CN109839826A - Double drive coordinated movement of various economic factors synchronisation control means - Google Patents
Double drive coordinated movement of various economic factors synchronisation control means Download PDFInfo
- Publication number
- CN109839826A CN109839826A CN201910161291.5A CN201910161291A CN109839826A CN 109839826 A CN109839826 A CN 109839826A CN 201910161291 A CN201910161291 A CN 201910161291A CN 109839826 A CN109839826 A CN 109839826A
- Authority
- CN
- China
- Prior art keywords
- double drive
- fuzzy
- formula
- economic factors
- control
- 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.)
- Pending
Links
Landscapes
- Feedback Control In General (AREA)
Abstract
The invention discloses a kind of double drive coordinated movement of various economic factors synchronisation control means, including establish kinematics model for existing single shaft+The gear deceleration driving method；Design self-adapting fuzzy frictional compensation device compensates the non-linear friction of system；The robustness of system is improved using global synovial membrane control algolithm；Establish the double drive traffic signal coordination controlled based on two shaft position error couplers；Double drive coordinated movement of various economic factors synchronously control is completed using the control algolithm of foundation.The method of the present invention can ensure the location error of kinematic system and the equal asymptotic convergence of synchronous error in zero, simultaneously, control method also possesses good robustness, parameter of electric machine variation bring disturbance caused by external loading variation or interference can be effectively resisted, and can be widely applied in respective double drive kinematic system.
Description
Technical field
Present invention relates particularly to a kind of double drive coordinated movement of various economic factors synchronisation control means.
Background technique
With the development of economic technology, traditional industry has also welcome new opportunity to develop.In traditional industrial machinery
In, a motor is usually used to drive production equipment.But with the development of modern industrial technology, modern industry is mechanical
Equipment develops towards high-precision, large inertia, varying load, good dynamic response performance direction, therefore is driven again with single motor
The requirement of the production work of modern industry is no longer satisfied, but drives loaded work piece jointly using multiple electric motors.Phase
It is driven than single motor, multi-motor driving can increase the output power of system, increase the freedom degree of equipment and can provide more
Function, be widely used in various heavy duties, varying load, high-precision requirement occasion in.
However, the problem of being related to synchronously control using multi-motor driving, this is the difficult point place of multi-drive system,
It is the research hotspot problem of motion control field.But although there are many for double drive coordinated movement of various economic factors synchronously control in recent years
Research achievement, but its synchronously control effect is still bad.
Summary of the invention
The purpose of the present invention is to provide a kind of high reliablity, robustness is preferable and the higher double drive of control precision is coordinated
Move synchronisation control means.
This double drive coordinated movement of various economic factors synchronisation control means provided by the invention, includes the following steps:
S1. it is directed to existing single shaft+The gear deceleration driving method, establishes kinematics model；
S2. it is directed to single axial movement, design self-adapting fuzzy frictional compensation device compensates the non-linear friction of system；
S3. the robustness of system is improved using global synovial membrane control algolithm；
S4. the double drive traffic signal coordination based on the control of two shaft position error couplers is established；
S5. the double drive traffic signal coordination established using step S4 controls existing single shaft+The gear deceleration driving
System, to complete double drive coordinated movement of various economic factors synchronously control.
It is directed to existing single shaft+The gear deceleration driving method described in step S1, establishes kinematics model, specially uses
Following steps establish kinematics model:
A. moment of friction suffered by system is equivalent on motor shaft, and the uncertainty of model is equivalent to distracter,
To according to following formula founding mathematical models:
J in formulamFor total rotary inertia of motor and transmission mechanism, θmFor motor angular displacement, f (t) is that system is converted to motor
Moment of friction on axis, TaFor transmission mechanism output torque, d (t) is system parameter uncertainty item and external interference item, u (t)
For motor output torque, TbFor transmission mechanism input torque, θ is load axis angular displacement, and i is reduction ratio, JbThe idling that is negative is dynamic used
Amount；
B. the mathematical model obtained according to step A, using following formula to establish with motor torque is input, load shaft angle position
Move the dynamic property equation for output:
J=J in formulab/i+iJm。
Design self-adapting fuzzy frictional compensation device described in step S2, is specially designed using following steps:
A. the input sample point in input space U is transformed into the fuzzy set A in output SPACE V by fuzzy devicelIn；
B. according to the rule in knowledge base, the fuzzy subset of V can be mapped to fuzzy rule R by inference machinemFuzzy subset
In；
C. defuzzifier is again by fuzzy rule RmIn fuzzy set be mapped to discrete point set RnIn；
D. weighted mean method is used, using the output F of following formula computing systemi:
J=1 in formula, 2 ..., M, M are the sum of rule,l
=1,2 ..., M,For free parameter and composition vectorFor degree of membership letter
Number, xiFor input variable.
Global synovial membrane control algolithm, specifically comprises the following steps: described in step S3
(1) using following formula as global sliding mode function s:
E is tracking error and e=θ-θ in formulad, θ is actual motion track, θdFor ideal motion profile, c is greater than 0
Constant, g (t) are that the function and g (t) designed to reach global sliding mode must satisfy following 3 conditions: condition 1:G (t) → 0 when condition 2:t → ∞；Condition 3:g (t) has first derivative；
(2) using following formula as control law:
In formulaFor the estimated value of J, Δ J isMaximum deviation, D be disturb d (t) maximum value, g be g (t) contracting
It writes, KDFor positive control gain, sgn (s) is sign function,For the output valve of self-adapting fuzzy frictional compensation device.
The function expression of the function g (t) designed to reach global sliding mode is g (t)=g (0) e-kt。
The double drive traffic signal coordination that foundation described in step S4 is controlled based on two shaft position error couplers, is specially adopted
Use formula as the control amount u of double drive coordinated movement of various economic factors synchronously control:
In formulaFor the estimation of inertial matrix J, c=diag { c1,c2It is sliding-mode surface parameter matrix,For the PD feedback control amount of position synchronous error, KD、KEPAnd KEDIt is the parameter square of positive value for element
Battle array, c are the constant greater than 0, and sgn (s) is sign function, and G is the gravity compensation on vertical direction, q=[q1,q2]TFor double drive
Vector composed by respective freedom degree direction, qdFor the d power of coordinate q, the d power that the second order in formula for q is led, the i.e. seat
Put on the d power of acceleration, s be sliding formwork functional vector andE is feed back input amount and E=(I+ α T) e, I is
Unit matrix, the synchronous error proportionality coefficient that α is positive,E=[e1 e2]T, e1And e2For the position of twin shaft,
KNIncludeThe compensation term of evaluated error and interference upper bound D and meet KN=[KN1,KN2,KN3,KN4]T、With
For the adaptive friction compensation item and satisfaction of each axisΘiFor fuzzy system parameter vector and its approach rate
It is designed as Θi=-s Γiξi, Γ is Strict Positive Real constant.
This double drive coordinated movement of various economic factors synchronisation control means provided by the invention is a kind of based on adaptive fuzzy friction benefit
It repays, the double drive coordinated movement of various economic factors synchronisation control means of total-sliding-mode control and cross-coupling control, is used for double drive mechanical equipment
Synchronously control in movement；The method of the present invention can ensure the location error of kinematic system and the equal asymptotic convergence of synchronous error in
Zero, meanwhile, control method also possesses good robustness, can effectively resist motor caused by external loading variation or interference
The disturbance of Parameters variation bring, and can be widely applied in respective double drive kinematic system, such as H-type goes up and down truss, work
Industry robot etc..
Detailed description of the invention
Fig. 1 is the uniaxial transmission mechanism schematic diagram that the method for the present invention is applicable in.
Fig. 2 is the control process schematic diagram of the method for the present invention.
Specific embodiment
This double drive coordinated movement of various economic factors synchronisation control means provided by the invention, includes the following steps:
S1. it is directed to existing single shaft+The gear deceleration driving method (its structure is as shown in Figure 1), establishes kinematics model；Tool
Body is to establish kinematics model using following steps:
A. moment of friction suffered by system is equivalent on motor shaft, and the uncertainty of model is equivalent to distracter,
To according to following formula founding mathematical models:
J in formulamFor total rotary inertia of motor and transmission mechanism, θmFor motor angular displacement, f (t) is that system is converted to motor
Moment of friction on axis, TaFor transmission mechanism output torque, d (t) is system parameter uncertainty item and external interference item, u (t)
For motor output torque, TbFor transmission mechanism input torque, θ is load axis angular displacement, and i is reduction ratio, JbThe idling that is negative is dynamic used
Amount；
B. the mathematical model obtained according to step A, using following formula to establish with motor torque is input, load shaft angle position
Move the dynamic property equation for output:
J=J in formulab/i+iJm；
S2. it is directed to single axial movement, design self-adapting fuzzy frictional compensation device compensates the non-linear friction of system；
Fuzzy rule form are as follows: if (if) condition, (then) conclusion；
For multi-input multi-output system, fuzzy rule is writeable are as follows:
L=1,2 in formula ..., M；
U=U1×U2×...×Un
V=V1×V2×...×Vm
Wherein Ui∈Rn, Vi∈Rm, M is the total quantity of rule, xiAnd yiIt is to output and input vector respectively,WithPoint
It is not fuzzy subset UiAnd ViOn fuzzy set, can be by subordinating degree functionWithIt is quantitatively described；
Therefore, in the specific implementation, can be designed using following steps:
A. the input sample point in input space U is transformed into the fuzzy set A in output SPACE V by fuzzy devicelIn；
B. according to the rule in knowledge base, the fuzzy subset of V can be mapped to fuzzy rule R by inference machinemFuzzy subset
In；
C. defuzzifier is again by fuzzy rule RmIn fuzzy set be mapped to discrete point set RnIn；
D. weighted mean method is used, using the output F of following formula computing systemi:
J=1 in formula, 2 ..., M, M are the sum of rule,l
=1,2 ..., M,For free parameter and composition vectorFor degree of membership letter
Number, xiFor input variable；
Simultaneously as frictional force is only related with speed, so the output of adaptive fuzzy system is represented by
Due in general fuzzy system,It is constant, but in the methods of the invention, in order to allow system not
Determining parameter and distracter has good adaptability, introduces adaptive algorithm, enablesFor free parameter and composition vectorTo obtain above-mentioned adaptive fuzzy system；
S3. the robustness of system is improved using global synovial membrane control algolithm；
In general, the response of traditional Sliding Mode Variable Structure System is divided into two stages, i.e., reaching mode response with
And sliding mode response；Since sliding formwork function is not zero in movement original state, thus tradition SMC system is only in sliding mode mistake
Exist in journey to external interference and the probabilistic robustness of object parameters, robust is not present in the reaching mode stage
Property；Based on this analysis, a kind of kinematic nonlinearity sliding-mode surface equation can be constructed, so that sliding formwork function also can in movement original state
It levels off to zero, there is robustness, i.e. total-sliding-mode control to achieve the purpose that control overall process；
Therefore, the global synovial membrane control algolithm, specifically comprises the following steps:
(1) using following formula as global sliding mode function s:
E is tracking error and e=θ-θ in formulad, θ is actual motion track, θdFor ideal motion profile, c is greater than 0
Constant, g (t) are that the function and g (t) designed to reach global sliding mode must satisfy following 3 conditions: condition 1:G (t) → 0 when condition 2:t → ∞；Condition 3:g (t) has first derivative；
Specifically, the function expression of g (t) can be designed as g (t)=g (0) e-kt；
(2) using following formula as control law:
In formulaFor the estimated value of J, Δ J isMaximum deviation, D be disturb d (t) maximum value, g be g (t) contracting
It writes, KDFor positive control gain, sgn (s) is sign function,For the output valve of self-adapting fuzzy frictional compensation device；
S4. the double drive traffic signal coordination based on the control of two shaft position error couplers is established；
For dual drive system, can set the synchronous error of axis 1,2 as
I.e.
I.e.
ε=Te
The control target of the twin shaft coordinated movement of various economic factors is i.e. so that εi→ 0, i.e., the tracking error situation of change of each axis reaches unanimity；
On this basis, the feed back input amount that coupling error is coordinated as the twin shaft designed below is introduced, is defined as:
E=e+ α ε=(I+ α T) e
The wherein synchronous error proportionality coefficient that α is positive；There are e → 0, ε → 0 in obvious E → 0 item；
To tracking double-shaft moving system, mathematical model is writeable are as follows:
Q=[q in formula1,q2]TFor vector composed by the respective freedom degree direction of double drive, J=diag { J1,J2Be etc.
The inertial matrix of effect, Ff=[f1,f2]TFor with speedRelevant non-linear friction item, d=[d1,d2]TIt is disturbed for extraneous outside
It is dynamic, u=[u1,u2]TFor the input torque of each axis；
By attached drawing 2 it is found that the expression formula of the control amount u of double drive coordinated movement of various economic factors synchronously control proposed by the present invention are as follows:
In formulaFor the estimation of inertial matrix J, c=diag { c1,c2It is sliding-mode surface parameter matrix,For the PD feedback control amount of position synchronous error, KD、KEPAnd KEDIt is the parameter square of positive value for element
Battle array, c are the constant greater than 0, and sgn (s) is sign function, and G is the gravity compensation on vertical direction, q=[q1,q2]TFor double drive
Vector composed by respective freedom degree direction, qdFor the d power of coordinate q, the d power that the second order in formula for q is led, the i.e. seat
Put on the d power of acceleration, s be sliding formwork functional vector andE is feed back input amount and E=(I+ α T) e, I is
Unit matrix, the synchronous error proportionality coefficient that α is positive,E=[e1 e2]T, e1And e2For the position of twin shaft,
KNIncludeThe compensation term and interference upper bound D and satisfaction of evaluated error
WithFor the adaptive friction compensation item and satisfaction of each axisΘiFor
Fuzzy system parameter vector and its rate of approaching is designed as Θi=-s Γiξi, Γ is Strict Positive Real constant；
S5. the double drive traffic signal coordination established using step S4 controls existing single shaft+The gear deceleration driving
System, to complete double drive coordinated movement of various economic factors synchronously control.
Claims (6)
1. a kind of double drive coordinated movement of various economic factors synchronisation control means, includes the following steps:
S1. it is directed to existing single shaft+The gear deceleration driving method, establishes kinematics model；
S2. it is directed to single axial movement, design self-adapting fuzzy frictional compensation device compensates the non-linear friction of system；
S3. the robustness of system is improved using global synovial membrane control algolithm；
S4. the double drive traffic signal coordination based on the control of two shaft position error couplers is established；
S5. the double drive traffic signal coordination established using step S4 controls existing single shaft+The gear deceleration driving, from
And complete double drive coordinated movement of various economic factors synchronously control.
2. double drive coordinated movement of various economic factors synchronisation control means according to claim 1, it is characterised in that needle described in step S1
To existing single shaft+The gear deceleration driving method, kinematics model is established, specially establishes kinematics mould using following steps
Type:
A. moment of friction suffered by system is equivalent on motor shaft, and the uncertainty of model is equivalent to distracter, thus
According to following formula founding mathematical models:
J in formulamFor total rotary inertia of motor and transmission mechanism, θmFor motor angular displacement, f (t) is that system is converted onto motor shaft
Moment of friction, TaFor transmission mechanism output torque, d (t) is system parameter uncertainty item and external interference item, and u (t) is electricity
Machine output torque, TbFor transmission mechanism input torque, θ is load axis angular displacement, and i is reduction ratio, JbFor load rotating inertia；
B. the mathematical model obtained according to step A, using following formula to establish with motor torque is input, load axis angular displacement is
The dynamic property equation of output:
J=J in formulab/i+iJm。
3. double drive coordinated movement of various economic factors synchronisation control means according to claim 2, it is characterised in that set described in step S2
Self-adapting fuzzy frictional compensation device is counted, is specially designed using following steps:
A. the input sample point in input space U is transformed into the fuzzy set A in output SPACE V by fuzzy devicelIn；
B. according to the rule in knowledge base, the fuzzy subset of V can be mapped to fuzzy rule R by inference machinemFuzzy subset in；
C. defuzzifier is again by fuzzy rule RmIn fuzzy set be mapped to discrete point set RnIn；
D. weighted mean method is used, using the output F of following formula computing systemi:
J=1 in formula, 2 ..., M, M are the sum of rule,L=1,
2 ..., M,For free parameter and composition vector For subordinating degree function, xi
For input variable.
4. double drive coordinated movement of various economic factors synchronisation control means according to claim 3, it is characterised in that complete described in step S3
Office's synovial membrane control algolithm, specifically comprises the following steps:
(1) using following formula as global sliding mode function s:
E is tracking error and e=θ-θ in formulad, θ is actual motion track, θdFor ideal motion profile, c is normal greater than 0
Number, g (t) is that the function and g (t) designed to reach global sliding mode must satisfy following 3 conditions: condition 1:G (t) → 0 when condition 2:t → ∞；Condition 3:g (t) has first derivative；
(2) using following formula as control law:
In formulaFor the estimated value of J, Δ J isMaximum deviation, D be disturb d (t) maximum value, g be g (t) abbreviation, KDFor
Positive control gain, sgn (s) are sign function,For the output valve of self-adapting fuzzy frictional compensation device.
