CN111082732B - Automatic learning system for current curve mode of voice coil motor driver - Google Patents
Automatic learning system for current curve mode of voice coil motor driver Download PDFInfo
- Publication number
- CN111082732B CN111082732B CN201911408001.9A CN201911408001A CN111082732B CN 111082732 B CN111082732 B CN 111082732B CN 201911408001 A CN201911408001 A CN 201911408001A CN 111082732 B CN111082732 B CN 111082732B
- Authority
- CN
- China
- Prior art keywords
- curve
- register
- current
- fastest
- serial number
- 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
Images
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
- H02P25/032—Reciprocating, oscillating or vibrating motors
- H02P25/034—Voice coil 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
- H02P23/0004—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control
- H02P23/0031—Control strategies in general, e.g. linear type, e.g. P, PI, PID, using robust control implementing a off line learning phase to determine and store useful data for on-line control
Landscapes
- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Databases & Information Systems (AREA)
- Control Of Linear Motors (AREA)
Abstract
The invention discloses an automatic learning system for a current curve mode of a voice coil motor driver, which is characterized in that the optimal combination of the step length of each section and the step distance of each section of a current curve is calculated by continuously learning different section numbers, different step lengths selected by each section and different oscillation stability results generated by the combination of different step distances selected by each section through an automatic learning algorithm, so that the focusing speed of the current curve is higher, the precision is higher, a driving current curve is rapidly and accurately selected aiming at the whole working process of an actuating mechanism, the voice coil motor driver is controlled to work, and the actuating mechanisms such as a camera and the like are rapidly, stably and accurately driven to move.
Description
Technical Field
The invention relates to an automatic control device of a voice coil motor, in particular to an automatic learning system of a current curve mode of a voice coil motor driver.
Background
The driving current control of the traditional voice coil motor driver usually directly appoints one of a plurality of preset driving current curves to control, and usually only one driving current curve can be fixedly selected on the basis of testing to be applied to the whole working process of a product, so that the driving object is difficult to control to move quickly, stably and accurately.
A Voice Coil Motor (Voice Coil Motor) is a device for converting electric energy into mechanical energy, and is a device for generating regular motion by utilizing the interaction between magnetic poles in a magnetic field generated by permanent magnetic steel and a conductor of an electrified Coil, and can realize linear motion and motion with a limited swing angle. The voice coil motor is moved by the principle that an electrified coil receives force in a magnetic field, and the precise control needs to be realized by some external components, such as a Drive IC, and the magnitude and the time of current are controlled and output through the Drive IC, so that the position which the voice coil motor needs to reach is controlled. Because the voice coil motor is a non-commutation type power device, the positioning accuracy is completely dependent on the feedback and control system, and is independent of the voice coil motor. The positioning accuracy can easily reach 10NM and the acceleration can reach 300g (the actual acceleration also depends on the condition of the load) by adopting a proper positioning feedback and induction device.
Disclosure of Invention
The technical problem to be solved by the invention is to provide an automatic learning system for the current curve mode of the voice coil motor driver, which can enable the focusing speed of the current curve to be faster and the precision to be higher, and is convenient for selecting a driving current curve rapidly and accurately according to the whole working process of an actuating mechanism, controlling the voice coil motor driver to work, and rapidly, stably and accurately actuating the mechanism to move.
