CN110286582A - A kind of motion control method and system of small-sized six-shaft industrial mechanical arm - Google Patents

A kind of motion control method and system of small-sized six-shaft industrial mechanical arm Download PDF

Info

Publication number
CN110286582A
CN110286582A CN201910566551.7A CN201910566551A CN110286582A CN 110286582 A CN110286582 A CN 110286582A CN 201910566551 A CN201910566551 A CN 201910566551A CN 110286582 A CN110286582 A CN 110286582A
Authority
CN
China
Prior art keywords
mechanical arm
parameter
sized
small
signal
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
Application number
CN201910566551.7A
Other languages
Chinese (zh)
Inventor
李克丽
田野
梁颖
李娟�
田粉仙
孙欣欣
杨军
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Yunnan University YNU
Original Assignee
Yunnan University YNU
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Yunnan University YNU filed Critical Yunnan University YNU
Priority to CN201910566551.7A priority Critical patent/CN110286582A/en
Publication of CN110286582A publication Critical patent/CN110286582A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B11/00Automatic controllers
    • G05B11/01Automatic controllers electric
    • G05B11/36Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential
    • G05B11/42Automatic controllers electric with provision for obtaining particular characteristics, e.g. proportional, integral, differential for obtaining a characteristic which is both proportional and time-dependent, e.g. P. I., P. I. D.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Feedback Control In General (AREA)

Abstract

The invention discloses the motion control methods and system of a kind of small-sized six-shaft industrial mechanical arm, this method is acquired to obtain status signal to the motion state of small-sized six-shaft industrial mechanical arm, status signal is measured to obtain measured value y (t), and departure e (t) and deviation variation rate ec (t) is calculated according to the desired value r (t) of measured value y (t) and setting, according to parameter Kp、Ki、KdThe fuzzy matrix rule list that the Adjustment principle met in different e (t) and ec (t) determines, finds corrected parameter Δ K using departure e (t) and deviation variation rate ec (t)p、ΔKi、ΔKd, complete to parameter Kp、Ki、KdCorrection, then complete system using the PID controller of correction parameter and control.The present invention can be improved control precision and response speed do not solve the problems, such as it is of the existing technology.

