CN105892406B - Intelligence test and appraisal Open motion control experimental teaching unit - Google Patents
Intelligence test and appraisal Open motion control experimental teaching unit Download PDFInfo
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- CN105892406B CN105892406B CN201610288316.4A CN201610288316A CN105892406B CN 105892406 B CN105892406 B CN 105892406B CN 201610288316 A CN201610288316 A CN 201610288316A CN 105892406 B CN105892406 B CN 105892406B
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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 kind of intelligence test and appraisal Open motion control experimental teaching unit, composition connection structure is：Microcontroller is connected to graphic alphanumeric display, data storage, data transmission interface and MODBUS interfaces etc. respectively, and constitutes open-type motion by said modules.Host computer contains intelligence test and appraisal design module and Test Sample Design module, and open-type motion, which contains intelligent testing, discusses and select model workers block and test case execution module.Intelligently test and appraisal comprise the steps of controller：Execute the servo control algorithm of user's design；Generate control algolithm performance monitoring signal；Test case execution module each test case of automatic running etc. in order.It is tested and assessed in real time by intelligent testing block of discussing and select model workers, obtains the subitem evaluation index and comprehensive evaluation index of servo control algorithm, show as evaluating result and automatically.The present invention can carry out motion control experiment effect according to operation data the objective evaluation of intelligent automation.
Description
Technical field
The invention belongs to technical field of mechanical automation, and in particular to the experimental teaching with motion control class correlated curriculum
Device.
Background technology
Movement control technology is one of core technology of modern industry, in the automation of institution of higher learning, electrical engineering, machinery
In the undergraduate and graduate teaching of the profession such as manufacture, precision instrument, it is related to the multiple and relevant course of motion control, such as《It watches
Clothes control》,《Numeric Control Technology》,《Robot controls》Deng.Since movement control technology has very strong practicality, experimental ring
Section is the important component of this kind of course, and it is the culture indispensable hand of outstanding personnel to develop corresponding experimental teaching equipment
One of section.
Regrettably insufficient below existing motion control experimental teaching equipment generally existing at present：(1) to student experimenting
The assessment method for the result neither one synthesis produced effects, teacher's experience is excessively relied on to the evaluation of experiment grade；(2) it is utilized
Experimental provision cannot be satisfied open and ease for use requirement, and artificial Teaching validity is excessive, limits the development of creative experiments；
(3) lack automation, intelligentized measuring technology and executive means, it is difficult to quickly, fully assess control effect.Based on this, originally
The it is proposed of invention device and experimental method can receive good effect to the practice of above-mentioned course.
Invention content
The object of the present invention is to propose a kind of intelligence test and appraisal Open motion control experimental teaching unit, it is current to solve
The multiple functions defect of motion control experimental teaching equipment device.
Technical scheme is as follows：Intelligence test and appraisal Open motion control experimental teaching unit has：Host computer, N
Set drive and motor, motion ontology, sensor group, open-type motion module, control algorithm design module, control
Emulation module processed, intelligence test and appraisal design module, Test Sample Design module, communication service module, is opened control program generating module
Discuss and select model workers block and test case of formula servo control module, data acquiring and recording module, data display module, intelligent testing is put to execute
Module etc..
Wherein open-type motion has：Microcontroller, graphic alphanumeric display, data storage, control program are downloaded
Interface, data transmission interface, D/A interfaces, encoder interfaces, A/D interfaces, I/O interfaces and MODBUS interfaces.Drive system
Including N set drives and motor and motion ontology.
Its system forms：Open-type motion module constitutes tandem mode with drive system and sensor group.
Host computer is connect with open-type motion, and host computer is equipped with experimental development environment, the operation of open-type motion module
Real-time.
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, intelligence
Can test and assess module, test case execution module and the second communication service module.
It is above-mentioned intelligence test and appraisal Open motion control experimental teaching unit operation method, by open-type motion into
Row intelligence test and appraisal, the operation of open-type motion comprise the steps of：
S1:Start the open servo control module, executes the servo control algorithm of user's design；Simultaneously to servo control
The execution time of algorithm processed and EMS memory occupation are monitored, control algolithm performance monitoring signal is generated.
S2:Start the test case execution module, in order each test case of automatic running.
S3:It is obtained from position, electric current, temperature sensor in the sensor group using the data acquiring and recording module
Feedback, generate external monitoring signal；Read motor command signal, servo control algorithm internal state variable, driver simultaneously
The data such as internal state generate internal control signal.
S4:Comprehensive internal control signal, external monitoring signal and control algolithm performance monitoring signal, are tested and assessed by the intelligence
Module is tested and assessed in real time, the subitem evaluation index and comprehensive evaluation index of servo control algorithm is obtained, 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 calculate network portion using the three layers of feedforward linear neural fusion connected entirely：First layer is input layer,
The second layer is subitem evaluation layer, and third layer is overall merit layer；The subitem evaluation index and overall merit are calculated in step S4
The process of index, includes the following steps：
S41:Read the internal control signal needed, external monitoring signal and control algolithm performance monitoring signal.
S42：The real-time computing engines of characteristic index call the feature extraction algorithm defined in feature extraction Support Library, according to step
The signal real-time online read in rapid S41 calculates motion control test and appraisal characteristic index.
S43：Calculated motion control test and appraisal characteristic index in step S42 is input to assessment indicator and calculates the defeated of network
Enter node layer, the output of input layer is each motion control test and appraisal characteristic index.
S44：The weight between node layer is evaluated according to input layer to subitem, linear weighted function is carried out to the output of input layer
Summation calculates the output of subitem evaluation each node of layer, obtains each subitem evaluation index.
S45：According to subitem evaluation layer to the weight between overall merit node layer, each node output of subitem evaluation layer is carried out
Linear weighted function is summed, and is calculated the output of overall merit node layer, is obtained comprehensive evaluation index.
Intelligence test and appraisal design module in above-mentioned host computer experimental development environment, to the intelligence in open-type motion
Test and appraisal module is configured, and configuration process comprises the steps of：
S101：Setting needs the inside and outside portion's monitoring signal recorded, control algolithm performance monitoring signal.
S102：Select the algorithm in feature extraction Support Library, the real-time computing engines of configuration feature index.
S103：Set the weight coefficient that assessment indicator calculates network.
Advantages of the present invention and the good effect of generation are：
(1) test and appraisal that intelligent automation is carried out to motion control experiment effect can be realized based on actual operating data,
It can quickly, objectively reflect the effect of control algolithm.With different levels evaluation method can make the quick analyzing influence experiment of student
As a result the reason of, student's trial and error, development can be accelerated by quickly feeding back, and the test and appraisal executed automatically reduce subjective assessment
It influences, decreases the workload of teacher.
(2) experimental provision has the advantages that open, easy-to-use, intuitive.The open by design of control algolithm is not only realized,
Realize Making Innovation Experiments scheme, and automatic assessment method is also open configurable, can be carried out according to different needs certainly
Definition improves the flexibility of motion control experiment.Host computer has copying, intuitively safely can carry out mould to system
It is quasi-；Controller is configured with data acquisition, displaying, transfer function, so that student is observed control system on experimental provision inside and outside
The state of portion's signal, and experimental result can be further analysed in host computer.
Description of the drawings
Fig. 1 is the hardware connection block diagram of the present invention.
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.
Specific implementation mode
It is further described below in conjunction with attached drawing and by embodiment to the composition and implementation steps of apparatus of the present invention.
It should be noted that following embodiments be descriptive and not restrictive the content that is covered of the present invention be not limited to it is following
Embodiment.
As shown in Figure 1, intelligence test and appraisal Open motion control experimental teaching unit has：Host computer 11, open movement
Controller 15, drive system and sensor group 14.Drive system include N set drives and motor 12-1,12-2 ... 12-n,
And motion ontology 13.
Wherein open-type motion 15 has：Microcontroller 1, graphic alphanumeric display 2, data storage 3, control program
Download interface 4, data transmission interface 5, D/A interfaces 6, encoder interfaces 7, A/D interfaces 8, I/O interfaces 9 and MODBUS interfaces
10。
The composed structure of apparatus of the present invention hardware and software is：Open-type motion module 15 and drive system and biography
Sensor group 14 constitutes tandem mode, and host computer 11 is connect with open-type motion 15.Host computer 11 is equipped with experimental development ring
Border 22, open-type motion module run real-time 28.
As shown in Fig. 2, experimental development environment includes：Control algorithm design module 16, control emulation module 17, control program
Generation module 18, intelligence test and appraisal design module 19, Test Sample Design module 20 and the first communication service module 21-1.
As shown in figure 3, real-time includes：Open servo control module 23, data acquiring and recording module 24, number
It discusses and select model workers block 26, test case execution module 27 and the second communication service module 21-2 according to display module 25, intelligent testing.
It is above-mentioned intelligence test and appraisal Open motion control experimental teaching unit operation method, by open-type motion into
Row intelligence test and appraisal, the operation of open-type motion comprise the steps of：
S1:Start open servo control module 23, executes the servo control algorithm of user's design；Simultaneously to SERVO CONTROL
The execution time of algorithm and EMS memory occupation are monitored, control algolithm performance monitoring signal is generated.
S2:Start test case execution module 27, in order each test case of automatic running.
S3:It is obtained from position, electric current, temperature sensor in the sensor group 14 using data acquiring and recording module 24
Feedback, generate external monitoring signal；Read motor command signal, servo control algorithm internal state variable, driver simultaneously
The data such as internal state generate internal control signal.
S4:Comprehensive internal control signal, external monitoring signal and control algolithm performance monitoring signal are discussed and select model workers block by intelligent testing
26 are tested and assessed in real time, the subitem evaluation index and comprehensive evaluation index of servo control algorithm are obtained, 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 net
Network, assessment indicator calculate network portion using the three layers of feedforward linear neural fusion connected entirely：First layer is input layer, the
Two layers are subitem evaluation layer, and third layer is overall merit layer.
Above-mentioned steps S4 falls into a trap point counting item evaluation index and the process of comprehensive evaluation index, includes the following steps：
S41:Read the internal control signal needed, external monitoring signal and control algolithm performance monitoring signal.
S42：The real-time computing engines of characteristic index call the feature extraction algorithm defined in feature extraction Support Library, according to step
The signal real-time online read in rapid S41 calculates motion control test and appraisal characteristic index.
S43：Calculated motion control test and appraisal characteristic index in step S42 is input to assessment indicator and calculates the defeated of network
Enter node layer, the output of input layer is each motion control test and appraisal characteristic index.
S44：The weight between node layer is evaluated according to input layer to subitem, linear weighted function is carried out to the output of input layer
Summation calculates the output of subitem evaluation each node of layer, obtains each subitem evaluation index.
S45：According to subitem evaluation layer to the weight between overall merit node layer, each node output of subitem evaluation layer is carried out
Linear weighted function is summed, and is calculated the output of overall merit node layer, is obtained comprehensive evaluation index.
Intelligence test and appraisal design module 19 in host computer experimental development environment, to the intelligence in open-type motion 15
Test and appraisal module 26 is configured.Intelligence test and appraisal design module is built based on Matlab scripts, for teacher according to experiment demand pair
Intelligent testing in open-type motion block of discussing and select model workers is configured, and configuration process comprises the steps of：
S101：Setting needs the inside and outside portion's monitoring signal recorded, control algolithm performance monitoring signal.
Internal control signal can include motor command signal, control algolithm internal state variable and internal drive
State etc.；External monitoring signal is the sensor signals such as code device signal, electric current, torque, temperature；Control algolithm performance monitoring is believed
Number comprising control algolithm the execution time 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 includes various real-time computing functions, most such as average value, variance yields, root-mean-square value, maximum
Small value, power, the rise time, adjustment time, overshoot, steady-state error, tracking error, profile errors calculating function.
S103：Set the weight coefficient that assessment indicator calculates network.
Weight coefficient can be specified directly, can also be learnt to expert analysis mode experience by neural network BP training algorithm,
Automatically generate coefficient.
The configuration of completion is converted to C programmer and C language constant array by Matlab Coder, and is added to movement
In the control program engineering of controller.
As embodiment：Motion ontology uses X-Y twin shaft rectangular co-ordinate motion platforms, therefore N=2.Motion
Position sensor, current sensor, torque sensor and temperature sensor are installed on ontology.Host computer uses desktop PC,
Motor and driver use permanent-magnet alternating current servo motor and the mating driver with analog input control mode.
As shown in Figure 1, each specific connection scheme of component is：Microcontroller 1 in open-type motion 15 passes through
Other hardware modules of its bus and open-type motion connect.It controls program download interface 4 and uses JTAG programming interface,
Host computer 11 is connect with control program download interface, the motion control program for updating controller.Data transmission interface 5 uses
RS-232 interface, host computer are connect with data transmission interface, and motion control state, parameter etc. are exchanged with host computer for controller
Data.D/A interfaces 6 convert the digital signal of controller to analog signal, as the instruction of each group motor, respectively with X-axis and Y
The dummy instruction input port connection of the driver and motor 12-1,12-2 of axis.The driver and motor of X-axis and Y-axis connect respectively
To motion ontology 13 (i.e. X-Y twin shafts rectangular co-ordinate motion platform), driver puts the analog signals that D/A interfaces export
Greatly, driving motor operates, and generates output torque, drives this running body of motion.By position sensor, current sensor, turn
Square sensor and temperature sensor composition sensor group 14, Position Sensor be mounted on be connected to motion ontology X and
In Y-axis, orthogonal intersection code signal is exported using photoelectric encoder, is connect with open-type motion by encoder interfaces 7.Electricity
Flow sensor, torque sensor are mounted on motor, and temperature sensor is mounted on kinematic pair, electric current, torque and temperature sensing
Device is all made of analog signal output, is connect with open-type motion by A/D interfaces 8.I/O interfaces 9 are connected to 2 drivings
The positive and negative limit switch signal of X-Y axis on the enable signal of device, alarm signal and motion ontology.MODBUS interfaces 10 connect
The MODBUS interfaces of driver form MODBUS buses, are used for read write drive internal state and parameter.
Host computer experimental development environment is built based on Windows 7, the operation for supporting each software module of host computer.
Control algorithm design module 16 is applicable in using the modelling function of Simulink softwares for student resource design
In the control algolithm of open-type motion, the special purpose interface of motion controller is carried, supports patterned programmed method.
Model emulation function of the emulation module 17 using Simulink is controlled, and devises driver, motor and fitness machine
The simulation model of structure ontology can carry out analog simulation survey by calling the control algolithm of student resource design to control algolithm
Examination is used for the feasibility of verification algorithm.
Coder function of the program generating module 18 based on Matlab softwares is controlled, for compiling designed control algolithm
It is translated into the motion control program that can be run on the microprocessor of open-type motion, containing for open movement control
Device processed is the automatic Compiling System special configuration file of target platform.The control algolithm of design passes through first after inspection
Matlab Coder are automatically converted to C programmer.By the C language comprising conversion in the control program engineering of motion controller
Program.
Test Sample Design module 20 is built based on Matlab scripts, multiple according to experiment Demand Design for teacher
Can on motion controller automated execution exercise test use-case.
Test case 1.Test X-axis (being axis where driver, 1 group of motor in the present embodiment) speed ring response characteristic refers to
Mark, specifically constructs the Velocity Step Technique input test use-case of X-axis, and step is to 100mm/s after delay in 1 second by static for speed, together
When in module of testing and assessing configuration X-axis actual speed signal is acquired in test case 1, and calculate rise time, adjustment time, super
Tune amount, the concrete numerical value of steady-state error.
Test case 2.Test Y-axis (being axis where driver, 2 groups of motor in this example) speed ring response characteristic index, with X
Axle speed ring response test principle is consistent.
Test case 3.Test the lower robust motion index of straight line linkage, test case be from coordinate (0,0) to (100,
100) linear motion order, the peak acceleration, acceleration in module of testing and assessing in configuration acquisition actual motion are as steady
Property index.
Test case 4.The profile errors in circular motion are tested, test case is the circle of central coordinate of circle (50,0) radius 50
Shape track, test and assess module in configuration acquisition actual path and instruct track between profile errors.
Test case is finally automatically converted to C programmer by Matlab Coder, and the control of motion controller is added
Program engineering.
First communication service module 21-1 is used to communicate with open-type motion, downloads compiled control software,
And state of a control, the supplemental characteristic of read-write open-type motion.Download function calls the C language of microcontroller to compile first
Ready program compiling, link in the control program engineering of motion controller are converted to binary image file, then by device
Image file is downloaded in open-type motion 15 by controlling program download interface 4, control software is completed and updates work
Make.State is communicated by data transmission interface 5 with open-type motion with parameter reading and writing function, reads and writes the control of record
The data such as state processed, parameter.
Real-time 28 is used to support the operation of each software model in open-type motion.It surveys in real time
Control system initializes motion controller microcontroller and each hardware module, then starts master control cycle, will in this cycle
Each software model of recursive call.
Open servo control module 23 executes the control algolithm designed in host computer in real time, and to the execution of control algolithm
Time and EMS memory occupation are monitored, control algolithm performance monitoring signal is generated.After calling host computer to be converted into C language
Control algolithm, you can realize that student designs the real-time execution of control algolithm.Control algolithm can be monitored when calling control algolithm
The execution time and EMS memory occupation situation, generate control algolithm performance monitoring signal.
Data acquiring and recording module 24 for acquiring the internal control signal of open-type motion and carrying out autobiography in real time
The external monitoring signal of sensor group.Data acquiring and recording module is fixed C programmer, is tested and assessed according to intelligence and designs module 19
The C language constant array of generation obtains configuration information, acquires the internal signal of needs and external letter in real time according to configuration information
Number, and recorded.
Data display module 25 with figure or numeric form for showing signal condition, supplemental characteristic on a graphic display
And intelligent evaluating result.Data display module has numerical value to show, waveform is shown, evaluating result shows three kinds of interfaces.In numerical value
Under display interface, signal and supplemental characteristic are shown according to digital form；Under waveform display interface, signal data is plotted as numerical value
With the wavy curve of time relationship；Under evaluating result display interface, servo control algorithm is shown in a manner of number and block diagram
Subitem evaluation index and comprehensive evaluation index.
Intelligent testing discusses and select model workers block 26 according to the intelligence test and appraisal configuration designed in host computer, and intelligence is carried out for motion control arithmetic
Online test and appraisal.
As shown in figure 4, intelligent testing is discussed and select model workers, block includes that the real-time computing engines of characteristic index, feature extraction Support Library and test and appraisal refer to
Mark calculates network, and assessment indicator calculates network portion using the three layers of feedforward linear neural fusion connected entirely：First layer is
Input layer, the second layer are subitem evaluation layer, and third layer is overall merit layer.
Each node layer of neural network is numbered, each node serial number of input layer is a1、a2……am, subitem evaluation layer section
Point is b1、b2……bn, overall merit node layer number c1.Weight coefficient between each node layer is numbered, from input layer ai(i
=1,2 ...) arrive the node b that subitem evaluates layerjThe weights number of (j=1,2 ...) is wij, from the node of subitem evaluation layer
bj(j=1,2 ...) arrive overall merit node layer c1Weights number be vj。
The C language constant array that weight coefficient generates in testing and assessing design module 19 from intelligence between each node layer of neural network is read
It takes.Each weight coefficient can be positive and negative or 0, and the intelligence test and appraisal design module in upper computer software determines, have it is directly specified and
Training two ways.When directly specified, teacher can define the meaning of each node output of subitem evaluation layer, such as in this example b1、
b2、b3The evaluation of output difference corresponding performance, efficiency rating and the reliability evaluation of node.
Teacher can set weight according to experiment demand, and subitem evaluation and comprehensive evaluation result is made to be directed to different experiments
Target is given priority to.It, can be using subitem evaluation layer as the implicit of neural network in a manner of obtaining network weight by training
Layer, the score provided under experienced expert combines different Control performance standards are (reversed to pass using BP as training sample
Broadcast) algorithm is trained neural network, weights are obtained, to allow neural network learn to arrive the principle of expert analysis mode automatically.
In step S4, intelligent testing discuss and select model workers block calculate subitem evaluation index and comprehensive evaluation index process further comprise with
Lower step：
S41:Read the internal control signal needed, external monitoring signal and control algolithm performance monitoring signal.
The inside and outside portion's monitoring signal recorded, the configuration information of control algolithm performance monitoring signal is needed to be set from intelligence test and appraisal
The C language constant array generated in meter module 19 is read.
S42：The real-time computing engines of characteristic index call the feature extraction algorithm defined in feature extraction Support Library, according to step
The signal real-time online read in rapid S41 calculates motion control test and appraisal characteristic index.
The C language constant that the configuration information of the real-time computing engines of characteristic index generates in testing and assessing design module (19) from intelligence
Array is read.Used in the present embodiment motion control test and appraisal characteristic index include：
Precision index：X-Y axle speeds respond steady-state error, X-Y axis position error, X-Y axis resettings error, X-Y axis
Tracking error average value, X-Y axis tracking error variances value, profile errors average value, profile errors variance yields.
Loss objective：Move run time, energy expenditure, maximum instantaneous torque
Riding index：Peak acceleration, maximum acceleration, the step response number of oscillation
Response index：Velocity Step Technique responds rise time, Velocity Step Technique response adjustment time, Velocity Step Technique response overshoot
Algorithm index：The average CPU holding times of control algolithm, the maximum memory occupancy of control algolithm
Other indexs：Kinematic pair Wen Sheng
S43：Calculated motion control test and appraisal characteristic index in step S42 is input to assessment indicator and calculates the defeated of network
Enter node layer, the output of input layer is each motion control test and appraisal characteristic index.
S44：The weight between node layer is evaluated according to input layer to subitem, linear weighted function is carried out to the output of input layer
Summation calculates the output of subitem evaluation each node of layer, obtains each subitem evaluation index.
Assuming that each evaluation index numerical value for being connected to input layer is xi, then the output y of each node for evaluation layer of itemizingjIt can be by
Under
Formula calculates
S45：According to subitem evaluation layer to the weight between overall merit node layer, each node output of subitem evaluation layer is carried out
Linear weighted function is summed, and is calculated the output of overall merit node layer, is obtained comprehensive evaluation index.
The output z of each node of overall merit layer1It can be calculated by following formula
Test case execution module 27 is for being performed automatically in the items designed in host computer Test Sample Design module 20
Exercise test use-case.In the present embodiment, test case execution module 27 is called in order by host computer Test Sample Design module
Designed test case 1~4 realizes automatic test.
Second communication service module 21-2 downloads compiled control software, and transmission is opened for being communicated with host computer
Put the data such as state of a control, the parameter of formula motion controller.Download function is wiped inside microcontroller first in flash storage
Then original control program is established with host computer and is connected.New control software is received by controlling program download interface, and is written
Flash storage inside microcontroller.Motion control data read-write capability can be led to by data transmission interface and host computer
News upload collected data or read-write parameter.
After completing control software update, open-type motion can be in the motion control arithmetic of student resource design
Support under execute automatically teacher design a series of test cases.During this period, position sensor, current sensor can be obtained
With the data such as state variable inside temperature sensor reading, motor command signal, internal drive state and control algolithm,
And be shown and transmit, and tested and assessed in real time to control effect by intelligent testing block of discussing and select model workers.After end of run, intelligent testing
Block of discussing and select model workers will provide evaluating result, and by result immediate feedback to the teachers and students for participating in experiment.It can be seen that intelligence proposed by the present invention
The Open motion control experimental teaching unit that can test and assess is realized to the automating of control algolithm, intelligentized quick, objective survey
It comments, is provided simultaneously with open, flexible, easy-to-use, intuitive advantage, can greatly improve the teaching effect of conventional motion control experimental courses
Fruit.
Claims (4)
1. intelligence test and appraisal Open motion control experimental teaching unit, has：Host computer, N set drives and motor, motion
Ontology, sensor group, open-type motion, control algorithm design module, control emulation module, control Program Generating mould
Block, intelligence test and appraisal design module, Test Sample Design module, communication service module, open servo control module, data acquisition
Logging modle, data display module, intelligent testing are discussed and select model workers block and test case execution module, wherein open-type motion
Have：Microcontroller (1), graphic alphanumeric display (2), data storage (3), control program download interface (4), data transmission interface
(5), D/A interfaces (6), encoder interfaces (7), A/D interfaces (8), I/O interfaces (9) and MODBUS interfaces (10), driving system
System includes N set drives and motor (12-1,12-2 ... 12-n) and motion ontology (13), it is characterised in that：It opens
It puts formula motion controller and constitutes tandem mode with drive system and sensor group (14), host computer (11) is controlled with open movement
Device (15) connection processed, host computer are equipped with experimental development environment (22), and open-type motion runs real-time
(28), experimental development environment includes：Control algorithm design module (16), control emulation module (17), control program generating module
(18), intelligence test and appraisal design module (19), Test Sample Design module (20) and the first communication service module (21-1)；It is real
When TT&C system include：Open servo control module (23), data acquiring and recording module (24), data display module (25),
Intelligent testing is discussed and select model workers block (26), test case execution module (27) and the second communication service module (21-2)；Open movement control
Open servo control module (23) in device (15) processed executes the servo control algorithm of user's design；Intelligence in host computer (11)
Can test and appraisal design module (19) block (26) of discussing and select model workers of the intelligent testing in open-type motion (15) is configured, needed with setting
The inside and outside portion's monitoring signal to be recorded, control algolithm performance monitoring signal, the algorithm in selection feature extraction Support Library, configuration
The real-time computing engines of characteristic index, setting assessment indicator calculate the weight coefficient of network；Test case in host computer (11) is set
Meter module (20) is for designing in multiple test case execution modules (27) in open-type motion (15) in order
The exercise test use-case of automated execution；Intelligent testing is discussed and select model workers in block (26) comprising the real-time computing engines of characteristic index, feature extraction
Support Library and use the three layers of feedforward linear neural network connected entirely assessment indicator calculate network to realize intelligent test and appraisal；Sensing
Device group (14) is made of position sensor, current sensor, torque sensor and temperature sensor, to generate intelligence test and appraisal
Required external monitoring signal.
2. a kind of operation method according to Open motion control experimental teaching unit of intelligently testing and assessing described in claim 1, special
Sign is：Intelligent test and appraisal are carried out by the open-type motion, the operation of open-type motion includes following step
Suddenly：
S1:Start the open servo control module (23), executes the servo control algorithm of user's design；Simultaneously to servo control
The execution time of algorithm processed and EMS memory occupation are monitored, control algolithm performance monitoring signal is generated；
S2:Start the test case execution module (27), in order each test case of automatic running；
S3:It is obtained using the data acquiring and recording module (24) and is passed from position, electric current, temperature in the sensor group (14)
The feedback of sensor generates external monitoring signal；Motor command signal is read simultaneously, servo control algorithm internal state variable, is driven
Dynamic device internal state data, generates internal control signal；
S4:Comprehensive internal control signal, external monitoring signal and control algolithm performance monitoring signal are discussed and select model workers block by the intelligent testing
(26) it is tested and assessed in real time, the subitem evaluation index and comprehensive evaluation index of servo control algorithm is obtained, as evaluating result；
S5:After test case is finished, data display module (25) shows evaluating result automatically.
3. according to the operation method for Open motion control experimental teaching unit of intelligently testing and assessing described in claim 2, feature exists
In：Intelligent testing block (26) of discussing and select model workers includes the real-time computing engines of characteristic index, feature extraction Support Library and assessment indicator meter
Network is calculated, assessment indicator calculates network portion using the three layers of feedforward linear neural fusion connected entirely：First layer is input
Layer, the second layer are subitem evaluation layer, and third layer is overall merit layer；The subitem evaluation index is calculated in step S4 and synthesis is commented
The process of valence index, includes the following steps：
S41:Read the internal control signal needed, external monitoring signal and control algolithm performance monitoring signal；
S42：The real-time computing engines of characteristic index call the feature extraction algorithm defined in feature extraction Support Library, according to step
The signal real-time online read in S41 calculates motion control test and appraisal characteristic index；
S43：Calculated motion control test and appraisal characteristic index in step S42 is input to the input layer that assessment indicator calculates network
The output of node, input layer is each motion control test and appraisal characteristic index；
S44：The weight between node layer is evaluated according to input layer to subitem, carrying out linear weighted function to the output of input layer asks
With, calculate subitem evaluation each node of layer output, obtain each subitem evaluation index；
S45：According to subitem evaluation layer to the weight between overall merit node layer, each node output of subitem evaluation layer is carried out linear
Weighted sum calculates the output of overall merit node layer, obtains comprehensive evaluation index.
4. according to the operation method for Open motion control experimental teaching unit of intelligently testing and assessing described in claim 2, feature exists
In：Intelligence test and appraisal design module (19) in host computer experimental development environment, described in open-type motion (15)
Intelligent testing block (26) of discussing and select model workers is configured, and configuration process comprises the steps of：
S101：Setting needs the inside and outside portion's monitoring signal recorded, control algolithm performance monitoring signal；
S102：Select the algorithm in feature extraction Support Library, the real-time computing engines of configuration feature index；
S103：Set the weight coefficient that assessment indicator calculates network.
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