CN110058522A - Embedded load characteristic identification system, switching mode digital power and die casting equipment - Google Patents
Embedded load characteristic identification system, switching mode digital power and die casting equipment Download PDFInfo
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Abstract
The present invention relates to identification fields, specially a kind of embedded load characteristic identification system, switching mode digital power and die casting equipment, wherein embedded load characteristic automatic identification system includes: soft-core processor, the identification excitation generating module and logging modle connecting with soft-core processor bus；Wherein the identification excitation generating module is suitable for generating identification input；The logging modle is suitable for that input will be recognizedIt is exported with corresponding identificationIt is recorded as a pairI/OData pair；The soft-core processor is suitable for reading identification inputIt is exported with corresponding identification, and inputted according to identificationIt is exported with corresponding identificationAdaptive state-space model is constructed, and its identification is inputted according to the identification output variation adjustment for being identified object by the adaptive state-space model.It is implemented without additional sensor and feedback signal, is recognized to object is identified.
Description
Technical field
The present invention relates to identification field, specially a kind of embedded load characteristic identification system, switching mode digital power and
Die casting equipment.
Background technique
Nowadays, additional to pacify in order to realize that discriminating function needs additional sensor and identification signal in different field
Dress sensor and acquisition identification signal can bring many troubles in the field of utilization, and inconvenient.
Based on above-mentioned technical problem, need to design the new embedded load characteristic identification system of one kind, switching mode number electricity
Source and die casting equipment.
Summary of the invention
The object of the present invention is to provide a kind of embedded load characteristic identification system, switching mode digital power and die casting dresses
It sets.
In order to solve the above technical problem, the present invention provides a kind of embedded load characteristic automatic identification systems, comprising:
Soft-core processor, the identification excitation generating module and logging modle being connect with soft-core processor bus；Wherein
The identification excitation generating module is suitable for generating identification input；
The logging modle is suitable for that input will be recognizedIt is exported with corresponding identificationIt is recorded as a pairI/ONumber
According to right；
The soft-core processor is suitable for reading identification inputIt is exported with corresponding identification, and according to identification
InputIt is exported with corresponding identificationAdaptive state-space model is constructed, and by the adaptive state
Spatial model inputs its identification according to the identification output variation adjustment for being identified object.
Further, the logging modle is suitable for that input will be recognizedIt is exported with corresponding identificationRecord
For a pairI/OData pair, i.e.,
Using the unit module with load characteristic as object is identified, it is identified object and is generated according to identification excitation generating module
Identification inputIt generates and is inputted with identificationCorresponding identification output；
Logging modle inputs identificationIt is exported with corresponding identificationIt is recorded as the adaptive state space
A pair of modelI/OData pair.
Further, the soft-core processor is suitable for reading identification inputIt is exported with corresponding identification,
And it is inputted according to identificationIt is exported with corresponding identificationAdaptive state-space model is constructed, i.e.,
According toI/OThe number of data pairAdaptive state-space model order is estimated in calculating, constructionHankelInstitute when matrix
The matrix columns used, and constructionHankelUsed matrix line number when matrixValue, with buildingHankel
Matrix, wherein
；
Setting adaptive state-space model hasDimension input andDimension output, and corresponding identification inputs, setting identification output；
In formula,It is greater than5 times,For the dimension of input signal；
For the dimension of output signal；For discrete-time variable；For real number field.
Further, according to,WithValue building identification inputIt is exported with identification'sHankelSquare
Battle array, i.e.,；
；
；
；
Above-mentionedHankelIn matrix,ForInput before momentHankelMatrix；
ForMoment is toThe input at momentHankelMatrix；ForOutput before momentHankel
Matrix；ForMoment is toThe output at momentHankelMatrix.
Further, will、、WithIt carries outLQIt decomposes, makees orthogonal
Projection extends considerable matrix to be obtained from adaptive state spatial model, i.e.,
；
In formula,,,,,,,,,,；Wherein
It reflectsRow vector at space,Row vector at sky
Between arrive respectivelyRow vector at space,Row vector at space projection components.
Further, rightWithMatrix singular value decomposition is carried out, i.e.,
；
In formula,ForThe premultiplication matrix that matrix is obtained through matrix singular value decomposition；
ForMatrix multiplies matrix through the right side that matrix singular value decomposition obtains；
For the eigenvalue matrix of adaptive state-space model；
For transposition；
For the adaptive state-space model nonzero eigenvalue for being identified object；
For null matrix；
According toNumber pairPiecemeal is carried out,Columns be equal toLine number,Columns be equal toLine number；And
According toNumber pairPiecemeal is carried out,Line number be equal toColumns,Line number be equal toColumns.
Further, it takesThe left sideA column vector is denoted as,It is upperRow note
For, underRow is denoted as, then adaptive state-space model matrix,ForIt is upperRow；To pass throughThe practical order obtained.
Further, by least square solution overdetermined equation, obtained from adaptive state spatial model matrix,,,And original state, and construct the adaptive state-space model for being identified object, i.e.,
The overdetermined equation are as follows:
；
In formula:To incite somebody to actionNumerical value write as the form of single-row vector；System to be identified object expands
Open up considerable matrix；For intermediate variable；
；For the column tandem of all identification output datas；
；
,ForKroneckerProduct；
,ForTie up unit matrix；
,For by the rectangular array tandem in bracket；For subfix used in accumulating operation；
The adaptive state-space model are as follows:
；
In formula,It is currentThe state variable forecast for being identified object of the subsequent time at moment；To be distinguished
Know objectThe state variable estimate at moment；To be identified objectThe input signal at moment；To be identified
ObjectThe output signal at moment is forecast.
Further, whether accurate the soft-core processor is further adapted for verifying adaptive state-space model, i.e.,
It is identified object and is receiving verifying identification inputVerifying identification output is generated afterwards, and using certainly
Adaptive state spatial model is according to verifying identification inputObtain output signal forecast, whenWithJudge that adaptive state-space model is accurate when identical.
Another aspect, the present invention also provides a kind of switching mode digital powers, comprising: power major loop and for controlling
The digital control board of power major loop output voltage；
The digital control board is suitable for being changed by above-mentioned embedded load characteristic automatic identification system according to load characteristic
The output voltage is stablized in adjusting.
The third aspect, the present invention also provides a kind of die casting equipments, comprising:
Above-mentioned embedded load characteristic automatic identification system, for receiving identification inputTransmitter；
The transmitter drives the oil pipeline of die casting motor control to generate relevant pressure and stream by die casting motor-drive circuit
Amount, the pressure value and flow value of oil pipeline are acquired by sensor, and above-mentioned value is passed throughADCModule is exported as the identificationIt is transmitted to logging modle.
The invention has the advantages that the present invention, by soft-core processor, the identification connecting with soft-core processor bus swashs
It encourages and module and logging modle occurs；Wherein the identification excitation generating module is suitable for generating identification input；The record
Module is suitable for that input will be recognizedIt is exported with corresponding identificationIt is recorded as a pairI/OData pair；The soft core
Processor is suitable for reading identification inputIt is exported with corresponding identification, and inputted according to identificationWith with
Its corresponding identification outputAdaptive state-space model is constructed, and by the adaptive state-space model according to quilt
The identification output variation adjustment of identification objects inputs its identification, to be implemented without additional sensor and feedback signal,
It is recognized to object is identified.
Detailed description of the invention
Present invention will be further explained below with reference to the attached drawings and examples.
Fig. 1 is the system block diagram of embedded load characteristic automatic identification system of the present invention；
Fig. 2 is the work flow diagram of embedded load characteristic automatic identification system of the present invention；
Fig. 3 is according to the present inventionPRNGIndividuallyLFSRFigure；
Fig. 4 is according to the present inventionPRNGFeedback mechanism figure；
Fig. 5 is according to the present inventionPRNGOutput generates figure；
Fig. 6 (a) be the adaptive state-space model of resistive load of the present invention the discrete figure of prediction error；
Fig. 6 (b) be resistance sense loaded self-adaptive state-space model of the present invention the discrete figure of prediction error；
Fig. 7 is the structural block diagram of die casting equipment according to the present invention.
Specific embodiment
In conjunction with the accompanying drawings, the present invention is further explained in detail.These attached drawings are simplified schematic diagram, only with
Illustration illustrates basic structure of the invention, therefore it only shows the composition relevant to the invention.
Embodiment 1
As shown in Figure 1, the present embodiment provides a kind of embedded load characteristic automatic identification systems, comprising: soft-core processor is (described
Soft-core processor can be, but not limited to useSOPCSoft-core processor), the identification excitation connecting with soft-core processor bus occurs
Module and logging modle；Wherein the identification excitation generating module is suitable for generating identification input；The logging modle is suitable for
Identification is inputtedIt is exported with corresponding identificationIt is recorded as a pairI/OData pair；The soft-core processor is suitable
It is inputted in reading identificationIt is exported with corresponding identification, and inputted according to identificationWith it is corresponding
Identification outputConstruct adaptive state-space model, and by the adaptive state-space model according to being identified object
Identification output variation adjustment its identification is inputted；It realizes and does not need additional sensor and feedback signal, to being identified
Object is recognized, i.e., by the existing control framework of the digital control platform of different application, integrating in soft-core processor shouldIPCore,
The method for constructing adaptive state-space model is transplanted among soft core or hard nucleus management device again.
As shown in Fig. 2, in the present embodiment, the logging modle is suitable for that input will be recognizedIt is distinguished with corresponding
Know outputIt is recorded as a pairI/OData pair, i.e., it is (described using the unit module with load characteristic as object is identified
Being identified object can be, but not limited to be transmitter, filter unit and load), object is identified according to identification excitation generating module
The identification of generation inputsIt generates and is inputted with identificationCorresponding identification output；The soft-core processor is suitable for
Read identification inputIt is exported with corresponding identification, and inputted according to identificationIt is distinguished with corresponding
Know outputConstruct adaptive state-space model, and by the adaptive state-space model according to being identified object
Identification output variation adjustment inputs its identification；Logging modle inputs identificationIt is exported with corresponding identificationIt is recorded as a pair of the adaptive state-space modelI/OData pair.
In the present embodiment, pass throughFPGAOn piece realizes identification excitation generating module, and (the identification excitation generating module can
With but be not limited to using pseudo-random sequence generatorPRNG) issue a series of configurable amplitudes, length and update cycle it is pseudo- with
Machine sequence, the sequence are to input as the identification for being identified object, it is identified object and existsEffect is lower to generate a system
Column response, by spot sensor andADCIt is converted to the digital signal that control unit is capable of handling and recognizes output；?
During identification process, control unit sending is synchronously written signal, and (logging modle can be, but not limited to use logging modleFIFOType memory,FIFOMemory is responsible for completing in the case where recognizing synchronizing clock signals to being identified object input/output terminal message
The acquisition and storage of number value, and after the completion of identification using signal value asI/OData are read to bus is supplied to, therefore are one
A storage unit for being synchronously written asynchronous reading) the synchronous storage under the signal functionWithValue, one by one by it
The input/output of correspondence composition (I/O) data to and wait the reading signal of on-chip bus；Using pseudo-random sequence generatorPRNG, it may be implemented the strong randomness signal of long repetition period, the data update cycle (DUC), amplitude, length can be by recognizing
Command parameter is specified；And the signal has the characteristics that big bandwidth, wide spectrum and intensity are adjustable, compared to use system noise come into
The method of row identification, can achieve better identification effect；When being finished according to the update of preset data length, as distinguish
Knowledge process finish time；Hereafter in processing out of chip device, (the processing out of chip device can be, but not limited to use soft-core processorPCDeng)
Instruction under or automatically by on-chip bus read logging modle inI/OData pair, and depositing in memory, if exist on plate compared with
Large capacityFPGAOutside pieceRAM, can be configured as using thisRAMMemory as on-chip processor；It is soft after data enter memory
Core processor is suitable for readingI/OData pair, and according toI/OData are identified the adaptive state-space model of object to building；
Described control unit, that is, Control card, the Control card can be, but not limited to include one piece integratedFPGAThe mainboard of chip, one
Block digital quantityI/OPlate, one pieceADDAPlate and one piece of power panel, it is described integratedFPGAThe mainboard of chip can be, but not limited to adopt
ToCycloneII EP2C70 FPGARealized for main control chip, and in piece soft-core processor, Peripheral Interface,Avalon MMBus andSSDCUser is customizedIP, common peripheral hardware such as 2 has been built on plateMB SSRAM、EPCS64(64Mb) serially match
Set device, for the 16 of non-volatile memoriesMB FlashMemory,RJ45 network interfaces andRS232 local communication interfaces,
AndSanta CruzStandard extension card interface；The digital quantityI/OIt is defeated to can be, but not limited to build digital quantity input on plate
Diode, optocoupler and level conversion device out are responsible for the main control action of power supply and Collection；It is describedADDAPlate can
With but be not limited to includeADCWithDACAnd mating conditioning circuit, it is responsible for sampling the level signal of sensor；Power supply
Plate can be, but not limited to be responsible for providing 24 comprising a mini-switch power sourceVRegulated power supply.
In the present embodiment, the identification excitation generating module is with pseudo-random sequence generatorPRNGFor be illustrated and distinguish
Know inputGeneration.
Based on linear feedback shift register (Linear Feedback Shift Registers,LFSR) pseudorandom
It is that a kind of application is relatively broad and be easy to that algorithm, which occurs, for sequenceFPGAThe method of upper realization；LFSROutput be its current shape
The linear function (feedback function) of state, and feed back and arrive stateMSB(Most Significant Bit) on, original state
Referred to as seed；LFSRState be limited, since seed is determining value, and export calculate and shifting function be certainty
, soLFSROutput be finally bound to enter be repeated cyclically, but design a good feedback function or increase feedback machine
The complexity of system can make it have the longer repetition period.
Utilize one group of difference seedLFSRArray can improve the randomness of output significantly, then pass through some numerical value
(also known asMagic Word) rightXOROperation is disturbed, and can be further improved randomness.This systemPRNGRealization
Method may be summarized to be following steps to carry out:
Step 1, it constructsLFSRSequence,PRNGIndividuallyLFSRAs shown in figure 3, in Fig. 3DFor input data；QFor output data；FFor
The benefit of output data；clkFor clock signal；
Step 2, by 25 32 " seed (Seed) " write-in 32 25LFSRIn, in order to improve randomness, adopt
Take intersection writing mode:Seed0:bit0–>LFSR0:bit0,Seed0:bit1–>LFSR1:bit0 ...,Seed1:bit0–>LFSR0:bit1 ..., and so on；
Step 3, as shown in figure 4,LFSR1 arrivesLFSR31 outputQConstitute registerQLow 31 (i.e.Q(30:0)), it posts
StorageQHighest order (i.e.Q(31)) it is set to 0(i.e.Q(31)≤0),LFSR0 arrivesLFSR31 outputFConstitute registerF,
Then by registerQNumerical value and registerFNumerical value carry outXORIt operates and utilizesMAG_FEEDBACKWithLFSR0:QIt is rightXOROperation carries out random perturbation, result after disturbance as feedback (FeedbackRegister) it updatesLFSRState；By
In takingLFSRSequence and more complex feedback mechanism,FeedbackRandomness get a promotion；
Step 4, as shown in figure 5, utilizingMAG_OUTAWithMAG_OUTBNext pairQIt carries out a series ofXOROperation is to obtain most
EventuallyPRNGOutput, i.e. identification input, all connecting lines are 32 in Fig. 5bit。
PRNGUpper layer received according to the first external clock first and input seed, then updated according to the second external clock
Random sequence output, two clocks can be different；First external clock under the premise of meeting timing requirements as quickly as possible, outside second
Portion's clock has to comply with the sequence update cycle that user gives；The former is significantly faster than the latter to general warranty, so thatPRNGIt puts into
Just start output virtual value in postrun first update cycle (to distinguish needed for i.e. embedded load characteristic automatic identification system
Know input)；By rightLFSRThe operation of clock, can be with the arbitrary disposition sequence update cycle；Pass through counter and output
Shielding, can configure its sequence length.
In the present embodiment, while passing through two configurable data bit widesDataWidthAnd data lengthDataDepth's
First in, first outFIFOType memory exports to store identification input and identification respectively, and configurability passes throughVHDLMacro-instruction is realized.