Description

A kind of motion control method and system of small-sized six-shaft industrial mechanical arm
Technical field
The present invention relates to movement control technology fields, more particularly to a kind of motion control of small-sized six-shaft industrial mechanical arm Method and system.
Background technique
Wang Hong is disclosed herein one kind in " sliding Mode Robust Controls of the six shaft mechanical arms based on T-S fuzzy compensation " one and is based on The six-shaft industrial mechanical arm Sliding Mode Robust control method of motion trace of T-S fuzzy compensation, this method pass through linear feedback first Known portions in the equivalent Manipulator Dynamics of mode, then overcome manipulator motion system with classical sliding formwork control In uncertainty, finally apply T-S fuzzy model, convert the foolproof fuzzy cunning of rule for classical sliding mode controller Mould controller, the motion profile for small-sized six shaft mechanicals arm control.This method design principle is simple, and there is no classical sliding formwork controls Jitter problem in system, and stability is good, occupies the mechanical arm control that is few, but realizing using the control method of hardware logic resource That there are system response times is slow for system processed, and the not high deficiency of control precision is not suitable for having compared with high control precision and compared with Gao Xiang Answer the occasion of rate request.
Summary of the invention
The invention mainly solves the technical problem of providing a kind of motion control method of small-sized six-shaft industrial mechanical arm and System can be improved control precision and response speed.
In order to solve the above technical problems, one technical scheme adopted by the invention is that: a kind of small-sized six-shaft industrial machine is provided The motion control method of tool arm, comprising: the motion state of small-sized six-shaft industrial mechanical arm is acquired to obtain status signal;It is right The status signal measures to obtain measured value y (t), and is calculated according to the desired value r (t) of the measured value y (t) and setting Obtain departure e (t) and deviation variation rate ec (t);Departure e (t) and deviation variation rate ec (t) are input to fuzzy control Device finds out departure e (t) and the corresponding amendment of deviation variation rate ec (t) using fuzzy matrix rule list by fuzzy controller Parameter, Δ Kp、ΔKi、ΔKd, and utilize corrected parameter Δ Kp、ΔKi、ΔKdTo parameter Kp、Ki、KdIt is corrected, wherein described Fuzzy matrix rule list is according to parameter Kp、Ki、KdThe adjustment met in different departure e (t) and deviation variation rate ec (t) What principle determined;By the parameter K after correctionp、Ki、KdIt is input to PID controller, by PID controller according to the parameter after correction Kp、Ki、KdThe input control signal u (t) of the small-sized each axis of six-shaft industrial mechanical arm is generated, and the input control of each axis is believed Number u (t) is respectively outputted to the corresponding steering engine of each axis;Each steering engine is realized according to input control signal u (t) to joint of mechanical arm The accurate control of angle, enables mechanical arm to complete deliberate action.
Preferably, the status signal includes voice signal, attitude signal and ultrasonic distance measurement signal.
In order to solve the above technical problems, another technical solution used in the present invention is: providing a kind of small-sized six-shaft industrial The kinetic control system of mechanical arm, including main control chip, signal-processing board, sensor, operation input module and steering engine, six institutes Steering engine is stated to be respectively used to control the movement of six axis of small-sized six-shaft industrial mechanical arm;The operation input module is small for setting The desired value r (t) of type six-shaft industrial manipulator motion;The sensor is used for the motion state to small-sized six-shaft industrial mechanical arm It is acquired to obtain status signal;The signal-processing board is used to measure to obtain measured value y (t) to the status signal, And departure e (t) and deviation variation rate ec (t) is calculated according to the desired value r (t) of the measured value y (t) and setting; The main control chip is used to departure e (t) and deviation variation rate ec (t) being input to fuzzy controller, by fuzzy controller benefit Departure e (t) and the corresponding corrected parameter Δ K of deviation variation rate ec (t) are found out with fuzzy matrix rule listp、ΔKi、ΔKd, And utilize corrected parameter Δ Kp、ΔKi、ΔKdTo parameter Kp、Ki、KdIt is corrected, wherein the fuzzy matrix rule list is root According to parameter Kp、Ki、KdWhat the Adjustment principle met in different departure e (t) and deviation variation rate ec (t) determined;And will Parameter K after correctionp、Ki、KdIt is input to PID controller, by PID controller according to the parameter K after correctionp、Ki、KdIt generates small-sized The input control signal u (t) of each axis of six-shaft industrial mechanical arm, and the input control signal u (t) of each axis is respectively outputted to On the corresponding steering engine of each axis;Each steering engine is used to be realized according to input control signal u (t) to joint of mechanical arm angle Accurate control, enables mechanical arm to complete deliberate action.