In order to solve the technical problems, the invention provides an automatic learning system of a current curve mode of a voice coil motor driver, which comprises a parameter control register module, an automatic learning algorithm module, a current curve generation module and a displacement amplitude detection module;
the parameter control register module is used for receiving an external operation instruction and performing read-write operation on the parameter register;
the parameter registers comprise an automatic learning starting control register, a fastest stable time register and a fastest stable curve sequence number register;
the parameter control register module receives an external write operation instruction and sets the automatic learning starting control register to be in a starting state or a waiting state;
the fastest stabilization time register is used for registering the fastest displacement stabilization time, and the initial register value of the fastest stabilization time register is the maximum value;
the fastest stable curve serial number register is used for registering a curve serial number m;
the current curve generation module generates a current curve m corresponding to the curve serial number m according to the section number corresponding to the curve serial number m, the selected step length of each section, the selected step pitch of each section and the curve type after receiving the curve starting signal, and controls the voice coil motor driver to work according to the current curve m;
the displacement amplitude detection module detects a displacement amplitude signal of the voice coil motor driver after receiving the curve starting signal, starts timing by using a clock signal, stops timing if the amplitude of the displacement amplitude signal is smaller than a set value, and sends the displacement stabilization time to the automatic learning algorithm module by using a timing value after the timing is started as the displacement stabilization time;
when the state of the dynamic learning starting control register is a starting state, the automatic learning algorithm module enters a one-time self-learning process of one type of current curve, and the process is as follows:
setting one type of current curve as N sections, and setting step length and step pitch in each section, wherein the step length in each section can be selected between the minimum step length and the maximum step length, and the step pitch in each section can be selected between the minimum step pitch and the maximum step pitch; different segment numbers, different step lengths selected by the segments and combinations of different step distances selected by the segments correspond to different curve serial numbers m;
outputting a segment number corresponding to a curve serial number m, a step length selected by each segment, a step distance selected by each segment and the type of a current curve to a current curve generation module, and outputting a curve starting signal to the current curve generation module and the displacement amplitude detection module;
if the displacement stabilization time sent by the displacement amplitude detection module is shorter than the register time in the fastest stabilization time register, updating the register value in the fastest stabilization time register to be the displacement stabilization time, writing the curve serial number m of the current curve m output by the current curve generation module at this time into the fastest stabilization curve serial number register, and writing the learning experience data of the curve serial number m into a memory;
the automatic learning algorithm module sequentially outputs segment numbers corresponding to all curve serial numbers m, selected step lengths of all the segments and selected step distances of all the segments of a type of current curve to the current curve generation module, after the current curve generation module generates the current curve m corresponding to all the curve serial numbers m, the register time in the fastest stable time register is the fastest displacement stable time of the type of current curve, and the curve serial number m registered in the fastest stable curve serial number register is the optimal curve serial number of the type of current curve.
Preferably, the learning experience data comprises curve segment number, step size and step distance.
Preferably, the parameter register further comprises a curve learning result register;
the curve learning result register is used for registering the optimal curve serial number, learning experience data and the fastest displacement stabilization time after the automatic learning algorithm module completes the self-learning process on one type of current curve;
the automatic learning algorithm module is used for registering the optimal curve serial number and the corresponding learning experience data and the fastest displacement stabilization time thereof into the curve learning result register
Preferably, the parameter control register module is configured to receive an external operation instruction, and read out an optimal curve serial number, learning experience data, and a fastest displacement stabilization time of one type of current curve from the curve learning result register.
Preferably, the parameter register further includes a curve initial value register and a curve target value register;
the curve initial value register is used for registering an initial current value of the current curve, the initial current value is defaulted to 0 when being electrified, and after the parameter control register module receives an execution completion signal generated by the current curve, the initial current value is replaced by a value of the curve target value register;
the curve target value register is used for registering a target current value of the current curve, the target current value is defaulted to 0 when electrified, and the parameter control register module receives an external write operation instruction to write the target current value into the curve target value register.
Preferably, the current curve generating module generates a current curve m corresponding to the curve number m according to the segment number corresponding to the curve number m, the step length selected by each segment, the step pitch selected by each segment, the curve type, the initial current value and the target current value after receiving the curve starting signal, and controls the voice coil motor driver to work according to the current curve m.
Preferably, the external operation instruction cannot write to the curve initial value register and can only read;
preferably, the auto-learn start control register defaults to a wait state when powered on.
Preferably, the current curve mode automatic learning system of the voice coil motor driver further comprises a memory module;
the memory module is used for storing learning experience data of a current curve;
and if the displacement stabilization time sent by the displacement amplitude detection module is shorter than the register time in the fastest stabilization time register, the automatic learning algorithm module updates the register value in the fastest stabilization time register to the displacement stabilization time, writes the curve serial number m of the current curve m output by the current curve generation module at this time into the fastest stabilization curve serial number register, and writes the learning experience data of the curve serial number m into a memory.
