CN108638064A - A kind of identification of Multi-arm robots auto-adaptive parameter and position synchronization control method based on mean value coupling - Google Patents
A kind of identification of Multi-arm robots auto-adaptive parameter and position synchronization control method based on mean value coupling Download PDFInfo
- Publication number
- CN108638064A CN108638064A CN201810460826.4A CN201810460826A CN108638064A CN 108638064 A CN108638064 A CN 108638064A CN 201810460826 A CN201810460826 A CN 201810460826A CN 108638064 A CN108638064 A CN 108638064A
- Authority
- CN
- China
- Prior art keywords
- formula
- mechanical arm
- matrix
- error
- parameter
- 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.)
- Granted
Links
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1602—Programme controls characterised by the control system, structure, architecture
- B25J9/1605—Simulation of manipulator lay-out, design, modelling of manipulator
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
- G06F17/12—Simultaneous equations, e.g. systems of linear equations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
Abstract
A kind of identification of Multi-arm robots auto-adaptive parameter and position synchronization control method based on mean value coupling, include the following steps：Step 1, Multi-arm robots model is established；Step 2, more mechanical arm tracking errors, synchronous error and mean value coupling error are defined；Step 3, design adaptive parameter estimation rule and controller.Parameter identification and synchronous control scheme designed by the present invention have good identification and control effect to Multi-arm robots, and Multi-arm robots is enable to realize that High Accuracy Parameter recognizes and has good tracking performance and net synchronization capability.
Description
Technical field
The present invention relates to a kind of more mechanical arm online adaptive parameter identifications and position synchronization control based on mean value coupling
Method.
Background technology
With the fast development of state-of-the-art technology and the continuous improvement of industrial automatization, Multi-arm robots are being played the part of
More and more important role.Compared to one-link robot system, Multi-arm robots have higher reliability, bigger it is flexible
Property and bearing capacity, while more complicated task can be completed.Since Multi-arm robots are easy to by external disturbance, friction etc.
Factor influences, high-precision control relative difficulty.Therefore, for how to improve the parameter identification and synchronous control performance of more mechanical arms
It is the research hotspot of existing Industry Control.
For the control system with unknown parameter or immeasurability parameter, auto-adaptive parameter identification is a kind of effectively
Method.Currently, most parameters identification uses off-line identification, this method can not timely response parameter variable condition,
And control performance may be influenced.It is therefore proposed that a kind of online adaptive identification system unknown parameter, and ginseng can be reacted in time
The method of number variation is very necessary.
For improving the synchronous control accuracy of more mechanical arms, multiple synchronization control strategy, such as deviation have been proposed at present
Coupling control, cross-coupling control, annular coupling control etc..If more mechanical arm net synchronization capability effects are poor, production can be influenced and appointed
Business, therefore select the ring that a kind of suitable Strategy For Synchronization Control is important in Multi-arm robots control.Meanwhile it being controlled synchronous
On the basis of system, a kind of suitable control algolithm is selected to improve control accuracy.In numerous control methods, sliding formwork control due to
Its is simple in structure, high reliability and be widely used.
Invention content
In order to overcome the shortcomings of that the parameter identification precision of existing Multi-arm robots is relatively low and synchronous control performance is poor, this
Invention provides a kind of more mechanical arm online adaptive Identification of parameter and synchronisation control means based on mean value coupling.This method
The parameter identification method based on parameter error information is devised, and devises the sliding formwork control recognized based on auto-adaptive parameter
Device ensures the high-precision control of Multi-arm robots.
In order to solve the above-mentioned technical problem the technical solution proposed is as follows：
A kind of more mechanical arm Adaptable System parameter identifications and position synchronization control method based on mean value coupling, the control
Method processed includes the following steps：
Step 1, more Manipulator Dynamics are established；
One more mechanical arm dynamic system model by the n joint m is expressed as form：
Wherein n is the quantity of mechanical arm, and m is the amount of articulation of each mechanical arm, The respectively joint Angular position vector of mechanical arm, velocity vector and acceleration
Spend vector, M (q)=diag ([M1(q) … Mn(q)] it is) the positive definite inertial matrix of mechanical arm,Indicate centrifugal force and coriolis force matrix,To act on the gravitational vectors on joint,For joint control
Input torque vector；
Step 2, it is as follows that more mechanical arm tracking errors, synchronous error and mean value coupling error, process are defined：
2.1, defining more mechanical arm tracking error e is：
E=qd-q (2)
Wherein,For joint turning error,For desired joint angle
Position vector；
2.2, defining more mechanical arm synchronous error ε is：
ε=Te (3)
Wherein
I is unit diagonal matrix；
2.3, defining more mechanical arm mean value coupling error E is：
E=e+ β ε=Ae (4)
WhereinA=I+ β T are coefficient of coup matrix, β=diag ([β1 … βn]) represent together
Coefficient is walked, and is positive definite matrix；
Step 3, design adaptive parameter estimation rule and controller, process are as follows：
3.1, designing sliding-mode surface is：
Whereinλ1The parameters in order to control of ＞ 0, companion matrixWith its differential formRepresentation
For：
3.2, define companion matrixRegression matrixIt is as follows：
WhereinIt is known regression matrix, θ is unknown parameter；
By formula (1), formula (5), formula (6) and formula (7) obtain：
Wherein
It is obtained by formula (7) and formula (8)：
3.3, by regression matrixCarry out following filtering operation：
WhereinAnd τfIt is respectivelyAnd τ
Filtered variable, k are adjustment parameters；
It is obtained by formula (9) and formula (10)：
WhereinForFiltered variable；
3.4, it is as follows to define two dynamical equations P and Q：
Wherein, l is adjustment parameter；P (0), Q (0) are the initial value of P and Q respectively；
It is obtained by formula (12)：
3.5, the information about parameter error is obtained by formula (11) and formula (13)：
Q=P θ (14)
WhereinFor the estimated value of θ,For evaluated error；
3.6, design adaptive parameter estimation, which is restrained, is：
Wherein Γ ＞ 0, κ ＞ 0 is adaptive gain matrix；
3.7, designing adaptive controller is：
Wherein K ＞ 0 device parameters in order to control；
3.8, designing liapunov function is：
V derivations are obtained：
Formula (8) and formula (16)-(17) are substituted into formula (19), obtainedWherein μ=min { 2 λmin(K)/λmax(M(I
+βT)-1),2κλmin(P)/λmax(Γ-1), λmax() and λmin() is the minimum and maximum characteristic value of homography, thus
Decision-making system is stable, and quantity of state is restrained.
The present invention is based on mean value coupling Strategy For Synchronization Control and parameter identification are theoretical, devise and a kind of coupled based on mean value
Multi-arm robots parameter identification and position synchronization control method, realize the identification of Multi-arm robots unknown parameter, synchronous
Control performance and Position Tracking Control.
The present invention technical concept be：For the Multi-arm robots with unknown parameter, the present invention passes through extracting parameter
Control information designs auto-adaptive parameter identification rule, and devises sliding mode controller based on auto-adaptive parameter identification, ensures multimachine
Tool arm system high-precision control.
Advantages of the present invention is：Ensure the net synchronization capability and tracking performance of Multi-arm robots, realizes to the online of parameter
Identification, realizes the convergence of Multi-arm robots.
Description of the drawings
Fig. 1 is the control flow chart of the present invention；
Fig. 2 is that reference locus is qdPursuit path design sketch when=0.5*sin (t)；
Fig. 3 is reference locus qdTracking error design sketch when=0.5*sin (t) is；
Fig. 4 is reference locus qdSynchronous error design sketch when=0.5*sin (t) is；
Fig. 5 is reference locus qdThe design sketch of Parameter identification joint quality when=0.5*sin (t) is；
Fig. 6 is reference locus qdThe design sketch of Parameter identification articulation inertia when=0.5*sin (t) is；
Fig. 7 is reference locus qdControl when=0.5*sin (t) is inputs τ design sketch.
Specific implementation mode
The present invention will be further described below in conjunction with the accompanying drawings.
- Fig. 7 referring to Fig.1, a kind of control synchronous with position of more mechanical arm Adaptable System parameter identifications based on mean value coupling
Method processed, the control method include the following steps：
Step 1, more Manipulator Dynamics are established；
One more mechanical arm dynamic system model by the n joint m is expressed as form：
Wherein n is the quantity of mechanical arm, and m is the amount of articulation of each mechanical arm, The respectively joint Angular position vector of mechanical arm, velocity vector and plus
Velocity vector, M (q)=diag ([M1(q) … Mn(q)] it is) the positive definite inertial matrix of mechanical arm,Indicate centrifugal force and coriolis force matrix,To act on the gravitational vectors on joint,For joint control
Input torque vector；
Step 2, it is as follows that more mechanical arm tracking errors, synchronous error and mean value coupling error, process are defined：
2.1, defining more mechanical arm tracking error e is：
E=qd-q (2)
Wherein,For joint turning error,For desired joint angle
Position vector；
2.2, defining more mechanical arm synchronous error ε is：
ε=Te (3)
Wherein
I is unit diagonal matrix；
2.3, defining more mechanical arm mean value coupling error E is：
E=e+ β ε=Ae (4)
WhereinA=I+ β T are coefficient of coup matrix, β=diag ([β1 … βn]) represent together
Coefficient is walked, and is positive definite matrix；
Step 3, design adaptive parameter estimation rule and controller, process are as follows：
3.1, designing sliding-mode surface is：
Whereinλ1The parameters in order to control of ＞ 0, companion matrixWith its differential formExpression shape
Formula is：
3.2, define companion matrixRegression matrixIt is as follows：
WhereinIt is known regression matrix, θ is unknown parameter；
By formula (1), formula (5), formula (6) and formula (7) obtain：
Wherein
It is obtained by formula (7) and formula (8)：
3.3, by regression matrixCarry out following filtering operation：
WhereinAnd τfIt is respectivelyAnd τ
Filtered variable, k are adjustment parameters；
It is obtained by formula (9) and formula (10)：
WhereinForFiltered variable；
3.4, it is as follows to define two dynamical equations P and Q：
Wherein, l is adjustment parameter；P (0), Q (0) are the initial value of P and Q respectively；
It is obtained by formula (12)：
3.5, the information about parameter error is obtained by formula (11) and formula (13)：
Q=P θ (14)
WhereinFor the estimated value of θ,For evaluated error；
3.6, design adaptive parameter estimation, which is restrained, is：
Wherein Γ ＞ 0, κ ＞ 0 is adaptive gain matrix；
3.7, designing adaptive controller is：
Wherein K ＞ 0 device parameters in order to control；
3.8, designing liapunov function is：
V derivations are obtained：
Formula (8) and formula (16)-(17) are substituted into formula (19), obtainedWherein μ=min { 2 λmin(K)/λmax(M(I+
βT)-1),2κλmin(P)/λmax(Γ-1), λmax() and λmin() is the minimum and maximum characteristic value of homography, is thus sentenced
It is stable to determine system, and quantity of state is restrained.
To verify the validity of Parameter identification and synchronisation control means, the present invention has carried out emulation experiment to it.If
Set experiment in primary condition and control parameter be：Systematic parameter r1=0.2, r2=0.3, m1=0.3, m2=0.5, g=
9.81 j1=0.05, j2=0.1；Identification and controller parameter k=0.001, l=1, β=0.8, λ1=diag ([3 3333
33 3]), ([3 333333 3]) K=diag, κ=1, Γ=diag ([1 1111111555555
5 5]), primary condition ΦRf(0)=0, ΦHf(0)=0, ΦFf(0)=0, τ (0)=0, P (0)=0, Q (0)=0, q (0)=
[0.1 0.25 0.1 0.2 0.1 0.25 0.1 0.2]T。
Fig. 2-Fig. 7 is the more mechanical arm auto-adaptive parameters identification coupled based on mean value and control simulated effect figure.Fig. 2, Fig. 3
Indicate that when reference locus be q respectively with Fig. 4dPursuit path, tracking error and synchronous error when=0.5*sin (t), from Fig. 3 and
The tracking error and synchronous error that mechanical arm 1- mechanical arms 4 are found out in Fig. 4 can reach very small range, this two width chart is bright
Higher tracking performance and net synchronization capability may be implemented in the method proposed.Fig. 5 and Fig. 6 indicates that when reference locus be qd=0.5*
Parameter identification result figure when sin (t).Fig. 5 is the joint quality identification result of mechanical arm 1- mechanical arms 4, and Fig. 6 is mechanical arm
The identification of rotational inertia of 1- mechanical arms 4 is as a result, as can be seen from the figure joint quality and rotary inertia can be converged to effectively very
Value.Fig. 7 indicates that when reference locus be qdSystem input when=0.5*sin (t), as can be seen from the figure almost without buffeting.
From the point of view of the result of emulation experiment, more mechanical arm parameter identifications and position synchronization control based on mean value coupling can realize multimachine
The High Accuracy Parameter of tool arm system recognizes, high performance Position Tracking Control and synchronous control.
Described above is emulation experiment of the present invention to show the validity of designed method, but the present invention is not limited to
Examples detailed above can to it under the premise of without departing from essence spirit of the present invention and without departing from range involved by substantive content of the present invention
Make various deformations to be implemented.Parameter identification and synchronous control scheme designed by the present invention have Multi-arm robots good
Identification and control effect, enable Multi-arm robots realize High Accuracy Parameter recognize and with good tracking performance and
Net synchronization capability.
Claims (1)
1. a kind of identification of Multi-arm robots auto-adaptive parameter and position synchronization control method, feature based on mean value coupling exist
In the control method includes the following steps：
Step 1, more Manipulator Dynamics are established；
One more mechanical arm dynamic system model by the n joint m is expressed as form：
Wherein n is the quantity of mechanical arm, and m is the amount of articulation of each mechanical arm, The respectively joint Angular position vector of mechanical arm, velocity vector and
Acceleration, M (q)=diag ([M1(q) … Mn(q)] it is) the positive definite inertial matrix of mechanical arm,Indicate centrifugal force and coriolis force matrix,To act on the gravitational vectors on joint,For joint control
Input torque vector；
Step 2, it is as follows that more mechanical arm tracking errors, synchronous error and mean value coupling error, process are defined：
2.1, defining more mechanical arm tracking error e is：
E=qd-q (2)
Wherein,For joint turning error,It is sweared for desired joint Angle Position
Amount；
2.2, defining more mechanical arm synchronous error ε is：
ε=Te (3)
Wherein
I is unit diagonal matrix；
2.3, defining more mechanical arm mean value coupling error E is：
E=e+ β ε=Ae (4)
WhereinA=I+ β T are coefficient of coup matrix, β=diag ([β1 … βn]) represent synchronous system
Number, and be positive definite matrix；
Step 3, design adaptive parameter estimation rule and controller, process are as follows：
3.1, designing sliding-mode surface is：
Whereinλ1The parameters in order to control of ＞ 0, companion matrixWith its differential formRepresentation be：
3.2, define companion matrixRegression matrixIt is as follows：
WhereinIt is known regression matrix, θ is unknown parameter；
By formula (1), formula (5), formula (6) and formula (7) obtain：
Wherein
It is obtained by formula (7) and formula (8)：
3.3, by regression matrixCarry out following filtering operation：
WhereinAnd τfIt is respectivelyIt is filtered with τ
Variable afterwards, k are adjustment parameters；
It is obtained by formula (9) and formula (10)：
WhereinForFiltered variable；
3.4, it is as follows to define two dynamical equations P and Q：
Wherein, l is adjustment parameter；P (0), Q (0) are the initial value of P and Q respectively；
It is obtained by formula (12)：
3.5, the information about parameter error is obtained by formula (11) and formula (13)：
Q=P θ (14)
WhereinFor the estimated value of θ,For evaluated error；
3.6, design adaptive parameter estimation, which is restrained, is：
Wherein Γ ＞ 0, κ ＞ 0 is adaptive gain matrix；
3.7, designing adaptive controller is：
Wherein K ＞ 0 device parameters in order to control；
3.8, designing liapunov function is：
V derivations are obtained：
Formula (8) and formula (16)-(17) are substituted into formula (19), obtainedWherein μ=min { 2 λmin(K)/λmax(M(I+βT
)-1),2κλmin(P)/λmax(Γ-1), λmax() and λmin() is the minimum and maximum characteristic value of homography, is thus judged
System is stable, and quantity of state is restrained.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810460826.4A CN108638064B (en) | 2018-05-15 | 2018-05-15 | Mean value coupling-based adaptive parameter identification and position synchronization control method for multi-mechanical arm system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810460826.4A CN108638064B (en) | 2018-05-15 | 2018-05-15 | Mean value coupling-based adaptive parameter identification and position synchronization control method for multi-mechanical arm system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108638064A true CN108638064A (en) | 2018-10-12 |
| CN108638064B CN108638064B (en) | 2020-10-27 |
Family
ID=63755565
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810460826.4A Active CN108638064B (en) | 2018-05-15 | 2018-05-15 | Mean value coupling-based adaptive parameter identification and position synchronization control method for multi-mechanical arm system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108638064B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110247585A (en) * | 2019-04-17 | 2019-09-17 | 湖南工业大学 | A kind of multiple-axis servo control with changed scale cooperative control method based on sliding moding structure |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104238580A (en) * | 2014-09-30 | 2014-12-24 | 中国航天空气动力技术研究院 | Low-altitude flight control method applied to airborne geophysical prospecting of unmanned aerial vehicle |
| CN107454866A (en) * | 2016-05-23 | 2017-12-08 | 达闼科技（北京）有限公司 | A kind of three-dimension modeling method and apparatus |
| CN107443382A (en) * | 2017-09-12 | 2017-12-08 | 清华大学 | Industrial robot structure parameter error recognizes and compensation method |
-
2018
- 2018-05-15 CN CN201810460826.4A patent/CN108638064B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104238580A (en) * | 2014-09-30 | 2014-12-24 | 中国航天空气动力技术研究院 | Low-altitude flight control method applied to airborne geophysical prospecting of unmanned aerial vehicle |
| CN107454866A (en) * | 2016-05-23 | 2017-12-08 | 达闼科技（北京）有限公司 | A kind of three-dimension modeling method and apparatus |
| CN107443382A (en) * | 2017-09-12 | 2017-12-08 | 清华大学 | Industrial robot structure parameter error recognizes and compensation method |
Non-Patent Citations (2)
| Title |
|---|
| MAOLIN JIN: "Practical Nonsingular Terminal Sliding-Mode Control of Robot Manipulators for High-Accuracy Tracking Control", 《IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS》 * |
| 张博: "空间机器人自主接管非合作目标的轨迹规划与控制研究", 《中国博士学位论文全文数据库 信息科技辑》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110247585A (en) * | 2019-04-17 | 2019-09-17 | 湖南工业大学 | A kind of multiple-axis servo control with changed scale cooperative control method based on sliding moding structure |
| CN110247585B (en) * | 2019-04-17 | 2021-04-30 | 湖南工业大学 | Multi-axis servo variable-proportion cooperative control method based on sliding mode variable structure |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108638064B (en) | 2020-10-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109782601B (en) | Design method of self-adaptive neural network synchronous robust controller of coordinated mechanical arm | |
| CN110597268B (en) | Wheel type mobile robot track tracking control method based on cascade system theory | |
| CN109176525A (en) | A kind of mobile manipulator self-adaptation control method based on RBF | |
| CN112904728B (en) | Mechanical arm sliding mode control track tracking method based on improved approach law | |
| CN110977988B (en) | Multi-joint mechanical arm impedance control method based on finite time command filtering | |
| CN108614425A (en) | Mobile robot Adaptive Integral sliding-mode control | |
| Gong et al. | Adaptive backstepping sliding mode trajectory tracking control for a quad-rotor | |
| CN105607473B (en) | The attitude error Fast Convergent self-adaptation control method of small-sized depopulated helicopter | |
| Dong et al. | A high-performance flight control approach for quadrotors using a modified active disturbance rejection technique | |
| CN108942924A (en) | Model uncertainty mechanical arm motion control method based on multilayer neural network | |
| CN109807902A (en) | A kind of double-mechanical arm strength based on Backstepping/position fuzzy hybrid control method | |
| CN106826807B (en) | Sliding mode variable structure control method of three-degree-of-freedom wrist structure | |
| CN109352656B (en) | Multi-joint mechanical arm control method with time-varying output constraint | |
| CN108656111A (en) | A kind of double mechanical arms system finite time parameter identification and position synchronization control method based on mean value coupling | |
| Ren et al. | Cascade PID controller for quadrotor | |
| CN115256386B (en) | Uncertain mechanical arm neural self-adaptive control method considering tracking error constraint | |
| CN110456816A (en) | A kind of quadrotor Trajectory Tracking Control method based on continuous terminal sliding mode | |
| CN108646563A (en) | A kind of Multi-arm robots set time parameter identification and position synchronization control method based on mean value coupling | |
| CN115480583A (en) | Visual servo tracking and impedance control method of flying operation robot | |
| CN108638064A (en) | A kind of identification of Multi-arm robots auto-adaptive parameter and position synchronization control method based on mean value coupling | |
| CN114942593A (en) | Mechanical arm self-adaptive sliding mode control method based on disturbance observer compensation | |
| CN109062039B (en) | Adaptive robust control method of three-degree-of-freedom Delta parallel robot | |
| Qian et al. | Neural network-based hybrid three-dimensional position control for a flapping wing aerial vehicle | |
| CN108646562A (en) | One kind is based on cross-linked Multi-arm robots finite time parameter identification and position synchronization control method | |
| Lee et al. | An adaptive control technique for motion synchronization by on-line estimation of a recursive least square method |
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 | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20230111 Address after: No.1 Zhengxue Road, Qinhuai District, Nanjing, Jiangsu 210001 Patentee after: NANJING CHENGUANG GROUP Co.,Ltd. Address before: B-2704, Woye Garden Business Office Building, No. 81, Ganquan Road, Shushan District, Hefei City, Anhui Province, 230088 Patentee before: HEFEI LONGZHI ELECTROMECHANICAL TECHNOLOGY Co.,Ltd. Effective date of registration: 20230111 Address after: B-2704, Woye Garden Business Office Building, No. 81, Ganquan Road, Shushan District, Hefei City, Anhui Province, 230088 Patentee after: HEFEI LONGZHI ELECTROMECHANICAL TECHNOLOGY Co.,Ltd. Address before: 310014 science and technology office, Zhejiang University of Technology, No. 18 Chao Wang Road, Xiacheng District, Hangzhou, Zhejiang Patentee before: JIANG University OF TECHNOLOGY |
|
| TR01 | Transfer of patent right |