CN106936408B - Filtering method, device and electronic equipment - Google Patents
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Abstract
The present invention provides a kind of filtering method, device and electronic equipments, are related to technical field of filtering.Filtering method includes：Establish global two type T S fuzzy time-delay systems models of section；It establishes global two pattern of section and pastes filter model；Filtering error model is established according to two type T S fuzzy time-delay systems models of section and two pattern of section paste filter model, and is filtered according to filtering error model.Filtering method, device and electronic equipment provided by the invention can preferably handle the nonlinear system with parameter uncertainty, complete the design of filter parameter, and filtering is made more to stablize.
Description
Technical Field
The invention relates to the technical field of filtering, in particular to a filtering method, a filtering device and electronic equipment.
Background
In recent years, a T-S fuzzy model is widely concerned, the T-S fuzzy model is a global model formed by smoothly connecting a series of linear sub-models by nonlinear fuzzy weights, can approach any smooth nonlinear function in a convex compact set with any precision, and plays a great role in the aspects of stability analysis, controller synthesis, filter design and the like of a fuzzy system and obtains a great theoretical result.
It is noted that the above results are based on a type of fuzzy logic, and these conventional type of T-S fuzzy controls are usually based on the assumption that the fuzzy weights do not contain uncertainty information. However, in practical applications, not only non-linearity but also uncertainty is often accompanied, and once the considered system is a non-linear system with parameter uncertainty, the T-S fuzzy control method based on a single fuzzy logic cannot be directly applied.
Therefore, how to better handle the nonlinear system with parameter uncertainty, complete the design of filter parameters, and stabilize the error filtering system is an urgent problem in the prior art.
Disclosure of Invention
In view of the above, an object of the embodiments of the present invention is to provide a filtering method, a filtering apparatus and an electronic device to improve the above problem.
In a first aspect, an embodiment of the present invention provides a filtering method, where the filtering method includes:
establishing a global interval two type T-S fuzzy time-lag system model;
establishing a global interval type-two fuzzy filter model;
and establishing a filtering error model according to the two-type interval T-S fuzzy time lag system model and the two-type interval fuzzy filter model, and filtering according to the filtering error model.
In a second aspect, an embodiment of the present invention provides a filtering apparatus, where the filtering apparatus includes:
the first establishing module is used for establishing a global interval type T-S fuzzy time-lag system model;
the second establishing module is used for establishing a global interval type two fuzzy filter model;
the third establishing module is used for establishing a filtering error model according to the interval type T-S fuzzy time lag system model and the interval type II fuzzy filter model;
and the filtering module is used for filtering according to the filtering error model.
In a third aspect, an embodiment of the present invention provides an electronic device, where the electronic device includes:
a memory;
a processor; and
a filtering device installed in the memory and including one or more software function modules executed by the processor, the filtering device comprising:
the first establishing module is used for establishing a global interval type T-S fuzzy time-lag system model;
the second establishing module is used for establishing a global interval type two fuzzy filter model;
the third establishing module is used for establishing a filtering error model according to the interval type T-S fuzzy time lag system model and the interval type II fuzzy filter model;
and the filtering module is used for filtering according to the filtering error model.
Compared with the prior art, the filtering method, the filtering device and the electronic equipment provided by the invention have the following beneficial effects:
the filtering method, the filtering device and the electronic equipment provided by the invention can better process a nonlinear system with parameter uncertainty, complete the design of filter parameters and enable the filtering to be more stable.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a block diagram of an electronic device according to a preferred embodiment of the invention.
Fig. 2 is a flow chart of a filtering method according to a preferred embodiment of the invention.
Fig. 3 is a force-receiving schematic diagram of a spring damping system according to a preferred embodiment of the present invention.
FIG. 4 shows the initial condition x in FIG. 31＝1，The state of time reverts to the graph.
FIG. 5 shows the initial condition x in FIG. 32＝-2，The state of time reverts to the graph.
Fig. 6 is a graph of error recovery for fig. 3 at zero initial conditions.
Fig. 7 is a block diagram of a filtering apparatus according to a preferred embodiment of the invention.
Icon: 10-an electronic device; 101-a memory; 102-a memory controller; 103-a processor; 104-peripheral interfaces; 105-a display unit; 106-an audio unit; 107-input-output unit; 200-a filtering means; 210-a first setup module; 220-a second setup module; 230-a third setup module; 240-filtering module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present invention, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, a block diagram of an electronic device 10 according to a preferred embodiment of the present invention is shown, and a filtering apparatus 200 according to an embodiment of the present invention can be applied to the electronic device 10. The electronic device 10 may be, but is not limited to, a smart phone, a Personal Computer (PC), a tablet PC, a Personal Digital Assistant (PDA), a Mobile Internet Device (MID), and the like. The operating system of the electronic device 10 may be, but is not limited to, an Android system, an ios (Android system), a Windows phone system, a Windows system, and the like.
In the embodiment of the present invention, the electronic device 10 further includes a memory 101, a memory controller 102, a processor 103, a peripheral interface 104, a display unit 105, an audio unit 106, and an input/output unit 107.
The memory 101, the memory controller 102, the processor 103, the peripheral interface 104, the display unit 105, the audio unit 106, and the input/output unit 107 are electrically connected to each other directly or indirectly, so as to implement data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The filtering apparatus 200 includes at least one software functional module which can be stored in the memory 101 in the form of software or firmware (firmware) or is fixed in an Operating System (OS) of the electronic device 10. The processor 103 is configured to execute an executable module stored in the memory 101, for example, a software functional module or a computer program included in the filtering apparatus 200.
The processor 103 may be an integrated circuit chip having signal processing capabilities. The Processor 103 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor 103 may be any conventional processor or the like.
The peripheral interface 104 couples various input/output devices to the processor 103 as well as to the memory 101. In some embodiments, the peripheral interface 104, the processor 103, and the memory controller 102 may be implemented in a single chip. In other examples, they may be implemented separately from the individual chips.
The display unit 105 provides an interactive interface (e.g., a user interface) between the electronic device 1010 and a user or for displaying image data to a user reference. In this embodiment, the display unit 105 may be a liquid crystal display or a touch display. In the case of a touch display, the display can be a capacitive touch screen or a resistive touch screen, which supports single-point and multi-point touch operations. The support of single-point and multi-point touch operations means that the touch display can sense touch operations simultaneously generated from one or more positions on the touch display, and the sensed touch operations are sent to the processor for calculation and processing.
Audio unit 106 provides an audio interface to a user, which may include one or more microphones, one or more speakers, and audio circuitry.
The input/output unit 107 is used for providing input data to the user to realize the interaction of the user with the electronic device 10. The input/output unit 107 may be, but is not limited to, a mouse, a keyboard, and the like.
Referring to fig. 2, a flow chart of a filtering method applied to the filtering apparatus 200 according to a preferred embodiment of the invention is shown, and the specific flow described in fig. 2 will be described in detail.
And step S101, establishing a global interval type T-S fuzzy time-lag system model.
In this embodiment, the global interval is of type two T-S fuzzyStagnation System model fαComprises the following steps:
wherein i 1,2, … p, α 1,2, … R, x (t) e RnIs the state vector, z (t) e RvIs the control output, y (t) e RmIs the measurement output, w ∈ RqIs a disturbance input, Ai,Adi,D1i,Ci,Cdi,D2i,Ei,EdiAnd D3iIs a known system matrix, d (t) is a time-varying time lag, d (t) satisfies:
h and mu are two scalar quantities which, ai(x(t))∈[0,1]andis two non-linear functions and satisfies
Specifically, when establishing a global interval type T-S fuzzy time-lag system model, firstly consider the following rule if f1(x (t)) isAnd f isr(x (t)) isThen:
whereinIs about a function fα(x (t)) section-type fuzzy set, i 1,2, … p, α 1,2, … R, x (t) e RnIs the state vector, z (t) e RvIs the control output, y (t) e RmIs the measurement output, w ∈ RqIs a disturbance input, Ai,Adi,D1i,Ci,Cdi,D2i,Ei,EdiAnd D3iIs a known system matrix. d (t) is a time-varying time lag, d (t) satisfies:
where h and μ are two scalars.
The activation strength of the ith rule is defined as the following set of intervals:
whereinAndrespectively representing upper and lower degrees of membership.
Then, a global interval type T-S fuzzy time-lag system model can be obtained:
wherein, a i(x(t))∈[0,1]andis two non-linear functions and satisfies
And step S102, establishing a global interval type two fuzzy filter model.
In this embodiment, the global interval type two fuzzy filter model gβComprises the following steps:
wherein j is 1,2, … p, β is 1,2, … r, Afj，BfjAnd CfjIs the parameter of the filtering that is, β j(x(t))∈[0,1]andis two non-linear functions and satisfies
Specifically, a two-type interval fuzzy filter with unmatched precondition membership functions is defined, and a filter system rule is as follows: if g is1(x (t)) isAnd g isl(x (t)) isThen:
whereinIs about the function gβ(x (t)) section-type fuzzy set, j 1,2, … p, β 1,2, … r, afj，BfjAnd CfjAre the filter parameters. The activation strength of the jth rule is defined as the following set of intervals:
wherein
Andrespectively representing upper and lower degrees of membership.
Then, a global interval type two fuzzy filter model is obtained:
wherein
β j(x(t))∈[0,1]Andis two non-linear functions and satisfies
And step S103, establishing a filtering error model and filtering according to the filtering error model.
In this embodiment, the filtering error model is:
wherein,
specifically, after obtaining the formulas (3) and (5), the filtering error model can be obtained by the calculation of the formulas (3) and (5).
And after the filtering error model is obtained, filtering according to the filtering error model.
For example, as shown in fig. 3, it is a force diagram of a spring damping system, which can be obtained from newton's law of motion:
where m is the mass of the object, FfAnd FsThe friction force of the object and the elastic force of the spring are respectively, u (t) is the resultant force in the horizontal direction, and x represents the displacement. Due to the fact thatWhereinAnd a is a constant. The above equation can be expressed as:
definition ofLet x1(t)∈[-2,2]，m＝1kg，c＝2N·m/s，a＝0.3m-1. Suppose thatThen whenWhen the temperature of the water is higher than the set temperature,take the maximum value asWhen in useWhen the temperature of the water is higher than the set temperature,take the minimum value asDue to the fact thatFor uncertain parameters, the existing one-type fuzzy filtering method cannot be applied. In the embodiment of the invention, the original nonlinear system can be approximately converted into a global interval type T-S fuzzy time-lag system model of formula (3).
Wherein the relevant parameters are:
C1＝[0.1 0.1]，C2＝[0.1 0.1]，Cd1＝[-0.8 0.6]，Cd2＝[-0.2 1]，D21＝-0.7，D22＝0.2，E1＝[1 0]，E2＝[1 0]，Ed1＝[0.1 0]，Ed2＝[0 0.2]，D31＝0，D32＝0。
due to uncertain parametersThe values are different, and the upper and lower membership functions of the two-type fuzzy filter model in the global interval are as follows:
next, L is given2-L∞And designing parameters of the filter under the performance index. Let phi ═ I, Ψ1＝Ψ2＝0，Ψ3＝γ2I. When α is equal to 1, β is equal to 10, h is equal to 0.5 and mu is equal to 0.2, the minimum L is obtained2-L∞The performance index γ is 1.0302, and the filter gain matrix is found as:
Cf1＝[-0.0009 0.0270]，
Cf2＝[-0.0009 0.0271]。
at initial condition x1＝1,x2＝-2,The state recovery curves of (1) are shown in FIGS. 4 and 5.
Let the disturbance beThe error recovery curve for the system at zero initial conditions is shown in fig. 6.
As can be seen from fig. 4-6, the filtering method provided by the embodiment of the invention is effective for the spring damping system with uncertain parameters.
In summary, the filtering method provided by the embodiment of the invention adopts the interval two-type T-S fuzzy model, better handles the nonlinear system with parameter uncertainty, completes the design of filter parameters, and makes filtering more stable.
Referring to fig. 7, which is a block diagram of a filtering apparatus 200 according to a preferred embodiment of the present invention, the filtering apparatus 200 includes a first establishing module 210, a second establishing module 220, a third establishing module 230, and a filtering module 240.
The first establishing module 210 is configured to establish a global interval type T-S fuzzy time-lag system model.
Specifically, the filtering apparatus 200 is used to establish a global interval two type T-S fuzzy time-lag system model f through the first establishing module 210α
Wherein i 1,2, … p, α 1,2, … R, x (t) e RnIs the state vector, z (t) e RvIs the control output, y (t) e RmIs the measurement output, w ∈ RqIs a disturbance input, Ai,Adi,D1i,Ci,Cdi,D2i,Ei,EdiAnd D3iIs a known system matrix, d (t) is a time-varying time lag, d (t) satisfies:
h and mu are two scalar quantities which, a i(x(t))∈[0,1]andis two non-linear functions and satisfies
It is understood that the first establishing module 210 may be configured to perform the step S101.
The second building module 220 is used for building a global interval type two fuzzy filter model.
Specifically, the filtering apparatus 200 is used for establishing a global interval type two-stage fuzzy filter model g through the second establishing module 220β
Wherein j is 1,2, … p, β is 1,2, … r, Afj，BfjAnd CfjIs the parameter of the filtering that is, β j(x(t))∈[0,1]andis two non-linear functions and satisfies
It is understood that the second establishing module 220 may be configured to perform the step S102.
The third establishing module 230 is configured to establish a filtering error model according to the interval type T-S fuzzy time lag system model and the interval type two fuzzy filter model.
Specifically, the filtering apparatus 200 is used for determining the global interval type T-S fuzzy time-lag system model f according to the third establishing module 230αAnd said global interval two-type fuzzy filter model gβEstablishing a filtering error model
Wherein,
it is understood that the third establishing module 230 can be configured to perform the process of establishing the filtering error model according to the interval type T-S fuzzy time lag system model and the interval type fuzzy filter model in step S103.
The filtering module 240 is configured to perform filtering according to the filtering error model.
After the filtering error model is established, the filtering module 240 of the filtering apparatus 200 performs filtering according to the filtering error model.
It is understood that the filtering module 240 may be configured to perform the filtering process according to the filtering error model in step S103.
In summary, the filtering apparatus 200 according to the embodiment of the present invention uses the interval two-type T-S fuzzy model to better process the nonlinear system with parameter uncertainty, complete the design of filter parameters, and make filtering more stable.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus 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 apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (8)
1. A method of filtering, the method comprising:
establishing a global interval two type T-S fuzzy time-lag system model;
establishing a global interval type-two fuzzy filter model;
establishing a filtering error model according to the two-type interval T-S fuzzy time lag system model and the two-type interval fuzzy filter model, and filtering according to the filtering error model; the establishing of the global interval type T-S fuzzy time-lag system model comprises the following steps:
establishing a global interval two type T-S fuzzy time-lag system model fα
Wherein i 1,2, … p, α 1,2, … R, x (t) e RnIs the state vector, z (t) e RvIs the control output, y (t) e RmIs the measurement output, w ∈ RqIs a disturbance input, Ai,Adi,D1i,Ci,Cdi,D2i,Ei,EdiAnd D3iIs a known system matrix, d (t) is a time-varying time lag, d (t) satisfies:
0≤d(t)≤h，
h and mu are two scalar quantities which, a i(x(t))∈[0,1]andis two non-linear functions and satisfies
2. The filtering method according to claim 1, wherein said establishing a global interval type two-stage blur filter model comprises:
establishing a global interval two-type fuzzy filter model gβ
Wherein j is 1,2, … p, β is 1,2, … r, Afj，BfjAnd CfjIs the parameter of the filtering that is, β j(x(t))∈[0,1]andis two non-linear functions and satisfies
3. The filtering method according to claim 2, wherein the modeling a filtering error according to the interval type T-S fuzzy time-lag system model and the interval type two fuzzy filter model comprises:
according to the global interval two type T-S fuzzy time-lag system model fαAnd said global interval two-type fuzzy filter model gβEstablishing a filtering error model
Wherein,
4. a filtering apparatus, characterized in that the filtering apparatus comprises:
the first establishing module is used for establishing a global interval type T-S fuzzy time-lag system model;
the second establishing module is used for establishing a global interval type two fuzzy filter model;
the third establishing module is used for establishing a filtering error model according to the interval type T-S fuzzy time lag system model and the interval type II fuzzy filter model;
the filtering module is used for filtering according to the filtering error model; the first establishing module is used for establishing a global interval two-type T-S fuzzy time-lag system model fα
Wherein i 1,2, … p, α 1,2, … R, x (t) e RnIs the state vector, z (t) e RvIs the control output, y (t) e RmIs the measurement output, w ∈ RqIs a disturbance input, Ai,Adi,D1i,Ci,Cdi,D2i,Ei,EdiAnd D3iIs a known system matrix, d (t) is a time-varying time lag, d (t) satisfies:
0≤d(t)≤h，
h and mu are two scalar quantities which,a i(x(t))∈[0,1]the sum is two non-linear functions and satisfies
5. The filtering apparatus as claimed in claim 4, wherein the second establishing module is configured to establish a global interval type two-stage fuzzy filter model gβ
Wherein j is 1,2, … p, β is 1,2, … r, Afj，BfjAnd CfjIs the parameter of the filtering that is, β j(x(t))∈[0,1]andis two non-linear functions and satisfies
6. The filtering apparatus as claimed in claim 5, wherein the third establishing module is configured to determine the global interval-type T-S fuzzy time-lag system model f according to the global interval-type T-S fuzzy time-lag system modelαAnd said global interval two-type fuzzy filter model gβEstablishing a filtering error model
Wherein,
7. an electronic device, characterized in that the electronic device comprises:
a memory;
a processor; and
a filtering device installed in the memory and including one or more software function modules executed by the processor, the filtering device comprising:
the first establishing module is used for establishing a global interval type T-S fuzzy time-lag system model;
the second establishing module is used for establishing a global interval type two fuzzy filter model;
the third establishing module is used for establishing a filtering error model according to the interval type T-S fuzzy time lag system model and the interval type II fuzzy filter model;
the filtering module is used for filtering according to the filtering error model;
wherein the first establishingThe module is used for establishing a global interval two type T-S fuzzy time-lag system model fα
Wherein i 1,2, … p, α 1,2, … R, x (t) e RnIs the state vector, z (t) e RvIs the control output, y (t) e RmIs the measurement output, w ∈ RqIs a disturbance input, Ai,Adi,D1i,Ci,Cdi,D2i,Ei,EdiAnd D3iIs a known system matrix, d (t) is a time-varying time lag, d (t) satisfies:
0≤d(t)≤h，
h and mu are two scalar quantities which, a i(x(t))∈[0,1]andis two non-linear functions and satisfies
8. The electronic device of claim 7, wherein the electronic device is a personal computer.
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| CN101364277A (en) * | 2008-08-21 | 2009-02-11 | 上海交通大学 | Model building system based on T-S fuzzy model of interval type-2 fuzzy set |
| CN103595050A (en) * | 2013-11-22 | 2014-02-19 | 河海大学常州校区 | Method for controlling active power filter through model reference self-adaption fuzzy control |
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