CN109947117A - A kind of servo synchronization control system and control method suitable for monocular vision logistics distribution trolley - Google Patents
A kind of servo synchronization control system and control method suitable for monocular vision logistics distribution trolley Download PDFInfo
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Abstract
The invention discloses a kind of servo synchronization control systems suitable for monocular vision logistics distribution trolley, comprising: monitoring system is used to monitor the operating status of the logistics distribution trolley；Master control system, input terminal are electrically connected with the output end of the monitoring system；Position Fixing Navigation System, output end are electrically connected with the input terminal of the master control system；Hoisting system, output end are electrically connected with the input terminal of the master control system；Servo-system, and institute master control system is two-way is electrically connected, and the servo-system can receive the command signal of the master control system transmitting, and run signal is simultaneously fed back to the master control system by adjustment operating status.Revolving speed and steering when can adjust logistics distribution trolley travelling are regulated the speed fast, and control precision is high, and synchronism is good.The present invention also provides a kind of control methods of servo synchronization control system suitable for monocular vision logistics distribution trolley.
Description
Technical field
The present invention relates to a kind of logistics distribution trolley, especially a kind of servo suitable for monocular vision logistics distribution trolley
Synchronous control system and its control method.
Background technique
Current servo-system is usually used in high-precision industrial operations, such as logistics distribution trolley, logistics distribution trolley, number
Lathe, laser processing, component assembling etc..These industrial operations need multiple agent include servo motor and its intelligent driver and
The cooperation of relevant device guarantees that the synchronism controlled in servo-system is the pass for making servo-system complete high-precision operation
Key.
With China's expanding economy and the improvement of people's living standards, electric business logistics is rapidly developed, therewith
Requirement of the people to electric business logistics service quality and efficiency is also higher and higher, and logistics distribution trolley comes into being, and can be realized
The automation of express delivery sorting promotes express delivery sorting ability.
The servo-system poor synchronization of existing monocular vision logistics distribution trolley is adjusted when trolley deviates desired guiding trajectory
Speed is slow, influences traffic efficiency.
Summary of the invention
The present invention has designed and developed a kind of servo synchronization control system suitable for monocular vision logistics distribution trolley, can
Revolving speed and steering when adjustment logistics distribution trolley travelling, regulate the speed fast, and control precision is high, and synchronism is good.
The present invention has also designed and developed a kind of servo synchronization control method suitable for monocular vision logistics distribution trolley, leads to
Cross BP neural network and the operating status of logistics distribution trolley be acquired and adjusted, improve logistics distribution trolley regulate the speed and
Precision is controlled, guarantees the synchronism of logistics distribution trolley travelling.
Another goal of the invention of the invention controls distribution trolley and objects in front in logistics distribution trolley traveling process
Safe distance, guarantee distribution trolley operation working efficiency.
Technical solution provided by the invention are as follows:
A kind of servo synchronization control system suitable for monocular vision logistics distribution trolley, comprising:
Monitoring system is used to monitor the operating status of the logistics distribution trolley；
Master control system, input terminal are electrically connected with the output end of the monitoring system；
Position Fixing Navigation System, output end are electrically connected with the input terminal of the master control system；
Hoisting system, output end are electrically connected with the input terminal of the master control system；
Servo-system, and institute master control system is two-way is electrically connected, and the servo-system can receive the master control system and pass
The command signal passed adjusts operating status and run signal is fed back to the master control system.
Preferably, the monitoring system includes: camera, acceleration transducer, velocity sensor and gravity sensitive
Device.
Preferably, the servo-system includes: revolver servo-control system and right wheel servo-control system, respectively to object
Driving wheel at left and right sides of stream distribution trolley is controlled.
Preferably,
The revolver servo-control system includes: left servo drive motor and left driving wheel, the left servo drive system
The speed and steering of the left driving wheel are controlled by left servo drive motor；
The right wheel servo-control system includes: right servo drive motor and right driving wheel, the right servo drive system
The speed and steering of the right driving wheel are controlled by right servo drive motor.
A kind of control method of the servo synchronization system suitable for monocular vision logistics distribution trolley is applicable in using described
In the servo synchronization control system of monocular vision logistics distribution trolley, which is characterized in that specifically include:
Step 1: target information is input in the master control system, and read the position in the Position Fixing Navigation System
Information exports the target travel track of the logistics distribution trolley travelling；
Step 2: by monitoring system, according to the period, the travel speed V of logistics distribution trolley, acceleration a are acquired, with before
The distance between square object body d, lift height H and the gravity G lifted；
Step 3: successively the parameter of acquisition is normalized, determine that the input layer vector of three layers of BP neural network is x
={ x1,x2,x3,x4,x5}；Wherein, x1For velocity coeffficient, x2For acceleration factor, x3To be with the distance between objects in front
Number, x4For lift height coefficient, x5The gravity coefficient lifted；
Step 4: the input layer DUAL PROBLEMS OF VECTOR MAPPING is to middle layer, the middle layer vector y={ y1,y2,…,ym}；During m is
Interbed node number；
Step 5: obtaining output layer vector o={ o1,o2}；o1For revolver servo-control system adjustment signal, o2For right wheel
Servo-control system adjustment signal；
Wherein, small to logistics distribution to realize by acceleration and deceleration simultaneously when two driving motors are in revolving speed same state
The control of vehicle speed realizes the direction controlling to distribution trolley when two driving motor revolving speeds are different or turn to opposite.
Preferably, the safe distance between the logistics distribution trolley and objects in front is d0, set d >=d0, d0Warp
Test formula are as follows:
Wherein, σ is correction coefficient,For logistics distribution trolley setting speed, t is logistics distribution trolley travelling time, H0For
The lift height of setting, G0For the gravity for lifting object of setting, e is the natural logrithm truth of a matter, r1For the revolving speed of revolver driving motor,
r2For the revolving speed of right wheel driving motor, λ1For first constant relevant to logistics distribution trolley, λ1=0.76~0.92, λ2For with
The relevant second constant of logistics distribution trolley, λ2=0.95~1.20.
Preferably, the revolver servo-control system and the right wheel servo-control system pass through fuzzy-adaptation PID control
Algorithm is corrected the travel track of logistics distribution trolley, specifically includes:
By the revolving speed r of preset servo motor and turn to the servo motor in d and the practical traveling process of logistics distribution trolley
Revolving speed r and turn to d be compared, by fuzzy PID control method to logistics distribution trolley in traveling proceduredriven motor
Duty ratio compensates.
Preferably, the Fuzzy PID specifically includes:
The deviation of input speed, steering deviation, export proportionality coefficient, the proportion integral modulus of PID in fuzzy controller
And differential coefficient, the duty ratio that proportionality coefficient, proportion integral modulus and differential coefficient input PID controller carry out PWM compensate control
System；
Proportionality coefficient, proportion integral modulus and the differential coefficient of the output PID is divided into 7 grades；
The fuzzy set of the fuzzy controller output and input is { NB, NM, NS, 0, PS, PM, PB }.
It is of the present invention the utility model has the advantages that this system is in logistics distribution trolley traveling process, pass through acquisition logistics distribution
The operating condition of trolley adjusts the travel condition of logistics distribution trolley in real time, and control precision is high, regulates the speed fast, makes this system
Net synchronization capability it is excellent, guarantee trolley entirety operation conditions.
By BP neural network training, training result is fed directly to left servo drive system and right servo-drive system
System shortens feedback time, improves the working efficiency of servo-system, it is ensured that the synchronism of logistics distribution trolley travelling improves object
Precision is regulated the speed and controlled to stream distribution trolley.
In logistics distribution trolley traveling process, the safe distance of logistics distribution trolley and objects in front is controlled, prevents from matching
It send trolley to collide, guarantees the working efficiency of distribution trolley operation.
Detailed description of the invention
Fig. 1 is that the structure of the servo synchronization control system of the present invention suitable for monocular vision logistics distribution trolley is shown
It is intended to.
Fig. 2 is that the control of the servo synchronization control system of the present invention suitable for monocular vision logistics distribution trolley is former
Reason figure.
Specific embodiment
Present invention will be described in further detail below with reference to the accompanying drawings, to enable those skilled in the art referring to specification text
Word can be implemented accordingly.
As shown in Figs. 1-2, the present invention provides a kind of servo synchronization control system suitable for monocular vision logistics distribution trolley
System, can be monitored specific traveling situation of the logistics distribution trolley in practical traveling process, adjust logistics distribution in real time
The operation conditions of trolley guarantees the synchronism of system.It specifically includes, monitoring system, master control system, servo-system, hoisting system
And Position Fixing Navigation System.
Monitoring system includes that the camera that trolley front is arranged in, acceleration transducer, velocity sensor and gravity pass
Sensor, the output end for monitoring system are electrically connected with the input terminal of master control system, will monitor the fortune for the distribution trolley that system monitoring arrives
Market condition passes to master control system, and hoisting system is electrically connected with master control system, the output end of hoisting system and master control system it is defeated
Enter end electrical connection, for guaranteeing height that logistics distribution trolley is lifted during traveling, Position Fixing Navigation System and master control system
System electrical connection, the input terminal of the output end connection master control system of Position Fixing Navigation System, when advancing for acquiring logistics distribution trolley
Location information, and pass to master control system；Servo-system with master control system is two-way is electrically connected, the output end of servo-system and master
The input terminal of control system is electrically connected, while the output end of master control system is electrically connected with the input terminal of servo-system, and servo-system will
The operating condition of logistics distribution trolley passes to master control system, while can receive the order of master control system transmitting,
Servo-system includes revolver servo-control system and right wheel servo-control system, wherein revolver servo-control system
Further include: left servo drive motor and left driving wheel, left servo drive system control the left drive by left servo drive motor
The speed and steering of driving wheel；
Right wheel servo-control system includes: right servo drive motor and right driving wheel, and right servo drive system is watched by the right side
Take speed and steering that driving motor controls the right driving wheel.
The course of work of entire control system is as follows: the target information of logistics distribution trolley is input in master control system,
And the location information in Position Fixing Navigation System is read, the target travel track of logistics distribution trolley operation is exported, logistics distribution is small
Vehicle is run according to target travel track, in the process of running, by monitoring system monitoring logistics distribution trolley traveling process
In speed, acceleration, the gravity with the distance between objects in front and lifted object, adjusted and held in the palm by lifting mechanism
The height and flip angle of object are lifted, monitors system and hoisting system for the information real-time delivery of monitoring to master control system, positioning
The advanced positions of system real-time monitoring logistics distribution trolley simultaneously pass to master control system, master control system receive come self-monitoring system,
Hoisting system and the information of positioning system transmitting, determine the current operating status of logistics distribution trolley, when monitoring that logistics matches
When sending trolley offset track, master control system is according to specific operating condition to revolver servo-control system and right wheel SERVO CONTROL system
System makes command adapted thereto, and then is adjusted correspondingly to the revolving speed and steering of left and right sidesing driving wheel, by constantly recycling and adjusting
It is whole, so that logistics distribution trolley can finally be run on correct path.
The present invention also provides a kind of servo synchronization control methods suitable for monocular vision logistics distribution trolley, pass through BP mind
Through network training, training result is fed directly to left servo drive system and right servo drive system, shortens feedback time, mentions
The working efficiency of high servo-system, it is ensured that the synchronism of logistics distribution trolley travelling improves the adjustment speed of logistics distribution trolley
Degree and control precision, specifically include:
Step 1: target information is input in the master control system, and read the position in the Position Fixing Navigation System
Information exports the target travel track of the logistics distribution trolley travelling；
Step 2: establishing BP neural network model；
For the BP network architecture that the present invention uses by up of three-layer, first layer is input layer, total n node, corresponding
Indicate that n detection signal of equipment working state, these signal parameters are provided by data preprocessing module.The second layer is hidden layer,
Total m node is determined in an adaptive way by the training process of network.Third layer is output layer, total p node, by system
Actual needs output in response to determining that.
The mathematical model of the network are as follows:
Input layer vector: x=(x1,x2,…,xn)T
Middle layer vector: y=(y1,y2,…,ym)T
Output layer vector: z=(z1,z2,…,zp)T
In the present invention, input layer number is n=5, and output layer number of nodes is p=2, and hidden layer number of nodes m is estimated by following formula
It obtains:
5 parameters of input signal respectively indicate are as follows: x1For velocity coeffficient, x2For acceleration factor, x3For with objects in front it
Between distance coefficient, x4For lift height coefficient, x5The gravity coefficient lifted；
Since the data that sensor obtains belong to different physical quantitys, dimension is different.Therefore, people is inputted in data
Before artificial neural networks, need to turn to data requirement into the numerical value between 0-1.
By the distance between logistics distribution trolley travel speed V, acceleration a and objects in front d, lift height H and institute
The gravity G lifted is normalized respectively, normalizes formula are as follows:
Wherein, xjFor the parameter in input layer vector, XjRespectively measurement parameter: V, a, d, H and G, j=1,2,3,4,
5；XjmaxAnd XjminMaximum value and minimum value in respectively corresponding measurement parameter.
Specifically, after being normalized, obtaining velocity coeffficient x for the travel speed V of logistics distribution trolley1,
Wherein, VminAnd VmaxThe respectively minimum value and maximum value of logistics distribution trolley travel speed.
Likewise, after being normalized, obtaining acceleration system for the acceleration a in logistics distribution trolley traveling process
Number x2,
Wherein, aminAnd amaxThe respectively minimum value and maximum value of logistics distribution trolley traveling acceleration.
Likewise, after being normalized, obtaining distance system for the distance between logistics distribution trolley and objects in front d
Number x3,
Wherein, dminAnd dmaxThe minimum value and maximum value of distance respectively between logistics distribution trolley and objects in front；
Likewise, after being normalized, obtaining lift height coefficient x for the lift height H of logistics distribution trolley4,
Wherein, HminAnd HmaxThe respectively minimum value and maximum value of logistics distribution trolley lift height；
Likewise, the gravity of object lifted for logistics distribution trolley, after being normalized, obtains gravity coefficient x5,
Output layer vector is expressed as o={ o1,o2}；o1For revolver servo-control system adjustment signal, o2For right wheel servo control
System call interception signal processed.
In another embodiment, the safe distance between logistics distribution trolley and objects in front is d0, set d >=d0, d0's
Empirical equation are as follows:
Wherein, σ is correction coefficient,For logistics distribution trolley setting speed, unit m/s, t are logistics distribution trolley fortune
Row time, unit s, H0For the lift height of setting, unit m, G0For the gravity for lifting object of setting, unit N, e are certainly
The right logarithm truth of a matter, r1For the revolving speed of revolver driving motor, unit r/min, r2For the revolving speed of right wheel driving motor, unit r/
Min, λ1For first constant relevant to logistics distribution trolley, λ1=0.76~0.92, λ2It is relevant to logistics distribution trolley
Two constants, λ2=0.95~1.20.
Step 3: carrying out BP neural network training
The sample of training, and the connection between given input node i and hidden layer node j are obtained according to historical empirical data
Weight Wij, hidden node j and output node layer k between connection weight Wjk, the threshold θ of hidden node jj, output node layer k's
Threshold θk、Wij、Wjk、θj、θkIt is the random number between -1 to 1.
In the training process, W is constantly correctedij、WjkValue, until systematic error be less than or equal to anticipation error when, complete mind
Training process through network.
(1) training method
Each subnet is using individually trained method；When training, first have to provide one group of training sample, each of these sample
This, to forming, when all reality outputs of network and its consistent ideal output, is shown to train by input sample and ideal output
Terminate；Otherwise, by correcting weight, keep the ideal output of network consistent with reality output；
The output sample of 1 network training of table
(2) training algorithm
BP network is trained using error back propagation (Backward Propagation) algorithm, and step can be concluded
It is as follows:
Step 1: a selected structurally reasonable network, is arranged the initial value of all Node B thresholds and connection weight.