In the present embodiment, the soft-core processor is suitable for reading identification inputIt is exported with corresponding identification, and inputted according to identificationIt is exported with corresponding identificationAdaptive state-space model is constructed, i.e.,
According toI/OThe number of data pair(identification command parameter) calculates and estimates adaptive state-space model orderIt is (described
Estimate adaptive state-space model orderIt requires to determine by the load characteristic and identification that are identified object, greater than being identified pair
The Main Patterns number of elephant can be, but not limited to be appointed as slightly larger 10 rank of value as a parameter of identification order),
ConstructionHankelUsed matrix columns when matrix, and constructionHankelUsed matrix line number when matrix's
Value, with buildingHankelMatrix, wherein
；
Setting adaptive state-space model hasDimension input andDimension output, and corresponding identification inputs, setting identification output；
In formula,It is greater than5 times,For the dimension of input signal；For
The dimension of output signal；For discrete-time variable；For real number field.
In the present embodiment, according to,WithValue building identification inputIt is exported with identification'sHankelMatrix, i.e.,；
；
；
；
Above-mentionedHankelIn matrix,For(i.e. initial time to before momentMoment) inputHankelMatrix (willValue arrange to obtain)；ForMoment is toThe input at momentHankelMatrix (willValue arrange to obtain)；For(i.e. initial time to before momentWhen
Carve) outputHankelMatrix (willValue arrange to obtain)；ForMoment is toMoment it is defeated
OutHankelMatrix (willValue arrange to obtain)；,Value be equal to matrix columnsValue,'s
Value, which is equal to, estimates adaptive state-space model orderValue.
In the present embodiment, will、、WithIt carries outLQIt decomposes, makees
Rectangular projection extends considerable matrix to be obtained from adaptive state spatial model, i.e.,
；
In formula,,,,,,,,,,；Wherein
It reflectsRow vector at space,Row vector at sky
Between arrive respectivelyRow vector at space,Row vector at space projection components；
It is right、、WithIt carries outLQIt decomposes
It arrivesQMatrix is obtained by piecemeal.
In the present embodiment, rightWithMatrix singular value decomposition is carried out, i.e.,
；
In formula,ForThe premultiplication matrix that matrix is obtained through matrix singular value decomposition；ForMatrix multiplies matrix through the right side that matrix singular value decomposition obtains；
For the eigenvalue matrix of adaptive state-space model；
For transposition；
For the adaptive state-space model nonzero eigenvalue for being identified object；
For null matrix；
According toNumber pairPiecemeal is carried out,Columns be equal toLine number,Columns be equal toLine number；And
According toNumber pairPiecemeal is carried out,Line number be equal toColumns,Line number be equal toColumns.
In the present embodiment, it takesThe left sideA column vector is denoted as,It is upperRow is denoted as, underRow is denoted as, then adaptive state-space model square
Battle array,ForIt is upperRow；To pass throughThe practical order obtained, i.e.,Value exist
It is reduced to be identified the practical order that object shows under current sample frequency automatically in calculating。
In the present embodiment, by least square solution overdetermined equation, obtained from adaptive state spatial model matrix,,,And original state, and construct the adaptive state-space model for being identified object, i.e.,
The overdetermined equation are as follows:
；
In formula:To incite somebody to actionNumerical value write as the form of single-row vector；For the system extension for being identified object
Considerable matrix；For intermediate variable；
；For the column tandem of all identification output datas；
；
,ForKroneckerProduct；
,ForTie up unit matrix；
,For by the rectangular array tandem in bracket；For subfix used in accumulating operation；
The adaptive state-space model are as follows:
；
In formula,It is currentThe state variable forecast for being identified object of the subsequent time at moment；To be distinguished
Know objectThe state variable estimate at moment；To be identified objectThe input signal at moment；To be identified
ObjectThe output signal at moment is forecast.
In the present embodiment, whether accurate the soft-core processor is further adapted for verifying adaptive state-space model, i.e.,
It is identified object and is receiving verifying identification inputVerifying identification output is generated afterwards, and utilize adaptive
Answer state-space model according to verifying identification inputObtain output signal forecast, whenWithJudge that adaptive state-space model is accurate when identical；To guarantee to verify the accuracy of adaptive state-space model,WithShould have a biggish irrelevance, adaptive state-space model will by withIt is visibly differentIt calculates and meetsI/OThe output data of data pair；It can be in most stringent of condition as test input using random number
The lower accuracy for investigating adaptive state-space model.
In the present embodiment, the reading identification inputIt is exported with corresponding identification, and according to distinguishing
Know inputIt is exported with corresponding identificationThe method for constructing adaptive state-space model, can with but it is unlimited
In passing throughC++ it is programmed in soft-core processor to realize and construct adaptive state-space model.
Embodiment 2
On the basis of embodiment 1, the present embodiment 2 also provides a kind of switching mode digital power, comprising: power major loop and
For controlling the digital control board of power major loop output voltage；The digital control board is suitable for by above-mentioned embedding
Enter formula load characteristic automatic identification system and the output voltage is stablized according to load characteristic variation adjusting.
In the present embodiment, the digital control board can be, but not limited to include one piece integratedFPGAThe mainboard of chip,
One piece of digital quantityI/OPlate, one pieceADDAPlate and one piece of power panel, it is described integratedFPGAThe mainboard of chip can be, but not limited to
Use withCycloneII EP2C70 FPGARealized for main control chip, and in piece soft-core processor, Peripheral Interface,Avalon MMBus andSSDCUser is customizedIP, common peripheral hardware such as 2 has been built on plateMB SSRAM、EPCS64(64Mb) serially match
Set device, for the 16 of non-volatile memoriesMB FlashMemory,RJ45 network interfaces andRS232 local communication interfaces,
AndSanta CruzStandard extension card interface；The digital quantityI/OIt is defeated to can be, but not limited to build digital quantity input on plate
Diode, optocoupler and level conversion device out are responsible for the main control action of power supply and Collection；It is describedADDAPlate
Can be, but not limited to includeADCWithDACAnd mating conditioning circuit, it is responsible for sampling the level signal of sensor；Electricity
Source plate can be, but not limited to be responsible for providing 24 comprising a mini-switch power sourceVRegulated power supply.
It, will to verify working condition of the adaptive state-space model under actual switch type digital power and loading condition
Switching mode digital power is respectively connected to the load of four different characteristics, and adaptive state-space model testing procedure is as follows:
It utilizesPRNG(recognizing excitation generating module in i.e. embedded load characteristic automatic identification system) generates identification input, be converted to as control inputPWMSignal, load are excited, and output current sample is as identification output,
Embedded load characteristic automatic identification method utilizesWithConstruct adaptive state-space model；
It utilizes againPRNGGenerate verifying identification input, and equally excitation load is verified identification output；
Using adaptive state-space model andOutput signal forecast is calculated, and withCompare
To check the accuracy of adaptive state-space model.
To guarantee to verify the accuracy of adaptive state-space model,WithShould have biggish uncorrelated
Property, adaptive state-space model will by withIt is visibly differentIt calculates and meetsI/OThe output of data pair
Data；The accurate of adaptive state-space model can be verified as test input under the conditions of most stringent of using random number
Property.
As Fig. 6 (a) and Fig. 6 (b) shown in, 0.07 is used respectivelyResistive load and 0.23/4.5mHResistance inductive load obtains
The test result arrived, when normalizing given range respectively ± 0.1 and ± 0.05, output signal is pre- under the conditions of resistive load
ReportWith verifying identification outputData covariance is 1.54 × 10−4(numerical value is mainly by the mistake of original state
Difference influences), lower magnet load is 3.47 × 10−6, it is seen that modelI/OCharacteristic and the practical controlled device goodness of fit are preferable.
Embodiment 3
As shown in fig. 7, the present embodiment 3 also provides a kind of die casting equipment, comprising: such as on the basis of embodiment 1 and embodiment 2
Embodiment 1 and embedded load characteristic automatic identification system as described in example 2, for receiving identification inputPick-up
Device；The driving signal of the transmitter output is by, by filtering unit filters, passing through die casting motor-drive circuit after driver
It drives the oil pipeline (pressure execution unit or various types casting etc.) of die casting motor control to generate relevant pressure and flow, leads to
The pressure value and flow value of sensor acquisition oil pipeline are crossed, and above-mentioned value is passed throughADCModule is exported as the identificationIt is transmitted to logging modle.
In the present embodiment, the die casting equipment is to be identified involved in embedded load characteristic automatic identification system
Object.
