CN106602945B - A kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm - Google Patents
A kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm Download PDFInfo
- Publication number
- CN106602945B CN106602945B CN201611169775.7A CN201611169775A CN106602945B CN 106602945 B CN106602945 B CN 106602945B CN 201611169775 A CN201611169775 A CN 201611169775A CN 106602945 B CN106602945 B CN 106602945B
- Authority
- CN
- China
- Prior art keywords
- direct current
- current motor
- brush direct
- control
- subcycle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
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
- H02P7/00—Arrangements for regulating or controlling the speed or torque of electric DC motors
- H02P7/06—Arrangements for regulating or controlling the speed or torque of electric DC motors for regulating or controlling an individual dc dynamo-electric motor by varying field or armature current
- H02P7/18—Arrangements for regulating or controlling the speed or torque of electric DC motors for regulating or controlling an individual dc dynamo-electric motor by varying field or armature current by master control with auxiliary power
- H02P7/24—Arrangements for regulating or controlling the speed or torque of electric DC motors for regulating or controlling an individual dc dynamo-electric motor by varying field or armature current by master control with auxiliary power using discharge tubes or semiconductor devices
- H02P7/28—Arrangements for regulating or controlling the speed or torque of electric DC motors for regulating or controlling an individual dc dynamo-electric motor by varying field or armature current by master control with auxiliary power using discharge tubes or semiconductor devices using semiconductor devices
- H02P7/285—Arrangements for regulating or controlling the speed or torque of electric DC motors for regulating or controlling an individual dc dynamo-electric motor by varying field or armature current by master control with auxiliary power using discharge tubes or semiconductor devices using semiconductor devices controlling armature supply only
- H02P7/29—Arrangements for regulating or controlling the speed or torque of electric DC motors for regulating or controlling an individual dc dynamo-electric motor by varying field or armature current by master control with auxiliary power using discharge tubes or semiconductor devices using semiconductor devices controlling armature supply only using pulse modulation
Abstract
This application discloses a kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithms, subcycle division is carried out by the whole cycle to power switch tube, brush direct current motor speed-regulating system sub-sampling period discrete state-space model can be established, the hybrid characters of brush direct current motor speed-regulating system essence can be reacted.On this basis, it is control variable with pulse duty factor, according to switching present position difference, brush direct current motor speed-regulating system is divided into v kind situation, the v kind separate manufacturing firms model in entire switching tube cycle T is established respectively, is the piecewise affine model of duty ratio, is reduced averaging model bring error in traditional approach, modeling accuracy can be improved by increasing subcycle number.Meanwhile also overcoming in traditional approach, the shortcomings that system dynamic behaviour can not describe in switch periods, separate manufacturing firms model basis is provided for PREDICTIVE CONTROL conceptual design.
Description
Technical field
This application involves a kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithms, in the technical solution
Holding and obtains project of national nature science fund project (61304095), Jiangsu Province's Nsfc Projects (BK20130317) are subsidized,
Jiangsu Province post-doctor research fund plan (1302103B) is subsidized.
Background technique
Dc motor is the motor that direct current energy is converted to mechanical energy, with good speed adjusting performance in electricity
Power dragging in be used widely, industry, agricultural, communications and transportation, urban construction, energy conservation and in terms of have it is non-
Often important application.Dc motor can be divided into according to its structure brush and brushless two kinds, wherein brush DC motors, leads to
It crosses brush the positive and negative anodes of power supply are introduced on the phase changer of rotor, phase changer is connected to the coil on rotor, and coil polarity is continuous
Checker and fixed magnetic field form active force and rotate.Brush motor is simple to manufacture, and technical threshold is low, at low cost
It is honest and clean, it is very widely used.Increasingly extensive with brush direct current motor application, every field adjusts the speed it, energy-efficient performance etc. is wanted
It asks higher and higher, the performance of brush direct current motor mainly is improved by studying advanced control strategy to this.
One distinguishing feature of brush direct current motor is that common speed-regulating scheme, which has, adjusts armature supply electricity containing brush
Three kinds of pressure, change motor main flux, change armature circuit resistance etc..Changing armature voltage speed regulation is that brush direct current motor is most main
The speed regulating method wanted, needs controllable direct current power supply.
By taking the brush direct current motor circuit of armature control shown in FIG. 1 as an example, Constant Direct Current power supply is generallyd use or can not
Rectifier power source power supply is controlled, adjustable direct current average voltage is generated using dc chopper or pulse width modulated inverter, to realize
The speed regulation of brush direct current motor.
Traditional approach uses the linear PI based on pulse modulation technology (Pulse Width Modulation, PWM)
(Proportional Integral) control method, as shown in Fig. 2, according to brush direct current motor actual speed and rotating speed of target
Difference, feed back to PI controller (Proportional Integral Controller), calculate armature average voltage ginseng
Value is examined, then the average reference value is realized by pulse duration modulation method (Pulse Width Modulation, PWM).
Pulse duration modulation method usually as shown in figure 3, using Constant Direct Current power supply or the power supply of uncontrollable rectifier power source, utilizes function
Rate switch controlled keeps switching frequency constant (i.e. switch periods T is remained unchanged), adjusts pulse width Ton, it is flat to adjust output
Equal voltage Ud, to realize the revolving speed control of brush direct current motor.
Conventional PI control scheme as shown in Figure 2, when carrying out pulse width modulation controlled, using system in a cycle T
Interior averaging model only accounts for the load dynamic of system, has ignored PWM modulation technology, since the switch of power switch tube is dynamic
The Hybrid dynamics behavior made, and generated.Therefore, conventional PI control scheme can not be embodied based on PWM speed-governing dc brush motor sheet
The change procedure of hybrid characters and its internal system state in a pulse width period in matter.Due to the mistake of averaging model
Difference leads to its revolving speed control accuracy difference, and due to the intrinsic dynamic of PWM, algorithm response speed is slow.Conventional PI control scheme, by
In control structure itself the shortcomings that, the constraint condition of system mode and output can not be considered, also cannot achieve for specifics
Can index optimum control, so that Vehicles Collected from Market can not be adapted to the performance of brush direct current motor speed-regulating system and efficiency increasingly
Harsh requirement.
Summary of the invention
The purpose of the present invention is to provide a kind of brush direct current motor revolving speed it is discrete control and explicit forecast Control Algorithm, with
Overcome deficiency in the prior art.
To achieve the above object, the invention provides the following technical scheme:
The embodiment of the present application discloses a kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm, comprising:
S1, brush direct current motor speed-regulating system sub-sampling period discrete state-space model is established:
Within each period of power switch tube, subcycle division is carried out to whole cycle, according to switch motion switching
Subcycle is divided into three classes by position:
The first kind: the subcycle before switching,
Second class: the subcycle after switching,
Third class: the subcycle when switching,
The number v of subcycle is determined by control accuracy requirement and control algolithm calculation amount synthesis, according to the sub-sampling period
Different type carries out discretization to the system dynamic in pulse width period, establishes the brush direct current motor speed-regulating system sub-sampling period
Separate manufacturing firms model；
It s2, is that control variable adjusts the speed brush direct current motor according to switching present position difference with pulse duty factor
System is divided into v kind situation: the 1st kind to v kind, wherein v kind refers to that switch switches in v-th of subcycle；
S3, with the output of brush direct current motor revolving speed and the difference of target value, the frequency of switching device with the performance indicators such as be lost
Weighted value is index, comprehensively considers the constraint condition of system mode and output, the explicit prediction optimization control of system is realized, to shape
State space carries out subregion, the corresponding optimal control law in each Condition Areas.
Preferably, in the above-mentioned discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm, the step
S1 includes:
Power switch tube cycle T is divided into T/T0A subcycle, with T0After being divided for the sub-sampling period, three can be divided into
Class subcycle, for every class subcycle, brush direct current motor speed-regulating system sub-sampling period discrete state-space model is as follows:
The first kind:
ξ (n+1)=Φ ξ (n)+Ψ
Second class:
ξ (n+1)=Φ ξ (n)
Third class:
ξ (n+1)=Φ ξ (n)+Ψ (vd (k)-n)
Wherein:
Preferably, in the above-mentioned discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm, the step
S2 includes: to establish 3 kinds of situations on the basis of brush direct current motor speed-regulating system sub-sampling period discrete state-space model
Under, the separate manufacturing firms piecewise affine model in entire switching tube cycle T:
。
Preferably, in the above-mentioned discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm, the step
In s2, on the basis of brush direct current motor speed-regulating system sub-sampling period discrete state-space model, to v kind situation, respectively
The separate manufacturing firms model in entire switching tube cycle T is established, is the piecewise affine model of duty ratio.
Compared with the prior art, the advantages of the present invention are as follows:
(1), subcycle division is carried out by the whole cycle to power switch tube, brush direct current motor speed regulation system can be established
System sub-sampling period discrete state-space model, can react the hybrid characters of brush direct current motor speed-regulating system essence, can be right
The switching of system mode and dynamic process are modeled when power switch tube switches in pulse width period.Reduce traditional approach
Middle averaging model bring error can improve modeling accuracy by increasing subcycle number.Meanwhile also overcoming Traditional control
In scheme, the shortcomings that system dynamic behaviour can not describe in switch periods, provides discrete state sky for PREDICTIVE CONTROL conceptual design
Between model basis.
(2), according to switching present position difference, brush direct current motor speed-regulating system is divided into v kind situation, Neng Gouzhun
The dynamic behaviour of system in the true entire switching tube cycle T of description, to establish brush direct current motor according to pulse duration ratio
The piecewise affine separate manufacturing firms model of speed-regulating system.On the basis of piecewise affine Accurate Model, it can solve corresponding explicit
PREDICTIVE CONTROL problem.
(3), the difference of brush direct current motor revolving speed output and target value, frequency and the performance indicators such as loss of switching device add
Weight is index, comprehensively considers the constraint condition of system mode and output, can be realized optimal under conditions of meeting system restriction
Change control, mention high control precision and response speed, realizes that the comprehensive performance of brush direct current motor revolution speed control system is optimal.
(4), it is control variable with pulse duty factor, subregion is carried out to state space, each Condition Areas corresponding one is optimal
Control law realizes explicit PREDICTIVE CONTROL, can iteratively solve online PREDICTIVE CONTROL optimal problem, switchs to solve offline, online
Condition Areas problem, can effectively reduce on-line calculation, improves the real-time of the control algolithm, guarantee it portable belonging to judging
The feasibility applied in rapid system.
Detailed description of the invention
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The some embodiments recorded in application, for those of ordinary skill in the art, without creative efforts,
It is also possible to obtain other drawings based on these drawings.
Fig. 1 show the brush direct current motor circuit theory schematic diagram of armature control in the prior art；
Fig. 2 show the linear PI control structure figure based on pulse modulation technology in the prior art；
Fig. 3 show pulsewidth modulation in the prior art (Pulse Width Modulation, PWM) schematic diagram；
Fig. 4 show in the specific embodiment of the invention subcycle in switch periods and divides schematic diagram；
Fig. 5 show subcycle in one embodiment of the present invention and divides schematic diagram；
Fig. 6 show brush direct current motor governor system control structure chart in the specific embodiment of the invention.
Specific embodiment
Term is explained:
Brush direct current motor is the rotating electric machine that direct current energy is converted into mechanical energy by brushgear.
Discrete control is to carry out discretization to continuous system using the specific sampling period, obtains corresponding discrete time mould
Type, and control algolithm is designed based on discrete time model.
Explicit PREDICTIVE CONTROL is to realize system prediction, on-line optimization and feedback compensation, and based on system model with explicit
Method solve optimal control law modern control technology.
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out detailed retouch
It states, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Based on the present invention
In embodiment, those of ordinary skill in the art's every other implementation obtained without making creative work
Example, shall fall within the protection scope of the present invention.
The discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm include following steps.
As shown in connection with fig. 4, using sub-sampling cycle T0Power switch tube cycle T is divided into T/T0A subcycle, and according to
Subcycle is divided into three classes by the position of switch motion switching: the 1. subcycle before switching, 2. the son after switching
Period, the 3. subcycle when switching (switch switch in the subcycle).And three classes subcycle T is established respectively0It establishes
Brush direct current motor speed-regulating system sub-sampling period discrete state-space model.Shared three classes subcycle separate manufacturing firms mould
Type, number of sub-periods is more, and system modelling precision is higher, but corresponding control algolithm computation burden is also bigger.
Power switch tube cycle T is divided into T/T0A subcycle, with T0After being divided for the sub-sampling period, three can be divided into
Class subcycle, for every class subcycle, brush direct current motor speed-regulating system sub-sampling period discrete state-space model is as follows:
The first kind:
ξ (n+1)=Φ ξ (n)+Ψ
Second class:
ξ (n+1)=Φ ξ (n)
Third class:
ξ (n+1)=Φ ξ (n)+Ψ (vd (k)-n)
Wherein:
Further, being control variable with pulse duty factor, according to switching present position difference, by brush direct current motor
Speed-regulating system is divided into v kind situation.1st kind: switch is changed in the 1st subcycle inscribe；2nd kind: switch is in the 2nd subcycle inscribe
It changes；……；V kind: switch switches in v-th of subcycle.In brush direct current motor speed-regulating system sub-sampling period discrete shape
It on the basis of state space model, establishes in the case of v kind, the separate manufacturing firms piecewise affine model in entire switching tube cycle T.
For more subcycle situations, algorithm is analogized.
The model can accurately respond the Mode-switch in one power switch tube period of brush direct current motor speed-regulating system
And dynamic process, and on the basis of piecewise affine Accurate Model, corresponding explicit PREDICTIVE CONTROL problem can be solved.
On the basis of this model, with the output of brush direct current motor revolving speed and the difference of target value, the frequency of switching device and
The performance indicators weighted values such as loss are index, comprehensively consider the constraint condition of system mode and output, divide state space
Area, the corresponding optimal control law in each Condition Areas, realizes explicit PREDICTIVE CONTROL.PREDICTIVE CONTROL optimal problem is asked in line interation
Solution, switchs to solve offline, online to judge affiliated Condition Areas problem, can effectively reduce on-line calculation, improves the control algolithm
Real-time, guarantee its feasibility applied in portable rapid system.Finally, brush direct current motor governor system control structure
As shown in Figure 6.
In a preferred embodiment, the brush direct current motor speed-regulating system period is divided into 3 subcycles, from
Bulk state space modeling method is joined shown in Fig. 5.Power switch tube cycle T divides 3 subcycles, and can be divided into three classes subcycle.
It is control variable with pulse duty factor, according to switching present position difference, brush direct current motor is adjusted the speed into system
System is divided into 3 kinds of situations.1st kind: switch is changed in the 1st subcycle inscribe；2nd kind: switch is changed in the 2nd subcycle inscribe；3rd
Kind: switch is changed in the 3rd subcycle inscribe.In brush direct current motor speed-regulating system sub-sampling period discrete state-space model
On the basis of, it establishes in the case of 3 kinds, the separate manufacturing firms piecewise affine model in entire switching tube cycle T.
For more subcycle situations, algorithm is analogized.
