CN105892406A - Teaching device for intelligent evaluation of open-type motion control experiment - Google Patents
Teaching device for intelligent evaluation of open-type motion control experiment Download PDFInfo
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- CN105892406A CN105892406A CN201610288316.4A CN201610288316A CN105892406A CN 105892406 A CN105892406 A CN 105892406A CN 201610288316 A CN201610288316 A CN 201610288316A CN 105892406 A CN105892406 A CN 105892406A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/414—Structure of the control system, e.g. common controller or multiprocessor systems, interface to servo, programmable interface controller
- G05B19/4141—Structure of the control system, e.g. common controller or multiprocessor systems, interface to servo, programmable interface controller characterised by a controller or microprocessor per axis
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/34—Director, elements to supervisory
- G05B2219/34282—Using special api's allowing user access to control machine, motion, servo
Abstract
The invention discloses a teaching device for intelligent evaluation of an open-type motion control experiment. A constituent connecting structure of the device is characterized in that a micro computer is connected to a graphic display, a data storage device, a data transmission interface, an MODBUS interface and the like respectively; and the assemblies constitute an open-type motion controller. An upper computer comprises an intelligent evaluation design module and a testing case design module; and the open-type motion controller comprises an intelligent evaluation module and a testing case execution module. Intelligent evaluation of the controller comprises the steps that a servo control algorithm designed by a user is executed; a performance monitoring signal of the control algorithm is generated; and the testing case execution module automatically operates each testing case and the like in sequence. The intelligent evaluation module carries out real-time evaluation, obtains itemized evaluation indexes and comprehensive evaluation indexes of the servo control algorithm, takes the indexes as evaluation results and displays the results. The device disclosed by the invention has the advantages that intelligent, automatic and objective evaluation can be carried out to effects of the motion control experiment according to operating data. The device is open, easy-to-use and visual, etc.
Description
Technical field
The invention belongs to technical field of mechanical automation, be specifically related to and the experimental teaching unit of motor control class correlated curriculum.
Background technology
Movement control technology is one of core technology of modern industry, the automatization of institution of higher learning, electrical engineering, machine-building,
Precision instrument etc. specialty undergraduate and graduate teaching in, relate to multiple course relevant to motor control, as " SERVO CONTROL ",
" Numeric Control Technology ", " robot control " etc..Owing to movement control technology has the strongest practicalness, therefore experiment link is this
The important component part of class course, develop corresponding experimental teaching equipment be cultivate outstanding personnel must one of obligato means.
The most current existing motor control experimental teaching equipment generally has the disadvantage that what student experimenting was produced effects by (1)
The assessment method that result neither one is comprehensive, the evaluation to experiment grade too much relies on teacher's experience；(2) the experiment dress utilized
Putting the requirement that cannot meet open and ease for use, artificial Teaching validity is too much, limits carrying out of creative experiments；(3) lack
Weary automatization, intelligentized measuring technology and executive means, it is difficult to quick, comprehensive assessment controls effect.Based on this, the present invention
Device and the proposition of experimental technique, can receive good effect to the practice of above-mentioned course.
Summary of the invention
It is an object of the invention to, propose a kind of intelligence test and appraisal Open motion control experimental teaching unit, to solve to move at present control
The several functions defect of experimental teaching equipment device processed.
Technical scheme is as follows: intelligence test and appraisal Open motion control experimental teaching unit has: host computer, N group are driven
Dynamic device and motor, motion body, sensor group, open-type motion module, control algorithm design module, control
Emulation module, control program generating module, intelligence test and appraisal design module, Test Sample Design module, communication service module, open
Put formula servo control module, data acquiring and recording module, data display module, Intelligent testing discuss and select model workers block and test case performs
Module etc..
Wherein open-type motion has: microcontroller, pictorial displays, data storage, control download program interface,
Data transmission interface, D/A interface, encoder interfaces, A/D interface, I/O interface and MODBUS interface.Drive system
Including N set drive and motor and motion body.
Its system composition is: open-type motion module constitutes tandem mode with drive system and sensor group.Host computer
Being connected with open-type motion, host computer is provided with experimental development environment (22), and open-type motion module is run really
Time TT&C system.
Experimental development environment includes: control algorithm design module, control emulation module, control program generating module, intelligence test and appraisal
Design module, Test Sample Design module and the first communication service module.
Real-time includes: open servo control module, data acquiring and recording module, data display module, Intelligent testing
Block, the test case of discussing and select model workers performs module and the second communication service module.
The operation method of above-mentioned intelligence test and appraisal Open motion control experimental teaching unit, is carried out intelligence by open-type motion
Test and appraisal, the operation of open-type motion comprises the steps of
S1: start described open servo control module, performs the servo control algorithm of user's design；SERVO CONTROL is calculated simultaneously
The execution time of method and EMS memory occupation monitor, produce control algolithm performance monitoring signal.
S2: start described test case and perform module, the most automatically run each test case.
S3: utilize described data acquiring and recording module to obtain from position in described sensor group, electric current, temperature sensor anti-
Feedback, produces outside monitoring signal；Read motor command signal, servo control algorithm internal state variable, internal drive simultaneously
The data such as state, produce internal control signal.
S4: comprehensive internal control signal, outside monitoring signal and control algolithm performance monitoring signal, discussed and select model workers block by described Intelligent testing
Test and assess in real time, obtain subitem evaluation index and the comprehensive evaluation index of servo control algorithm, as evaluating result.
S5: after test case is finished, data display module shows evaluating result automatically.
Above-mentioned Intelligent testing block of discussing and select model workers includes that the real-time computing engines of characteristic index, feature extraction Support Library and assessment indicator calculate network,
Assessment indicator calculates network portion and uses the complete three layers of feedforward linear neural fusion connected: ground floor is input layer, the second layer
Evaluating layer for subitem, third layer is overall merit layer；Subitem evaluation index and the mistake of comprehensive evaluation index is calculated described in step S4
Journey, comprises the following steps:
S41: read the internal control signal needed, outside monitoring signal and control algolithm performance monitoring signal.
The real-time computing engines of S42: characteristic index calls the feature extraction algorithm defined in feature extraction Support Library, according to step S41
The signal real-time online of middle reading calculates motor control test and appraisal characteristic index.
S43: the motor control calculated in step S42 test and appraisal characteristic index is input to assessment indicator and calculates the input layer joint of network
Point, the output of input layer is each motor control test and appraisal characteristic index.
S44: evaluating the weight between node layer according to input layer to subitem, the output to input layer carries out linear weighted function summation,
Calculate subitem and evaluate the output of each node of layer, obtain each subitem evaluation index.
S45: according to the weight between subitem evaluation layer to overall merit node layer, evaluates the output of layer each node and linearly adds subitem
Power summation, calculates the output of overall merit node layer, obtains comprehensive evaluation index.
Intelligence test and appraisal design module in above-mentioned host computer experimental development environment, discusses and select model workers to the Intelligent testing in open-type motion
Block configures, and configuration process comprises the steps of
S101: set the monitoring of inside and outside portion signal, the control algolithm performance monitoring signal needing record.
S102: select the algorithm in feature extraction Support Library, the real-time computing engines of configuration feature index.
S103: set assessment indicator and calculate the weight coefficient of network.
Having the active effect that of advantages of the present invention and generation
(1) can realize motor control experiment effect is carried out the test and appraisal of intellectuality, automatization based on actual operating data, can be fast
Speed, reflect the effect of control algolithm objectively.With different levels evaluation methodology can make the former of student's quick analyzing influence experimental result
Cause, quickly feedback can accelerate student's trial and error, development, and the test and appraisal automatically performed decrease the impact of subjective assessment, also
Decrease the workload of teacher.
(2) this experimental provision has open, easy-to-use, advantage intuitively.Not only achieve the open by design of control algolithm, it is achieved
Making Innovation Experiments scheme, and automatic assessment method is also open configurable, can carry out self-defined according to different demands,
Improve the motility of motor control experiment.Host computer has copying, can be simulated system the most safely；Control
Device is configured with data acquisition, displaying, transfer function, makes student can observe control system inside and outside portion signal on experimental provision
State, and at host computer, experimental result can be further analysed.
Accompanying drawing explanation
Fig. 1 is that the hardware of the present invention connects block diagram.
Fig. 2 is the host computer experimental development environment module Organization Chart of the present invention.
Fig. 3 is the open-type motion real-time module rack composition of the present invention.
Fig. 4 is the intelligent assessment work schematic diagram of the present invention.
Detailed description of the invention
Below in conjunction with accompanying drawing and by embodiment, the composition of apparatus of the present invention and enforcement step are further described.Need
Bright is, and following embodiment is narrative, is not determinate, and the content that the present invention is contained is not limited to following embodiment.
As it is shown in figure 1, intelligence test and appraisal Open motion control experimental teaching unit has: host computer 11, Open motion control
Device 15, drive system and sensor group 14.Drive system include N set drive and motor 12-1,12-2 ... 12-n, with
And motion body 13.
Wherein open-type motion 15 has: microcontroller 1, pictorial displays 2, data storage 3, control program
Download interface 4, data transmission interface 5, D/A interface 6, encoder interfaces 7, A/D interface 8, I/O interface 9 and MODBUS
Interface 10.
The composition structure of apparatus of the present invention hardware and software is: open-type motion module 15 and drive system and sensor group
14 constitute tandem mode, and host computer 11 is connected with open-type motion 15.Host computer 11 is provided with experimental development environment 22,
Open-type motion module runs real-time 28.
As in figure 2 it is shown, experimental development environment includes: control algorithm design module 16, control emulation module 17, control program are raw
Become module 18, intelligence test and appraisal design module 19, Test Sample Design module 20 and the first communication service module 21-1.
As it is shown on figure 3, real-time includes: open servo control module 23, data acquiring and recording module 24, data
Display module 25, Intelligent testing discuss and select model workers block 26, test case perform module 27 and the second communication service module 21-2.
The operation method of above-mentioned intelligence test and appraisal Open motion control experimental teaching unit, is carried out intelligence by open-type motion
Test and appraisal, the operation of open-type motion comprises the steps of
S1: start open servo control module 23, performs the servo control algorithm of user's design；Simultaneously to servo control algorithm
The execution time and EMS memory occupation monitor, produce control algolithm performance monitoring signal.
S2: start test case and perform module 27, the most automatically run each test case.
S3: utilize data acquiring and recording module 24 to obtain in described sensor group 14 position, electric current, temperature sensor
Feedback, produces outside monitoring signal；Read in motor command signal, servo control algorithm internal state variable, driver simultaneously
The data such as portion's state, produce internal control signal.
S4: comprehensive internal control signal, outside monitoring signal and control algolithm performance monitoring signal, entered by Intelligent testing block 26 of discussing and select model workers
Row test and appraisal in real time, obtain subitem evaluation index and the comprehensive evaluation index of servo control algorithm, as evaluating result.
S5: after test case is finished, data display module 25 shows evaluating result automatically.
Intelligent testing block 26 of discussing and select model workers includes that the real-time computing engines of characteristic index, feature extraction Support Library and assessment indicator calculate network, surveys
Comment index to calculate network portion and use the complete three layers of feedforward linear neural fusion connected: ground floor is input layer, and the second layer is
Subitem evaluates layer, and third layer is overall merit layer.
Above-mentioned steps S4 is fallen into a trap point counting item evaluation index and the process of comprehensive evaluation index, comprises the following steps:
S41: read the internal control signal needed, outside monitoring signal and control algolithm performance monitoring signal.
The real-time computing engines of S42: characteristic index calls the feature extraction algorithm defined in feature extraction Support Library, according to step S41
The signal real-time online of middle reading calculates motor control test and appraisal characteristic index.
S43: the motor control calculated in step S42 test and appraisal characteristic index is input to assessment indicator and calculates the input layer joint of network
Point, the output of input layer is each motor control test and appraisal characteristic index.
S44: evaluating the weight between node layer according to input layer to subitem, the output to input layer carries out linear weighted function summation,
Calculate subitem and evaluate the output of each node of layer, obtain each subitem evaluation index.
S45: according to the weight between subitem evaluation layer to overall merit node layer, evaluates the output of layer each node and linearly adds subitem
Power summation, calculates the output of overall merit node layer, obtains comprehensive evaluation index.
Intelligence test and appraisal design module 19 in host computer experimental development environment, to the intelligence test and appraisal in open-type motion 15
Module 26 configures.Intelligence test and appraisal design module builds based on Matlab script, for teacher according to experiment demand to opening
Intelligent testing in formula motion controller block of discussing and select model workers configures, and configuration process comprises the steps of
S101: set the monitoring of inside and outside portion signal, the control algolithm performance monitoring signal needing record.
Internal control signal can comprise motor command signal, control algolithm internal state variable and internal drive state etc.；
Outside monitoring signal is the sensor signals such as code device signal, electric current, torque, temperature；Control algolithm performance monitoring signal packet contains
The execution time of control algolithm and EMS memory occupation.
S102: select the algorithm in feature extraction Support Library, the real-time computing engines of configuration feature index.
Characteristics extraction Support Library comprises various real-time computing function, as meansigma methods, variance yields, root-mean-square value, maximin,
Power, rise time, adjustment time, overshoot, steady-state error, tracking error, the calculating function of profile errors.
S103: set assessment indicator and calculate the weight coefficient of network.
Weight coefficient can directly be specified, it is possible to is learnt expert analysis mode experience by neural network BP training algorithm, automatically gives birth to
Become coefficient.
The configuration completed is converted to C programmer and C language constant array by Matlab Coder, and joins motor control
In the control program engineering of device.
As embodiment: motion body uses X-Y twin shaft rectangular coordinate motion platform, therefore N=2.Motion body
On position sensor, current sensor, torque sensor and temperature sensor are installed.Host computer uses desktop PC, motor
And driver uses permanent-magnet alternating current servo motor and the supporting driver with analog input control mode.
As it is shown in figure 1, the concrete connection scheme of each parts is: the microcontroller 1 in open-type motion 15 total by it
Line is connected with other hardware modules of open-type motion.Control download program interface 4 and use JTAG DLL, upper
Machine 11 is connected with controlling download program interface, for updating the motion control program of controller.Data transmission interface 5 uses RS-232
Interface, host computer is connected with data transmission interface, for data such as controller and host computer exchange motor control state, parameters.
The digital signal of controller is converted into analogue signal by D/A interface 6, as the instruction of each group of motor, respectively with X-axis and Y-axis
Driver and motor 12-1,12-2 dummy instruction input port connect.X-axis and the driver of Y-axis and motor are respectively connected to
Motion body 13 (i.e. X-Y twin shaft rectangular coordinate motion platform), the analog signals that D/A interface exports is put by driver
Greatly, drive motor rotation, produce output torque, drive this running body of motion.By position sensor, current sensor,
Torque sensor and temperature sensor composition sensor group 14, its Position Sensor is arranged on and is connected to motion body X
With in Y-axis, use photoelectric encoder output orthogonal coding signal, be connected with open-type motion by encoder interfaces 7.
Current sensor, torque sensor are arranged on motor, and temperature sensor is arranged on kinematic pair, and electric current, torque and temperature pass
Sensor all uses analog signal output, is connected with open-type motion by A/D interface 8.I/O interface 9 is connected to 2
The positive and negative limit switch signal of X-Y axle on enable signal, alarm signal and the motion body of platform driver.MODBUS connects
Mouth 10 driver connected MODBUS interfaces, form MODBUS bus, for read write drive internal state and parameter.
Host computer experimental development environment is built based on Windows 7, for supporting the operation of each software module of host computer.
Control algorithm design module 16 uses the modelling function of Simulink software, is applicable to out for student resource design
Put the control algolithm of formula motion controller, with the special purpose interface of motion controller, support patterned programmed method.
Control emulation module 17 and use the model emulation function of Simulink, and devise driver, motor and motion originally
The phantom of body, by calling the control algolithm of student resource design, can be simulated emulation testing to control algolithm, use
Feasibility in verification algorithm.
Control program generating module 18 Coder based on Matlab software function, for the control algolithm designed being compiled as
The motion control program can run on the microprocessor of open-type motion, containing promising with open-type motion be
The automatic Compiling System special configuration file of target platform.The control algolithm of design, after inspection, first passes through Matlab Coder
It is automatically converted to C programmer.The C programmer of conversion will be comprised in the control program engineering of motion controller.
Test Sample Design module 20 builds based on Matlab script, multiple permissible according to experiment Demand Design for teacher
The exercise test use-case of automated execution on motion controller.
Test case 1.Test X-axis (being driver, 1 group of place axle of motor in the present embodiment) speed ring response characteristic index, tool
Body constructs the Velocity Step Technique input test use-case of X-axis, speed by static after 1 second postpones step to 100mm/s, exist simultaneously
Test and appraisal module is arranged in test case 1 collection X-axis actual speed signal, and calculates rise time, adjustment time, overshoot
Amount, the concrete numerical value of steady-state error.
Test case 2.Test Y-axis (being driver, 2 groups of place axles of motor in this example) speed ring response characteristic index, with X
Axle speed ring response test principle is consistent.
Test case 3.The lower robust motion index of test straight line linkage, test case is the straight line from coordinate (0,0) to (100,100)
Motion command, in test and appraisal module, configuration gathers the peak acceleration in actual motion, acceleration as riding index.
Test case 4.Profile errors in test circular motion, test case is the circle of central coordinate of circle (50,0) radius 50
Track, in test and appraisal module, configuration gathers the profile errors between actual path and instruction track.
Test case is finally automatically converted to C programmer by Matlab Coder, and adds the control program work of motion controller
Journey.
First communication service module 21-1 is used for and open-type motion communication, downloads compiled control software, and reads
Write the controlled state of open-type motion, supplemental characteristic.First download function calls the C language compiler of single-chip microcomputer, will
Ready program compiling in the control program engineering of motion controller, link are converted to binary image file, then by control
Image file is downloaded in open-type motion 15 by processing procedure sequence download interface 4, completes to control software upgrading work.State
Communicated with open-type motion by data transmission interface 5 with parameter reading and writing function, read-write record controlled state,
The data such as parameter.
In open-type motion, real-time 28 is for supporting the operation of each software model.Real-time
Motion controller single-chip microcomputer and each hardware module are initialized, then starts master control circulation, at this by recursive call in circulation
Each software model.
Open servo control module 23 performs the control algolithm in host computer design in real time, and to execution time of control algolithm and
EMS memory occupation monitors, produces control algolithm performance monitoring signal.It is converted into the control after C language calculates by calling host computer
Method, can realize student and design the real-time execution of control algolithm.When can monitor the execution of control algolithm when calling control algolithm
Between and EMS memory occupation situation, generate control algolithm performance monitoring signal.
Data acquiring and recording module 24 is for the internal control signal of Real-time Collection open-type motion with from sensor group
Monitoring signal outside.Data acquiring and recording module is fixing C programmer, generates according to intelligence test and appraisal design module 19
C language constant array, it is thus achieved that configuration information, the internal signal needed according to configuration information Real-time Collection and external signal, go forward side by side
Row record.
Data display module 25 is used for the most graphically or numeric form display signal condition, supplemental characteristic and intelligence
Can evaluating result.Data display module has numerical value to show, waveform shows, evaluating result shows three kinds of interfaces.Boundary is shown at numerical value
Under face, signal and supplemental characteristic show according to digital form；Under waveform display interface, signal data is plotted as numerical value and time
The wavy curve of relation；Under evaluating result display interface, show that the subitem of servo control algorithm is commented with numeral and block diagram mode
Valency index and comprehensive evaluation index.
Intelligent testing discuss and select model workers block 26 according to design at host computer intelligence test and appraisal configuration, intelligent online survey is carried out for motion control arithmetic
Comment.
As shown in Figure 4, Intelligent testing block of discussing and select model workers includes the real-time computing engines of characteristic index, feature extraction Support Library and assessment indicator meter
Calculating network, assessment indicator calculates network portion and uses the complete three layers of feedforward linear neural fusion connected: ground floor is input layer,
The second layer evaluates layer for subitem, and third layer is overall merit layer.
Being numbered by each for neutral net node layer, each node serial number of input layer is a1、a2……am, subitem evaluates node layer
For b1、b2……bn, overall merit node layer numbering c1.Weight coefficient between each node layer is numbered, from input layer ai
(i=1,2 ...) arrive to itemize and evaluate the node b of layerj(j=1,2 ...) the numbered w of weightsij, evaluate layer from subitem
Node bj(j=1,2 ...) arrive overall merit node layer c1The numbered v of weightsj。
The C language constant array that between neutral net each node layer, weight coefficient generates from intelligence test and appraisal design module 19 reads.Respectively
Weight coefficient can be positive and negative or 0, and the intelligence test and appraisal design module in upper computer software determines have and directly specify and training
Two ways.When directly specifying, teacher's definable subitem evaluates the implication of layer each node output, such as b in this example1、b2、
b3The most corresponding performance evaluation of the output of node, efficiency rating and reliability evaluation.
Weight can be set by teacher according to experiment demand, makes subitem evaluation and comprehensive evaluation result have for different experiments target
Stressed.In in the way of obtaining network weight by training, will be able to have using subitem evaluation layer as the hidden layer of neutral net
The expert of the experience mark to being given under different Control performance standard combinations, as training sample, uses BP (back propagation) algorithm
Neutral net is trained, obtains weights, thus allow neutral net automatically learn the principle to expert analysis mode.
In step S4, Intelligent testing block of discussing and select model workers calculates subitem evaluation index and the process of comprehensive evaluation index farther includes following step
Rapid:
S41: read the internal control signal needed, outside monitoring signal and control algolithm performance monitoring signal.
The inside and outside portion monitoring signal of record, the configuration information of control algolithm performance monitoring signal is needed to design module from intelligence test and appraisal
The C language constant array generated in 19 reads.
The real-time computing engines of S42: characteristic index calls the feature extraction algorithm defined in feature extraction Support Library, according to step S41
The signal real-time online of middle reading calculates motor control test and appraisal characteristic index.
The C language constant array that the configuration information of the real-time computing engines of characteristic index generates from intelligence test and appraisal design module (19) is read
Take.The motor control test and appraisal characteristic index used in the present embodiment includes:
Precision index: X-Y axle speed responsive steady-state error, X-Y axle position error, X-Y axle resetting error, X-Y axle
Tracking error meansigma methods, X-Y axle tracking error variance value, profile errors meansigma methods, profile errors variance yields.
Loss objective: motion operation time, energy expenditure, maximum instantaneous torque
Riding index: peak acceleration, maximum acceleration, the step response number of oscillation
Response index: Velocity Step Technique response rise time, Velocity Step Technique response adjustment time, Velocity Step Technique response overshoot
Algorithm index: the average CPU holding time of control algolithm, the maximum memory occupancy of control algolithm
Other indexs: kinematic pair temperature rise
S43: the motor control calculated in step S42 test and appraisal characteristic index is input to assessment indicator and calculates the input layer joint of network
Point, the output of input layer is each motor control test and appraisal characteristic index.
S44: evaluating the weight between node layer according to input layer to subitem, the output to input layer carries out linear weighted function summation,
Calculate subitem and evaluate the output of each node of layer, obtain each subitem evaluation index.
Assume that each evaluation index numerical value being connected to input layer is xi, then the output y of each node of subitem evaluation layerjCan be by following formula meter
Calculate
S45: according to the weight between subitem evaluation layer to overall merit node layer, evaluates the output of layer each node and linearly adds subitem
Power summation, calculates the output of overall merit node layer, obtains comprehensive evaluation index.
The output z of each node of overall merit layer1Can be calculated by following formula
Test case performs module 27 and surveys for the every motion being performed automatically in host computer Test Sample Design module 20 design
Example on probation.In the present embodiment, test case performs module 27 and calls in order and designed by host computer Test Sample Design module
Test case 1～4, it is achieved automatic test.
Second communication service module 21-2 is used for and host computer communication, downloads compiled control software, and transmits open fortune
The data such as the controlled state of movement controller, parameter.First download function wipes the original control in the internal flash storage of single-chip microcomputer
Processing procedure sequence, then sets up with host computer and is connected.The control software new by controlling download program interface, and write single-chip microcomputer
Internal flash storage.Motion control data read-write capability can carry out communication by data transmission interface and host computer, uploads
The data collected or read-write parameter.
After completing to control software upgrading, open-type motion can be in the support of the motion control arithmetic of student resource design
The lower a series of test cases automatically performing teacher's design.During this period, position sensor, current sensor and temperature can be obtained
The data such as sensor reading, motor command signal, internal drive state and the state variable within control algolithm, and carry out
Show and transmission, and by Intelligent testing discuss and select model workers block to control effect test and assess in real time.After end of run, Intelligent testing is discussed and select model workers block
Evaluating result will be given, and result immediate feedback will be given the teachers and students participating in experiment.It can be seen that the intelligence test and appraisal that the present invention proposes
Open motion control experimental teaching unit achieves the automatization to control algolithm, intelligentized quick, objective evaluation, simultaneously
Possesses open, flexible, easy-to-use, advantage intuitively, it is possible to greatly improve the teaching efficiency of conventional motion Control release course.
Claims (4)
1. intelligence test and appraisal Open motion control experimental teaching unit, has: host computer, N set drive and motor, fitness machine
Structure body, sensor group, open-type motion, control algorithm design module, control emulation module, control Program Generating
Module, intelligence test and appraisal design module, Test Sample Design module, communication service module, open servo control module, data
Discuss and select model workers block and test case of acquisition and recording module, data display module, Intelligent testing performs module, the most open motion control
Utensil processed has: microcontroller (1), pictorial displays (2), data storage (3), control download program interface (4), number
According to coffret (5), D/A interface (6), encoder interfaces (7), A/D interface (8), I/O interface (9) and MODBUS
Interface (10), drive system includes N set drive and motor (12-1,12-2 ... 12-n) and motion body (13),
It is characterized in that: open-type motion constitutes tandem mode, host computer (11) with drive system and sensor group (14)
Being connected with open-type motion (15), host computer is provided with experimental development environment (22), and open-type motion is run
Real-time (28), experimental development environment includes: control algorithm design module (16), control emulation module (17), control
Program generating module processed (18), intelligence test and appraisal design module (19), Test Sample Design module (20) and the first communication clothes
Business module (21-1)；Real-time includes: open servo control module (23), data acquiring and recording module (24),
Discuss and select model workers block (26), test case of data display module (25), Intelligent testing performs module (27) and the second communication service module
(21-2)。
2. according to an operation method for intelligence test and appraisal Open motion control experimental teaching unit, its feature described in claim 1
It is: being carried out intelligence test and appraisal by described open-type motion, the operation of open-type motion comprises the steps of
S1: start described open servo control module (23), performs the servo control algorithm of user's design；Simultaneously to servo control
The execution time of algorithm processed and EMS memory occupation monitor, produce control algolithm performance monitoring signal；
S2: start described test case and perform module (27), the most automatically run each test case；
S3: utilize described data acquiring and recording module (24) to obtain from position, electric current, temperature in described sensor group (14)
The feedback of degree sensor, produces outside monitoring signal；Read simultaneously motor command signal, servo control algorithm internal state variable,
The data such as internal drive state, produce internal control signal；
S4: comprehensive internal control signal, outside monitoring signal and control algolithm performance monitoring signal, discussed and select model workers block by described Intelligent testing
(26) test and assess in real time, obtain subitem evaluation index and the comprehensive evaluation index of servo control algorithm, as evaluating result；
S5: after test case is finished, data display module (25) shows evaluating result automatically.
3. according to the operation method of intelligence test and appraisal Open motion control experimental teaching unit described in claim 2, it is characterised in that:
Described Intelligent testing block (26) of discussing and select model workers includes that the real-time computing engines of characteristic index, feature extraction Support Library and assessment indicator calculate net
Network, assessment indicator calculates network portion and uses the complete three layers of feedforward linear neural fusion connected: ground floor is input layer, the
Evaluating layer for subitem for two layers, third layer is overall merit layer；Subitem evaluation index and comprehensive evaluation index is calculated described in step S4
Process, comprise the following steps:
S41: read the internal control signal needed, outside monitoring signal and control algolithm performance monitoring signal；
The real-time computing engines of S42: characteristic index calls the feature extraction algorithm defined in feature extraction Support Library, according to step S41
The signal real-time online of middle reading calculates motor control test and appraisal characteristic index；
S43: the motor control calculated in step S42 test and appraisal characteristic index is input to assessment indicator and calculates the input layer joint of network
Point, the output of input layer is each motor control test and appraisal characteristic index；
S44: evaluating the weight between node layer according to input layer to subitem, the output to input layer carries out linear weighted function summation,
Calculate subitem and evaluate the output of each node of layer, obtain each subitem evaluation index；
S45: according to the weight between subitem evaluation layer to overall merit node layer, evaluates the output of layer each node and linearly adds subitem
Power summation, calculates the output of overall merit node layer, obtains comprehensive evaluation index.
4. according to the operation method of intelligence test and appraisal Open motion control experimental teaching unit described in claim 2, it is characterised in that:
Intelligence test and appraisal design module (19) in described host computer experimental development environment, described in open-type motion (15)
Intelligent testing block (26) of discussing and select model workers configures, and configuration process comprises the steps of
S101: set the monitoring of inside and outside portion signal, the control algolithm performance monitoring signal needing record；
S102: select the algorithm in feature extraction Support Library, the real-time computing engines of configuration feature index；
S103: set assessment indicator and calculate the weight coefficient of network.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1916578A1 (en) * | 2006-10-24 | 2008-04-30 | Triphase NV | A system for real-time process control |
| CN101567136A (en) * | 2009-01-21 | 2009-10-28 | 上海广茂达伙伴机器人有限公司 | Automatic control test device based on robot platform |
| CN102147987A (en) * | 2011-04-18 | 2011-08-10 | 中国人民解放军国防科学技术大学 | Teaching experiment device for aircraft navigation, guidance and control technology |
| CN102830629A (en) * | 2012-08-29 | 2012-12-19 | 东北大学 | Testing device and method of power electronic control system |
| CN103488126A (en) * | 2013-09-30 | 2014-01-01 | 天津市中环电子计算机有限公司 | Multi-axis motion control system development platform |
| US9114529B2 (en) * | 2012-03-08 | 2015-08-25 | Nanjing Estun Robotics Co. Ltd | Dual-system component-based industrial robot controller |
-
2016
- 2016-05-03 CN CN201610288316.4A patent/CN105892406B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1916578A1 (en) * | 2006-10-24 | 2008-04-30 | Triphase NV | A system for real-time process control |
| CN101567136A (en) * | 2009-01-21 | 2009-10-28 | 上海广茂达伙伴机器人有限公司 | Automatic control test device based on robot platform |
| CN102147987A (en) * | 2011-04-18 | 2011-08-10 | 中国人民解放军国防科学技术大学 | Teaching experiment device for aircraft navigation, guidance and control technology |
| US9114529B2 (en) * | 2012-03-08 | 2015-08-25 | Nanjing Estun Robotics Co. Ltd | Dual-system component-based industrial robot controller |
| CN102830629A (en) * | 2012-08-29 | 2012-12-19 | 东北大学 | Testing device and method of power electronic control system |
| CN103488126A (en) * | 2013-09-30 | 2014-01-01 | 天津市中环电子计算机有限公司 | Multi-axis motion control system development platform |
Non-Patent Citations (2)
| Title |
|---|
| 周春华: "基于开放式数控系统的综合实验平台的研究与开发", 《中国优秀硕士学位论文全文数据库 工程科技Ⅰ辑（月刊）》 * |
| 杨青 等: "基于LabVIEW的综合测试柜在创新实验中的应用", 《机械设计》 * |
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