Step 2: making following calculate to each input sample:
(a) forward calculation: to l layers of j unit
In formula,L layers of j unit information weighted sum when being calculated for n-th,For l layers of j units with it is previous
Connection weight between the unit i of layer (i.e. l-1 layers),For preceding layer (i.e. l-1 layers, number of nodes nl-1) unit i send
Working signal；When i=0, enable For the threshold value of l layers of j unit.
If the activation primitive of unit j is sigmoid function,
And
If neuron j belongs to the first hidden layer (l=1), have
If neuron j belongs to output layer (l=L), have
And ej(n)=xj(n)-oj(n)；
(b) retrospectively calculate error:
For output unit
To hidden unit
(c) weight is corrected:
η is learning rate.
Step 3: new sample or a new periodic samples are inputted, and until network convergence, the sample in each period in training
Input sequence is again randomly ordered.
BP algorithm seeks nonlinear function extreme value using gradient descent method, exists and falls into local minimum and convergence rate is slow etc.
Problem.A kind of more efficiently algorithm is Levenberg-Marquardt optimization algorithm, it makes the e-learning time shorter,
Network can be effectively inhibited and sink into local minimum.Its weighed value adjusting rate is selected as
Δ ω=(JTJ+μI)-1JTe；
Wherein, J is error to Jacobi (Jacobian) matrix of weight differential, and I is input vector, and e is error vector,
Variable μ is the scalar adaptively adjusted, for determining that study is completed according to Newton method or gradient method.
In system design, system model is one merely through the network being initialized, and weight needs basis using
The data sample obtained in journey carries out study adjustment, devises the self-learning function of system thus.Specify learning sample and
In the case where quantity, system can carry out self study, to constantly improve network performance.
Revolver servo-control system and right wheel servo-control system pass through Fuzzy PID to logistics distribution trolley
It carries out track to be corrected, revolver servo-control system and the control process of right wheel servo-control system are identical a, revolver servo
The specific control process of control system is as follows:
By the revolving speed of preset revolver servo motorAnd steeringWith turning in the practical traveling process of logistics distribution trolley
Fast r1With steering d1Be compared, by fuzzy PID control method to logistics distribution trolley revolver servo motor during traveling
Duty ratio compensate, to be corrected to the running track of logistics distribution trolley, make its operation to target position.
The revolving speed deviation e of revolver servo motor is inputted in fuzzy controllerv, turn to deviation ed, export the ratio system of PID
Number Kp, proportion integral modulus KiWith differential coefficient Kd, by Proportional coefficient Kp, proportion integral modulus KiWith differential coefficient KdInput PID
The duty ratio that PWM is carried out in controller compensates control.
When without control, revolving speed deviation evThe steering deviation e of sumdFuzzy domain is [- 0.06,0.06], the quantification factor
It is 1, exports the Proportional coefficient K of PIDpFuzzy domain be [- 1,1], the quantification factor be 0.1, proportion integral modulus KiMould
Pasting domain is [- 1,1], and the quantification factor is 0.056, and the fuzzy domain of differential coefficient is [- 1,1], and the quantification factor is
0.003；In order to guarantee to control precision, realizes preferably control, experiment is repeated, it is determined that optimal input rank and output
Grade, wherein revolving speed deviation evThe steering deviation e of sumd7 grades are divided into, the Proportional coefficient K of PID is exportedp, proportional integration system
Number KiWith differential coefficient KdBe divided into 7 grades, the fuzzy set of fuzzy controller output and input be NB, NM, NS, 0,
PS, PM, PB, the subordinating degree function output and input are all made of triangular membership, wherein fuzzy controller obscures
Control rule are as follows:
1, as revolving speed deviation evThe steering deviation e of sumdWhen larger, increase KpValue, so that deviation be made quickly to reduce, but
Biggish deviation variation rate is produced simultaneously, lesser K should be takend, usually take Ki=0；
2, as horizontal revolving speed deviation evThe steering deviation e of sumdWhen value is in medium, to avoid overshoot, suitably reduction KpTake
Value, makes KiIt is smaller, select appropriately sized Kd；
3, as revolving speed deviation evThe steering deviation e of sumdWhen smaller, increase Kp、KiValue, it is steady in system to avoid the occurrence of
The wild effect that state value oscillates about usually makes to work as ev、edWhen larger, lesser K is takend；Work as ev、edWhen smaller, take biggish
Kd；Specific fuzzy control rule is detailed in table one, two and three；
The Proportional coefficient K of one PID of tablepFuzzy control table
The Proportional coefficient K of two PID of tableiFuzzy control table
The differential coefficient K of three PID of tabledFuzzy control table
Input revolver servo motor revolving speed deviation evWith steering deviation ed, export proportionality coefficient, the proportion integral modulus of PID
And differential coefficient, proportionality coefficient, proportion integral modulus and differential coefficient carry out defuzzification with height method, input PID controller
The duty ratio for carrying out PWM compensates control, controls formula are as follows:After discretization
It obtains:
U (k)=Δ Kpe(k)+ΔKi∑e(k)+ΔKd[e(k)-e(k-1)]
When deviation occurs in left driving wheel travel track, and revolver servo-control system needs to be adjusted, fuzzy is to it
It is corrected, when deviation occurs in right driving wheel travel track, there are driving wheel servo-control system needs to be adjusted, obscure
PID is corrected it；
When revolver servo motor and right wheel servo motor are under revolving speed same state, realized by acceleration-deceleration simultaneously pair
The control of the small vehicle speed of logistics distribution, when revolving speed is different or turns to opposite, the revolving speed by controlling servo motor is realized to object
The control for flowing distribution trolley direction is adjusted, by the tune constantly recycled by revolving speed to left and right driving wheel and steering
It is whole, logistics distribution trolley is run on the right track.The corresponding speed of servo-system is fast, and synchronism is high.
Although the embodiments of the present invention have been disclosed as above, but its is not only in the description and the implementation listed
With it can be fully applied to various fields suitable for the present invention, for those skilled in the art, can be easily
Realize other modification, therefore without departing from the general concept defined in the claims and the equivalent scope, the present invention is simultaneously unlimited
In specific details and legend shown and described herein.
Claims (8)
1. a kind of servo synchronization control system suitable for monocular vision logistics distribution trolley characterized by comprising
Monitoring system is used to monitor the operating status of the logistics distribution trolley；
Master control system, input terminal are electrically connected with the output end of the monitoring system；
Position Fixing Navigation System, output end are electrically connected with the input terminal of the master control system；
Hoisting system, output end are electrically connected with the input terminal of the master control system；
Servo-system, and institute master control system is two-way is electrically connected, and the servo-system can receive the master control system transmitting
Command signal adjusts operating status and run signal is fed back to the master control system.
2. the servo synchronization control system according to claim 1 suitable for monocular vision logistics distribution trolley, feature
It is, the monitoring system includes: camera, acceleration transducer, velocity sensor and gravity sensor.
3. the servo synchronization control system according to claim 2 suitable for monocular vision logistics distribution trolley, feature
It is, the servo-system includes: revolver servo-control system and right wheel servo-control system, respectively to a logistics distribution trolley left side
The driving wheel of right two sides is controlled.
4. the servo synchronization control system according to claim 3 suitable for monocular vision logistics distribution trolley, feature
It is,
The revolver servo-control system includes: left servo drive motor and left driving wheel, and the left servo drive system passes through
Left servo drive motor controls the speed and steering of the left driving wheel；
The right wheel servo-control system includes: right servo drive motor and right driving wheel, and the right servo drive system passes through
Right servo drive motor controls the speed and steering of the right driving wheel.
5. a kind of servo synchronization control method suitable for monocular vision logistics distribution trolley, any one using claim 1-4
The servo synchronization control system suitable for monocular vision logistics distribution trolley described in, which is characterized in that specifically include:
Step 1: target information is input in master control system, and the location information in the Position Fixing Navigation System is read, exported
The target travel track of the logistics distribution trolley travelling；
Step 2:, according to the period, acquiring the travel speed V, acceleration a and front object of logistics distribution trolley by monitoring system
The distance between body d, lift height H and the gravity G lifted；
Step 3: successively the parameter of acquisition is normalized, determine that the input layer vector of three layers of BP neural network is x=
{x1,x2,x3,x4,x5}；Wherein, x1For velocity coeffficient, x2For acceleration factor, x3For with the distance between objects in front coefficient,
x4For lift height coefficient, x5The gravity coefficient lifted；
Step 4: the input layer DUAL PROBLEMS OF VECTOR MAPPING is to middle layer, the middle layer vector y={ y1,y2,…,ym}；M is middle layer
Node number；
Step 5: obtaining output layer vector o={ o1,o2}；o1For revolver servo-control system adjustment signal, o2For right wheel servo control
System call interception signal processed；
Wherein, it when two driving motors are in revolving speed same state, is realized by acceleration and deceleration simultaneously to the small speed of logistics distribution
The control of degree is realized when two driving motor revolving speeds are different or turn to opposite to distribution trolley direction controlling.
6. the servo synchronization control method according to claim 5 suitable for monocular vision logistics distribution trolley, spy exists
In the safe distance between the logistics distribution trolley and objects in front is d0, set d >=d0, d0Empirical equation are as follows:
Wherein, σ is correction coefficient,For logistics distribution trolley setting speed, t is logistics distribution trolley travelling time, H0For setting
Lift height, G0For the gravity for lifting object of setting, e is the natural logrithm truth of a matter, r1For the revolving speed of revolver driving motor, r2For
The revolving speed of right wheel driving motor, λ1For first constant relevant to logistics distribution trolley, λ1=0.76~0.92, λ2For with logistics
The relevant second constant of distribution trolley, λ2=0.95~1.20.
7. the servo synchronization control method according to claim 6 suitable for monocular vision logistics distribution trolley, feature
It is, the revolver servo-control system and the right wheel servo-control system pass through Fuzzy PID and match to logistics
It send the travel track of trolley to be corrected, specifically includes:
By the revolving speed r of preset servo motor and turn to turn of the d with the servo motor in the practical traveling process of logistics distribution trolley
Fast r and turn to d be compared, by fuzzy PID control method to logistics distribution trolley traveling proceduredriven motor duty
Than compensating.
8. the servo synchronization control method according to claim 7 suitable for monocular vision logistics distribution trolley, feature
It is, the Fuzzy PID specifically includes:
In fuzzy controller the deviation of input speed, turn to deviation, export the proportionality coefficient of PID, proportion integral modulus and micro-
Divide coefficient, the duty ratio that proportionality coefficient, proportion integral modulus and differential coefficient input PID controller carry out PWM compensates control；
Proportionality coefficient, proportion integral modulus and the differential coefficient of the output PID is divided into 7 grades；
The fuzzy set of the fuzzy controller output and input is { NB, NM, NS, 0, PS, PM, PB }.
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Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201818317U (en) * | 2010-09-21 | 2011-05-04 | 吉林大学 | Duct piece intelligent assembling system of shield tunnelling machine |
| CN102497156A (en) * | 2011-12-27 | 2012-06-13 | 东南大学 | Neural-network self-correcting control method of permanent magnet synchronous motor speed loop |
| EP2659697A1 (en) * | 2010-12-30 | 2013-11-06 | Telecom Italia S.p.A. | Method for the prediction of coverage areas of a cellular network |
| CN103454919A (en) * | 2013-08-19 | 2013-12-18 | 江苏科技大学 | Motion control system and method of mobile robot in intelligent space |
| CN104298165A (en) * | 2014-09-19 | 2015-01-21 | 西北农林科技大学 | PLC control system of orchard working platform |
| CN105741637A (en) * | 2016-02-01 | 2016-07-06 | 辽宁工业大学 | Four-wheel hub motor electric automobile intelligent steering control method |
| CN205691058U (en) * | 2016-03-03 | 2016-11-16 | 华北电力大学（保定） | A kind of device of remote moving object elevation carrection based on machine vision |
| CN107065881A (en) * | 2017-05-17 | 2017-08-18 | 清华大学 | A kind of robot global path planning method learnt based on deeply |
| CN107193281A (en) * | 2017-06-02 | 2017-09-22 | 吉林大学珠海学院 | A kind of intelligent vehicle-carried label A GV control systems and its control method |
| CN107673276A (en) * | 2017-09-26 | 2018-02-09 | 林德（中国）叉车有限公司 | A kind of fork truck maximum lift height method for limiting and system |
| CN108292141A (en) * | 2016-03-01 | 2018-07-17 | 深圳市大疆创新科技有限公司 | Method and system for target following |
| CN108482481A (en) * | 2018-03-21 | 2018-09-04 | 辽宁工业大学 | Four motorized wheels and the four-wheel steering control method for turning to electric vehicle |
| CN108523756A (en) * | 2018-04-17 | 2018-09-14 | 辽宁石化职业技术学院 | A kind of clean robot and its control method |
| CN108646763A (en) * | 2018-07-18 | 2018-10-12 | 扬州大学 | A kind of autonomous driving trace tracking and controlling method |
| CN108973578A (en) * | 2018-07-23 | 2018-12-11 | 浙江大学滨海产业技术研究院 | AGV suspension flexible adjustment method based on deeply study |
| CN109319525A (en) * | 2018-11-16 | 2019-02-12 | 西安中科光电精密工程有限公司 | A kind of the intelligent heavy-load loading system and method for whole pile entrucking |
-
2019
- 2019-04-19 CN CN201910315303.5A patent/CN109947117A/en not_active Withdrawn
Patent Citations (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201818317U (en) * | 2010-09-21 | 2011-05-04 | 吉林大学 | Duct piece intelligent assembling system of shield tunnelling machine |
| EP2659697A1 (en) * | 2010-12-30 | 2013-11-06 | Telecom Italia S.p.A. | Method for the prediction of coverage areas of a cellular network |
| CN102497156A (en) * | 2011-12-27 | 2012-06-13 | 东南大学 | Neural-network self-correcting control method of permanent magnet synchronous motor speed loop |
| CN103454919A (en) * | 2013-08-19 | 2013-12-18 | 江苏科技大学 | Motion control system and method of mobile robot in intelligent space |
| CN104298165A (en) * | 2014-09-19 | 2015-01-21 | 西北农林科技大学 | PLC control system of orchard working platform |
| CN105741637A (en) * | 2016-02-01 | 2016-07-06 | 辽宁工业大学 | Four-wheel hub motor electric automobile intelligent steering control method |
| CN108292141A (en) * | 2016-03-01 | 2018-07-17 | 深圳市大疆创新科技有限公司 | Method and system for target following |
| CN205691058U (en) * | 2016-03-03 | 2016-11-16 | 华北电力大学（保定） | A kind of device of remote moving object elevation carrection based on machine vision |
| CN107065881A (en) * | 2017-05-17 | 2017-08-18 | 清华大学 | A kind of robot global path planning method learnt based on deeply |
| CN107193281A (en) * | 2017-06-02 | 2017-09-22 | 吉林大学珠海学院 | A kind of intelligent vehicle-carried label A GV control systems and its control method |
| CN107673276A (en) * | 2017-09-26 | 2018-02-09 | 林德（中国）叉车有限公司 | A kind of fork truck maximum lift height method for limiting and system |
| CN108482481A (en) * | 2018-03-21 | 2018-09-04 | 辽宁工业大学 | Four motorized wheels and the four-wheel steering control method for turning to electric vehicle |
| CN108523756A (en) * | 2018-04-17 | 2018-09-14 | 辽宁石化职业技术学院 | A kind of clean robot and its control method |
| CN108646763A (en) * | 2018-07-18 | 2018-10-12 | 扬州大学 | A kind of autonomous driving trace tracking and controlling method |
| CN108973578A (en) * | 2018-07-23 | 2018-12-11 | 浙江大学滨海产业技术研究院 | AGV suspension flexible adjustment method based on deeply study |
| CN109319525A (en) * | 2018-11-16 | 2019-02-12 | 西安中科光电精密工程有限公司 | A kind of the intelligent heavy-load loading system and method for whole pile entrucking |
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