In conclusion the present invention passes through soft-core processor, the identification excitation generating module connecting with soft-core processor bus
And logging modle；Wherein the identification excitation generating module is suitable for generating identification input；The logging modle is suitable for will
Identification inputIt is exported with corresponding identificationIt is recorded as a pairI/OData pair；The soft-core processor is suitable for
Read identification inputIt is exported with corresponding identification, and inputted according to identificationIt is distinguished with corresponding
Know outputConstruct adaptive state-space model, and by the adaptive state-space model according to being identified object
Identification output variation adjustment inputs its identification, to be implemented without additional sensor and feedback signal, to being identified pair
As being recognized.
Taking the above-mentioned ideal embodiment according to the present invention as inspiration, through the above description, relevant staff is complete
Various changes and amendments can be carried out without departing from the scope of the technological thought of the present invention' entirely.The technology of this invention
Property range is not limited to the contents of the specification, it is necessary to which the technical scope thereof is determined according to the scope of the claim.
Claims (11)
1. a kind of embedded load characteristic automatic identification system characterized by comprising
Soft-core processor, the identification excitation generating module and logging modle being connect with soft-core processor bus；Wherein
The identification excitation generating module is suitable for generating identification input；
The logging modle is suitable for that input will be recognizedIt is exported with corresponding identificationIt is recorded as a pairI/OData
It is right；
The soft-core processor is suitable for reading identification inputIt is exported with corresponding identification, and it is defeated according to recognizing
EnterIt is exported with corresponding identificationAdaptive state-space model is constructed, and by the adaptive state space
Model inputs its identification according to the identification output variation adjustment for being identified object.
2. embedded load characteristic automatic identification system as described in claim 1, which is characterized in that
The logging modle is suitable for that input will be recognizedIt is exported with corresponding identificationIt is recorded as a pairI/OData
It is right, i.e.,
Using the unit module with load characteristic as object is identified, it is identified object and is generated according to identification excitation generating module
Identification inputIt generates and is inputted with identificationCorresponding identification output；
Logging modle inputs identificationIt is exported with corresponding identificationIt is recorded as the adaptive state space mould
A pair of typeI/OData pair.
3. embedded load characteristic automatic identification system as claimed in claim 2, which is characterized in that
The soft-core processor is suitable for reading identification inputIt is exported with corresponding identification, and it is defeated according to recognizing
EnterIt is exported with corresponding identificationAdaptive state-space model is constructed, i.e.,
According toI/OThe number of data pairAdaptive state-space model order is estimated in calculating, constructionHankelInstitute when matrix
The matrix columns used, and constructionHankelUsed matrix line number when matrixValue, with buildingHankel
Matrix, wherein
；
Setting adaptive state-space model hasDimension input andDimension output, and corresponding identification inputs, setting identification output；
In formula,It is greater than5 times,For the dimension of input signal；For
The dimension of output signal；For discrete-time variable；For real number field.
4. embedded load characteristic automatic identification system as claimed in claim 3, which is characterized in that
According to,WithValue building identification inputIt is exported with identification'sHankelMatrix, i.e.,；
；
；
；
Above-mentionedHankelIn matrix,ForInput before momentHankelMatrix；For
?Moment is toThe input at momentHankelMatrix；ForOutput before momentHankel
Matrix；ForMoment is toThe output at momentHankelMatrix.
5. embedded load characteristic automatic identification system as claimed in claim 4, which is characterized in that
It will、、WithIt carries outLQIt decomposes, it is suitable to be obtained to make rectangular projection
State-space model is answered to extend considerable matrix, i.e.,
；
In formula,,,,,,,,,,；Wherein
It reflectsRow vector at space,Row vector at sky
Between arrive respectivelyRow vector at space,Row vector at space projection components.
6. embedded load characteristic automatic identification system as claimed in claim 5, which is characterized in that
It is rightWithMatrix singular value decomposition is carried out, i.e.,
；
In formula,ForThe premultiplication matrix that matrix is obtained through matrix singular value decomposition；
ForMatrix multiplies matrix through the right side that matrix singular value decomposition obtains；
For the eigenvalue matrix of adaptive state-space model；
For transposition；
For the adaptive state-space model nonzero eigenvalue for being identified object；
For null matrix；
According toNumber pairPiecemeal is carried out,Columns be equal toLine number,Columns be equal toLine number；And
According toNumber pairPiecemeal is carried out,Line number be equal toColumns,Line number be equal toColumns.
7. embedded load characteristic automatic identification system as claimed in claim 6, which is characterized in that
It takesThe left sideA column vector is denoted as,It is upperRow is denoted as, underRow is denoted as, then adaptive state-space model matrix,ForIt is upperRow；To pass throughThe practical order obtained.
8. embedded load characteristic automatic identification system as claimed in claim 7, which is characterized in that
By least square solution overdetermined equation, obtained from adaptive state spatial model matrix,,,With
Original state, and construct the adaptive state-space model for being identified object, i.e.,
The overdetermined equation are as follows:
；
In formula:To incite somebody to actionNumerical value write as the form of single-row vector；For the system extension for being identified object
Considerable matrix；For intermediate variable；
；For the column tandem of all identification output datas；
；
,ForKroneckerProduct；
,ForTie up unit matrix；
,For by the rectangular array tandem in bracket；For subfix used in accumulating operation；
The adaptive state-space model are as follows:
；
In formula,It is currentThe state variable forecast for being identified object of the subsequent time at moment；To be distinguished
Know objectThe state variable estimate at moment；To be identified objectThe input signal at moment；To be identified
ObjectThe output signal at moment is forecast.
9. embedded load characteristic automatic identification system as claimed in claim 8, which is characterized in that
Whether the soft-core processor is further adapted for verifying adaptive state-space model accurate, i.e.,
It is identified object and is receiving verifying identification inputVerifying identification output is generated afterwards, and utilize adaptive
Answer state-space model according to verifying identification inputObtain output signal forecast, whenWith
Judge that adaptive state-space model is accurate when identical.
10. a kind of switching mode digital power characterized by comprising power major loop and for controlling power master
The digital control board of output voltage loop；
The digital control board is suitable for by being as the described in any item embedded load characteristics of claim 1-9 recognize automatically
System is adjusted according to load characteristic variation stablizes the output voltage.
11. a kind of die casting equipment characterized by comprising
Such as the described in any item embedded load characteristic automatic identification systems of claim 1-9, inputted for receiving identification
Transmitter；
The transmitter drives the oil pipeline of die casting motor control to generate relevant pressure and stream by die casting motor-drive circuit
Amount, the pressure value and flow value of oil pipeline are acquired by sensor, and above-mentioned value is passed throughADCModule is exported as the identificationIt is transmitted to logging modle.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110095982A (en) * | 2019-04-22 | 2019-08-06 | 江苏中科云控智能工业装备有限公司 | The control method of load characteristic automatic identification method, state-space model and power supply |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104038055A (en) * | 2014-06-03 | 2014-09-10 | 武汉理工大学 | FPGA (Field Programmable Gate Array) based DC (Direct Current)/DC converter prediction control device and method |
| CN104102127A (en) * | 2014-07-17 | 2014-10-15 | 厦门大学 | Airborne aerodynamic parameter identification system |
| US20150023602A1 (en) * | 2013-07-19 | 2015-01-22 | Kamil Wnuk | Fast recognition algorithm processing, systems and methods |
| CN104699905A (en) * | 2015-03-18 | 2015-06-10 | 中国航空工业集团公司雷华电子技术研究所 | Identification modeling method for gear transmission mechanism of speed regulating system based on frequency domain response |
-
2019
- 2019-04-22 CN CN201910321160.9A patent/CN110058522A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150023602A1 (en) * | 2013-07-19 | 2015-01-22 | Kamil Wnuk | Fast recognition algorithm processing, systems and methods |
| CN104038055A (en) * | 2014-06-03 | 2014-09-10 | 武汉理工大学 | FPGA (Field Programmable Gate Array) based DC (Direct Current)/DC converter prediction control device and method |
| CN104102127A (en) * | 2014-07-17 | 2014-10-15 | 厦门大学 | Airborne aerodynamic parameter identification system |
| CN104699905A (en) * | 2015-03-18 | 2015-06-10 | 中国航空工业集团公司雷华电子技术研究所 | Identification modeling method for gear transmission mechanism of speed regulating system based on frequency domain response |
Non-Patent Citations (1)
| Title |
|---|
| 疏坤 等: "加速器磁铁电源的被控对象辨识模块设计", 《核技术》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110095982A (en) * | 2019-04-22 | 2019-08-06 | 江苏中科云控智能工业装备有限公司 | The control method of load characteristic automatic identification method, state-space model and power supply |
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