According to the automatic learning system for the current curve mode of the voice coil motor driver, disclosed by the invention, through an automatic learning algorithm, the optimal combination of the step length of each section and the step pitch of each section of the current curve is calculated by continuously learning different section numbers of the current curve, different step lengths selected by each section and different oscillation stability results generated by the combination of different step pitches selected by each section, so that the focusing speed of the current curve is higher and the precision is higher. When the driver is designed, the current curves of different starting points and different stopping points are judged without fixed test parameters and a determined lookup table; in the testing stage, a lookup table can be generated by automatic learning statistics of different results; in the application stage, a proper current curve can be automatically selected according to input data, and the voice coil motor driver is controlled to work. The automatic learning system for the current curve mode of the voice coil motor driver is convenient for quickly and accurately selecting a driving current curve aiming at the whole working process of the actuating mechanism, controlling the voice coil motor driver to work and quickly, stably and accurately driving the actuating mechanisms such as a camera to move.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the present invention are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of an embodiment of an automatic learning system for current curve mode of a voice coil motor driver according to the present invention;
fig. 2 is a schematic diagram of one type of current curve segmentation and step size, step pitch.
Detailed Description
The technical solutions in the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example one
As shown in fig. 1 and 2, the current curve mode automatic learning system of the voice coil motor driver includes a parameter control register module, an automatic learning algorithm module, a current curve generation module, and a displacement amplitude detection module;
the parameter control register module is used for receiving an external operation instruction and performing read-write operation on the parameter register;
the parameter registers comprise an automatic learning starting control register, a fastest stable time register and a fastest stable curve sequence number register;
the parameter control register module receives an external write operation instruction and sets the automatic learning starting control register to be in a starting state or a waiting state;
the fastest stabilization time register is used for registering the fastest displacement stabilization time, and the initial register value of the fastest stabilization time register is the maximum value;
the fastest stable curve serial number register is used for registering a curve serial number m;
the current curve generation module generates a current curve m corresponding to the curve serial number m according to the section number corresponding to the curve serial number m, the selected step length of each section, the selected step pitch of each section and the curve type after receiving the curve starting signal, and controls the voice coil motor driver to work according to the current curve m;
the displacement amplitude detection module detects a displacement amplitude signal of the voice coil motor driver after receiving the curve starting signal, starts timing by using a clock signal, stops timing if the amplitude of the displacement amplitude signal is smaller than a set value, and sends the displacement stabilization time to the automatic learning algorithm module by using a timing value after the timing is started as the displacement stabilization time;
when the state of the dynamic learning starting control register is a starting state, the automatic learning algorithm module enters a one-time self-learning process of one type of current curve, and the process is as follows:
setting one type of current curve as N sections, and setting step length and step pitch in each section, wherein the step length in each section can be selected between the minimum step length and the maximum step length, and the step pitch in each section can be selected between the minimum step pitch and the maximum step pitch; different segment numbers, different step lengths selected by the segments and combinations of different step distances selected by the segments correspond to different curve serial numbers m;
outputting a segment number corresponding to a curve serial number m, a step length selected by each segment, a step distance selected by each segment and the type of a current curve to a current curve generation module, and outputting a curve starting signal to the current curve generation module and the displacement amplitude detection module;
if the displacement stabilization time sent by the displacement amplitude detection module is shorter than the register time in the fastest stabilization time register, updating the register value in the fastest stabilization time register to be the displacement stabilization time, writing the curve serial number m of the current curve m output by the current curve generation module at this time into the fastest stabilization curve serial number register, and writing the learning experience data of the curve serial number m into a memory;
the automatic learning algorithm module sequentially outputs segment numbers corresponding to all curve serial numbers m, selected step lengths of all the segments and selected step distances of all the segments of a type of current curve to the current curve generation module, after the current curve generation module generates the current curve m corresponding to all the curve serial numbers m, the register time in the fastest stable time register is the fastest displacement stable time of the type of current curve, and the curve serial number m registered in the fastest stable curve serial number register is the optimal curve serial number of the type of current curve.
Preferably, the learning experience data includes curve segment number, step size and step distance.
In the current curve mode automatic learning system of the voice coil motor driver according to the first embodiment, the optimal combination of the step length of each segment and the step pitch of each segment of the current curve is calculated by continuously learning different segment numbers, different step lengths selected by each segment, and different oscillation stabilization results generated by the combination of different step pitches selected by each segment of one type of current curve through an automatic learning algorithm, so that the focusing speed of the current curve is faster and the precision is higher. When the driver is designed, the current curves of different starting points and different stopping points are judged without fixed test parameters and a determined lookup table; in the testing stage, a lookup table can be generated by automatic learning statistics of different results; in the application stage, a proper current curve can be automatically selected according to input data, and the voice coil motor driver is controlled to work. The automatic learning system for the current curve mode of the voice coil motor driver, provided by the embodiment, is convenient for quickly and accurately selecting a driving current curve aiming at the whole working process of the actuating mechanism, controlling the voice coil motor driver to work, and quickly, stably and accurately driving the actuating mechanisms such as the camera to move.
Example two
Based on the current curve mode automatic learning system of the voice coil motor driver of the first embodiment, the parameter register further comprises a curve learning result register;
the curve learning result register is used for registering the optimal curve serial number, learning experience data and the fastest displacement stabilization time after the automatic learning algorithm module completes the self-learning process on one type of current curve;
and the automatic learning algorithm module is used for registering the optimal curve serial number and the corresponding learning experience data and the fastest displacement stabilization time to the curve learning result register.
Preferably, the parameter control register module is configured to receive an external operation instruction, and read out an optimal curve serial number, learning experience data, and a fastest displacement stabilization time of one type of current curve from the curve learning result register.
EXAMPLE III
Based on the current curve mode automatic learning system of the voice coil motor driver of the second embodiment, the parameter register further comprises a curve initial value register and a curve target value register;
the curve initial value register is used for registering an initial current value of the current curve, the initial current value is defaulted to 0 when being electrified, and after the parameter control register module receives an execution completion signal generated by the current curve, the initial current value is replaced by a value of the curve target value register;
the curve target value register is used for registering a target current value of the current curve, the target current value is defaulted to 0 when electrified, and the parameter control register module receives an external write operation instruction to write the target current value into the curve target value register.
Preferably, the current curve generating module generates a current curve m corresponding to the curve number m according to the segment number corresponding to the curve number m, the step length selected by each segment, the step pitch selected by each segment, the curve type, the initial current value and the target current value after receiving the curve starting signal, and controls the voice coil motor driver to work according to the current curve m.
Preferably, the external operation instruction cannot write to the curve initial value register and can only read;
preferably, the auto-learn start control register defaults to a wait state when powered on.
Example four
Based on the current curve mode automatic learning system of the voice coil motor driver of the first, second or third embodiment,
the automatic learning system of the current curve mode of the voice coil motor driver also comprises a memory module;
the memory module is used for storing learning experience data of a current curve;
and if the displacement stabilization time sent by the displacement amplitude detection module is shorter than the register time in the fastest stabilization time register, the automatic learning algorithm module updates the register value in the fastest stabilization time register to the displacement stabilization time, writes the curve serial number m of the current curve m output by the current curve generation module at this time into the fastest stabilization curve serial number register, and writes the learning experience data of the curve serial number m into a memory.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (9)
1. A voice coil motor driver current curve mode automatic learning system is characterized by comprising a parameter control register module, an automatic learning algorithm module, a current curve generation module and a displacement amplitude detection module;
the parameter control register module is used for receiving an external operation instruction and performing read-write operation on the parameter register;
the parameter registers comprise an automatic learning starting control register, a fastest stable time register and a fastest stable curve sequence number register;
the parameter control register module receives an external write operation instruction and sets the automatic learning starting control register to be in a starting state or a waiting state;
the fastest stabilization time register is used for registering the fastest displacement stabilization time, and the initial register value of the fastest stabilization time register is the maximum value;
the fastest stable curve serial number register is used for registering a curve serial number m;
the current curve generation module generates a current curve m corresponding to the curve serial number m according to the section number corresponding to the curve serial number m, the selected step length of each section, the selected step pitch of each section and the curve type after receiving the curve starting signal, and controls the voice coil motor driver to work according to the current curve m;
the displacement amplitude detection module detects a displacement amplitude signal of the voice coil motor driver after receiving the curve starting signal, starts timing by using a clock signal, stops timing if the amplitude of the displacement amplitude signal is smaller than a set value, and sends the displacement stabilization time to the automatic learning algorithm module by using a timing value after the timing is started as the displacement stabilization time;
when the state of the automatic learning starting control register is a starting state, the automatic learning algorithm module enters a one-time self-learning process of one type of current curve, and the process is as follows:
setting one type of current curve as N sections, and setting step length and step pitch in each section, wherein the step length in each section can be selected between the minimum step length and the maximum step length, and the step pitch in each section can be selected between the minimum step length and the maximum step pitch; different segment numbers, different step lengths selected by the segments and combinations of different step distances selected by the segments correspond to different curve serial numbers m;
outputting a segment number corresponding to a curve serial number m, a step length selected by each segment, a step distance selected by each segment and the type of a current curve to a current curve generation module, and outputting a curve starting signal to the current curve generation module and the displacement amplitude detection module;
if the displacement stabilization time sent by the displacement amplitude detection module is shorter than the register time in the fastest stabilization time register, updating the register value in the fastest stabilization time register to be the displacement stabilization time, writing the curve serial number m of the current curve m output by the current curve generation module at this time into the fastest stabilization curve serial number register, and writing the learning experience data of the curve serial number m into a memory;
the automatic learning algorithm module sequentially outputs segment numbers corresponding to all curve serial numbers m, selected step lengths of all the segments and selected step distances of all the segments of a type of current curve to the current curve generation module, after the current curve generation module generates the current curve m corresponding to all the curve serial numbers m, the register time in the fastest stable time register is the fastest displacement stable time of the type of current curve, and the curve serial number m registered in the fastest stable curve serial number register is the optimal curve serial number of the type of current curve.
2. The voice coil motor driver current profile mode auto-learning system of claim 1,
the learning experience data comprises curve segmentation number, step size and step distance.
3. The voice coil motor driver current profile mode auto-learning system of claim 1,
the parameter register also comprises a curve learning result register;
the curve learning result register is used for registering the optimal curve serial number, learning experience data and the fastest displacement stabilization time after the automatic learning algorithm module completes the self-learning process on one type of current curve;
and the automatic learning algorithm module is used for registering the optimal curve serial number and the corresponding learning experience data and the fastest displacement stabilization time to the curve learning result register.
4. The voice coil motor driver current profile mode auto-learning system of claim 3,
and the parameter control register module is used for receiving an external operation instruction and reading out the optimal curve serial number, learning experience data and the fastest displacement stabilization time of one type of current curve from the curve learning result register.
5. The system of claim 4, wherein the voice coil motor driver current profile mode auto-learning system,
the parameter register also comprises a curve initial value register and a curve target value register;
the curve initial value register is used for registering an initial current value of the current curve, the initial current value is defaulted to 0 when being electrified, and after the parameter control register module receives an execution completion signal generated by the current curve, the initial current value is replaced by a value of the curve target value register;
the curve target value register is used for registering a target current value of the current curve, the target current value is defaulted to 0 when electrified, and the parameter control register module receives an external write operation instruction and writes the target current value into the curve target value register.
6. The system of claim 5, wherein the voice coil motor driver current profile mode auto-learning system,
and the current curve generation module generates a current curve m corresponding to the curve serial number m according to the section number corresponding to the curve serial number m, the selected step length of each section, the selected step pitch of each section, the curve type, the initial current value and the target current value after receiving the curve starting signal, and controls the voice coil motor driver to work according to the current curve m.
7. The voice coil motor driver current profile mode auto-learning system of claim 1,
the external operation instruction cannot write to the curve initial value register and can only read.
8. The voice coil motor driver current profile mode auto-learning system of claim 1,
the automatic learning starts the control register, and the default is a waiting state when the power is on.
9. The voice coil motor driver current profile mode automatic learning system of any one of claims 1 to 6,
the automatic learning system of the current curve mode of the voice coil motor driver also comprises a memory module;
the memory module is used for storing learning experience data of a current curve;
and if the displacement stabilization time sent by the displacement amplitude detection module is shorter than the register time in the fastest stabilization time register, the automatic learning algorithm module updates the register value in the fastest stabilization time register to the displacement stabilization time, writes the curve serial number m of the current curve m output by the current curve generation module at this time into the fastest stabilization curve serial number register, and writes the learning experience data of the curve serial number m into a memory.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911408001.9A CN111082732B (en) | 2019-12-31 | 2019-12-31 | Automatic learning system for current curve mode of voice coil motor driver |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911408001.9A CN111082732B (en) | 2019-12-31 | 2019-12-31 | Automatic learning system for current curve mode of voice coil motor driver |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111082732A CN111082732A (en) | 2020-04-28 |
| CN111082732B true CN111082732B (en) | 2021-07-23 |
Family
ID=70320438
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911408001.9A Active CN111082732B (en) | 2019-12-31 | 2019-12-31 | Automatic learning system for current curve mode of voice coil motor driver |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111082732B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08123552A (en) * | 1994-10-21 | 1996-05-17 | Fujitsu Ltd | Motor control method with learning function |
| CN103795320A (en) * | 2014-03-10 | 2014-05-14 | 绍兴光大芯业微电子有限公司 | Voice coil motor driving method for achieving quick focusing |
| CN104270046A (en) * | 2014-09-26 | 2015-01-07 | 嘉善博工数控科技有限公司 | Motor control method based on self-learning of rotating speed-current two-dimensional fuzzy model |
| CN104343627A (en) * | 2013-07-23 | 2015-02-11 | 山东建筑大学 | Control method and device of maximum wind energy capture in off-grid wind power generation |
| CN105787563A (en) * | 2014-12-18 | 2016-07-20 | 中国科学院沈阳自动化研究所 | Self-learning mechanism-base fast matching fuzzy reasoning method |
| CN108512474A (en) * | 2018-02-09 | 2018-09-07 | 旋智电子科技（上海）有限公司 | Current of electric method of adjustment and current of electric adjusting apparatus |
-
2019
- 2019-12-31 CN CN201911408001.9A patent/CN111082732B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH08123552A (en) * | 1994-10-21 | 1996-05-17 | Fujitsu Ltd | Motor control method with learning function |
| CN104343627A (en) * | 2013-07-23 | 2015-02-11 | 山东建筑大学 | Control method and device of maximum wind energy capture in off-grid wind power generation |
| CN103795320A (en) * | 2014-03-10 | 2014-05-14 | 绍兴光大芯业微电子有限公司 | Voice coil motor driving method for achieving quick focusing |
| CN104270046A (en) * | 2014-09-26 | 2015-01-07 | 嘉善博工数控科技有限公司 | Motor control method based on self-learning of rotating speed-current two-dimensional fuzzy model |
| CN105787563A (en) * | 2014-12-18 | 2016-07-20 | 中国科学院沈阳自动化研究所 | Self-learning mechanism-base fast matching fuzzy reasoning method |
| CN108512474A (en) * | 2018-02-09 | 2018-09-07 | 旋智电子科技（上海）有限公司 | Current of electric method of adjustment and current of electric adjusting apparatus |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111082732A (en) | 2020-04-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8222841B2 (en) | VCM control circuit | |
| CN102904512A (en) | Control system and control method for step motor | |
| CN111082732B (en) | Automatic learning system for current curve mode of voice coil motor driver | |
| US6476576B2 (en) | Motor control apparatus | |
| JP4665507B2 (en) | Pen recorder | |
| JP5345248B2 (en) | Motor driver control device | |
| JP4760210B2 (en) | Driving apparatus and driving method for winding switching linear motor | |
| CN111050065B (en) | Lens driving device, lens driving method, and storage medium | |
| JP2018166387A (en) | Motor control device and control method of stepping motor | |
| US7791306B2 (en) | Apparatus, method, and system for controlling stepping motor | |
| CN111082715B (en) | Voice coil motor driver drive current segmentation control circuit | |
| KR100761689B1 (en) | Torque limited motor controll methode & motor controller | |
| US7342377B2 (en) | Stepping-motor control apparatus and method of controlling the apparatus | |
| EP1752977A1 (en) | Optical disk device | |
| JP2011221596A (en) | Positioning device and positioning method for positioning stage | |
| US11988952B2 (en) | Lens driving devices and driving methods thereof | |
| JP4340080B2 (en) | Camera moving device | |
| JP2023034841A (en) | Origin setting device and origin setting method | |
| US10372094B2 (en) | Motor control device and game machine | |
| JPH06197576A (en) | Motor controller | |
| JP2020101664A (en) | Drive device and control method for the same | |
| JP2012053762A (en) | Data input/output control device | |
| JPH0876849A (en) | Positioning controller | |
| CN118337093A (en) | Driving circuit, system and method for resonance device | |
| JP2000166298A (en) | Motor drive control method and device |
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 | ||
| CB02 | Change of applicant information |
Address after: Room 504, 560 shengxia Road, Pudong New Area, Shanghai, 201210 Applicant after: Praran semiconductor (Shanghai) Co.,Ltd. Address before: 201210, room 560, 503, midsummer Road, Shanghai, Pudong New Area Applicant before: PUYA SEMICONDUCTOR (SHANGHAI) Co.,Ltd. |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |