CN107493054A - A kind of switched reluctance machines Direct Torque Control based on improvement ADRC - Google Patents

A kind of switched reluctance machines Direct Torque Control based on improvement ADRC Download PDF

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Publication number
CN107493054A
CN107493054A CN201710407977.9A CN201710407977A CN107493054A CN 107493054 A CN107493054 A CN 107493054A CN 201710407977 A CN201710407977 A CN 201710407977A CN 107493054 A CN107493054 A CN 107493054A
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CN
China
Prior art keywords
adrc
switched reluctance
torque control
direct torque
reluctance machines
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CN201710407977.9A
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Chinese (zh)
Inventor
易灵芝
冯江
桂庆忠
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Xiangtan University
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Xiangtan University
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Priority to CN201710407977.9A priority Critical patent/CN107493054A/en
Publication of CN107493054A publication Critical patent/CN107493054A/en
Pending legal-status Critical Current

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Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P25/00—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details
    • H02P25/02—Arrangements or methods for the control of AC motors characterised by the kind of AC motor or by structural details characterised by the kind of motor
    • H02P25/08—Reluctance motors
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P23/00—Arrangements or methods for the control of AC motors characterised by a control method other than vector control
    • H02P23/30—Direct torque control [DTC] or field acceleration method [FAM]

Abstract

The invention discloses one kind based on improvement automatic disturbance rejection controller（Active disturbance Rejection Control, ADRC）Switched reluctance machines Direct Torque Control, its method is to utilize Auto Disturbances Rejection Control Technique, and on the basis of the switched reluctance machines Direct Torque Control based on ADRC, obtained least square method supporting vector machine is trained by discrete（Least Squares Support Vector Machine, LSSVM）Optimum regression model is dissolved into ADRC, completes the improvement to ADRC.The present invention can significantly improve the response speed and antijamming capability of switched reluctance machines direct Torque Control, the robustness of strengthening system.

Description

A kind of switched reluctance machines Direct Torque Control based on improvement ADRC
Technical field
The present invention relates to a kind of based on the switched reluctance machines Direct Torque Control side for improving automatic disturbance rejection controller (ADRC) Method, belong to switched reluctance machines method for controlling torque field.
Background technology
Because switched reluctance machines are simple in construction, reliable operation, control are flexible, it is adapted to work in adverse circumstances；Meanwhile Because it has the superiority that starting current is small, detent torque is big, switched reluctance motor system is set to be highly suitable for electric automobile With the transmission control field such as mining of mining.
In traditional Direct Torque Control, speed ring uses PI controllers；When controlled and object is in strongly disturbing environment When central, conventional PI control is difficult to the effect for reaching control.With regard to needing to make improvements.
The content of the invention
It is an object of the invention to the deficiency for existing switched reluctance machines Study on direct torque control technology, it is proposed that a kind of Antijamming capability is stronger based on the switched reluctance machines Direct Torque Control for improving ADRC, to improve switched reluctance machines Control performance.
The present invention solve above-mentioned technical problem technical scheme be：
It is a kind of to be obtained discrete training based on the switched reluctance machines Direct Torque Control for improving ADRC, methods described LSSVM optimum regression models be dissolved into ADRC, to complete the improvement to ADRC.The switched reluctance machines for improving ADRC are straight Connect in moment controlling system, the function of LSSVM models is：It can be in real time according to the input signal values of system, to calculate System current suffered portion disturbances value F, the disturbed value z that F and ESO are estimated in real time2' total disturbance as system, rear Feedforward compensation is carried out to system in continuous control, the antijamming capability of control system is improved with this.The control method include with Lower step：
Step 1：In the switched reluctance machines Direct Torque Control based on ADRC, to the defeated of the ESO in ADRC controllers Go out variable and sampled.
Step 2：Using as LSSVM input variable, as its output variable, discrete training is carried out to LSSVM, obtained Its optimal regression model.
Step 3：Obtained optimum regression model and ADRC systems are combined together, obtain improving ADRC switch magnetic Hinder motor direct Torque Control.
2nd, improvement ADRC according to claim 1 switched reluctance machines Direct Torque Control, carry out from Kernel function when dissipating training chooses gaussian radial basis function, and its expression formula is：
ADRC mathematical modelings after improvement：
The present invention propose it is a kind of can be with based on the switched reluctance machines Direct Torque Control for improving ADRC, this method ADRC accuracy of observation is improved, the dynamic responding speed and antijamming capability of SRM direct Torque Controls is further improved, increases The robustness of strong system.
Brief description of the drawings
Fig. 1 is the switched Reluctance Motor Control System principle schematic provided by the invention based on ADRC.
Fig. 2 is the switched reluctance machines direct Torque Control principle schematic provided by the invention based on ADRC.
Fig. 3 is provided by the invention based on the switched reluctance machines direct Torque Control principle signal for improving ADRC Figure.
Embodiment
The present invention is described in further detail with embodiment below in conjunction with the accompanying drawings.
With given rotating speed ωr *With actual speed ωrAs input signal, to give torque Te *As output signal, design Go out and be based on ADRC controllers, it is shown in Figure 1 to be based on ADRC controller principle schematic diagrames to be provided by the invention, it be by with Track differentiator (TD), extended state observer (ESO) and nonlinear state error feedback (NLSEF) three parts composition.With given Rotational speed omegar *As TD input signals, its output signal ω1For ωr *Pursuit gain；With motor actual speed ωrAs the defeated of ESO Enter signal, its output signal is ωrPursuit gain Z1With system suffered by the estimate Z that disturbs2；According to ω1And Z1Obtain system State error e1=ω1-Z1As NLSEF input signal, NLSEF exports initial controlled quentity controlled variable u0；Final controlled quentity controlled variable
According to ADRC principles, system is regarded into the change of switched reluctance machines applied load, moment of friction and rotary inertia Suffered disturbance w (t), system can estimate that system is suffered to be disturbed and timely compensated in real time in ADRC.
In the switched reluctance machines direct Torque Control based on ADRC, the disturbed value w (t) suffered by system is entirely Estimated in real time by the ESO in ADRC speed regulators.In the improvement ADRC systems carried, in ESO to system Before disturbance estimation, it is known that the disturbed value w1 of the current part of system, then the disturbed value w2 of estimation will become needed for ESO It is small, it can thus improve the precision that ESO is estimated disturbed value.Now total disturbance w (t)=w1+w2 of system.
A kind of switched reluctance machines Direct Torque Control for improvement ADRC that the present invention announces, the LSSVM are optimal The discrete training method of regression model comprises the following steps that：
The first step：It is shown in Figure 2 in the switched reluctance machines direct Torque Control based on ADRC, its ADRC Partial internal structure is as shown in Figure 1.ADRC systems are according to the given rotating speed ω of inputr *With actual speed ωrObtain motor to Determine torque value Te *.Compared with the real-time torque value of motor, the switch shape of power inverter is controlled by hysteresis comparator State, the operation of driving switch reluctance motor.
Second step：To the output Z of the ESO in the ADRC of above-mentioned first step system1And Z2Value sampled.
3rd step：By Z1As LSSVM input variable, Z2As its output variable, discrete training is carried out to LSSVM, Obtain LSSVM optimum regression model.The principle of LSSVM regression trainings is as follows：
If the sample data of training is { (xk,yk) | k=1,2 ..., N }, wherein xkAnd ykRespectively training sample is defeated Enter output data.
The target of LSSVM regression models isWherein w is weight vector, and b is offset,For Nuclear space mapping function.
Constraints：
Wherein, J is optimization object function, and γ is regularization parameter, εkFor the relaxation factor of insensitive loss function.
Using Lagrange Multiplier Methods：
Respectively to w, b, αk,εkAsking local derviation to be equal to zero can obtain：
Finally neutralizing is the form of following equations group：
In formula:L=[1,1 ..., 1]T；I is N × N unit matrix；α=[α1, α2..., αN]T；Y=[y1,y2,..., yN]T；K(xi,xj) it is kernel function, the present invention chooses Gaussian radial basis function, its expression formula For：
Make M=Ω+γ-1I, it, which is solved, to obtain：
The regression model for obtaining Function Optimization is：
4th step：The LSSVM models trained are put into ADRC controllers, have obtained base as shown in Figure 3 In improved ADRC controllers.The function of LSSVM models is：It can be in real time according to the input signal values of system, to calculate Go out the current suffered portion disturbances value F of system, total disturbance using the disturbed value that F and ESO are estimated in real time as system, follow-up Control in system carry out feedforward compensation.
Thus, the ADRC mathematical modelings that can be improved are：
Wherein, f1And f2It is defined as follows：
。

Claims (2)

1. it is a kind of based on improve ADRC switched reluctance machines Direct Torque Control, it is characterised in that the control method be On the basis of switched reluctance machines Direct Torque Control based on ADRC, ADRC is improved.First with LSSVM principles pair Parameter in ADRC carries out discrete training and obtains optimum regression model, then mutually ties the optimum regression model with ADRC controllers Close, to complete the improvement to ADRC.ADRC after improvement can improve it and estimate the dynamic responding speed of precision and control system, And it is substantially reduced the steady-state error of switched reluctance machines direct Torque Control.
Step 1：In the switched reluctance machines Direct Torque Control based on ADRC, the output to the ESO in ADRC controllers becomes Measure Z1And Z2Sampled.
Step 2：By Z1As LSSVM input variable, Z2As its output variable, discrete training is carried out to LSSVM, obtains it Optimal regression model.
Step 3：Obtained optimum regression model and ADRC systems are combined together, obtain improving ADRC switching magnetic-resistance electricity Machine direct Torque Control.
2. it is according to claim 1 based on improve ADRC switched reluctance machines Direct Torque Control, carry out from Kernel function when dissipating training chooses gaussian radial basis function, and its expression formula is：
ADRC mathematical modelings after improvement：
。
CN201710407977.9A 2017-06-02 2017-06-02 A kind of switched reluctance machines Direct Torque Control based on improvement ADRC Pending CN107493054A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112532134A (en) * 2020-11-26 2021-03-19 江苏大学 Five-freedom-degree magnetic suspension electric spindle least square support vector machine optimization control system
CN113765453A (en) * 2021-08-30 2021-12-07 江苏大学 Magnetic suspension switched reluctance motor suspension control system with wide-narrow pole characteristic

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102611381A (en) * 2012-03-12 2012-07-25 浙江工业大学 Direct torque control system of permanent-magnet synchronous motor
CN103576552A (en) * 2013-10-24 2014-02-12 广东电网公司电力科学研究院 Active-disturbance-rejection control method and device of single-input single-output pure lag self-balancing object
CN103746627A (en) * 2013-12-31 2014-04-23 华北电力大学（保定） Direct torque control method of PMSM (Permanent Magnet Synchronous Motor)
CN104281055A (en) * 2014-03-18 2015-01-14 江南大学 Active-disturbance-rejection control method for temperature of a constant stirring polypropylene reaction kettle
CN106292273A (en) * 2016-09-26 2017-01-04 长春理工大学 The Auto-disturbance-rejection Control weakened for the lag time of large time delay temperature system
CN106788036A (en) * 2016-12-30 2017-05-31 南京邮电大学 The modified active disturbance rejection positioner and its method for designing of a kind of direct current generator

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102611381A (en) * 2012-03-12 2012-07-25 浙江工业大学 Direct torque control system of permanent-magnet synchronous motor
CN103576552A (en) * 2013-10-24 2014-02-12 广东电网公司电力科学研究院 Active-disturbance-rejection control method and device of single-input single-output pure lag self-balancing object
CN103746627A (en) * 2013-12-31 2014-04-23 华北电力大学（保定） Direct torque control method of PMSM (Permanent Magnet Synchronous Motor)
CN104281055A (en) * 2014-03-18 2015-01-14 江南大学 Active-disturbance-rejection control method for temperature of a constant stirring polypropylene reaction kettle
CN106292273A (en) * 2016-09-26 2017-01-04 长春理工大学 The Auto-disturbance-rejection Control weakened for the lag time of large time delay temperature system
CN106788036A (en) * 2016-12-30 2017-05-31 南京邮电大学 The modified active disturbance rejection positioner and its method for designing of a kind of direct current generator

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
刘国海等: "基于自抗扰控制器的两电机变频调速系统最小二乘支持向量机逆控制", 《中国电机工程学报》 *
刘英培等: "基于最小二乘支持向量机优化自抗扰控制器的永磁同步电机直接转矩控制方法", 《中国电机工程学报》 *
张之超，邹德伟主编: "《新能源汽车驱动电机与控制技术》", 31 August 2016, 北京理工大学出版社 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112532134A (en) * 2020-11-26 2021-03-19 江苏大学 Five-freedom-degree magnetic suspension electric spindle least square support vector machine optimization control system
CN113765453A (en) * 2021-08-30 2021-12-07 江苏大学 Magnetic suspension switched reluctance motor suspension control system with wide-narrow pole characteristic

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