CN113703397A - Industrial internet multi-axis motion-oriented IEID synchronous control method - Google Patents

Industrial internet multi-axis motion-oriented IEID synchronous control method Download PDF

Info

Publication number
CN113703397A
CN113703397A CN202110996859.2A CN202110996859A CN113703397A CN 113703397 A CN113703397 A CN 113703397A CN 202110996859 A CN202110996859 A CN 202110996859A CN 113703397 A CN113703397 A CN 113703397A
Authority
CN
China
Prior art keywords
subsystem
equivalent input
input interference
ith
vector
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110996859.2A
Other languages
Chinese (zh)
Other versions
CN113703397B (en
Inventor
王瑶为
吴祥
张文安
吴敏
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China University of Geosciences
Original Assignee
China University of Geosciences
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China University of Geosciences filed Critical China University of Geosciences
Priority to CN202110996859.2A priority Critical patent/CN113703397B/en
Publication of CN113703397A publication Critical patent/CN113703397A/en
Application granted granted Critical
Publication of CN113703397B publication Critical patent/CN113703397B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • G05B19/408—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 characterised by data handling or data format, e.g. reading, buffering or conversion of data
    • G05B19/4086—Coordinate conversions; Other special calculations
    • 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
    • G05B2219/35—Nc in input of data, input till input file format
    • G05B2219/35356—Data handling
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The invention relates to the field of motion control of industrial Internet of things, and provides an IEID synchronous control method for industrial Internet multi-axis motion, which comprises the following steps: constructing an initial state space model of the initial multi-axis motion system, and acquiring composite disturbance of the initial state space model; modifying an initial estimator of an initial state space model through composite disturbance to obtain an equivalent input interference estimator, and obtaining a filtered equivalent input interference vector through the equivalent input interference estimator; modifying the initial synchronous controller of the initial state space model through the equivalent input interference vector after filtering to obtain an equivalent input interference synchronous controller; and constructing an equivalent input interference multi-axis motion synchronous control system by an equivalent input interference estimator and an equivalent input interference synchronous controller. The invention can effectively process the influence of the complex disturbance formed by the uncertainty caused by network induction and the disturbance of external load and the like on the system, and obviously improves the flexibility, the complex disturbance processing and inhibiting capability, the rapidity and the control precision of the system.