Preferably, the sensor includes sound transducer, attitude transducer and ultrasonic distance-measuring sensor, the state Signal includes voice signal, attitude signal and ultrasonic distance measurement signal.
It is in contrast to the prior art, the beneficial effects of the present invention are:
There is higher degree of fitting to preset motion profile, shake is small, and control effect is substantially better than traditional PI D and is based on The control method of T-S fuzzy compensation has so as to mention high control precision and response speed and supports multiple sensors control, The advantages such as easy to operate.
Detailed description of the invention
Fig. 1 is the flow diagram of the motion control method of the small-sized six-shaft industrial mechanical arm of the embodiment of the present invention.
Fig. 2 is PID control response curve.
Fig. 3 is the emulation schematic diagram of the motion control method of the small-sized six-shaft industrial mechanical arm of the embodiment of the present invention.
Fig. 4 is six-shaft industrial mechanical arm Sliding Mode Robust control method of motion trace, traditional PI D based on T-S fuzzy compensation The simulation comparison result of the motion control method of control method and the present embodiment.
Fig. 5 is the experimental field figure that the motion control method of the embodiment of the present invention repeat station accuracy experiment.
Fig. 6 is the experimental result picture that the motion control method of the embodiment of the present invention repeat station accuracy experiment.
Fig. 7 is the configuration diagram of the kinetic control system of the small-sized six-shaft industrial mechanical arm of the embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete Site preparation description, it is clear that the described embodiments are merely a part of the embodiments of the present invention, instead of all the embodiments.It is based on Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other Embodiment shall fall within the protection scope of the present invention.
It is the flow diagram of the motion control method of the small-sized six-shaft industrial mechanical arm of the embodiment of the present invention referring to Fig. 1. The motion control method of the small-sized six-shaft industrial mechanical arm of the present embodiment includes:
S1: the motion state of small-sized six-shaft industrial mechanical arm is acquired to obtain status signal.
In the present embodiment, status signal includes voice signal, attitude signal and ultrasonic distance measurement signal.
S2: status signal is measured to obtain measured value y (t), and according to the desired value r of measured value y (t) and setting (t) departure e (t) and deviation variation rate ec (t) is calculated.
Wherein, departure e (t)=r (t)-y (t), deviation variation rate ec (t)=de (t)/dt.
S3: being input to fuzzy controller for departure e (t) and deviation variation rate ec (t), is utilized by fuzzy controller fuzzy Matrix rule list finds out departure e (t) and the corresponding corrected parameter Δ K of deviation variation rate ec (t)p、ΔKi、ΔKd, and utilize Corrected parameter Δ Kp、ΔKi、ΔKdTo parameter Kp、Ki、KdIt is corrected, wherein fuzzy matrix rule list is according to parameter Kp、Ki、 KdWhat the Adjustment principle met in different departure e (t) and deviation variation rate ec (t) determined.
According to the operating experience and PID control response curve of six shaft mechanical arms, wherein PID control response curve such as Fig. 2 institute Show, parameter Kp、Ki、KdMeet following adjustment rule in different departure e and deviation variation rate ec:
(1) 0A stage (e>0, ec<0)
0A is the characteristics of the stage: departure e>0 and tend to 0 from gradually becoming smaller greatly, deviation variation rate ec<0 and | ec | become from 0 It is small to become larger again.In order to obtain better control performance, Gain-scheduling control is taken at this stage.Become according to the size variation of e and ec 0A substage is tri- sections of OI, IJ and JA by gesture.
OI sections: since e is larger, | ec | become larger from 0, to accelerate response speed and integral being prevented to be saturated, KpTake larger, KdIt takes It is smaller, KiIt takes smaller or 0;
IJ sections: e is moderate, | ec | near the maximum, to prevent system overshoot, while in order to guarantee system response time, Kp、Ki、KdAll cannot be too big, KpAnd KdTake moderate, KiIt takes smaller;
JA sections: e smaller and trend 0, | ec | from becoming smaller greatly, K should be reducedp, and increase KiValue, while overshoot in order to prevent, Kd Take median size.
(2) AB stage (e < 0, ec < 0)
AB is the characteristics of the stage: departure e < 0 and | e | become larger from 0, deviation variation rate ec < 0 and | ec | become from big It is small.The purpose of stage is quickly to force down overshoot, reduces systematic steady state error, so should reinforce ratio and integral part control work With, while in order to maintain system near stable state, it should also reinforce the control action of differential part.So KpTake larger, KiTake compared with Greatly, KdTake median size.
(3) BC stage (e<0, ec>0)
BC is the characteristics of the stage: departure e<0 and | e | tend to 0 from gradually becoming smaller greatly, deviation variation rate ec>0 and | ec | from 0 becomes larger.The stage approaches to stable state direction, in order to reduce system reverse overshoot, should reduce or be not added integral action, can be with Increase differential part conduct.So KpTake moderate, KiIt takes smaller or for 0, KdTake median size.
(4) CD stage (e > 0, ec > 0)
CD is the characteristics of the stage: departure e > 0 and | e | slowly become larger from 0, deviation variation rate ec > 0 and | ec | from becoming smaller greatly Tend to 0.Although the stage system has small overshoot, but already close to stable state, system output is varied less.So KpTake moderate, Ki Take moderate, KdIt takes moderate.
(5) DE stage (e>0, ec<0)
DE is the characteristics of the stage: departure e>0 and | e | from slowly tending to 0 greatly, deviation variation rate ec<0 and | ec | it is attached 0 Closely.The stage deviation very little, and tend to stable state, control action should not be too strong, so integral action should be reduced, keeps ratio and micro- It is allocated as using, makes system keep stablizing, and have stronger anti-interference ability.So KpTake moderate, KiTake smaller, KdIt takes moderate.
According to it is above-mentioned to different e and ec when pid parameter Kp、Ki、KdThe analysis of Adjustment principle, fuzzy controller is to PID tri- Parameter is adjusted in real time, if Kp、Ki、KdThere is following relationship with e and ec:
In formula, Kp、Ki、KdIt is the pid parameter after being adjusted by fuzzy controller, Kp0、Ki0、Kd0It is by aritical ratio side The initial parameter for the PID controller that method obtains.ΔKp、ΔKi、ΔKdIt is by fuzzy relation function fp(e,ec)、fi(e,ec)、 fdThe PID adjustment amount related with e and ec that (e, ec) is obtained.
ΔKp、ΔKi、ΔKdFuzzy matrix rule list with E and EC is as shown in table 4.1 to 4.3.
4.1 Δ K of tablepFuzzy matrix rule list
4.2 Δ K of tableiFuzzy reasoning table
4.3 Δ K of tabledFuzzy reasoning table
By the variation range of departure e and deviation variation rate ec be defined as the domain in fuzzy set be e, ec=-3, -2, - 1,0,1,2,3 }, fuzzy subset E, EC={ FD, FZ, FX, LO, ZX, ZZ, ZD } export Δ Kp、ΔKi、ΔKdDomain take [- 10,10], output fuzzy subset is identical as input fuzzy subset.If E, EC and Δ Kp、ΔKi、ΔKdEqual Normal Distribution, and Subordinating degree function is identical.
S4: by the parameter K after correctionp、Ki、KdIt is input to PID controller, by PID controller according to the parameter after correction Kp、Ki、KdThe input control signal u (t) of the small-sized each axis of six-shaft industrial mechanical arm is generated, and the input control of each axis is believed Number u (t) is respectively outputted to the corresponding steering engine of each axis.
S5: each steering engine realizes the accurate control to joint of mechanical arm angle according to input control signal u (t), makes machinery Arm can complete deliberate action.
The software emulation of the motion control method of the present embodiment is as shown in Figure 3.The motion control method is in hardware configuration Intel i5 4200U, 8G memory, 256G solid state hard disk are equipped on the PC of 64 WIN10 operating systems and MATLAB2014a It is emulated.Six-shaft industrial mechanical arm Sliding Mode Robust control method of motion trace based on T-S fuzzy compensation, traditional PID control The simulation comparison result of the motion control method of method and the present embodiment is as shown in Figure 4, wherein Fig. 4 (a) is fuzzy based on T-S The simulation result of compensation campaign method for controlling trajectory, Fig. 4 (b) are the simulation result of traditional PID control method, and Fig. 4 (c) is this hair The simulation result of the motion control method of bright embodiment.
Comparing three kinds of simulation results can be seen that the motion control of the embodiment of the present invention when motion profile fluctuates Control method of motion trace of the method than traditional PID control method and based on T-S fuzzy compensation has preset motion profile Higher degree of fitting, system control precision is high, and shake is small, and control effect is significantly superior.
The motion control method of the embodiment of the present invention is carried out again to repeat station accuracy experiment, in this experiment, small-sized six Axis industrial machinery arm defines the positive direction under mechanical arm 0 degree of state of No. 1 axis steering engine angle for mechanical arm, from positive direction 190mm It is demarcated as the center of circle at (75mm comprising No. 1 axis center to steering engine chassis edge, similarly hereinafter), the circle of radius 20mm is drawn with the center of circle, Mechanical arm is allowed to hold stroke point 50 times in the center of circle.Experimental field figure is as shown in figure 5, experimental result picture is as shown in Figure 6, wherein Fig. 6 It (a) is the experimental result of the fortune function method for controlling trajectory based on T-S fuzzy compensation, Fig. 6 (b) is the reality of traditional PID control method It tests as a result, Fig. 6 (c) is the experimental result of the motion control method of the embodiment of the present invention.
From figure China as can be seen that the point of Fig. 6 (a) and Fig. 6 (b) is more dispersed, or even occur shaking due to mechanical arm And the company's pen generated, the company situation of Fig. 6 (c) is less, and point compares concentration.Illustrate the motion control method of the embodiment of the present invention It is relatively good to repeat fixed-point performance, control precision is high.
It is the configuration diagram of the kinetic control system of the small-sized six-shaft industrial mechanical arm of the embodiment of the present invention refering to Fig. 7. The kinetic control system of the embodiment of the present invention includes main control chip 10, signal-processing board 20, sensor 30, operation input module 40 With steering engine 50, six steering engines 50 are respectively used to control the movement of six axis of small-sized six-shaft industrial mechanical arm.
Operation input module 40 is used to set the desired value r (t) of small-sized six-shaft industrial manipulator motion.
Sensor 30 to the motion state of small-sized six-shaft industrial mechanical arm for being acquired to obtain status signal.Wherein, Sensor 30 includes sound transducer, attitude transducer and ultrasonic distance-measuring sensor, and status signal includes voice signal, posture Signal and ultrasonic distance measurement signal.
Signal-processing board 20 is used to measure to obtain to status signal measured value y (t), and according to measured value y (t) with set Departure e (t) and deviation variation rate ec (t) is calculated in fixed desired value r (t).
Main control chip 10 is used to departure e (t) and deviation variation rate ec (t) being input to fuzzy controller, by Fuzzy Control Device processed finds out departure e (t) and the corresponding corrected parameter Δ K of deviation variation rate ec (t) using fuzzy matrix rule listp、Δ Ki、ΔKd, and utilize corrected parameter Δ Kp、ΔKi、ΔKdTo parameter Kp、Ki、KdIt is corrected, wherein fuzzy matrix rule list is According to parameter Kp、Ki、KdWhat the Adjustment principle met in different departure e (t) and deviation variation rate ec (t) determined;And it will By the parameter K after correctionp、Ki、KdIt is input to PID controller, by PID controller according to the parameter K after correctionp、Ki、KdIt generates small The input control signal u (t) of each axis of type six-shaft industrial mechanical arm, and the input control signal u (t) of each axis is exported respectively Onto the corresponding steering engine 50 of each axis;
Each steering engine 50 is used for the accurate control according to input control signal u (t) realization to joint of mechanical arm angle, makes machine Tool arm can complete deliberate action.
It is in concrete application at one, main control chip 10 selects STM32 series monolithic, such as STM32F103C8T6, rudder The model of machine 50 selects LD-1501, and signal-processing board 20 selects Arduino Uno r3 development board, the model choosing of sound transducer ADXL335, the model of ultrasonic distance-measuring sensor are selected with the model of LM986 audio integrated power amplifier, attitude transducer Select US-100.
The kinetic control system of the small-sized six-shaft industrial mechanical arm of the present embodiment has small-sized six axis with previous embodiment The identical technical characteristic of the motion control method of industrial machinery arm, details are not described herein.
The above description is only an embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills Art field, is included within the scope of the present invention.

Claims (4)

1. a kind of motion control method of small-sized six-shaft industrial mechanical arm characterized by comprising
The motion state of small-sized six-shaft industrial mechanical arm is acquired to obtain status signal;
The status signal is measured to obtain measured value y (t), and according to the desired value r of the measured value y (t) and setting (t) departure e (t) and deviation variation rate ec (t) is calculated;
Departure e (t) and deviation variation rate ec (t) are input to fuzzy controller, advised by fuzzy controller using fuzzy matrix Then table finds out departure e (t) and the corresponding corrected parameter Δ K of deviation variation rate ec (t)p、ΔKi、ΔKd, and utilize amendment ginseng Number Δ Kp、ΔKi、ΔKdTo parameter Kp、Ki、KdIt is corrected, wherein the fuzzy matrix rule list is according to parameter Kp、Ki、Kd What the Adjustment principle met in different departure e (t) and deviation variation rate ec (t) determined;
By the parameter K after correctionp、Ki、KdIt is input to PID controller, by PID controller according to the parameter K after correctionp、Ki、KdIt is raw At the input control signal u (t) of the small-sized each axis of six-shaft industrial mechanical arm, and respectively by the input control signal u (t) of each axis It is output to the corresponding steering engine of each axis;
Each steering engine realizes the accurate control to joint of mechanical arm angle according to input control signal u (t), keeps mechanical arm complete At deliberate action.
2. the motion control method of small-sized six-shaft industrial mechanical arm according to claim 1, which is characterized in that the state Signal includes voice signal, attitude signal and ultrasonic distance measurement signal.
3. a kind of kinetic control system of small-sized six-shaft industrial mechanical arm, which is characterized in that including main control chip, signal processing Plate, sensor, operation input module and steering engine, six steering engines are respectively used to control six of small-sized six-shaft industrial mechanical arm The movement of axis;
The operation input module is used to set the desired value r (t) of small-sized six-shaft industrial manipulator motion;
The sensor to the motion state of small-sized six-shaft industrial mechanical arm for being acquired to obtain status signal;
The signal-processing board is used to measure to obtain measured value y (t) to the status signal, and according to the measured value y (t) departure e (t) and deviation variation rate ec (t) is calculated in the desired value r (t) with setting;
The main control chip is used to departure e (t) and deviation variation rate ec (t) being input to fuzzy controller, by fuzzy control Device finds out departure e (t) and the corresponding corrected parameter Δ K of deviation variation rate ec (t) using fuzzy matrix rule listp、ΔKi、 ΔKd, and utilize corrected parameter Δ Kp、ΔKi、ΔKdTo parameter Kp、Ki、KdIt is corrected, wherein the fuzzy matrix rule list It is according to parameter Kp、Ki、KdWhat the Adjustment principle met in different departure e (t) and deviation variation rate ec (t) determined;
And by the parameter K after correctingp、Ki、KdIt is input to PID controller, by PID controller according to the parameter K after correctionp、 Ki、KdGenerate the input control signal u (t) of the small-sized each axis of six-shaft industrial mechanical arm, and by the input control signal u of each axis (t) it is respectively outputted on the corresponding steering engine of each axis;
Each steering engine is used for the accurate control according to input control signal u (t) realization to joint of mechanical arm angle, makes machinery Arm can complete deliberate action.
4. the kinetic control system of small-sized six-shaft industrial mechanical arm according to claim 3, which is characterized in that the sensing Device includes sound transducer, attitude transducer and ultrasonic distance-measuring sensor, and the status signal includes voice signal, posture letter Number and ultrasonic distance measurement signal.
CN201910566551.7A 2019-06-27 2019-06-27 A kind of motion control method and system of small-sized six-shaft industrial mechanical arm Pending CN110286582A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910566551.7A CN110286582A (en) 2019-06-27 2019-06-27 A kind of motion control method and system of small-sized six-shaft industrial mechanical arm

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910566551.7A CN110286582A (en) 2019-06-27 2019-06-27 A kind of motion control method and system of small-sized six-shaft industrial mechanical arm

Publications (1)

Publication Number Publication Date
CN110286582A true CN110286582A (en) 2019-09-27

Family

ID=68007643

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910566551.7A Pending CN110286582A (en) 2019-06-27 2019-06-27 A kind of motion control method and system of small-sized six-shaft industrial mechanical arm

Country Status (1)

Country Link
CN (1) CN110286582A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110919692A (en) * 2019-12-12 2020-03-27 扬州大学 Mechanical arm and intelligent control technology
CN115524998A (en) * 2022-10-25 2022-12-27 山西建投集团装饰有限公司 Robot sliding mode control method based on self-adaptive fuzzy compensation

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160209816A1 (en) * 2015-01-21 2016-07-21 Linestream Technologies Cascaded active disturbance rejection controllers
CN108196442A (en) * 2018-03-02 2018-06-22 广州大学 Steering gear control system and method based on fuzzy neural PID control and absolute encoder
CN109683471A (en) * 2018-08-28 2019-04-26 杭州电子科技大学 Auto-disturbance-rejection Control, device and system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160209816A1 (en) * 2015-01-21 2016-07-21 Linestream Technologies Cascaded active disturbance rejection controllers
CN108196442A (en) * 2018-03-02 2018-06-22 广州大学 Steering gear control system and method based on fuzzy neural PID control and absolute encoder
CN109683471A (en) * 2018-08-28 2019-04-26 杭州电子科技大学 Auto-disturbance-rejection Control, device and system

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
张文庆: "基于BP神经网络的机械臂模糊自适应PID控制", 《黑龙江大学自然科学学报》 *
李航: "一种多自由度机械臂模糊自适应控制系统的设计", 《中国硕士学位论文全文数据库 信息科技专辑》 *
杨敏等: "柔性机械臂动力学建模与控制方法研究进展", 《长春工业大学学报(自然科学版)》 *
董森等: "基于模糊PID的机械臂控制系统设计", 《黑龙江八一农垦大学学报》 *
邱恒等: "基于模糊PD算法的三自由度机械臂遥操作双边控制", 《自动化与仪表》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110919692A (en) * 2019-12-12 2020-03-27 扬州大学 Mechanical arm and intelligent control technology
CN110919692B (en) * 2019-12-12 2022-06-14 扬州大学 Mechanical arm and intelligent control technology
CN115524998A (en) * 2022-10-25 2022-12-27 山西建投集团装饰有限公司 Robot sliding mode control method based on self-adaptive fuzzy compensation

Similar Documents

Publication Publication Date Title
CN111360830B (en) Vibration control method of flexible mechanical arm based on cooperative tracking
CN106873380A (en) Piezoelectric ceramics fuzzy PID control method based on PI models
Su et al. A neural-network-based controller for a single-link flexible manipulator using the inverse dynamics approach
CN110286582A (en) A kind of motion control method and system of small-sized six-shaft industrial mechanical arm
Sergi et al. On the stability and accuracy of high stiffness rendering in non-backdrivable actuators through series elasticity
Wang et al. Adaptive PID control of multi-DOF industrial robot based on neural network
CN101339404B (en) Aircraft posture kinetics simplified model gain switching proportion-differential control design method
CN110936374A (en) Flexible double-joint mechanical arm command filtering backstepping control method
CN111103792A (en) Robot control method, device, electronic equipment and readable storage medium
CN115502966A (en) Variable admittance control method for robot
CN110107416A (en) Air conditioner load pre-control method
Huang et al. State feedback control for stabilization of the ball and plate system
Insperger et al. Increasing the accuracy of digital force control process using the act-and-wait concept
Yuan et al. Identification and parameter sensitivity analyses of time-delay with single-fractional-pole systems under actuator rate limit effect
Kan et al. A minimum phase output based tracking control of ball and plate systems
CN110617152A (en) Throttle control system based on fuzzy PID control
CN114114903B (en) Cricket system integral terminal sliding mode control method based on variable exponent power approach law
CN114571451A (en) Adaptive sliding mode control method and device capable of adjusting funnel boundary
JPH02226304A (en) Group control system for fuzzy controller
CN111546329A (en) Multi-joint robot servo gain consistency control method
CN112454349B (en) Mechanical arm control transformation method considering variable stiffness joint delay characteristics
JPH0272404A (en) Deciding method for membership function
CN110928239B (en) Control method and system for feeding system of numerical control machine tool with time delay
CN117549311A (en) Mechanical arm track tracking control method and system based on self-learning control strategy
CN117215342A (en) Differential control circuit and control method for robot moment control

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
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20190927

WD01 Invention patent application deemed withdrawn after publication