Here, it should also be noted that, in order to avoid having obscured the present invention because of unnecessary details, in the accompanying drawings only
Show with closely related structure and/or processing step according to the solution of the present invention, and be omitted little with relationship of the present invention
Other details.
Finally, it is to be noted that, the terms "include", "comprise" or its any other variant be intended to it is non-exclusive
Property include so that include a series of elements process, method, article or equipment not only include those elements, but also
Further include other elements that are not explicitly listed, or further include for this process, method, article or equipment it is intrinsic
Element.
Claims (4)
1. a kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm characterized by comprising
S1, brush direct current motor speed-regulating system sub-sampling period discrete state-space model is established:
Within each period of power switch tube, subcycle division is carried out to whole cycle, the position switched according to switch motion
Subcycle is divided into three classes:
The first kind: the subcycle before switching,
Second class: the subcycle after switching,
Third class: the subcycle when switching,
The number v of subcycle is determined by control accuracy requirement and control algolithm calculation amount synthesis, according to the difference in sub-sampling period
Type carries out discretization to the system dynamic in pulse width period, establishes brush direct current motor speed-regulating system sub-sampling period discrete
State-space model；
It s2, take pulse duty factor as control variable, according to switching present position difference, by brush direct current motor speed-regulating system
It is divided into v kind situation: the 1st kind to v kind, wherein v kind refers to that switch switches in v-th of subcycle；
S3, with the output of brush direct current motor revolving speed and the difference of target value, the frequency and drain performance index weighted value of switching device
For index, the constraint condition of system mode and output is comprehensively considered, the explicit prediction optimization control of system is realized, to state space
Carry out subregion, the corresponding optimal control law in each Condition Areas.
2. the discrete control of brush direct current motor revolving speed according to claim 1 and explicit forecast Control Algorithm, feature exist
In: the step s1 includes:
Power switch tube cycle T is divided into T/T0A subcycle, with T0After being divided for the sub-sampling period, can be divided into three classes son
In the period, for every class subcycle, brush direct current motor speed-regulating system sub-sampling period discrete state-space model is as follows:
The first kind:
ξ (n+1)=Φ ξ (n)+Ψ
Second class:
ξ (n+1)=Φ ξ (n)
Third class:
ξ (n+1)=Φ ξ (n)+Ψ (vd (k)-n)
Wherein:
3. the discrete control of brush direct current motor revolving speed according to claim 2 and explicit forecast Control Algorithm, feature exist
In: the step s2 includes: to build on the basis of brush direct current motor speed-regulating system sub-sampling period discrete state-space model
In the case of 3 kinds vertical, the separate manufacturing firms piecewise affine model in entire switching tube cycle T:
4. the discrete control of brush direct current motor revolving speed according to claim 1 and explicit forecast Control Algorithm, feature exist
In: in the step s2, on the basis of brush direct current motor speed-regulating system sub-sampling period discrete state-space model, to v
Kind situation, establishes the separate manufacturing firms model in entire switching tube cycle T respectively, is the piecewise affine model of duty ratio.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611169775.7A CN106602945B (en) | 2016-12-16 | 2016-12-16 | A kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611169775.7A CN106602945B (en) | 2016-12-16 | 2016-12-16 | A kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106602945A CN106602945A (en) | 2017-04-26 |
| CN106602945B true CN106602945B (en) | 2019-02-12 |
Family
ID=58600975
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611169775.7A Active CN106602945B (en) | 2016-12-16 | 2016-12-16 | A kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106602945B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109003631A (en) * | 2018-07-13 | 2018-12-14 | 浙江工业大学之江学院 | The multiple dimensioned approximate explicit model forecast Control Algorithm of disk drive system |
| CN110557072B (en) * | 2019-09-29 | 2021-08-20 | 潍柴动力股份有限公司 | Method and device for controlling rotating speed and current loop of permanent magnet synchronous motor |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8024052B1 (en) * | 2007-03-30 | 2011-09-20 | Tim Hakala | Adaptive mapping of device output change to amounts of control effort |
| CN102938209A (en) * | 2012-11-19 | 2013-02-20 | 西安费斯达自动化工程有限公司 | On-line traffic bottleneck predictive control method based on field programmable gate array (FPGA) and improved dispersed macroscopic D model |
| CN105429493A (en) * | 2015-12-28 | 2016-03-23 | 苏州大学 | Discrete control and predictive control method of direct current-alternating current (DC-AC) inverter |
-
2016
- 2016-12-16 CN CN201611169775.7A patent/CN106602945B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8024052B1 (en) * | 2007-03-30 | 2011-09-20 | Tim Hakala | Adaptive mapping of device output change to amounts of control effort |
| CN102938209A (en) * | 2012-11-19 | 2013-02-20 | 西安费斯达自动化工程有限公司 | On-line traffic bottleneck predictive control method based on field programmable gate array (FPGA) and improved dispersed macroscopic D model |
| CN102938209B (en) * | 2012-11-19 | 2014-10-08 | 西安费斯达自动化工程有限公司 | On-line traffic bottleneck predictive control method based on field programmable gate array (FPGA) and improved dispersed macroscopic D model |
| CN105429493A (en) * | 2015-12-28 | 2016-03-23 | 苏州大学 | Discrete control and predictive control method of direct current-alternating current (DC-AC) inverter |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106602945A (en) | 2017-04-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Batiyah et al. | An MPC-based power management of standalone DC microgrid with energy storage | |
| CN106773648B (en) | Robust performance-guaranteeing design and parameter setting method for active disturbance rejection controller | |
| CN110022109B (en) | Method and system for controlling torque ripple of SRM (sequence-derived minimum-mean-square) of torque-current neural network model | |
| US8525468B2 (en) | Motor drive system with bus voltage control | |
| CN104085265B (en) | A kind of energy regenerative suspension self adaptation off-line Neural network inverse control system and method | |
| Peng et al. | Compound control for energy management of the hybrid ultracapacitor-battery electric drive systems | |
| CN104378038A (en) | Permanent magnet synchronous motor parameter identification method based on artificial neural network | |
| CN103051274A (en) | Variable damping-based passive control method for two-degree-of-freedom permanent magnetic synchronous motor | |
| Chi et al. | Proton exchange membrane fuel cell-powered bidirectional DC motor control based on adaptive sliding-mode technique with neural network estimation | |
| Xiaojuan et al. | A novel sliding mode control for BLDC motor network control system | |
| CN103208958A (en) | DC (direct control) servo drive control system | |
| CN106602945B (en) | A kind of discrete control of brush direct current motor revolving speed and explicit forecast Control Algorithm | |
| CN102437816B (en) | Adaptive motor motion control apparatus based on neural network | |
| CN108322116B (en) | Switched reluctance motor system efficiency optimization control method | |
| CN104135205A (en) | Control method for maximum torque current rate of induction motor | |
| CN109639192A (en) | A kind of durface mounted permanent magnet synchronous motor time-sharing control system and Time-sharing control method | |
| ELkholy et al. | Efficient dynamic performance of brushless DC motor using soft computing approaches | |
| CN104167968A (en) | Asynchronous motor vector control method | |
| CN105071709A (en) | Motor optimization control apparatus and method | |
| CN202435341U (en) | Constant magnetic flux keeping device for frequency converter | |
| CN104967380A (en) | Double salient generator voltage adjustment control device and method having anti-interference capability | |
| CN114825396A (en) | Method for improving DC bus voltage robustness of high-speed flywheel energy storage array | |
| Cao et al. | Neural network self-adaptive PID control for driving and regenerative braking of electric vehicle | |
| Kumar et al. | Soft sensing of speed in load torque estimation for boost converter fed DC motor | |
| Vittek et al. | Energy saving position control algorithm for PMSM drives with quadratic friction |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |