve these problems of the prior art, the technical scheme that the utility model provides is:
A kind of permagnetic synchronous motor multiplex control system based on fuzzy sliding formwork and neural net, comprise ring in rotating speed control outer shroud and the Current Control, control unit in the rotating speed control outer shroud adopts compound control module, described compound control module comprises fuzzy sliding mode tracking control module and ANN Control module, and fuzzy sliding mode tracking control module and ANN Control module are by two weighted factor λ
n, λ
fCombine.
The extension of the ANN Control module traditional PID control in the compound control module of the present utility model, on-line study by neural net, realization is to the optimization of control system, the fuzzy sliding mode tracking control module then is to adopt the integral variable structure control strategy in flower edging structure, in the design of sliding formwork line, introduce the State integral item, save and realize the required acceleration signal of sliding formwork speed control, directly the choice function switching controls is determined with respect to the ratio switching control parameter is easier.
For technique scheme, the applicant also has further implementing measure in detail.
As optimization, described rotating speed control outer shroud comprises the error comparison module, compound control module, first comparison module, the one PI adjustment module, three-phase inverter and rotating speed position detecting module, ring comprises second comparison module in the described Current Control, the 2nd PI adjustment module, the Park inverse transform module, the voltage vector pulse width modulation module, Clark conversion module and Park conversion module, three tunnel outputs of described three-phase inverter insert permagnetic synchronous motor, described permagnetic synchronous motor links to each other with the rotating speed position detecting module, described rotating speed position detecting module links to each other with the error comparison module, described error comparison module links to each other with compound control module, described compound adjustment module links to each other with first comparison module, described first comparison module connects a PI adjustment module, the output of described three-phase inverter links to each other with the Clark conversion module, be connected to first comparison module and second comparison module behind the output process Park conversion module of described Clark conversion module, described second comparison module connects the 2nd PI adjustment module, a described PI adjustment module and the 2nd PI adjustment module insert the Park inverse transform module, described Park inverse transform module links to each other with the voltage vector pulse width modulation module, and the output of described voltage vector pulse width modulation module links to each other with three-phase inverter.
Described Clark conversion module links to each other with the two-phase output of three-phase inverter.Described Park conversion module links to each other with described Park inverse transform module, and described rotating speed position detecting module links to each other respectively with described Park conversion module, Park inverse transform module.
Further, described outer shroud is speed ring, the fuzzy sliding formwork of speed ring sampling and the compound control optimization system of neural net performance.
Further, described interior circular current ring adopts the Current Control Strategy of breakdown torque current ratio below base speed, provides systematic function by weak magnetic control system more than base is fast.
Further, the main control chip of described control system for permanent-magnet synchronous motor employing is the TMS320F28335 digital processing chip.
As optimization, the output control signal of fuzzy sliding mode tracking control module is
, the output control signal of ANN Control module is
, through weighted factor λ
n, λ
fThe output control signal of the compound control module that fuzzy sliding mode tracking control module and ANN Control module is compound is C=λ
n 
+ λ
f 
, λ wherein
n+ λ
f=1.
Further, weighted factor λ
n, λ
fSpan be respectively 0≤λ
n≤ 1,0≤λ
f≤ 1.
Than solution of the prior art, the utility model advantage is:
1. the utility model utilizes vector conversion (comprising Clark conversion, Park conversion and Park inverse transformation) that the three-phase current of permagnetic synchronous motor is transformed into the d(d-axis), q(hands over axle) equivalent current on the axle, pass through the method for Current Control Strategy of breakdown torque current ratio again to the d of permagnetic synchronous motor, the further linearisation decoupling zero of Mathematical Modeling on the q axle; The control unit of speed ring then adopts the compound control module of fuzzy sliding mode tracking control and ANN Control, by the weighted factor λ of control in conjunction with the two
n, λ
fValue realize the compound control that fuzzy sliding mode tracking control and ANN Control are compound, work as weighted factor λ in addition
n, λ
fGet marginal value in other words limiting value be λ
n=1 or λ
fCan realize the control of undertaking of fuzzy sliding mode tracking control or ANN Control at=1 o'clock;
2. the utility model improves existing Sliding mode variable structure control and traditional PID control.In order to make control system realize the rapidity of response and good anti-interference effect, Sliding mode variable structure control can make system slide into the plane initial point fast by pre-set track, strong robustness, but sliding moding structure produces dither easily near the slip plane initial point, this is that actual control system institute is unallowed, adopting fuzzy sliding mode tracking control is that the compound control of fuzzy control and sliding moding structure then can overcome this problem, when guaranteeing strong robustness, be reduced near the dither the slip plane initial point, reach mutual supplement with each other's advantages.ANN Control then can be tackled control system better, the uncertainty of system parameters and the disturbance of variation and extraneous factor had adaptivity, make whole system less demanding to the accuracy of control system for permanent-magnet synchronous motor Mathematical Modeling, in order in to permagnetic synchronous motor Equivalent DC control procedure, obtain better static and dynamic performance.
Description of drawings
Below in conjunction with drawings and Examples the utility model is further described:
Fig. 1 is the overall structure block diagram of the control system of the utility model embodiment;
Fig. 2 is that the utility model is through the linear schematic diagram of the composite signals of weighting processing;
Fig. 3 is the structure principle chart of the ANN Control of the utility model embodiment;
Fig. 4 is the fuzzy control rule schematic diagram of the utility model fuzzy sliding mode tracking control.
Embodiment
Below in conjunction with specific embodiment such scheme is described further.Should be understood that these embodiment are not limited to limit the scope of the invention for explanation the present invention.The implementation condition that adopts among the embodiment can be done further adjustment according to the condition of concrete producer, and not marked implementation condition is generally the condition in the normal experiment.
Embodiment:
Present embodiment has been described a kind of permagnetic synchronous motor multiplex control system based on fuzzy sliding formwork and neural net, its overall structure as shown in Figure 1, it comprises ring in rotating speed control outer shroud and the Current Control, described rotating speed control outer shroud comprises error comparison module 1, compound control module 2, first comparison module 3, the one PI adjustment module 4, three-phase inverter 5 and rotating speed position detecting module 6, ring comprises second comparison module 7 in the described Current Control, the 2nd PI adjustment module 8, Park inverse transform module 9, voltage vector pulse width modulation module 10, Clark conversion module 11 and Park conversion module 12, three tunnel outputs of described three-phase inverter 5 insert permagnetic synchronous motor 13, described permagnetic synchronous motor 13 links to each other with rotating speed position detecting module 6, described rotating speed position detecting module 6 links to each other with error comparison module 1, described error comparison module 1 links to each other with compound control module 2, described compound adjustment module 2 links to each other with first comparison module 3, described first comparison module 3 connects a PI adjustment module 4, the output of described three-phase inverter 5 links to each other with Clark conversion module 11, be connected to first comparison module 3 and second comparison module 7 behind the output process Park conversion module 12 of described Clark conversion module 11, described second comparison module 7 connects the 2nd PI adjustment module 8, a described PI adjustment module 4 and the 2nd PI adjustment module 8 insert Park inverse transform module 9, described Park inverse transform module 9 links to each other with voltage vector pulse width modulation module 10, and the output of described voltage vector pulse width modulation module 10 links to each other with three-phase inverter 5.
The compound control module 2 that control unit in the rotating speed control outer shroud adopts comprises fuzzy sliding mode tracking control module 21 and ANN Control module 22, and fuzzy sliding mode tracking control module 21 is passed through two weighted factor λ with ANN Control module 22
n, λ
fCombine.The output control signal of fuzzy sliding mode tracking control module 21 is
, the output control signal of ANN Control module 22 is
, through weighted factor λ
n, λ
fThe output control signal of the compound control module that fuzzy sliding mode tracking control module and ANN Control module is compound is C=λ
n + λ
f 
, λ wherein
n+ λ
f=1, weighted factor λ
n, λ
fSpan be 0≤λ
n≤ 1,0≤λ
f≤ 1, its principle schematic as shown in Figure 2.
Present embodiment is by coordinate transform, make each physical quantity be transformed into synchronous rotating frame (d from rest frame (threephase stator coordinate system), the q coordinate system), thereby make Control of PMSM reach the control of DC effect, adopt the method for breakdown torque current ratio to internal permanent magnet synchronous motor d simultaneously, electric current on the q axle is given to be calculated, effective vector that on off state by suitable combination fundamental space vector on space voltage vector pulse width control (SVPWM) technical spirit of quoting produces approaches basic circle, namely comes the approximate simulation circle with changeable shape.Fuzzy sliding formwork and neural net composite control method are incorporated into speed ring in permagnetic synchronous motor electric current, the speed double closed-loop control.
As shown in Figure 2, can realize separately that at the special time period of multiplex control system fuzzy sliding formwork and neural net are to the control of speed ring, control system performance requirement according to reality, when error signal is big (such as electric automobile start and during gear shift operation), get higher value, allow composite controller and mainly or fully be in fuzzy sliding mode tracking control, force system according to the state trajectory motion of predetermined " sliding mode ", the controller response speed of this moment is fast, variation and external disturbance to parameter are insensitive, strong robustness, in the fuzzy sliding mode tracking control module of present embodiment, for saving the required acceleration signal of sliding formwork speed control, in switching function, introduce the State integral item, become structure and adopt the function switching controls.Fig. 4 is fuzzy control rule of the present utility model, and the sliding moding structure error is carried out Fuzzy Processing, can effectively remove buffeting.
When error signal hour (such as the electric automobile even running time), get bigger value, allow composite controller mainly or be in ANN Control fully, reduce overshoot and the vibration of system, make controller have better controlling performance.Fig. 3 is the utility model neural network structure, by selecting 3 layers of neural net for use, through on-line study, is conducive to the effect of further oscillation-damped.
The data reduction of present embodiment and processing are all based on the TMS320F28335 digital processing chip, this chip has powerful control and signal handling capacity, can realize complicated control algolithm, special-purpose Electric Machine Control interface is arranged, thereby be the huge help that implements of the present invention.
The extension of the ANN Control module traditional PID control in the compound control module of the present utility model, on-line study by neural net, realization is to the optimization of control system, the fuzzy sliding mode tracking control module then is to adopt the integral variable structure control strategy in flower edging structure, in the design of sliding formwork line, introduce the State integral item, save and realize the required acceleration signal of sliding formwork speed control, directly the choice function switching controls is determined with respect to the ratio switching control parameter is easier.
Above-mentioned example only is explanation technical conceive of the present invention and characteristics, and its purpose is to allow the people who is familiar with this technology can understand content of the present invention and enforcement according to this, can not limit protection scope of the present invention with this.All spirit essence is done according to the present invention equivalent transformation or modification all should be encompassed within protection scope of the present invention.
Claims (7)
1. permagnetic synchronous motor multiplex control system based on fuzzy sliding formwork and neural net, comprise ring in rotating speed control outer shroud and the Current Control, it is characterized in that: the control unit in the rotating speed control outer shroud adopts compound control module, described compound control module comprises fuzzy sliding mode tracking control module and ANN Control module, and fuzzy sliding mode tracking control module and ANN Control module are by two weighted factor λ
n, λ
fCombine.
2. according to claim 1 a kind of based on the permagnetic synchronous motor multiplex control system of bluring sliding formwork and neural net, it is characterized in that: described rotating speed control outer shroud comprises the error comparison module, compound control module, first comparison module, the one PI adjustment module, three-phase inverter and rotating speed position detecting module, ring comprises second comparison module in the described Current Control, the 2nd PI adjustment module, the Park inverse transform module, the voltage vector pulse width modulation module, Clark conversion module and Park conversion module, three tunnel outputs of described three-phase inverter insert permagnetic synchronous motor, described permagnetic synchronous motor links to each other with the rotating speed position detecting module, described rotating speed position detecting module links to each other with the error comparison module, described error comparison module links to each other with compound control module, described compound adjustment module links to each other with first comparison module, described first comparison module connects a PI adjustment module, the output of described three-phase inverter links to each other with the Clark conversion module, be connected to first comparison module and second comparison module behind the output process Park conversion module of described Clark conversion module, described second comparison module connects the 2nd PI adjustment module, a described PI adjustment module and the 2nd PI adjustment module insert the Park inverse transform module, described Park inverse transform module links to each other with the voltage vector pulse width modulation module, and the output of described voltage vector pulse width modulation module links to each other with three-phase inverter.
3. a kind of permagnetic synchronous motor multiplex control system based on fuzzy sliding formwork and neural net according to claim 2, it is characterized in that: described outer shroud is speed ring, the fuzzy sliding formwork of speed ring sampling and the compound control optimization system of neural net performance.
4. according to claim 2 a kind of based on the permagnetic synchronous motor multiplex control system of bluring sliding formwork and neural net, it is characterized in that: the circular current ring adopts the Current Control Strategy of breakdown torque current ratio in described below base speed, provides systematic function by weak magnetic control system more than the base speed.
5. according to claim 1 or 2 or 3 or 4 described a kind of permagnetic synchronous motor multiplex control systems based on fuzzy sliding formwork and neural net, it is characterized in that: the main control chip that described control system for permanent-magnet synchronous motor adopts is the TMS320F28335 digital processing chip.
6. according to claim 1 a kind of based on the permagnetic synchronous motor multiplex control system of bluring sliding formwork and neural net, it is characterized in that: the output control signal of fuzzy sliding mode tracking control module is
, the output control signal of ANN Control module is
, through weighted factor λ
n, λ
fThe output control signal of the compound control module that fuzzy sliding mode tracking control module and ANN Control module is compound is C=λ
n 
+ λ
f 
, λ wherein
n+ λ
f=1.
7. a kind of permagnetic synchronous motor multiplex control system based on fuzzy sliding formwork and neural net according to claim 6 is characterized in that: weighted factor λ
n, λ
fSpan be respectively 0≤λ
n≤ 1,0≤λ
f≤ 1.
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|---|---|---|---|
| CN2012204340371U CN203057059U (en) | 2012-08-29 | 2012-08-29 | Permanent magnet synchronous motor combination control system based on fuzzy sliding mode and neural network |
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| CN2012204340371U CN203057059U (en) | 2012-08-29 | 2012-08-29 | Permanent magnet synchronous motor combination control system based on fuzzy sliding mode and neural network |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103997272A (en) * | 2014-06-09 | 2014-08-20 | 浙江理工大学 | Load disturbance compensation device and method of permanent magnet synchronous motor |
| CN105262396A (en) * | 2015-11-26 | 2016-01-20 | 上海电机学院 | PMSM (Permanent Magnet Synchronous Motor) control method based on HCMAC neural network |
| CN109032038A (en) * | 2018-09-04 | 2018-12-18 | 南宁学院 | A kind of sewage treatment control system based on intensified learning |
| CN109951122A (en) * | 2019-04-02 | 2019-06-28 | 大连交通大学 | Improve the permanent magnet synchronous motor fuzzy sliding mode tracking control system and method for exponentially approaching rule |
-
2012
- 2012-08-29 CN CN2012204340371U patent/CN203057059U/en not_active Expired - Fee Related
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103997272A (en) * | 2014-06-09 | 2014-08-20 | 浙江理工大学 | Load disturbance compensation device and method of permanent magnet synchronous motor |
| CN105262396A (en) * | 2015-11-26 | 2016-01-20 | 上海电机学院 | PMSM (Permanent Magnet Synchronous Motor) control method based on HCMAC neural network |
| CN109032038A (en) * | 2018-09-04 | 2018-12-18 | 南宁学院 | A kind of sewage treatment control system based on intensified learning |
| CN109951122A (en) * | 2019-04-02 | 2019-06-28 | 大连交通大学 | Improve the permanent magnet synchronous motor fuzzy sliding mode tracking control system and method for exponentially approaching rule |
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| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20130710 Termination date: 20150829 |
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| EXPY | Termination of patent right or utility model |