CN105867125B - The optimal control method and device of refinery device coupling unit - Google Patents
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Abstract
The invention discloses a kind of optimal control method devices of refinery device coupling unit, wherein this method includes obtaining the closed-loop dynamic feedback decoupling compensator D (s) based on the pairing of Relative increasing rate circuit, controlled device G (s) is decoupled, G (s) is converted to generalized objectFor generalized objectDesign its internal mode controller C (s)；Calculate Indistinct Input amount, the output of process and process model output bias e (t) and deviation variation rateDetermine fuzzy rule, obtain internal mode controller parameter and e (t) andBetween fuzzy relation；By analysis to fuzzy rule, handles, tables look-up and operation is come on-line amending controller parameter λiValue, amendment are carried out according to following formula: λi=λi0+{Ei,ECi}λiWherein, λi0For according to the identification result of object model parameter and operating experience come to filter time constant, λiSet an initial value, { Ei,ECi}λiIt indicates after fuzzy logic inference calculates to λiOn-line amending.The whole process that this method can be realized controlled system automatically controls, and further preferably inhibits interference.
Description
Technical Field
The invention relates to the technical field of control, in particular to an optimization control method and device for a coupling unit of a refining device.
Background
At present, more than 1000 sets of oil refining and chemical production devices exist in the whole country, and due to the complex reaction in the chemical process, the problems of low automatic control rate, poor effect of control loops which are put into automatic operation, high labor intensity of device operators, unstable device operation and the like exist in the production field of oil refining and chemical industry. In order to solve the problems, various researches are carried out by a plurality of scientific researchers from different sides, the problems are classified into a plurality of aspects such as large time lag, nonlinearity, object complexity, frequent interference, poor use of a PID controller and the like, a plurality of solutions are provided, and the common problems are still not solved. Especially for the coupling unit, because of the correlation effect among the loops, the simple single-loop control cannot achieve the ideal control effect, and the engineering personnel usually decouple the multivariable object into the independent single-loop object for control. However, the conventional decoupling method often has the problems of complex design of the decoupler, incomplete decoupling, unsatisfactory control effect and the like.
In the production field, when the device carries out volume increase and volume reduction according to market demands, raw material conditions, factory scheduling and the like, if a plurality of loops of the device are in manual operation, operators are required to intensively adjust the volume of each position of the device: such as the outlet temperature of the heating furnace, the feeding and liquid level of the tower, the tower reflux and the like, the labor intensity of operators is high, the control precision of the device is low, the fluctuation is large, and the energy conservation and consumption reduction are not facilitated. Even when the device normally operates, due to the fact that a plurality of manual loops exist, the effect of a part of the loops which are put into automation is poor, the control loops of the device and unit equipment are not reasonable and perfect, the labor intensity of operators is high, the device has fluctuation, the control precision is low, and the energy consumption is high. If the full-flow automation is implemented, the labor intensity of operators can be greatly reduced, the device is stable and efficient to operate, and the energy consumption is reduced.
The internal model control is used as a novel control strategy in advanced control, and is widely applied to the multivariable control in the complex industrial process due to the characteristics of intuitive and simple design principle, easy adjustment, strong robustness and the like. However, the internal model control is a control method based on a controlled object model, and the accuracy of the model and the change of parameters directly affect the system performance. The parameters of the controlled object in the industrial field are often time-varying, the mismatch degree of the model is constantly changed, random interference always exists in the control process, and if fixed controller parameters are adopted, the control precision is difficult to ensure. Fuzzy control is intelligent control reflecting human intelligent thinking, is easy to process controlled objects or systems with complexity and fuzziness, does not need to know an accurate mathematical model of the controlled objects, and only needs to provide expert knowledge and experience or field operation data of skilled operators, so that the control mechanism and decision of the fuzzy control are easy to understand and receive, and the fuzzy control is beneficial to application and popularization. However, the precision of the fuzzy control is limited by the empirical rule and the quantization level, and in addition, for the ordinary fuzzy control, the control mode is similar to the control mode of proportional differentiation, a non-zero steady-state error is easy to generate, so that the fuzzy control belongs to poor regulation.
Disclosure of Invention
The object of the present invention is to solve at least to some extent one of the above mentioned technical problems.
Therefore, the first objective of the present invention is to provide an optimization control method for a coupling unit of a refining device, which can realize the full-flow automatic control of a controlled system and further better suppress interference.
A second object of the present invention is to provide an optimization control device for a coupling unit of a refining apparatus.
To achieve the above objects, embodiments of the first aspect of the present inventionThe optimization control method of the refining device coupling unit comprises the following steps: acquiring a closed-loop dynamic feedback decoupling compensator D(s) based on relative gain matrix loop pairing to decouple a controlled object G(s), and converting the G(s) into a generalized objectFor the generalized objectDesigning an inner mode controller C(s); calculating fuzzy input, deviation e (t) between process output and process model output and deviation change rateDetermining fuzzy rule to obtain internal model controller parameters and e (t) anda fuzzy relationship between; on-line correction of controller parameter lambda by analysis, processing, table look-up and calculation of said fuzzy ruleiThe value, corrected is according to the following formula:wherein λ isi0For the filter time constant, lambda, based on the identification result and operation experience of the object model parametersiAn initial value is set, and the initial value is set,represents the lambda after fuzzy logic reasoning calculationiOnline correction of (2).
According to the optimization control method of the coupling unit of the refining device, the closed-loop dynamic feedback decoupling compensator based on the relative gain matrix is designed to decouple the controlled object, the internal model controller is designed according to the characteristics of the decoupled generalized object, and finally the controller parameters are set by using the fuzzy control principle.
In one embodiment of the invention, the closed-loop dynamic feedback decoupling compensator D(s) based on the relative gain matrix loop pairing is obtained to decouple the controlled object G(s), and the G(s) is converted into a generalized objectThe method specifically comprises the following steps: the relative gain matrix (RGA) selects the controlled main loop T of each channel in several control loops coupled to each otheri-kI.e. the ith output is controlled by the kth input; row i and column k elements D of the closed loop dynamic feedback decoupler D(s)ikThe(s) element is set to 1, i.e. Dik(s) ═ 1; the closed loop dynamic feedback decoupler D(s) divides DikThe elements except for(s) are designed as follows:when the control object contains a non-minimum phase portion, performing skew compensation on the closed-loop dynamic feedback decoupler d(s), where the compensated closed-loop dynamic feedback decoupler d(s) can be represented as:wherein, tauik＝τ(Gik)-τi，Ensuring the generalized objectRelative gain matrix ofNone of the elements of (A) is less than zero, i.e.Wherein,
in an embodiment of the present invention, when the control object includes a non-minimum phase portion, performing skew compensation on the closed-loop dynamic feedback decoupler d(s) specifically includes: calculating τi：Determining generalized System element Hik(s)：Wherein G isik-(s) is GikMinimum phase part of(s), calculating DijTime lag τ (D) of(s)ij) And further determining a decoupler element Dij(s)：τ(Dij)＝τ(Gij)-τ(Hik)。
In order to achieve the above object, according to a second aspect of the present invention, there is provided an optimization control device for a coupling unit of a refining apparatus, comprising: a decoupling module for obtaining a closed loop dynamic feedback decoupling compensator D(s) based on a relative gain matrix loop pairing, decoupling and converting the controlled object G(s) into a generalized objectA design module for the generalized objectDesigning an inner mode controller C(s); a control module for calculating the deviation e (t) and the deviation change rate of the fuzzy input process output and the process model outputDetermining fuzzy rule to obtain internal model controller parameters and e (t) andthe fuzzy relation between the parameters is corrected on line by analyzing, processing, looking up table and operation on the fuzzy ruleiThe value, corrected is according to the following formula:wherein λ isi0To determine the time constant lambda of the filter based on the identification result and operation experience of the object model parametersiAn initial value is set, and the initial value is set,represents the lambda after fuzzy logic reasoning calculationiOnline correction of (2).
According to the optimization control device of the refining device coupling unit, the decoupling module is designed to decouple a controlled object based on a closed-loop dynamic feedback decoupling compensator of a relative gain matrix, the design module is used for designing the internal model controller according to the characteristics of the decoupled generalized object, and finally the control module is used for setting the parameters of the controller by utilizing the fuzzy control principle.
In an embodiment of the invention, the decoupling module is specifically configured to: the relative gain matrix selects the controlled main loop T of each channel in several control loops coupled to each otheri-kI.e. the ith output is controlled by the kth input; row i and column k elements D of the closed loop dynamic feedback decoupler D(s)ikThe(s) element is set to 1, i.e. Dik(s) ═ 1; the closed loop dynamic feedback decoupler D(s) divides DikThe elements except for(s) are designed as follows:when the control object contains a non-minimum phase portion, performing skew compensation on the closed-loop dynamic feedback decoupler d(s), where the compensated closed-loop dynamic feedback decoupler d(s) can be represented as:wherein, tauik＝τ(Gik)-τi，Ensure thatGeneralized objectRelative gain matrix ofNone of the elements of (A) is less than zero, i.e.Wherein,
in one embodiment of the invention, the decoupling module is further configured to: calculating τi：Determining generalized System element Hik(s)：Wherein G isik-(s) is GikMinimum phase part of(s), calculating DijTime lag τ (D) of(s)ij) And further determining a decoupler element Dij(s)：τ(Dij)＝τ(Gij)-τ(Hik)。
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
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The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which,
FIG. 1 is a flow chart of a method for optimizing control of a refinery unit coupling unit according to one embodiment of the present invention;
FIG. 2 is a schematic structural diagram of a decoupling control system of a closed loop dynamic feedback decoupler according to one embodiment of the present invention;
FIG. 3 is a schematic diagram of a fuzzy controller according to one embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an optimization control device of a refinery unit coupling unit according to an embodiment of the invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
The following describes an optimization control method and device for a coupling unit of a refining device according to an embodiment of the present invention with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for optimizing control of a refinery unit coupling unit according to one embodiment of the present invention.
As shown in fig. 1, the optimization control method of the refining device coupling unit may include:
s1, obtaining a closed loop dynamic feedback decoupling compensator D (S) based on the relative gain matrix loop pairing, decoupling and converting the controlled object G (S) into a generalized object
Wherein, for example, for a given n × n-dimensional controlled object g(s), the RGA of the system is:
selecting lambda according to the principle of loop pairing based on the relative gain matrixijThe circuit as close as possible to 1 is the optimal matching circuit to avoid lambdaij0 or λijThe < 0 loops are paired. And then the closed loop dynamic feedback decoupling compensator can be designed according to the pairing principle.
It should be noted that, in the embodiment of the present invention, the controlled main loop T of each channel is selected among several control loops coupled to each other with respect to the gain matrixi-kI.e. the ith output is controlled by the kth input; row i and column k elements D of closed loop dynamic feedback decoupler D(s)ikThe(s) element is set to 1, i.e. Dik(s) ═ 1; closed loop dynamic feedback decoupler D(s) divide DikThe elements except for(s) are designed as follows:when the control object contains the non-minimum phase part, the time lag compensation is carried out on the closed-loop dynamic feedback decoupler D(s), and the compensated closed-loop dynamic feedback decoupler D(s) can be expressed as follows:wherein, tauik＝τ(Gik)-τi，Securing generalized objectsRelative gain matrix ofNone of the elements of (A) is less than zero, i.e.Wherein,
it should be noted that, in the embodiment of the present invention, when the controlled object includes the non-minimum phase portion, performing the skew compensation on the closed-loop dynamic feedback decoupler d(s) specifically includes: calculating τi：Determining generalized System element Hik(s)，Wherein G isik-(s) is GikMinimum phase part of(s), calculating DijTime lag τ (D) of(s)ij) And further determining a decoupler element Dij(s)：τ(Dij)＝τ(Gij)-τ(Hik)。
For example, assume that the controlled object is 3 × 3, and after loop pairing, the optimal control loop is Ti-iFig. 2 shows a block diagram of a decoupling control system of the closed-loop dynamic feedback decoupler d(s). As can be seen from fig. 2, the system variables satisfy the following relationship:
U(s)＝D(s)M(s) (2)
wherein,
then
M(s)＝D-1(s)U(s) (3)
The compensator is acted on the controlled object to obtain a decoupled generalized object
Will Dij(s) bringing in and decomposing D(s) by:
inversion of D(s) by
D-1(s)＝G-1(s)GΛ(s) (6)
Wherein,
further, the decoupled objects can be obtained as follows:
if an open-loop transfer function H(s) obtained after the decoupling compensation is carried out on the system by adopting a closed-loop dynamic decoupling feedback decoupling device is adopted, the property of the compensator can be known as follows:
when the controlled object contains time lag part, in order to ensure Dij(s) with a time lag that must satisfy:
byIn a clear view of the above, it is known that,
τ(Dij)＝τ(Gij)-τ(Gii)≤τ(Gij)-τi (8)
wherein,
according to the decoupling structure analysis of the closed loop dynamic feedback decoupling device,
D(s)＝H-1(s)G(s) (9)
τ(Dij) Can be expressed as
τ(Dij)＝τ(Gij)-τ(Hii) (10)
To ensure tau (D)ij) More than or equal to 0, if H(s) contains the minimum time lag of the control object, that is
τ(Hii)＝τi (11)
Thereby decoupled diagonal element HiiCan be expressed as:
wherein G isii-(s) is GiiThe minimum phase part of(s).
That is, when the control object has the minimum phase portion, in order to ensure the stability and realizability of the system, the time lag compensation must be performed on the decoupler d(s), and the compensated decoupler d(s) can be expressed as
To realize the decoupling control of the multivariable system, not only a decoupling controller of the system needs to be designed, but also the stability of the system needs to be analyzed. Only when the decoupler is designed on the premise of ensuring the stability of the system, the decoupling control of the existing system is completed. The nature of the internal model control shows that only two points need to be ensured to realize the internal model control of the system: firstly, the controlled object is stable, and secondly, the designed internal model controller is stable. Therefore, the generalized object after adopting the feedforward-like decoupling control action can be provedAnd the system is stable, so that decoupling control of the system can be realized.
The relative gain matrix of the system may characterize the effect of any input of the system on the other output channels. In general, we want it to be a diagonal dominance matrix with each element greater than zero. If one element in the matrix is less than zero, the system has a negative coupling channel. When the open loop and the closed loop of other loops are switched, the phenomenon of instability of a negative coupling channel can be caused, and the stability of the whole system is influenced. Therefore, a broad system after decoupling is ensuredStability of (2), we only need to makeRelative gain matrix ofAny one of the elements is not less than zero. That is, forRelative gain matrix of
Only need to useStable control of the system can be achieved.
S2, aiming at the generalized objectThe inner mode controller C(s) is designed.
In particular, the amount of the solvent to be used,wherein,is composed ofThe minimum phase part of, f(s), the low-pass filter that the controller can implement, has the form:
wherein,λibeing the only adjustable parameter of the controller, niAre of relative order.
To ensure the realizability of the controller, niIt needs to be large enough. When the system is decoupled into a diagonal array, the internal model controller of the control system can be designed according to a single-variable system. From the foregoing analysis, it can be seen that the internal model of the post-decoupling systemIs composed of
Due to the fact thatContaining non-minimum phase parts and therefore requiring their decomposition into minimum phase partsAnd a non-minimum phase partThus obtaining an internal mold controller as follows:
wherein F(s) diagf11,F22,…,FnnTo ensure a low-pass filter that the controller can implement,λibeing the only adjustable parameter of the controller, niIn relative order, to ensure the realizability of the controller, niIt needs to be large enough.
Further, the internal model controller can be obtained as follows:
C(s)＝diag{C11(s),C22(s),C33(s)} (18)
wherein,
s3, calculating the deviation e (t) between the fuzzy input quantity process output and the process model output andrate of change of deviation
Establishing fuzzy rule according to process output Y(s) and process model output YmDeviation of(s) e(s) Y(s) -Ym(s) and the rate of change of deviation EC(s) are adjusted on-line.
S4, determining fuzzy rule to obtain internal model controller parameters and e (t) andthe fuzzy relationship between them.
S5, continuously correcting the controller parameter lambda on line by analyzing, processing, looking up tables and calculating fuzzy rulesiThe value, corrected is according to the following formula:wherein λ isi0For the filter time constant, lambda, based on the identification result and operation experience of the object model parametersiAn appropriate initial value is set for each of the first and second values,represents the lambda after fuzzy logic reasoning calculationiOnline correction of (2).
For example, the fuzzy controller structure is shown in FIG. 3. The decoupled controlled object is composed of 3 mutually independent loops, and the controller can be designed according to the control method of the univariate system. For the ith loop, the filter parameter λiIs output according to the processiAnd process model output ymiDeviation E ofi＝yi-ymiAnd rate of change of deviation ECiAnd performing online adjustment. Input to the fuzzy controller: deviation EiAnd rate of change of deviation ECiAnd performing seven-level language quantization according to fuzzy set theory, wherein language variables are { NB, NM, NS, Z, PS, PM, PB }, and respectively represent { negative large, negative medium, negative small, zero, positive small, positive medium, positive large }。EiAnd ECiThe membership function is selected in a form of combining triangular, Z-type and S-type membership functions, the domain of discourse is selected according to the actual controlled object, and lambda isiThe membership function of (a) is taken as a trigonometric function.
λiInitial value λ ofi0The determination of the discourse domain is based on a large number of simulations of the system, with an initial value of lambdai0Determined according to the model mismatch degree and robust performance analysis of the system, ensuring lambdaiThe value is not negative. For systems with large dead time or large time constant of inertia, λiInitial value λ ofi0A larger value is required to ensure that the system has stronger robustness and is more stable when the system starts to operate; λ when the system skew or inertia time constant is smalli0The value of the signal can be smaller to ensure that the system has higher response speed. Lambda [ alpha ]iIs determined based on a robust stability analysis of the system and the upper bound of lambda is determined based on a robust performance analysis of the system. In practical applications, λ can also be adjusted by changing the quantization factor for different process objectsiThe scope of discourse of (a).
Adjusting lambdaiThe fuzzy rule of (2) is established according to the following steps: deviation E between process output and process model outputiAnd rate of change of deviation ECiWhen large, a large λ is requirediWhen deviation EiAnd rate of change of deviation ECiVery small, a smaller λ is requiredi. Then, proper adjustment is carried out through a large number of simulation experiments, and finally the adjusted lambda is obtainediThe first column of the fuzzy rule table of (1) represents EiThe first row represents ECiAs shown in table 1:
TABLE 1 fuzzy control rules
In industrial field practical application, filtering can be performed according to identification result and operation experience of object model parametersTime constant lambda of the deviceiSetting a proper initial value lambdai0Then continuously correcting lambda online by analyzing, processing, looking up table and operation of fuzzy ruleiThe value, corrected is according to the following formula:
in the formula,represents the lambda after fuzzy logic reasoning calculationiOnline correction of (2).
According to the optimization control method of the coupling unit of the refining device, the closed-loop dynamic feedback decoupling compensator based on the relative gain matrix is designed to decouple the controlled object, the internal model controller is designed according to the characteristics of the decoupled generalized object, and finally the controller parameters are set by using the fuzzy control principle.
Corresponding to the optimization control method of the coupling unit of the refining apparatus provided in the above embodiment, an embodiment of the present invention further provides an optimization control device of the coupling unit of the refining apparatus, and since the optimization control method of the coupling unit of the refining apparatus provided in the embodiment of the present invention corresponds to the optimization control device of the coupling unit of the refining apparatus provided in the above embodiment, the embodiment of the optimization control method of the coupling unit of the refining apparatus provided in the above embodiment is also applicable to the optimization control device of the coupling unit of the refining apparatus provided in the present embodiment, and will not be described in detail in the present embodiment. FIG. 4 is a schematic structural diagram of an optimization control device of a refinery unit coupling unit according to an embodiment of the invention. As shown in fig. 4, the optimization control device of the refining device coupling unit may include: a decoupling module 10, a design module 20 and a control module 30.
Wherein the decoupling module 10 is used to acquire phase-basedA closed loop dynamic feedback decoupling compensator D(s) paired with the gain matrix loop decouples the controlled object G(s) and converts the decoupled object G(s) into a generalized object
Design module 20 is used to target generalized objectsThe inner mode controller C(s) is designed.
The control module 30 is used for calculating the deviation e (t) and the deviation change rate of the fuzzy input quantity process output and the process model outputDetermining fuzzy rule to obtain internal model controller parameters and e (t) andthe fuzzy relation between the parameters is corrected on line by analyzing, processing, looking up table and operation on the fuzzy ruleiThe value, corrected is according to the following formula:
wherein λ isi0To determine the time constant lambda of the filter based on the identification result and operation experience of the object model parametersiAn initial value is set, and the initial value is set,represents the lambda after fuzzy logic reasoning calculationiOnline correction of (2).
In one embodiment of the invention, the decoupling module 10 is particularly adapted to select the controlled main loop T of each channel among several control loops coupled to each other with respect to the gain matrixi-kI.e. the ith output is controlled by the kth input; closed loop dynamic feedbackRow i and column k elements D of decoupler D(s)ikThe(s) element is set to 1, i.e. Dik(s) ═ 1; closed loop dynamic feedback decoupler D(s) divide DikThe elements except for(s) are designed as follows:when the control object contains the non-minimum phase part, the time lag compensation is carried out on the closed-loop dynamic feedback decoupler D(s), and the compensated closed-loop dynamic feedback decoupler D(s) can be expressed as follows:wherein, tauik＝τ(Gik)-τi，Securing generalized objectsRelative gain matrix ofNone of the elements of (A) is less than zero, i.e.Wherein,
in an embodiment of the present invention, the decoupling module 10 is further configured to perform skew compensation on the closed-loop dynamic feedback decoupler d(s) when the control object includes a non-minimum phase portion, specifically including: calculating τi：Determining generalized System element Hik(s)，Wherein G isik-(s) is GikMinimum phase part of(s), calculating DijTime lag τ (D) of(s)ij) And further determining a decoupler element Dij(s)：τ(Dij)＝τ(Gij)-τ(Hik)。
According to the optimization control device of the refining device coupling unit, the decoupling module is designed to decouple a controlled object based on a closed-loop dynamic feedback decoupling compensator of a relative gain matrix, the design module is used for designing the internal model controller according to the characteristics of the decoupled generalized object, and finally the control module is used for setting the parameters of the controller by utilizing the fuzzy control principle.
In the description of the present invention, it is to be understood that the terms "first", "second" and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (4)
1. An optimization control method for a coupling unit of a refining device is characterized by comprising the following steps:
acquiring a closed-loop dynamic feedback decoupling compensator D(s) based on relative gain matrix loop pairing to decouple a controlled object G(s), and converting the G(s) into a generalized object
For the generalized objectDesigning an inner mode controller C(s);
calculating fuzzy input, deviation e (t) between process output and process model output and deviation change rate
Determining fuzzy rule to obtain internal model controller parameters and e (t) anda fuzzy relationship between;
on-line correction of controller parameter lambda by analysis, processing, table look-up and calculation of said fuzzy ruleiThe value, corrected is according to the following formula:
wherein λ isi0For the filter time constant, lambda, based on the identification result and operation experience of the object model parametersiAn initial value is set, and the initial value is set,represents the lambda after fuzzy logic reasoning calculationiOnline correction;
wherein the closed loop dynamic feedback decoupling compensator D(s) based on the relative gain matrix loop pairing is obtained to decouple the controlled object G(s), and the G(s) is converted into a generalized objectThe method specifically comprises the following steps:
the relative gain matrix selects the controlled main loop T of each channel in several control loops coupled to each otheri-kI.e. the ith output is controlled by the kth input;
row i and column k elements D of the closed loop dynamic feedback decoupler D(s)ikThe(s) element is set to 1, i.e. Dik(s)＝1；
The closed loop dynamic feedback decoupler D(s) divides DikThe elements except for(s) are designed as follows:
when the control object contains a non-minimum phase portion, performing skew compensation on the closed-loop dynamic feedback decoupler d(s), where the compensated closed-loop dynamic feedback decoupler d(s) can be represented as:
wherein, tauik＝τ(Gik)-τi，
Ensuring the generalized objectRelative gain matrix ofIs not less than zero for any of the elements,wherein,
2. the optimization control method according to claim 1, wherein the time lag compensating the closed loop dynamic feedback decoupler d(s) when the control object has a non-minimum phase portion specifically comprises:
calculating τi：
Determining generalized System element Hik(s)：
Wherein G isik-(s) is GikThe minimum phase portion of(s) is,
calculating DijTime lag τ (D) of(s)ij) And further determining a decoupler element Dij(s)：
τ(Dij)＝τ(Gij)-τ(Hik)。
3. An optimization control device for a coupling unit of a refining device, comprising:
a decoupling module for obtaining a closed loop dynamic feedback decoupling compensator D(s) based on a relative gain matrix loop pairing, decoupling and converting the controlled object G(s) into a generalized object
A design module for targeting said generalized objectDesigning an inner mode controller C(s);
a control module for calculating the deviation e (t) and deviation change rate of the fuzzy input process output and the process model outputDetermining fuzzy rule to obtain internal model controller parameters and e (t) andbetweenBy analyzing, processing, looking up tables and calculating the fuzzy rule to correct the controller parameter lambda on lineiThe value, corrected is according to the following formula:
wherein λ isi0To determine the time constant lambda of the filter based on the identification result and operation experience of the object model parametersiAn initial value is set, and the initial value is set,represents the lambda after fuzzy logic reasoning calculationiOnline correction;
wherein the decoupling module is specifically configured to:
the relative gain matrix selects the controlled main loop T of each channel in several control loops coupled to each otheri-kI.e. the ith output is controlled by the kth input;
row i and column k elements D of the closed loop dynamic feedback decoupler D(s)ikThe(s) element is set to 1, i.e. Dik(s)＝1；
The closed loop dynamic feedback decoupler D(s) divides DikThe elements except for(s) are designed as follows:
when the control object contains a non-minimum phase portion, performing skew compensation on the closed-loop dynamic feedback decoupler d(s), where the compensated closed-loop dynamic feedback decoupler d(s) can be represented as:
wherein, tauik＝τ(Gik)-τi，
Ensuring the generalized objectRelative gain matrix ofIs not less than zero for any of the elements,wherein,
4. the optimization control of claim 3, wherein the decoupling module is further configured to:
calculating τi：
Determining generalized System element Hik(s)：
Wherein G isik-(s) is GikThe minimum phase portion of(s) is,
calculating DijTime lag τ (D) of(s)ij) And further determining a decoupler element Dij(s)：
τ(Dij)＝τ(Gij)-τ(Hik)。
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