CN104950683A - Self-adaptive gap inverse model generating device for visual servo manipulator system - Google Patents
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Abstract
The invention discloses a self-adaptive gap inverse model generating device for a visual servo manipulator system. In the visual servo manipulator system, a self-adaptive module adjusts estimated gap parameters online as per a self-adaptive law and then transmits data to a gap inverse model module to change parameters of an inverse model, so that a smooth nonlinear gap inverse model is constructed to eliminate nonlinear gap constraints; the visual servo manipulator control system comprises a visual servo controller, a motion control module, a driving module, a six-degree-of-freedom manipulator, a detection module, a torque feedback module, a speed acquisition module, a position acquisition module and a visual module; through data transmission among all the modules, a closed-loop control system is formed in the visual servo manipulator control system. By the aid of the device, effects caused by the nonlinear gap constraints are effectively eliminated, so that the higher image tracking accuracy is realized.
Description
Technical field
The present invention relates to a kind of self-adaptation gap inversion model generating means of visual servo mechanical arm system, particularly visual servo mechanical arm system renovation technique on the input signals.
Background technology
Robot is the interdisciplinary study grown up in recent decades.It has concentrated the multi-disciplinary latest scientific research such as mechanical engineering, electronic engineering, computer engineering, automatic control engineering and artificial intelligence, and representing the most overachievement of electromechanical integration, is one of most active field of current development in science and technology.
The sixties in 20th century, due to the development of robot and computer technology, people begin one's study and have the robot of visual performance.But in these researchs, the action of robotic vision and robot, says it is open loop on strict.Robotic vision system is by image procossing, and obtain object pose, then according to object pose, calculate the pose of machine movement, in whole process, vision system " provides " information once, then just not participation process.In 1973, there is people that vision system is applied to robot control system, in this period, this process is called visual feedback.Until 1979, concept that hill and park proposes " visual servo ".Be common in the research of Robotics aspect." servo " one etymology in the meaning of Greek " slave ".People want " servo control mechanism " when individual handy apparatchik, obey the requirement of control signal and action.Before signal is come, stationary rotor is motionless; After signal is come, rotor rotates immediately; When signal disappears, rotor can stall voluntarily immediately.Due to its " servo " performance, therefore gain the name---servo-drive system.Visual servo, generally refer to, automatically receive by the device of optics and non-contacting sensor and process the image of a real-world object, by the information of image feedback, allowing machine system do machine and control further or the behavior of corresponding self-adaptative adjustment.Clearly, the implication of visual feedback just extracts feedback signal from visual information, visual servo is then include from visual signal process, to the overall process of robot controlling, so visual servo more fully can reflect the relevant research contents of robot vision and control than visual feedback.
Since 80 years 20th century, along with the development of computer technology and picture pick-up device, the technical matters of Visual Servoing System has attracted the attention of numerous researchist.In the past few years, Robot Visual Servoing all has made great progress in theory or in application aspect.In many academic conferences, visual servo technology is often classified as a special topic of meeting.Visual servo oneself develop into gradually and to control and an independent technique of the technical field such as image procossing across robot, automatically.
Robot serve control system's research of view-based access control model is a focus of all kinds of Research on Intelligent Robots always, but due to the complicacy of practical problems, Visual servoing control algorithm needs to be studied further, still there is the practical problemss such as Vision information processing bottleneck, narrow application range, system cost costliness in specific implementation process.In visual servo mechanical arm control system, all need to demarcate camera, but camera calibration is a loaded down with trivial details and inefficient job; Meanwhile, view-based access control model servo mechanical arm control system is the complication system of a non-linear strong coupling, and the impact of common non-linear factor all can make the motion of system change, such as backlash characteristics; The existence in gap, is equivalent to the impact in dead band, reduces the tracking accuracy of system.Because gap is non-uniform function, for identical input value x (t), the value exporting y (t) also depends on
symbol, the motion change thus by its load system affected is violent.For nonlinear system, due to driving wheel turn to time, need the backlash crossing twice, do not drive load therebetween, thus cause energy accumulation.When driving wheel cross backlash again drive load time, the release of accumulation energy will make load movement change aggravation.Its excesssive gap, then accumulation of energy is too much, and system will be caused from shake, and therefore, backlash characteristics has a strong impact on the performance of system.
Summary of the invention
The object of the invention is to the self-adaptation gap inversion model generating means of a kind of visual servo mechanical arm system proposed by backlash nonlinearity effect of constraint value on the input signals by the control system of visual servo mechanical arm.
Technical scheme of the present invention is: the self-adaptation gap inversion model generating means of visual servo mechanical arm system, includes Visual servoing control device, motion-control module, driver module, sixdegree-of-freedom simulation, detection module, torque-feedback module, speed acquisition module, station acquisition module and vision module, Visual servoing control device is made up of control signal generating unit, self-adaptation gap inversion model generating means, self-adaptation camera calibration device, communication unit, computer control unit, its feature is: the error signal of the image path formation of the real image track that Visual servoing control device reception graphics processing unit obtains and expectation, the torque signals of torque-feedback module acquires, the rate signal of speed acquisition module acquires, the position signalling of station acquisition module acquires, by the computing of Computing control module, message exchange is carried out by the communication unit between Visual servoing control device and vision module, by self-adaptation camera calibration device on-line proving camera, gap is built inverse and act on control signal by self-adaptation gap inversion model generating means, transmitted control signal to motion-control module by control signal generating unit, motion-control module modulation (PWM) ripple moves in driver module drive motor transmission sixdegree-of-freedom simulation, detected current of electric, speed and the positional information in driver module by detection module, and feed back to motion-control module and realize closed-loop control, vision module gathers the image coordinate of sixdegree-of-freedom simulation End features point and the input of feeding back in controller, forms the closed-loop control of the Visual servoing control system of band gap non-linear constrain.
The visual servo mechanical arm system of above-mentioned a kind of band gap non-linear constrain, is characterized in that: device comprises gap inversion model module, adaptation module, computing module; Gap comprises the parameter storage, amplifying circuit, Piezoelectric Driving, logical circuit, the circuit for generating that carry out information transmission with communication unit against module; Adaptation module comprises adaptive law storer, gap parameter adjustment storer, gap parameter initial value memory; Computing module comprises operand store, integration module, differential module, plus and minus calculation module, multiplication and division computing module and operand store.
The visual servo mechanical arm system of above-mentioned a kind of band gap non-linear constrain, it is characterized in that: the motor output torque in driver module, through torque-feedback module with by drive manipulator motion, then torque-feedback module, speed acquisition module, station acquisition module respectively by the information feed back that collects in Computing control module, through the reverse action of self-adaptation gap inversion model generating means, be delivered in motion-control module and driver module via control signal generating unit again, by the reverse action of self-adaptation gap inversion model generating means, thus eliminate the impact of gap constraint, the image trace precision of raising system.
The visual servo mechanical arm system of above-mentioned a kind of band gap non-linear constrain, the level and smooth inversion model being used for offsetting gap constraint can be expressed as follows:
τ in formula
+(t) and τ
-the input and output of inversion model,
input torque τ
+the derivative of (t).Wherein
l is a constant determined.About
,
there is following character:
1) to arbitrarily
2) to arbitrarily
with
3)
with
all continuous and can be micro-.
4) when
time,
; When
time,
When
time,
; When
time,
The visual servo mechanical arm system of above-mentioned a kind of band gap non-linear constrain, the parameter due to gap former is all that hypothesis is unknown, so c, B
r, B
lvalue be also all unknown.In order to the inversion model of estimation can be distinguished in smoothing model, therefore the output of Unknown Model and input table are shown as τ
-with
; Therefore, τ
-can design and become:
Wherein
c, cB respectively
r, cB
lprecompensation parameter vector, therefore above formula can be converted into following form:
The visual servo mechanical arm system of above-mentioned a kind of band gap non-linear constrain, is characterized in that: the adaptive law storer in adaptation module stores the programming code of adaptive law, can be expressed as by mathematical form:
Wherein
for the precompensation parameter vector of gap inversion model
derivative, and
, r
ithe positive definite symmetric matrices of a 3x3,
it is a sharing rate value.Parameter adjusts memory transfer in adaptive law storer by parameter storage by gap parameter; At the system cloud gray model initial stage, by gap parameter initial value memory by initial information transfer in operand store; After system cloud gray model, the data will being carried out calculating by adaptive law storer and gap parameter adjustment storer are delivered in operand store.
The visual servo mechanical arm system of above-mentioned a kind of band gap non-linear constrain, it is characterized in that: detection module realizes detecting and provides the close-loop feedback signal of Three-loop control, comprises QEP circuit and frequency measurement circuit, photoelectric encoder, A/D converter, current sensor; The pulse signal transmission that photoelectric encoder on machine shaft exports is to QEP circuit and frequency measurement circuit, pulse signal obtains position feed back signal through QEP processing of circuit, and the position control ring sent in motion-control module, pulse signal is through frequency measurement circuit process, obtain feedback speed signal, and the rate control module sent in motion-control module, current sensor detects machine winding current, and obtain its digital current signal by A/D converter, then sent to the current regulator in motion-control module.
The visual servo mechanical arm system of above-mentioned a kind of band gap non-linear constrain, it is characterized in that: the unique point that sixdegree-of-freedom simulation multiplely can be taken by camera unit at end mark, graphics processing unit detects, the image coordinate of this unique point is obtained by vision module.
The visual servo mechanical arm structure that the present invention adopts trick to be separated, namely camera is arranged on the fixed position being convenient to observe mechanical arm tail end unique point, by image path image transfer being extracted unique point to graphics processing unit of taking pictures.Fully take into account the problem of camera in addition, by self-adaptation camera calibration device online Prediction vision mode, decrease the complicated workload that calibration for cameras produces.Simultaneously the present invention also fully take into account mechanical arm system when face lose non-linear constrain input, utilize self-adaptation gap inversion model generating means to eliminate backlash nonlinearity constraint, the adaptive law taked effectively can set up corresponding gap inversion model.Experiment proves that this method reaches good effect, and the present invention is a kind of function admirable, is easy to the self-adaptation gap inversion model generating means built on the computer systems.
Accompanying drawing explanation
The general frame of the visual servo mechanical arm system of Fig. 1 band gap non-linear constrain;
Fig. 2 self-adaptation gap inversion model generating means schematic diagram;
Fig. 3 trick is separated visual servo physical arrangement schematic diagram;
The inverse gap former that Fig. 4 builds and the backlash nonlinearity schematic diagram that input torque passes through;
The control block diagram of Fig. 5 visual servo mechanical arm control system.
Embodiment
The present invention relates to a kind of gap inversion model generating means of visual servo mechanical arm control system, utilize the model parameter of the adaptive law online Prediction backlash nonlinearity constraint of design, and then build corresponding gap inversion model, effectively can eliminate the Visual servoing control mechanical arm under input signal constraint, make its End features point on the image plane progressive tracking expect image path, reach higher image trace precision.Below in conjunction with accompanying drawing and instantiation, the gap inversion model generating means to the visual servo mechanical arm control system designed by the present invention is described in detail.
Fig. 1 is the visual servo mechanical arm system the general frame of band gap non-linear constrain.The object designing Visual servoing control device is in FIG: when camera be demarcate and mechanical arm input torque by non-linear constrain, the motion of controller mechanical arm enables the desired image track of the unique point projection tracing preset on the image plane on mechanical arm tail end.Visual servoing control device 1 receives real image track that graphics processing unit 93 obtains and desired image track forms speed error signal, the position signalling gathered by station acquisition module 8, the rate signal gathered by speed acquisition module 7, the torque signals gathered by torque-feedback module 6, by computer control unit 15 computing, by the communication unit 91 between Visual servoing control device 1 and vision module 9, 11 carry out message exchange, then by self-adaptation camera calibration device 12 on-line proving camera, gap is built inverse and act on control signal generating unit 14 by self-adaptation gap inversion model generating means 13, transmit control signal to motion-control module 2 by control signal generating unit 14, wherein motion-control module 2 modulation (PWM) ripple moves in driver module 3 drive motor 33 transmission sixdegree-of-freedom simulation 4, last electric current, speed, the positional information detected by detection module 5 in driver module 3, and feed back to motion-control module 2 and realize closed-loop control, the image coordinate of vision module 9 harvester mechanical arm End features point also feeds back to the input of controller, form the closed-loop control of the Visual servoing control system of band gap non-linear constrain, controller can according to image feedback, and velocity feedback adjusts controller in time and exports the image trace performance providing the best.
Fig. 2 is self-adaptation gap inversion model generating means theory diagram.Can as seen from Figure 1, Fig. 2 is a part for Visual servoing control device, and the effect of this device is that structure one can the gap inversion model of on-line tuning, is used for eliminating the impact of unbalanced input, to greatest extent also intrinsic input torque.Gap inversion model module is according to the precompensation parameter vector obtained
build gap inversion model, the adaptive law designed is delivered in operation control module and calculates, according to adaptive law by adaptation module:
Obtain parameter vector
, continuous corrected parameter vector in the operational process of system
value, the disturbance making the input torque of design can offset non-linear input to greatest extent to bring.
Fig. 3 is that the trick that adopts of the present invention is separated visual servo physical arrangement schematic diagram, and camera is arranged on the fixed position that is convenient to observe mechanical arm tail end unique point, and camera and mechanical arm to be connected with computing machine by bus and to carry out message exchange.With camera is arranged on compared with mechanical arm tail end, the structure adopting eye hand to be separated effectively can reduce the camera shake because manipulator motion causes, and can clearly observe mechanical arm global motion, obtain the global information of unique point, by the motion control unit then controlled motion control module of computing machine, make manipulator motion.
Fig. 4 is that analog input moment is by the schematic diagram again by gap constraint after the inversion model of gap.Backlash nonlinearity can be described as:
In the description herein, τ
-t () is the input of backlash nonlinearity.τ
+t () exports, τ
+(t
-) be the initial value exported.Slope c is a permanent normal amount.B
rand B
lmeet B
r> 0, B
l< 0.
In order to offset the impact that gap constraint brings, we design a level and smooth inversion model, as follows:
τ in formula
+(t) and τ
-the input and output of inversion model,
input torque τ
+the derivative of (t).Wherein
, l is a constant determined.About
there is following character:
1) to arbitrarily
2) to arbitrarily
with
3)
with
all continuous and can be micro-.
4) when
time,
; When
time,
When
time,
; When
time,
Be used for offsetting the inversion model of gap constraint, the parameter due to gap former is all that hypothesis is unknown, so c, B
r, B
lvalue be also all unknown.In order to the inversion model of estimation can be distinguished in smoothing model, therefore the input and output of unknown inversion model are expressed as
and τ
-.Therefore, τ
-can design and become:
Wherein
c, cB respectively
r, cB
lprecompensation parameter vector.So driving moment is designed to as follows:
In order to set up gap inversion model, we must obtain unknown parameter
value, therefore, we design the adaptive law estimating unknown gap parameter as follows:
Wherein
for the precompensation parameter vector of gap inversion model
derivative, and
, r
ithe positive definite symmetric matrices of a 3x3,
it is a sharing rate value.Can be transferred data in operation control module by adaptive law and calculate, obtain
value, then go out gap inversion model by gap inversion model module construction.
So far, we have completed the structure of gap inversion model, and the several steps described in Fig. 4 complete in the inversion model generating means of self-adaptation gap, by the message exchange between each module, eliminate the impact that backlash nonlinearity is brought.
Fig. 5 is the control block diagram of visual servo mechanical arm control system, and this control block diagram is exactly the embodiment of principle installation drawing on controlling of Fig. 1.
Claims (8)
1. a visual servo mechanical arm system for band gap non-linear constrain, comprises Visual servoing control device (1), motion-control module (2), driver module (3), sixdegree-of-freedom simulation (4), detection module (5), torque-feedback module (6), speed acquisition module (7), station acquisition module (8) and vision module (9), Visual servoing control device (1) is made up of control signal generating unit (14), self-adaptation gap inversion model generating means (13), self-adaptation camera calibration device (12), communication unit (11), computer control unit (15), it is characterized in that: the error signal that the real image track obtained by Visual servoing control device (1) reception graphics processing unit (93) and the image path of expectation are formed, the torque signals that torque-feedback module (6) gathers, the rate signal that speed acquisition module (7) gathers, the position signalling that station acquisition module (8) gathers, by Computing control module (15) computing, by the communication unit (11) between Visual servoing control device (1) and vision module (9), (91) message exchange is carried out, by self-adaptation camera calibration device (12) on-line proving camera, gap is built inverse and act on control signal by self-adaptation gap inversion model generating means (13), transmitted control signal to motion-control module (2) by control signal generating unit (14), motion-control module (2) modulation (PWM) ripple moves in driver module (3) drive motor transmission sixdegree-of-freedom simulation (4), detect current of electric, speed and the positional information in driver module (3) by detection module (5), and feed back to motion-control module (2) and realize closed-loop control, vision module (9) gathers the image coordinate of sixdegree-of-freedom simulation (4) End features point and the input of feeding back in controller, forms the closed-loop control of the Visual servoing control system of band gap non-linear constrain.
2. the visual servo mechanical arm system of a kind of band gap non-linear constrain according to claim 1, is characterized in that: device comprises gap inversion model module (131), adaptation module (132), computing module (133); Gap comprises the parameter storage (1311), amplifying circuit (1312), Piezoelectric Driving (1313), logical circuit (1314), the circuit for generating (1315) that carry out information transmission with communication unit (11) against module (131); Adaptation module (132) comprises adaptive law storer (1321), gap parameter adjustment storer (1322), gap parameter initial value memory (1323); Computing module (133) comprises operand store (1331), integration module (1332), differential module (1333), plus and minus calculation module (1334), multiplication and division computing module (1335) and operand store (1336).
3. the visual servo mechanical arm system of a kind of band gap non-linear constrain according to claim 1, it is characterized in that: motor (33) output torque in driver module (3), through torque-feedback module (6) with by gearing (34) driver mechanical arm (4) motion, then torque-feedback module (6), speed acquisition module (7), station acquisition module (8) respectively by the information feed back that collects in Computing control module (15), through the reverse action in self-adaptation gap inversion model generating means (13), be delivered in motion-control module (2) and driver module (3) via control signal generating unit (14) again, by the reverse action in self-adaptation gap inversion model generating means (13), thus eliminate the impact of gap constraint (32), the image trace precision of raising system.
4. the visual servo mechanical arm system of a kind of band gap non-linear constrain according to claim 3, the level and smooth inversion model being used for offsetting gap constraint can be expressed as follows:
τ in formula
+(t) and τ
-the input and output of inversion model,
input torque τ
+the derivative of (t); Wherein
l is a constant determined; About
there is following character:
1) to arbitrary t>=0,
2) to arbitrary t>=0,
with
3)
with
all continuous and can be micro-;
4) when
during →-∞,
when
during → ∞,
When
during →-∞,
when
during → ∞,
5. the visual servo mechanical arm system of a kind of band gap non-linear constrain according to claim 4, the parameter due to gap former is all that hypothesis is unknown, so c, B
r, B
lvalue be also all unknown; In order to the inversion model of estimation can be distinguished in smoothing model, therefore the output of Unknown Model and input table are shown as τ
-with
therefore, τ
-can design and become:
Wherein
c, cB respectively
r, cB
lprecompensation parameter vector, so above formula can abbreviation be following form:
6. the visual servo mechanical arm system of a kind of band gap non-linear constrain according to claim 1, it is characterized in that: the adaptive law storer (1321) in adaptation module (132) stores the programming code of adaptive law, can be expressed as by mathematical form:
Wherein
for the precompensation parameter vector of gap inversion model
derivative, and
r
ithe positive definite symmetric matrices of a 3x3,
it is a sharing rate value.Aforesaid parameter adjusts storer (1322) by parameter storage (1311) by gap parameter and is delivered in adaptive law storer (1321); At the system cloud gray model initial stage, by gap parameter initial value memory (1323) by initial information transfer in operand store (1331); After system cloud gray model, the data will carrying out calculating by adaptive law storer (1321) and gap parameter adjustment storer (1322) are delivered in operand store (1331).
7. the visual servo mechanical arm system of a kind of band gap non-linear constrain according to claim 1, it is characterized in that: detection module (5) realizes detecting and provides the close-loop feedback signal of Three-loop control, comprises QEP circuit (51) and frequency measurement circuit (52), photoelectric encoder (53), A/D converter (54), current sensor (55), the pulse signal transmission that photoelectric encoder (53) on machine shaft exports is to QEP circuit (51) and frequency measurement circuit (52), pulse signal obtains position feed back signal through QEP circuit (51) process, and the position control ring (21) sent in motion-control module (2), pulse signal is through frequency measurement circuit process, obtain feedback speed signal, and the rate control module (22) sent in motion-control module (2), current sensor (55) detects machine winding current, and obtain its digital current signal by A/D converter (54), sent to the current regulator (23) in motion-control module (2) again.
8. the visual servo mechanical arm system of a kind of band gap non-linear constrain according to claim 1, it is characterized in that: the unique point that sixdegree-of-freedom simulation (4) multiplely can be taken by camera unit (94) at end mark, graphics processing unit (93) detects, the image coordinate of this unique point is obtained by vision module (9).
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105643607A (en) * | 2016-04-08 | 2016-06-08 | 深圳市中科智敏机器人科技有限公司 | Intelligent industrial robot with sensing and cognitive abilities |
| CN106054618A (en) * | 2016-08-20 | 2016-10-26 | 南京理工大学 | Motor servo system self-adaptive robustness control method including input interval |
| CN112904793A (en) * | 2021-03-25 | 2021-06-04 | 上海相石智能科技有限公司 | Intelligent servo system integrating PLC (programmable logic controller) and vision or force feedback |
| CN112904794A (en) * | 2021-03-25 | 2021-06-04 | 上海相石智能科技有限公司 | Integrated PLC, vision or force feedback integrated actuating mechanism |
| CN113625555A (en) * | 2021-06-30 | 2021-11-09 | 佛山科学技术学院 | Adaptive inverse control AGV rotation speed control method based on recursive subspace identification |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH01217601A (en) * | 1988-02-26 | 1989-08-31 | Ricoh Res Inst Of Gen Electron | Servo controller |
| US5483439A (en) * | 1992-10-06 | 1996-01-09 | International Business Machines Corporation | Digital servo control system |
| CN102540896A (en) * | 2012-02-29 | 2012-07-04 | 清华大学 | Nonlinear fuzzy combination and recursive control system for chemically and mechanically polishing transmission robot |
| CN104476544A (en) * | 2014-10-23 | 2015-04-01 | 广东工业大学 | Self-adaptive dead zone inverse model generating device of visual servo mechanical arm system |
-
2015
- 2015-06-23 CN CN201510372263.XA patent/CN104950683A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH01217601A (en) * | 1988-02-26 | 1989-08-31 | Ricoh Res Inst Of Gen Electron | Servo controller |
| US5483439A (en) * | 1992-10-06 | 1996-01-09 | International Business Machines Corporation | Digital servo control system |
| CN102540896A (en) * | 2012-02-29 | 2012-07-04 | 清华大学 | Nonlinear fuzzy combination and recursive control system for chemically and mechanically polishing transmission robot |
| CN104476544A (en) * | 2014-10-23 | 2015-04-01 | 广东工业大学 | Self-adaptive dead zone inverse model generating device of visual servo mechanical arm system |
Non-Patent Citations (2)
| Title |
|---|
| ZHI LIU,ETC.: "Decentralized Robust Fuzzy Adaptive Control of Humanoid Robot Manipulation With Unknown Actuator Backlash", 《IEEE TRANSACTIONS ON FUZZY SYSTEMS》 * |
| 章逸丰等: "兵乓球机器人的视觉伺服系统", 《中国科学》 * |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105643607A (en) * | 2016-04-08 | 2016-06-08 | 深圳市中科智敏机器人科技有限公司 | Intelligent industrial robot with sensing and cognitive abilities |
| CN106054618A (en) * | 2016-08-20 | 2016-10-26 | 南京理工大学 | Motor servo system self-adaptive robustness control method including input interval |
| CN106054618B (en) * | 2016-08-20 | 2019-03-05 | 南京理工大学 | The motor servo system adaptive robust control method in the gap containing input |
| CN112904793A (en) * | 2021-03-25 | 2021-06-04 | 上海相石智能科技有限公司 | Intelligent servo system integrating PLC (programmable logic controller) and vision or force feedback |
| CN112904794A (en) * | 2021-03-25 | 2021-06-04 | 上海相石智能科技有限公司 | Integrated PLC, vision or force feedback integrated actuating mechanism |
| CN113625555A (en) * | 2021-06-30 | 2021-11-09 | 佛山科学技术学院 | Adaptive inverse control AGV rotation speed control method based on recursive subspace identification |
| CN113625555B (en) * | 2021-06-30 | 2024-06-11 | 佛山科学技术学院 | Adaptive inverse control AGV (automatic guided vehicle) rotating speed control method based on recursive subspace identification |
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