5. double drive coordinated movement of various economic factors synchronisation control means according to claim 4, it is characterised in that described in order to reach
Global sliding mode and the function expression of function g (t) designed is g (t)=g (0) e-kt。
6. double drive coordinated movement of various economic factors synchronisation control means according to claim 5, it is characterised in that built described in step S4
The double drive traffic signal coordination of the two shaft position error couplers that are based on control specially is coordinated to transport using formula as double drive
The control amount u of dynamic synchronously control:
In formulaFor the estimation of inertial matrix J, c=diag { c1,c2It is sliding-mode surface parameter matrix,For the PD feedback control amount of position synchronous error, KD、KEPAnd KEDIt is the parameter square of positive value for element
Battle array, c are the constant greater than 0, and sgn (s) is sign function, and G is the gravity compensation on vertical direction, q=[q1,q2]TFor double drive
Vector composed by respective freedom degree direction, qdFor the d power of coordinate q, s be sliding formwork functional vector andE is
Feed back input amount and E=(I+ α T) e, I are unit matrix, the synchronous error proportionality coefficient that α is positive,E=
[e1 e2]T, e1And e2For the position of twin shaft, KNIncludeThe compensation term of evaluated error and interference upper bound D and meet KN=[KN1,
KN2,KN3,KN4]T、With | di(t)|≤Di；For the adaptive friction compensation item and satisfaction of each axisΘiFor fuzzy system parameter to
It measures and its rate of approaching is designed as Θi=-s Γiξi, Γ is Strict Positive Real constant.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910161291.5A CN109839826A (en) | 2019-03-04 | 2019-03-04 | Double drive coordinated movement of various economic factors synchronisation control means |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910161291.5A CN109839826A (en) | 2019-03-04 | 2019-03-04 | Double drive coordinated movement of various economic factors synchronisation control means |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109839826A true CN109839826A (en) | 2019-06-04 |
Family
ID=66885359
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910161291.5A Pending CN109839826A (en) | 2019-03-04 | 2019-03-04 | Double drive coordinated movement of various economic factors synchronisation control means |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109839826A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110879567A (en) * | 2019-11-29 | 2020-03-13 | 中国科学院微电子研究所 | Synchronous control method and system |
| CN111281743A (en) * | 2020-02-29 | 2020-06-16 | 西北工业大学 | Self-adaptive flexible control method for exoskeleton robot for upper limb rehabilitation |
| CN112147942A (en) * | 2020-10-26 | 2020-12-29 | 西安工业大学 | FPGA + DSP-based dual-motion platform synchronous control system and control method |
| CN112799304A (en) * | 2021-01-06 | 2021-05-14 | 武汉理工大学 | Dual-motor synchronous control method and device based on time-varying friction compensation |
| CN112904707A (en) * | 2019-12-04 | 2021-06-04 | 中南大学 | Synchronous control method of dual-drive vertical lifting servo system under variable load condition |
| CN112904741A (en) * | 2021-01-14 | 2021-06-04 | 上海交通大学 | High-precision synchronous control method and system for double-drive gantry truss system |
| CN115580189A (en) * | 2022-11-08 | 2023-01-06 | 哈尔滨工业大学 | High-speed gantry double-drive synchronous control method and system with disturbance suppression function |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100756602B1 (en) * | 2006-06-16 | 2007-09-07 | 인하대학교 산학협력단 | Motor control apparatus and control method therefor |
| CN105223809A (en) * | 2015-07-10 | 2016-01-06 | 沈阳工业大学 | The synchronous control system of the fuzzy neural network compensator of H type platform and method |
-
2019
- 2019-03-04 CN CN201910161291.5A patent/CN109839826A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100756602B1 (en) * | 2006-06-16 | 2007-09-07 | 인하대학교 산학협력단 | Motor control apparatus and control method therefor |
| CN105223809A (en) * | 2015-07-10 | 2016-01-06 | 沈阳工业大学 | The synchronous control system of the fuzzy neural network compensator of H type platform and method |
Non-Patent Citations (5)
| Title |
|---|
| 卢红 等: "双驱同步控制的误差预补偿算法与试验", 《机械科学与技术》 * |
| 孙红涛 等: "基于自适应滑模变结构控制的多轴同步协调控制系统建模", 《组合机床与自动化加工技术》 * |
| 张宇: "多电机伺服系统摩擦补偿与同步控制", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 邵质中 等: "重载伺服系统的自适应摩擦补偿全局滑模控制", 《计算机仿真》 * |
| 黄俊 等: "双驱动进给系统动态建模及变化规律研究", 《振动与冲击》 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110879567A (en) * | 2019-11-29 | 2020-03-13 | 中国科学院微电子研究所 | Synchronous control method and system |
| CN112904707A (en) * | 2019-12-04 | 2021-06-04 | 中南大学 | Synchronous control method of dual-drive vertical lifting servo system under variable load condition |
| CN112904707B (en) * | 2019-12-04 | 2022-05-20 | 中南大学 | Synchronous control method of dual-drive vertical lifting servo system under variable load condition |
| CN111281743A (en) * | 2020-02-29 | 2020-06-16 | 西北工业大学 | Self-adaptive flexible control method for exoskeleton robot for upper limb rehabilitation |
| CN112147942A (en) * | 2020-10-26 | 2020-12-29 | 西安工业大学 | FPGA + DSP-based dual-motion platform synchronous control system and control method |
| CN112799304A (en) * | 2021-01-06 | 2021-05-14 | 武汉理工大学 | Dual-motor synchronous control method and device based on time-varying friction compensation |
| CN112799304B (en) * | 2021-01-06 | 2022-06-14 | 武汉理工大学 | Dual-motor synchronous control method and device based on time-varying friction compensation |
| CN112904741A (en) * | 2021-01-14 | 2021-06-04 | 上海交通大学 | High-precision synchronous control method and system for double-drive gantry truss system |
| CN115580189A (en) * | 2022-11-08 | 2023-01-06 | 哈尔滨工业大学 | High-speed gantry double-drive synchronous control method and system with disturbance suppression function |
| CN115580189B (en) * | 2022-11-08 | 2023-07-25 | 哈尔滨工业大学 | High-speed gantry double-drive synchronous control method and system with disturbance suppression |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109839826A (en) | Double drive coordinated movement of various economic factors synchronisation control means | |
| CN110065070A (en) | A kind of robot adaptive impedance control system based on kinetic model | |
| CN107479385B (en) | Cartesian coordinate robot iteration sliding mode cross-coupling control method | |
| CN110007594B (en) | Self-adaptive robust sliding mode control method of series-parallel robot for automobile electrophoretic coating and conveying | |
| CN113681543B (en) | Mechanical arm zero-force control method based on model prediction | |
| CN108466289A (en) | A kind of dynamic modeling method for the parallel robot considering joint-friction | |
| CN108181813A (en) | A kind of fractional order sliding-mode control of flexible joint mechanical arm | |
| CN105598968B (en) | A kind of motion planning and control method of parallel mechanical arm | |
| CN110394801B (en) | Joint control system of robot | |
| CN107065562A (en) | A kind of anti-interference synchronization sliding-mode control of series parallel type automobile electrophoretic coating conveyor structure | |
| CN110597051A (en) | Stewart stable platform control method based on RBF neural network | |
| CN114952849A (en) | Robot trajectory tracking controller design method based on reinforcement learning and dynamics feedforward fusion | |
| Rani et al. | Motion/force control scheme for electrically driven cooperative multiple mobile manipulators | |
| CN111338369A (en) | Multi-rotor flight control method based on nonlinear inverse compensation | |
| Akbar et al. | Adaptive modified super-twisting control for a quadrotor helicopter with a nonlinear sliding surface | |
| CN108693776A (en) | A kind of robust control method of Three Degree Of Freedom Delta parallel robots | |
| CN109048995B (en) | Nonlinear joint friction force compensation method of three-degree-of-freedom Delta parallel robot | |
| Saied et al. | Actuator and friction dynamics formulation in control of PKMs: From design to real-time experiments | |
| CN110488608B (en) | Intelligent kinetic parameter identification method and module for driving and controlling integrated control system | |
| Wang et al. | Output regulation of the ball and plate system with a nonlinear velocity observer | |
| Liu et al. | Dynamic modeling and active disturbance rejection control of parallel aerial manipulator system | |
| CN112000014A (en) | Control method for model prediction and inversion of control mechanical arm | |
| Wang et al. | Adaptive robust control for accurate trajectory tracking of collaborative robots | |
| Sun et al. | Research on the tracing accurate of force based on fuzzy-pi control for a high-speed landing system | |
| TWI808852B (en) | Method for stable control of six-axis robotic arm by deep learning |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190604 |
|
| RJ01 | Rejection of invention patent application after publication |