Description

Industrial internet multi-axis motion-oriented IEID synchronous control method
Technical Field
The invention relates to the field of motion control of industrial Internet of things, in particular to an IEID synchronous control method for industrial Internet multi-axis motion.
Background
In modern intelligent manufacturing industry, multi-axis motion control is always a research hotspot in the field of motion control, wherein synchronous control is one of the core technologies. However, due to the requirement of complex device functions in an industrial application scene, external load and other disturbances have matching and mismatching conditions, which have significant influence on system performance, and the problem of synchronization control accuracy of the system cannot be effectively solved only from the viewpoint of suppression and elimination of the matching external load and other disturbances. Therefore, effective methods for dealing with disturbances such as matching and mismatching external loads must be employed to improve the control performance and production quality of such systems.
Meanwhile, with the rapid development of the industrial internet of things technology, a multi-axis motion system is developing towards networking and high-speed and high-precision. The network is introduced into the multi-axis motion system, and data communication is carried out between the controller and each subsystem through the network, so that the data transmission rate and reliability between the controller and each subsystem are improved, the system wiring is greatly reduced, and the system expansion capability is enhanced. However, the introduction of the network inevitably brings new problems, such as uncertainty of system security caused by network induction and network attack, etc. Particularly, a writer designs a networked multi-axis motion position synchronous control scheme based on an active disturbance rejection controller aiming at the problem of networked multi-axis motion synchronous control, so that a good time delay compensation effect is obtained; and a networked multi-axis motion position synchronous control scheme based on a generalized extended state observer is designed aiming at the problem of synchronous control of a networked large-correlation motion system, so that good decoupling synchronous control performance is obtained. However, how to effectively process a composite disturbance formed by multiple disturbances, wherein the composite disturbance comprises uncertainties caused by network induction and disturbances such as external loads, and the disturbances such as the external loads comprise matching and mismatching disturbances; and the flexibility, the complex disturbance processing and inhibiting capability, the rapidity and the control precision of the networked multi-axis motion system with the composite disturbance are improved, and a good solution is not provided at present.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to solve the technical problem that the influence of composite disturbance formed by multiple disturbances on a multi-axis motion system cannot be effectively processed in the prior art.
In order to achieve the above object, the present invention provides an IEID synchronization control method for industrial internet multi-axis motion, which includes:
s1: constructing an initial state space model of an initial multi-axis motion system, and acquiring composite disturbance of the initial state space model;
s2: modifying the initial estimator of the initial state space model through the composite disturbance to obtain an equivalent input interference estimator, and obtaining a filtered equivalent input interference vector through the equivalent input interference estimator
Figure BDA0003234158550000021
S3: by said filtered equivalent input interference vector
Figure BDA0003234158550000022
Modifying the initial synchronous controller of the initial state space model to obtain an equivalent input interference synchronous controller;
s4: and constructing an equivalent input interference multi-axis motion synchronous control system by the equivalent input interference estimator and the equivalent input interference synchronous controller.
Preferably, in step S1, the composite disturbance includes: network interference and external load disturbance;
the initial state space model comprises: m subsystems, an initial estimator and an initial synchronous controller, wherein m is a positive integer greater than 0;
the expression of the initial state space model is shown as formula one:
Figure BDA0003234158550000023
wherein x isi(t) is the state vector of the ith subsystem,
Figure BDA0003234158550000024
is xiDifferential of (t), ui(t) is the control input of the ith subsystem, ui(t- τ) is the control input for the ith subsystem in the presence of network inducement, yi(t) is the output of the i-th subsystem, dτi(t) network interference of the i-th subsystem, di(t) external load disturbance of the ith subsystem, Ai、Bi、CiAnd BdiIs a system matrix of the i-th subsystem and BdiIs a full rank matrix; wherein i represents the number of the subsystem, and i is more than 0 and less than or equal to m;
the ith subsystem is represented as:
Figure BDA0003234158550000025
preferably, step S2 is specifically:
s21: obtaining the equivalent input interference vector d of the ith subsystemei(t) an equivalent input interference vector d through said i-th subsystemei(t) network interference d of the i-th subsystemτi(t) and an external load disturbance d of the i-th subsystemi(t) modifying the ith subsystem to obtain a modified ith subsystem, wherein the expression is shown as a formula two:
Figure BDA0003234158550000031
s22: constructing an ith subsystem full-order observer through the modified ith subsystem;
s23: equivalent input interference vector d of the ith subsystem through the ith subsystem full-order observerei(t) modifying to obtain the equivalent input interference vector of the i-th subsystem after modification
Figure BDA0003234158550000032
S24: construction of the Filter Fi(s) inputting the modified equivalent interference vector of the i-th subsystem
Figure BDA0003234158550000033
Is inputted into the filter Fi(s) obtaining a filtered equivalent input interference vector for the ith subsystem
Figure BDA0003234158550000034
S25: repeating the steps S21-S25 m times to obtain the equivalent input interference vectors of all the filtered subsystems, and obtaining the equivalent input interference vectors after filtering through the equivalent input interference vector calculation of all the filtered subsystems
Figure BDA0003234158550000035
S26: constructing the equivalent input disturbance estimator from the modified i-th subsystem and the subsystem full-order observer.
Preferably, in step S22, the expression of the i-th subsystem full-order observer is as shown in formula three:
Figure BDA0003234158550000036
wherein L isiIs the gain matrix of the i-th subsystem full-order observer, ufi(t) is the input to the ith subsystem full order observer,
Figure BDA0003234158550000037
is the state vector x of the ith subsystemi(ii) an estimate of the value of (t),
Figure BDA0003234158550000038
is the output quantity y of the ith subsystemi(t) an estimated value.
Preferably, step S23 is specifically:
s231: let formula four be:
Figure BDA0003234158550000039
s232: and assume thatPresence of input quantity deltadi(t) satisfies the formula five:
Figure BDA00032341585500000310
s233: and calculating to obtain a formula six according to a formula two and a formula five:
Figure BDA00032341585500000311
s234: the modified equivalent input interference vector of the i-th subsystem is variable as formula seven:
Figure BDA00032341585500000312
preferably, step S24 is specifically:
s241: constructing the filter FiThe expression of(s) is as follows:
Figure BDA0003234158550000041
wherein, TfiIs a time constant, Tfi＜1/(εωfi) Epsilon is more than or equal to 1 and less than or equal to 10; alpha, beta and gamma are adjustable proportional attenuation coefficients respectively; omegafiIs the highest angular frequency, and Fi(s) satisfies | Fi(jωi)|≈1,
Figure BDA0003234158550000042
S242: the modified equivalent input interference vector of the ith subsystem
Figure BDA0003234158550000043
The following formula is input for calculation:
Figure BDA0003234158550000044
wherein the content of the first and second substances,
Figure BDA0003234158550000045
as equivalent input interference vector of ith filtered subsystem
Figure BDA0003234158550000046
The laplace transform of (a) is performed,
Figure BDA0003234158550000047
for the modified equivalent input interference vector of the i-th subsystem
Figure BDA0003234158550000048
Is performed by the laplace transform.
Preferably, in step S3, the expression of the equivalent input disturbance synchronization controller is as follows:
Figure BDA0003234158550000049
wherein r is0(t) is a reference signal, xi1(t) status of i-th subsystem, ei(t) is the ith subsystem tracking error, e (t) is the error vector,
Figure BDA00032341585500000410
is the differential of e (t), K is the control gain matrix, Γ is the synchronization matrix, δn/μIs a synchronous coupling factor, eta, mu, rho and theta are natural positive integers for quick adjustment,
Figure BDA00032341585500000411
and u (t) is the equivalent input interference vector after filtering, and u (t) is the synchronous control input quantity.
The invention has the following beneficial effects:
1. by designing an equivalent input interference estimator, the method adapts to composite disturbance formed by signal disturbances of different types, and realizes a good estimation effect of the composite disturbance;
2. by designing the equivalent input interference synchronous controller, the industrial internet multi-axis motion system with composite disturbance is ensured to have good flexibility and complex disturbance processing and inhibiting capability, and good high-speed high-precision synchronous control performance of the system is realized;
3. the synchronous control of the industrial internet multi-axis motion system with the composite disturbance can be realized, the influence of uncertainty caused by network induction and various disturbances such as matched and unmatched external loads on the system can be effectively processed, and meanwhile, the flexibility, the complex disturbance processing and inhibiting capacity, the rapidity and the control precision of the system are obviously improved.
Drawings
FIG. 1 is a flow chart of a method according to an embodiment of the present invention;
FIG. 2 is a diagram of an equivalent input disturbance multi-axis motion synchronization control system according to an embodiment of the present invention;
the implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1-2, the present invention provides an IEID synchronization control method for industrial internet multi-axis motion, wherein the IEID is a short for Improved Equivalent Input interference (Improved Equivalent-Input-Disturbance), and the method includes:
s1: constructing an initial state space model of an initial multi-axis motion system, and acquiring composite disturbance of the initial state space model;
s2: modifying the initial estimator of the initial state space model through the composite disturbance to obtain an equivalent input interference estimator, and obtaining a filtered equivalent input interference vector through the equivalent input interference estimator
Figure BDA0003234158550000051
S3: by said filtered equivalent input interference vector
Figure BDA0003234158550000052
Modifying the initial synchronous controller of the initial state space model to obtain equivalent input interference synchronous controlA machine;
s4: and constructing an equivalent input interference multi-axis motion synchronous control system by the equivalent input interference estimator and the equivalent input interference synchronous controller.
In step S1 of this embodiment, the composite disturbance includes: network interference and external load disturbance;
the initial state space model comprises: m subsystems, an initial estimator and an initial synchronous controller, wherein m is a positive integer greater than 0;
the expression of the initial state space model is shown as formula one:
Figure BDA0003234158550000053
wherein x isi(t) is the state vector of the ith subsystem,
Figure BDA0003234158550000054
is xiDifferential of (t), ui(t) is the control input of the ith subsystem, ui(t- τ) is the control input for the ith subsystem in the presence of network inducement, yi(t) is the output of the i-th subsystem, dτi(t) network interference of the i-th subsystem, di(t) external load disturbance of the ith subsystem, Ai、Bi、CiAnd BdiIs a system matrix of the i-th subsystem and BdiIs a full rank matrix; wherein i represents the number of the subsystem, and i is more than 0 and less than or equal to m;
wherein x isi(t)、ui(t)、ui(t-τ)、yi(t)、dτi(t) and di(t) are all
Figure BDA0003234158550000061
The ith subsystem is represented as:
Figure BDA0003234158550000062
in this embodiment, step S2 specifically includes:
s21: obtaining the equivalent input interference vector d of the ith subsystemei(t)，
Figure BDA0003234158550000063
Equivalent input interference vector d through the i-th subsystemei(t) network interference d of the i-th subsystemτi(t) and an external load disturbance d of the i-th subsystemi(t) modifying the ith subsystem to obtain a modified ith subsystem, wherein the expression is shown as a formula two:
Figure BDA0003234158550000064
s22: constructing an ith subsystem full-order observer through the modified ith subsystem;
s23: equivalent input interference vector d of the ith subsystem through the ith subsystem full-order observerei(t) modifying to obtain the equivalent input interference vector of the i-th subsystem after modification
Figure BDA0003234158550000065
S24: construction of the Filter Fi(s) inputting the modified equivalent interference vector of the i-th subsystem
Figure BDA0003234158550000066
Is inputted into the filter Fi(s) obtaining a filtered equivalent input interference vector for the ith subsystem
Figure BDA0003234158550000067
S25: repeating the steps S21-S25 m times to obtain the equivalent input interference vectors of all the filtered subsystems, and obtaining the equivalent input interference vectors after filtering through the equivalent input interference vector calculation of all the filtered subsystems
Figure BDA0003234158550000068
S26: constructing the equivalent input disturbance estimator from the modified i-th subsystem and the subsystem full-order observer.
In step S22 of this embodiment, the expression of the i-th subsystem full-order observer is shown in formula three:
Figure BDA0003234158550000069
wherein L isiIs the gain matrix of the i-th subsystem full-order observer, ufi(t) is the input to the ith subsystem full order observer,
Figure BDA0003234158550000071
is the state vector x of the ith subsystemi(ii) an estimate of the value of (t),
Figure BDA0003234158550000072
is the output quantity y of the ith subsystemi(t) an estimated value.
In this embodiment, step S23 specifically includes:
s231: let formula four be:
Figure BDA0003234158550000073
s232: and assumes that there is an input quantity deltadi(t) satisfies the formula five:
Figure BDA0003234158550000074
s233: and calculating to obtain a formula six according to a formula two and a formula five:
Figure BDA0003234158550000075
s234: the modified equivalent input interference vector of the i-th subsystem is variable as formula seven:
Figure BDA0003234158550000076
at this time, the i-th subsystem full-order observer can be further rewritten as shown in formula eight:
Figure BDA0003234158550000077
the formula three and the formula eight can be calculated to obtain:
Figure BDA0003234158550000078
in this embodiment, step S24 specifically includes:
s241: constructing the filter FiThe expression of(s) is as follows:
Figure BDA0003234158550000079
wherein, TfiIs a time constant, Tfi＜1/(εωfi) Epsilon is more than or equal to 1 and less than or equal to 10; alpha, beta and gamma are adjustable proportional attenuation coefficients respectively; omegafiIs the highest angular frequency, and Fi(s) satisfies | Fi(jωi)|≈1,
Figure BDA00032341585500000710
Adapting to equivalent input interference variables containing different types of signals;
s242: the modified equivalent input interference vector of the ith subsystem
Figure BDA00032341585500000711
The following formula is input for calculation:
Figure BDA00032341585500000712
wherein the content of the first and second substances,
Figure BDA00032341585500000713
as equivalent input interference vector of ith filtered subsystem
Figure BDA00032341585500000714
The laplace transform of (a) is performed,
Figure BDA00032341585500000715
for the modified equivalent input interference vector of the i-th subsystem
Figure BDA0003234158550000081
Is performed by the laplace transform.
In step S3 of this embodiment, the expression of the equivalent input interference synchronization controller is as follows:
Figure BDA0003234158550000082
wherein r is0(t) is a reference signal, xi1(t) status of i-th subsystem, ei(t) is the ith subsystem tracking error, e (t) is the error vector,
Figure BDA0003234158550000083
is the differential of e (t), K is the control gain matrix, Γ is the synchronization matrix, δη/μThe synchronous coupling factors eta, mu, rho and theta are natural positive integers which are quickly adjusted to ensure that the equivalent input interference synchronous controller well processes the composite disturbance and the inhibition capability and realizes the function of quickly eliminating the composite disturbance,
Figure BDA0003234158550000084
and u (t) is the equivalent input interference vector after filtering, and u (t) is the synchronous control input quantity.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third and the like do not denote any order, but rather the words first, second and the like may be interpreted as indicating any order.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (7)

1. An IEID synchronous control method for industrial internet multi-axis motion is characterized by comprising the following steps:
s1: constructing an initial state space model of an initial multi-axis motion system, and acquiring composite disturbance of the initial state space model;
s2: modifying the initial estimator of the initial state space model through the composite disturbance to obtain an equivalent input interference estimator, and obtaining a filtered equivalent input interference vector through the equivalent input interference estimator
Figure FDA0003234158540000011
S3: by said filtered equivalent input interference vector
Figure FDA0003234158540000012
Modifying the initial synchronous controller of the initial state space model to obtain an equivalent input interference synchronous controller;
s4: and constructing an equivalent input interference multi-axis motion synchronous control system by the equivalent input interference estimator and the equivalent input interference synchronous controller.
2. The industrial internet multi-axis motion-oriented IEID synchronization control method according to claim 1, wherein in step S1, the composite disturbance comprises: network interference and external load disturbance;
the initial state space model comprises: m subsystems, an initial estimator and an initial synchronous controller, wherein m is a positive integer greater than 0;
the expression of the initial state space model is shown as formula one:
Figure FDA0003234158540000013
wherein x isi(t) is the state vector of the ith subsystem,
Figure FDA0003234158540000014
is xiDifferential of (t), ui(t) is the control input of the ith subsystem, ui(t- τ) is the control input for the ith subsystem in the presence of network inducement, yi(t) is the output of the i-th subsystem, dτi(t) network interference of the i-th subsystem, di(t) external load disturbance of the ith subsystem, Ai、Bi、CiAnd BdiIs a system matrix of the i-th subsystem and BdiIs a full rank matrix; wherein i represents the number of the subsystem, and i is more than 0 and less than or equal to m;
the ith subsystem is represented as:
Figure FDA0003234158540000015
3. the IEID synchronization control method for industrial internet multi-axis motion according to claim 2, wherein step S2 specifically comprises:
s21: obtaining the equivalent input interference vector d of the ith subsystemei(t) an equivalent input interference vector d through said i-th subsystemei(t) network interference d of the i-th subsystemτi(t) and an external load disturbance d of the i-th subsystemi(t) modifying the ith subsystem to obtain a modified ith subsystem, wherein the expression is shown as a formula two:
Figure FDA0003234158540000021
s22: constructing an ith subsystem full-order observer through the modified ith subsystem;
s23: equivalent input interference vector d of the ith subsystem through the ith subsystem full-order observerei(t) modifying to obtain the equivalent input interference vector of the i-th subsystem after modification
Figure FDA0003234158540000022
S24: construction of the Filter Fi(s) inputting the modified equivalent interference vector of the i-th subsystem
Figure FDA0003234158540000023
Is inputted into the filter Fi(s) obtaining a filtered equivalent input interference vector for the ith subsystem
Figure FDA0003234158540000024
S25: repeating the steps S21-S25 m times to obtain the equivalent input interference vectors of all the filtered subsystems, and obtaining the equivalent input interference vectors after filtering through the equivalent input interference vector calculation of all the filtered subsystems
Figure FDA0003234158540000025
S26: constructing the equivalent input disturbance estimator from the modified i-th subsystem and the subsystem full-order observer.
4. The IEID synchronous control method for multi-axis motion of industrial Internet as claimed in claim 3, wherein in step S22, the expression of the i-th subsystem full-order observer is as shown in formula III:
Figure FDA0003234158540000026
wherein L isiIs the gain matrix of the i-th subsystem full-order observer, ufi(t) is the input to the ith subsystem full order observer,
Figure FDA0003234158540000027
is the state vector x of the ith subsystemi(ii) an estimate of the value of (t),
Figure FDA0003234158540000028
is the output quantity y of the ith subsystemi(t) an estimated value.
5. The IEID synchronous control method for multi-axis motion of industrial Internet as claimed in claim 3, wherein the step S23 is specifically:
s231: let formula four be:
Figure FDA0003234158540000029
s232: and assumes that there is an input quantity deltadi(t) satisfies the formula five:
Figure FDA0003234158540000031
s233: and calculating to obtain a formula six according to a formula two and a formula five:
Figure FDA0003234158540000032
s234: the modified equivalent input interference vector of the i-th subsystem is variable as formula seven:
Figure FDA0003234158540000033
6. the IEID synchronous control method for multi-axis motion of industrial Internet as claimed in claim 3, wherein the step S24 is specifically:
s241: constructing the filter FiThe expression of(s) is as follows:
Figure FDA0003234158540000034
wherein, TfiIs a time constant, Tfi＜1/(εωfi) Epsilon is more than or equal to 1 and less than or equal to 10; alpha, beta and gamma are adjustable proportional attenuation coefficients respectively; omegafiIs the highest angular frequency, and Fi(s) satisfies | Fi(jωi)|≈1,
Figure FDA0003234158540000035
S242: the modified equivalent input interference vector of the ith subsystem
Figure FDA0003234158540000036
The following formula is input for calculation:
Figure FDA0003234158540000037
wherein the content of the first and second substances,
Figure FDA0003234158540000038
as equivalent input interference vector of ith filtered subsystem
Figure FDA0003234158540000039
The laplace transform of (a) is performed,
Figure FDA00032341585400000310
for the modified equivalent input interference vector of the i-th subsystem
Figure FDA00032341585400000311
Is performed by the laplace transform.
7. The IEID synchronization control method for industrial internet multi-axis motion according to claim 2, wherein in step S3, the expression of the equivalent input interference synchronization controller is as follows:
Figure FDA00032341585400000312
wherein r is0(t) is a reference signal, xi1(t) status of i-th subsystem, ei(t) is the ith subsystem tracking error, e (t) is the error vector,
Figure FDA00032341585400000313
is the differential of e (t), K is the control gain matrix, Γ is the synchronization matrix, δη/μIs a synchronous coupling factor, eta, mu, rho and theta are natural positive integers for quick adjustment,
Figure FDA00032341585400000314
and u (t) is the equivalent input interference vector after filtering, and u (t) is the synchronous control input quantity.
CN202110996859.2A 2021-08-27 2021-08-27 Industrial internet multi-axis motion-oriented IEID synchronous control method Active CN113703397B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110996859.2A CN113703397B (en) 2021-08-27 2021-08-27 Industrial internet multi-axis motion-oriented IEID synchronous control method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110996859.2A CN113703397B (en) 2021-08-27 2021-08-27 Industrial internet multi-axis motion-oriented IEID synchronous control method

Publications (2)

Publication Number Publication Date
CN113703397A true CN113703397A (en) 2021-11-26
CN113703397B CN113703397B (en) 2022-09-30

Family

ID=78656107

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110996859.2A Active CN113703397B (en) 2021-08-27 2021-08-27 Industrial internet multi-axis motion-oriented IEID synchronous control method

Country Status (1)

Country Link
CN (1) CN113703397B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117092961A (en) * 2023-10-19 2023-11-21 南京航空航天大学 Switching control method and system for transition section of gyroplane based on equivalent input interference

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107241034A (en) * 2017-08-10 2017-10-10 中电科芜湖钻石飞机制造有限公司 A kind of permagnetic synchronous motor fluctuation of speed suppressing method
CN107703750A (en) * 2017-10-11 2018-02-16 浙江工业大学 A kind of networking multiaxial motion position synchronization control method based on automatic disturbance rejection controller
CN109001974A (en) * 2018-08-01 2018-12-14 浙江工业大学 The big coupled movements system position synchronisation control means of networking based on broad sense extended state observer
CN110581677A (en) * 2019-08-21 2019-12-17 中国地质大学（武汉） permanent magnet synchronous motor restraining method of sliding mode and equivalent input interference method
CN113067506A (en) * 2021-03-09 2021-07-02 中国地质大学（武汉） Permanent magnet synchronous motor periodic disturbance suppression method based on inner model equivalent input interference

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107241034A (en) * 2017-08-10 2017-10-10 中电科芜湖钻石飞机制造有限公司 A kind of permagnetic synchronous motor fluctuation of speed suppressing method
CN107703750A (en) * 2017-10-11 2018-02-16 浙江工业大学 A kind of networking multiaxial motion position synchronization control method based on automatic disturbance rejection controller
CN109001974A (en) * 2018-08-01 2018-12-14 浙江工业大学 The big coupled movements system position synchronisation control means of networking based on broad sense extended state observer
CN110581677A (en) * 2019-08-21 2019-12-17 中国地质大学（武汉） permanent magnet synchronous motor restraining method of sliding mode and equivalent input interference method
CN113067506A (en) * 2021-03-09 2021-07-02 中国地质大学（武汉） Permanent magnet synchronous motor periodic disturbance suppression method based on inner model equivalent input interference

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
吴祥: "网络环境下的轮廓跟踪控制算法研究", 《中国优秀博硕士学位论文全文数据库（博士）信息科技辑》 *
常军 等: "基于等价输入干扰估计器的永磁同步电机速度控制", 《东南大学学报(自然科学版)增刊》 *
方明星 等: "基于等价输入干扰补偿的直流电机定位控制", 《仪器仪表学报》 *
杨瑞峰 等: "PMSM位置伺服系统鲁棒控制技术研究", 《中国测试》 *
王瑶为 等: "基于线性自抗扰控制器的网络化多轴运动系统的轮廓误差", 《第37届中国控制会议论文集》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117092961A (en) * 2023-10-19 2023-11-21 南京航空航天大学 Switching control method and system for transition section of gyroplane based on equivalent input interference
CN117092961B (en) * 2023-10-19 2024-01-30 南京航空航天大学 Switching control method and system for transition section of gyroplane based on equivalent input interference

Also Published As

Publication number Publication date
CN113703397B (en) 2022-09-30

Similar Documents

Publication Publication Date Title
Das et al. Consensus+ innovations distributed Kalman filter with optimized gains
Pan et al. H/sup/spl infin//-optimal control for singularly perturbed systems. II. Imperfect state measurements
Xie et al. Fault estimation observer design of discrete-time nonlinear systems via a joint real-time scheduling law
CN113703397B (en) Industrial internet multi-axis motion-oriented IEID synchronous control method
Zhang et al. Fixed-time almost disturbance decoupling of nonlinear time-varying systems with multiple disturbances and dead-zone input
Yan et al. Observer-based time-varying formation tracking for one-sided Lipschitz nonlinear systems via adaptive protocol
Yu et al. Stabilization parametric region of distributed PID controllers for general first-order multi-agent systems with time delay
CN105955025A (en) Interference compensation and inhibition method for generalized uncertain system
Hsieh et al. General two-stage Kalman filters
Zhang et al. A novel disturbance observer design for a larger class of nonlinear strict-feedback systems via improved DSC technique
Shin et al. A new fusion formula and its application to continuous-time linear systems with multisensor environment
Yu et al. Low sensitivity control for minimum-phase systems using double feedback control
Schneider et al. An iterative partition-based moving horizon estimator for large-scale linear systems
CN112462796A (en) Adaptive inversion control system and method for attitude angle stabilization of rigid aircraft
Ge et al. Universal delayed Kalman filter with measurement weighted summation for the linear time invariant system
CN112230552B (en) Anti-interference control method for discrete time multi-agent game
CN110554601B (en) Design method and device of anti-interference PID controller
CN113608437A (en) Optimal control research method of network control system with packet loss and multiple time lags
Tang et al. Finite-time simultaneous stabilization for stochastic port-controlled Hamiltonian systems over delayed and fading channels
Berg et al. A canonical parameterization of the Kronecker form of a matrix pencil
CN110161857B (en) Design method of active disturbance rejection controller suitable for non-minimum phase system
Xu et al. Robust sequential fusion estimation based on adaptive innovation event-triggered mechanism for uncertain networked systems
Li et al. Distributed Receding Horizon Estimation for Discrete-Time Linear System with Observation Delays
Kanakalakshmi et al. Disturbance estimator based dynamic compensator design for fractional order fuzzy control systems
CN117492372B (en) Active disturbance rejection control method and computer storage medium

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant