Improved grey GM(1,1) prediction method and system for output current of EAST fast-control power supply

Abstract

The present invention relates to the technical field of EAST fast control power supply operation, and provides an improved grey GM (1,1) prediction method for the output current of an EAST fast control power supply, comprising: obtaining an original sequence X by sampling (0) And generate the cumulative sequence X (1) (k) In the background value construction of the gray GM(1,1) prediction model, the cumulative sequence is segmented to approximate the background value. When the predicted value sequence curve is different from the output current curve in terms of concavity and convexity, the cumulative sequence is reconstructed using the transformation operator, and the background value, gray development coefficient and gray amount are recalculated. The predicted output current of the next switching cycle is used to replace the old value in the original sequence to update the original sequence, and then the output current of the next two switching cycles is predicted to compensate for the inherent delay of digital hysteresis control. The output current of the EAST fast-control power supply is accurately predicted, the output current response speed is accelerated, and the balance control performance of the plasma vertical displacement is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of EAST fast control power supply operation, and in particular to an improved grey GM (1,1) prediction control method and system for the output current of an EAST fast control power supply. Background Art

[0002] The Experimental Advanced Superconducting Tokamak (EAST) is an important engineering device for achieving controlled nuclear fusion. The main function of the fast-controlled power supply is to excite the load coil according to the reference signal output current to ensure that the plasma can quickly achieve magnetic confinement balance control in the vertical displacement, avoiding the plasma hitting the vacuum wall and causing discharge failure.

[0003] The plasma vertical displacement active feedback control system detects the vertical displacement of the plasma in real time and calculates the reference signal required to maintain the vertical displacement balance of the plasma in real time. The EAST fast-control power supply tracks the given reference signal and quickly outputs current to excite the load coil to achieve rapid closed-loop feedback control of the plasma in the vertical direction, ensuring the rapidity of the vertical displacement of the plasma. The reference signal is linearly corresponding to the output current of the fast-control power supply. The given reference signal of ±10V corresponds to the output current of the EAST fast-control power supply branch of ±1500A. When the vertical displacement of the plasma deviates, in order to quickly pull the plasma back to the vertical equilibrium position to avoid plasma collision and fragmentation and discharge failure, the EAST fast-control power supply is required to have a fast output current dynamic response speed, which places high demands on the dynamic response performance of the power supply.

[0004] The EAST fast-control power supply utilizes a digital hysteresis control scheme. The output current speed is primarily limited by the voltage applied to the output load coil and the system's inherent delay time. A higher voltage level and a shorter digital hysteresis control system delay result in a faster output current buildup. In practical engineering applications, to further improve the output current buildup speed of the EAST fast-control power supply, the voltage level at the load coil output terminal must be increased. This also requires further improvements in the voltage and current withstand capabilities of the power devices in the EAST fast-control power supply. However, to avoid a significant increase in switching losses, the switching frequency of the power switching devices must be further reduced. The lower switching frequency introduces significant system control delay, resulting in a slower output current buildup speed. The need to increase the output voltage level and the constraint of lowering the switching frequency create conflicting constraints on the rapid output current buildup speed of the EAST fast-control power supply, making it difficult to further improve the dynamic response speed of the output current.

[0005] Predictive control, which predicts the output current trajectory in advance, is an effective means of improving the output current response speed of the EAST fast-control power supply. Gray GM(1,1) prediction requires only a small amount of known target information to achieve target quantity prediction. For example, Chinese invention patent publication number CN111523700A, "EAST fast-control power supply output current prediction method based on improved gray GM(1,1) model prediction," discloses an improved gray GM(1,1) model prediction method. Based on the monotonicity of the EAST fast-control power supply output current, the original gray prediction sequence is divided into two phases: ascending and descending. A non-uniformly spaced gray GM(1,1) prediction model is established for the ascending phase sequence, and an equally spaced gray GM(1,1) prediction model is established for the descending phase sequence, achieving precise and rapid control of the EAST fast-control power supply output current. Chinese invention patent publication number CN113269350A, "Transformer Fault Prediction Method Based on Gray GM(1,1) Model," sequentially optimizes the errors in the GM(1,1) model and, through permutation, produces eight optimized prediction schemes, meeting diverse needs. The Chinese invention patent with publication number CN113592131A, "A method for predicting the annual generation of construction waste based on an improved grey GM (1,1) model," divides the original sequence into different stage sequences and establishes a non-uniformly spaced improved grey GM (1,1) model to achieve precise positioning and rapid control of construction waste monitoring and management.

[0006] The above patent application modified the grey GM(1,1) prediction model and established a non-uniformly spaced improved grey GM(1,1) model or an optimized prediction scheme. However, in the output current prediction and control of the EAST fast-control power supply, there are still problems such as the inconsistency between the convexity and concavity of the grey GM(1,1) prediction value sequence and the actual output current curve, the overly complex background value construction process and even large errors, the outdated information of the original sequence seriously affecting the prediction accuracy, and the digital hysteresis control delay seriously affecting the output current response speed. These problems result in a decrease in the prediction accuracy of the output current of the EAST fast-control power supply and seriously affect the output current control performance. Summary of the Invention

[0007] The technical problem to be solved by the present invention is how to reduce the prediction error of the output current of the EAST fast-control power supply, thereby ensuring the rapidity and accuracy of the output current of the EAST fast-control power supply.

[0008] The present invention solves the above technical problems through the following technical means:

[0009] The present invention provides an improved grey GM (1,1) prediction method for the output current of an EAST fast-controlled power supply, comprising the following steps:

[0010] S1. Sample the output current of the EAST fast control power supply and obtain the original sequence X of the grey GM (1,1) prediction model composed of the output current sampling data in the last four switching cycles. (0) , the expression is:

[0011] X (0) =[X (0) (1),X (0) (2),...,X (0) (n)] (1)

[0012] S2, based on the original sequence X (0) , generate the cumulative sequence X (1) (k), where k represents the switching period, and then combined with the idea of ​​calculus, the cumulative sequence X (1) (k) The background value sequence Z is obtained by segmentation approximation calculation (1) (k);

[0013] S3, based on the background value sequence Z obtained in step S2 (1) (k) and the original current sampling data, calculate the gray development coefficient a and the gray amount b; judge whether the background value sequence Z needs to be reconstructed according to the size of the gray development coefficient a. (1) (k) and recalculate the gray development coefficient a and gray amount b;

[0014] S4, based on the gray development coefficient a, gray amount b and original sequence X obtained in step S3 (0) , predict the output current i(k+1) of the next switching cycle, and replace the original sequence X with the output current i(k+1) of the next switching cycle (0) The oldest current sampling value in the original sequence X is obtained (0) ;

[0015] S5, based on the updated original sequence X (0) , repeat steps S2 to S4 to predict the output current i(k+2) of the next switching cycle again;

[0016] S6. Take i(k+2) as the latest predicted value of the output current; subtract the signal corresponding to i(k+2) from the reference signal to obtain the output current error; when the output current error is small, adjust the proportional control parameter of the EAST fast-control power supply to be smaller; when the output current error is large, adjust the proportional control parameter of the EAST fast-control power supply to be larger to adjust the duty cycle of the power switch tube.

[0017] Furthermore, the cumulative sequence expression described in step S2 is

[0018]

[0019] Furthermore, the cumulative sequence X is combined with the calculus idea in step S2. (1) (k) The background value sequence Z is obtained by segmentation approximation calculation (1) (k) Specifically:

[0020] The accumulated sequence X (1) (k) The curve is divided into l rectangles, and the area of ​​l rectangles is used to approximate the integral value of the curve. The cumulative sequence X (1) (k) After segmentation, the background value sequence Z is approximately calculated (1) (k), the background value sequence expression is:

[0021]

[0022] Where k represents the switching period.

[0023] Furthermore, the gray development coefficient a and gray amount b are calculated in step S3, and the specific calculation expressions are:

[0024] X n =[X (0) (2) X (0) (3) X (0) (4)] T (5)

[0025]

[0026] Furthermore, in step S3, it is determined whether the background value sequence Z needs to be reconstructed by the size of the gray development coefficient a. (1) (k) and update the calculation of the gray development coefficient a and the gray amount b, specifically:

[0027] When a>0, the background value sequence Z is retained (1) (k), and retain the calculated gray development coefficient a and gray amount b;

[0028] When a<0, the cumulative sequence X is reconstructed through the transformation operator Δ(1) (k), and based on the reconstructed cumulative sequence X Δ(1) (k) Recalculate the background value sequence Z (1) (k), and then based on the recalculated background value sequence Z (1) (k) Update and calculate the gray development coefficient a and gray amount b.

[0029] Furthermore, the cumulative sequence X is reconstructed by the transformation operator Δ(1) (k), specifically:

[0030] Reconstruct the cumulative sequence X Δ(1) In the process of (k), the original sequence error caused by the inconsistency of concavity and convexity is first calculated as

[0031] Δ(k+1)=X (1) (nk)-X (1) (nk-1),k=0,1,...,n-2 (8)

[0032] The reconstructed cumulative sequence is

[0033]

[0034] Furthermore, the output current i(k+1) of the next switching cycle described in step S4 is predicted as follows:

[0035]

[0036] Furthermore, the updated original sequence X in step S4 (0) The expression is

[0037] X (0) =[X (0) (2),...,X (0) (n),i(k+1)]. (11)

[0038] The present invention also provides an improved grey GM (1,1) prediction system for the output current of an EAST fast-controlled power supply. The system adopts the above-mentioned method when running, and includes the following modules:

[0039] The sampling module is used to sample the output current of the EAST fast control power supply and obtain the original sequence X of the grey GM (1,1) prediction model composed of the output current sampling data in the last four switching cycles. (0) , the expression is:

[0040] X (0) =[X (0) (1),X (0) (2),...,X (0) (n)] (1)

[0041] Background value sequence calculation module is used to calculate the background value sequence based on the original sequence X (0) , generate the cumulative sequence X (1) (k), where k represents the switching period, and then combined with the idea of ​​calculus, the cumulative sequence X (1) (k) The background value sequence Z is obtained by segmentation approximation calculation (1) (k);

[0042] Gray parameter calculation module, used for background value sequence Z obtained based on background value sequence calculation module (1)(k) and the original current sampling data, calculate the gray development coefficient a and the gray amount b; judge whether the background value sequence Z needs to be reconstructed according to the size of the gray development coefficient a. (1) (k) and recalculate the gray development coefficient a and gray amount b;

[0043] The first current prediction module is used to calculate the gray development coefficient a, gray quantity b and original sequence X obtained in step S3. (0) , predict the output current i(k+1) of the next switching cycle, and replace the original sequence X with the output current i(k+1) of the next switching cycle (0) The oldest current sampling value in the original sequence X is obtained (0) ;

[0044] The second current prediction module is used to predict the current based on the updated original sequence X (0) , repeatedly run the background value sequence calculation module, the gray parameter calculation module and the first current prediction module to predict the output current i(k+2) of the next switching cycle again;

[0045] The control module is used to use i(k+2) as the latest predicted value of the output current; the signal corresponding to i(k+2) is subtracted from the reference signal to obtain the output current error; when the output current error is small, the proportional control parameter of the EAST fast-control power supply is adjusted to be smaller; when the output current error is large, the proportional control parameter of the EAST fast-control power supply is adjusted to be larger to adjust the duty cycle of the power switch tube.

[0046] Furthermore, the grey parameter calculation module includes a grey development coefficient a determination unit, and its specific operation mode is as follows:

[0047] When a>0, the background value sequence Z is retained (1) (k), and retain the calculated gray development coefficient a and gray amount b;

[0048] When a<0, the cumulative sequence X is reconstructed through the transformation operator Δ(1) (k), and based on the reconstructed cumulative sequence X Δ(1) (k) Recalculate the background value sequence Z (1) (k), and then based on the recalculated background value sequence Z (1) (k) Update and calculate the gray development coefficient a and gray amount b.

[0049] The advantages of the present invention are:

[0050] (1) This invention improves the background value sequence Z obtained by the median theorem in traditional grey prediction. (1) (k), combined with the idea of ​​calculus, the cumulative sequence X (1)(k) The curve is divided into l rectangles to replace the right trapezoid in the mean value theorem, and the area of ​​l rectangles is used to approximate the integral value of the curve. The cumulative sequence X (1) (k) After segmentation, the background value sequence Z is approximately calculated (1) (k) is used to reduce the error caused by the median theorem, so that the background value sequence is more consistent with the law of the grey GM (1,1) prediction model and the prediction accuracy of the grey GM (1,1) prediction model is improved.

[0051] (2) The present invention is based on the background value sequence Z (1) (k) and the original current sampling data, calculate the gray development coefficient a and the gray amount b, and further judge the value of a; when a>0, the concavity and convexity of the predicted value sequence curve obtained by prediction is the same as the concavity and convexity of the actual output current curve, and retain the background value sequence Z (1) (k), and retain the calculated gray development coefficient a and gray amount b; when a<0, the concavity and convexity of the predicted value sequence curve obtained by prediction is different from the concavity and convexity of the actual output current curve, then the cumulative sequence X is reconstructed through the transformation operator Δ(1) (k), then based on the reconstructed cumulative sequence X Δ(1) (k) and calculus ideas to recalculate the background value sequence Z (1) (k), and according to the updated background value sequence Z (1) (k) Recalculate the gray development coefficient a and the gray quantity b; determine whether the values ​​of a and b need to be recalculated based on the values ​​of the gray development coefficient a and the gray quantity b, ensuring that the predicted value sequence curve is consistent with the characteristic curve of the actual output current, so that the prediction accuracy of the output current is further improved.

[0052] (3) The present invention promptly discards the old original sequence value and updates the original sequence X (0) , the gray development coefficient a and gray amount b are calculated again, the influence of old information is eliminated, and a rolling two-step output current prediction is realized, which ensures the output current prediction accuracy. Especially when the reference signal mutates, the output current prediction accuracy is further improved.

[0053] (4) In step six of the present invention, the current i(k+2) is used as the latest predicted value of the output current, which compensates for the inherent delay of the EAST fast-controlled power supply digital hysteresis control system, so that the current value sampled in the k+1th cycle is actually the current output value obtained by the system under the control of the control quantity u(k+1), which is consistent with the value expected by the system, thereby improving the dynamic response speed of the output current and the tracking accuracy of the output current.

[0054] (5) Combining the gray GM (1,1) prediction model to make advance predictions on the output current trajectory, it is possible to achieve faster and more accurate output of the output current without increasing the power level of the power supply, and significantly improve the balance control performance of the plasma displacement in the vertical direction. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 Schematic diagram of the grey GM (1,1) model prediction process for the overall output current in an example of the present invention;

[0056] Figure 2 This is a schematic diagram of the background value sequence segmentation and approximate calculation in combination with the calculus idea in the example of the present invention;

[0057] Figure 3 Schematic diagram of compensating digital hysteresis control delay in an example of the present invention;

[0058] Figure 4 This is a schematic diagram of the predicted output current tracking given signal waveform of the EAST fast control power supply gray GM (1,1) in the example of the present invention. DETAILED DESCRIPTION

[0059] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0060] Example 1

[0061] This example provides an improved grey GM(1,1) prediction method for the output current of an EAST fast-control power supply. Figure 1 As shown, the following steps are included:

[0062] S1. The output current of the EAST fast control power supply is sampled through a 1:5000 current sensor and an ADC digital sampling chip, and the original sequence X of the grey GM (1,1) prediction model consisting of the output current sampling data in the last four switching cycles is obtained. (0) , the original sequence expression is

[0063] X (0) =[X (0) (1),X (0) (2),…,X (0) (n)] (1)

[0064] Among them, n can be 4, X (0) (1)~X (0)(n) represents the first 4 sampling data points, and X will be deleted first when the original sequence is updated later. (0) (1), the remaining data will be moved forward, and the newly added data will be placed at the end of the data group to ensure the time series validity of the original sequence.

[0065] S2, based on the original sequence X (0) , generate the cumulative sequence X (1) (k), the generated cumulative sequence expression is

[0066]

[0067] Among them, k represents the switching period, and then combined with the idea of ​​calculus, the cumulative sequence X (1) (k) The background value sequence Z is obtained by segmentation approximation calculation (1) (k).

[0068] In traditional grey prediction, the median theorem is used as a simple approximate substitute calculation, but there is a large error. The background value constructed is

[0069]

[0070] In this embodiment, the cumulative sequence X is combined with the idea of ​​calculus (1) (k) The curve is divided into l rectangles to replace the right trapezoid in the mean value theorem, such as Figure 2 As shown, the area of ​​1 rectangle is used to approximate the integral value of the curve, and the cumulative sequence X (1) (k) After segmentation, the background value sequence Z is approximately calculated (1) (k), in order to reduce the error caused by the mean value theorem, the background value sequence expression obtained by segmentation approximate calculation is:

[0071]

[0072] S3, based on background value sequence Z (1) (k) and the original current sampling data, calculate the gray development coefficient a and gray amount b, and the expressions are:

[0073] X n =[X (0) (2) X (0) (3) X (0) (4)] T (5)

[0074]

[0075] In traditional grey prediction, the output can be predicted by calculating the development coefficient a and the grey quantity b. However, in this embodiment, in order to ensure that the predicted value sequence curve is consistent with the actual output current curve characteristics and to ensure the accuracy of the prediction, it is necessary to further determine the value of a. When a>0, the predicted value sequence curve trend will show the characteristics of an increasing convex function and a decreasing concave function, which is the same as the characteristic curve of the actual output current. In this case, the background value sequence Z is retained. (1) (k), and retain the calculated gray development coefficient a and gray quantity b; when a<0, the trend of the predicted value sequence curve obtained by prediction will show the characteristics of increasing concave function and decreasing convex function, which is different from the characteristic curve of the actual output current. Then, the cumulative sequence X is reconstructed through the transformation operator. Δ(1) (k); Reconstruct the cumulative sequence X Δ(1) In the process of (k), the original sequence error caused by the inconsistency of concavity and convexity is first calculated as

[0076] Δ(k+1)=X (1) (nk)-X (1) (nk-1),k=0,1,…,n-2 (8)

[0077] The reconstructed cumulative sequence is

[0078]

[0079] Then based on the reconstruction cumulative sequence X Δ(1) (k) and calculus ideas to update the background value sequence Z (1) (k), according to the updated background value sequence Z (1) (k) Recalculate the gray development coefficient a and gray amount b.

[0080] S4, according to the gray development coefficient a and gray amount b and the original sequence X (0) , predict the output current i(k+1) of the next switching cycle, and its prediction expression is

[0081]

[0082] And replace the original sequence X with the output current i(k+1) of the next switching cycle (0) The oldest current sampling value in the original sequence X is obtained (0) , the newly added data will be placed at the end of the data group to ensure the time validity of the original sequence. The updated original sequence X (0) The expression is

[0083] X (0) =[X (0) (2),…,X (0) (n),i(k+1)] (11)

[0084] S5, based on the updated original sequence X (0) , repeat steps S2 to S4, and predict the output current i(k+2) of the next switching cycle again; when the reference signal suddenly changes at a certain moment, the original sequence X (0) The output current value before the mutation exists in , which reduces the prediction accuracy of the output current. In order to improve the prediction accuracy of the output current during the reference signal mutation process, the old original sequence value should be discarded in time to achieve rolling grey prediction. Therefore, according to formula (10), the output current i(k+2) of the next switching cycle is predicted, and two predicted currents i(k+1) and i(k+2) after the kth cycle are obtained, thereby eliminating the influence of the old information, realizing a rolling two-step output current prediction, and ensuring the output current prediction accuracy.

[0085] S6. Use the current i(k+2) as the latest predicted value of the output current to compensate for the inherent delay of the digital hysteresis control, and subtract the signal corresponding to i(k+2) from the reference signal to obtain the output current error; when the output current error is small, adjust the proportional control parameter of the EAST fast-control power supply to be smaller, and when the output current error is large, adjust the proportional control parameter of the EAST fast-control power supply to be larger, so as to obtain the optimal duty cycle of the power switch tube and realize fast and accurate prediction and control of the output current of the EAST fast-control power supply.

[0086] like Figure 3 As shown, T sis the switching cycle of the switch tube. The EAST fast control power supply digital hysteresis control system has a control delay of at least one switching cycle. According to the gray prediction model, the output current i(k+1) at the k+1 moment is predicted in the kth cycle, and the control quantity u(k) required by the EAST fast control power supply switch tube is calculated. The control module loads the PWM wave under the control quantity u(k-1) calculated in the previous cycle to drive the switch tube. Therefore, the current value sampled in the k+1th cycle is actually the current output value obtained by the system under the control of the control quantity u(k-1), which deviates from the value expected by the system. In order to compensate for the control delay of the EAST fast control power supply digital hysteresis control system and improve the output current prediction accuracy during the reference signal mutation process, the old The original sequence value realizes rolling grey prediction, so in the kth cycle, a rolling two-step output current prediction is realized to obtain i(k+2) and calculate the control quantity u(k+2), and u(k+2) is loaded in the k+1th cycle. Then, the current value sampled in the k+2th cycle is actually the current output value obtained by the system under the control of the control quantity u(k+2), which is consistent with the value expected by the system; the signal corresponding to i(k+2) is subtracted from the reference signal to obtain the output current error to ensure that the predicted current quickly and accurately tracks the reference signal, and the proportional control parameters of the EAST fast-control power supply are adjusted to obtain the optimal duty cycle of the power switch tube to ensure that the predicted current accurately tracks the reference signal, thereby realizing fast and accurate prediction and control of the output current of the EAST fast-control power supply.

[0087] In this embodiment, the improved grey GM (1,1) prediction method for the output current of the EAST fast control power supply is simulated and analyzed. The simulation parameters are: the DC supply voltage of the EAST fast control power supply is 540V, the load inductance is 160μH, the internal resistance of the load inductance is 0.08Ω, the switching frequency of the switching device is 5kHz, the reference signal is a 100Hz square wave of ±10V, and the output current rating is ±1500A. The improved grey GM (1,1) prediction control method is used to realize the prediction control of the output current of the EAST fast control power supply. Figure 4 As shown, analysis of the simulation waveform shows that when the reference signal is a 100Hz AC square wave of ±10V, the EAST fast-control power supply can quickly output a 100Hz AC square wave current of ±1500A. The proportional relationship between the reference signal value and the output current value of the EAST fast-control power supply fully meets the requirements for normal operation of the EAST fast-control power supply. The simulation waveform shows that the present invention can enable the EAST fast-control power supply to quickly and accurately follow the reference signal to output the corresponding current, and can well achieve the plasma vertical displacement balance control performance.

[0088] Example 2

[0089] It should be further explained that, based on the same inventive concept, this embodiment provides an EAST fast-control power supply output current improved grey GM (1,1) prediction system. When running, the system executes the method described in Example 1, including the following modules:

[0090] The sampling module is used to sample the output current of the EAST fast control power supply and obtain the original sequence X of the grey GM (1,1) prediction model composed of the output current sampling data in the last four switching cycles. (0) , the expression is:

[0091] X (0) =[X (0) (1),X (0) (2),...,X (0) (n)] (1)

[0092] Background value sequence calculation module is used to calculate the background value sequence based on the original sequence X (0) , generate the cumulative sequence X (1) (k), where k represents the switching period, and then combined with the idea of ​​calculus, the cumulative sequence X (1) (k) The background value sequence Z is obtained by segmentation approximation calculation (1) (k);

[0093] Gray parameter calculation module, used for background value sequence Z obtained based on background value sequence calculation module (1) (k) and the original current sampling data, calculate the gray development coefficient a and the gray amount b; judge whether the background value sequence Z needs to be reconstructed according to the size of the gray development coefficient a. (1) (k) and recalculate the gray development coefficient a and gray amount b;

[0094] The first current prediction module is used to calculate the gray development coefficient a, gray quantity b and original sequence X obtained in step S3. (0) , predict the output current i(k+1) of the next switching cycle, and replace the original sequence X with the output current i(k+1) of the next switching cycle (0) The oldest current sampling value in the original sequence X is obtained (0) ;

[0095] The second current prediction module is used to predict the current based on the updated original sequence X (0) , repeatedly run the background value sequence calculation module, the gray parameter calculation module and the first current prediction module to predict the output current i(k+2) of the next switching cycle again;

[0096] The control module is used to use i(k+2) as the latest predicted value of the output current; the signal corresponding to i(k+2) is subtracted from the reference signal to obtain the output current error; when the output current error is small, the proportional control parameter of the EAST fast-control power supply is adjusted to be smaller; when the output current error is large, the proportional control parameter of the EAST fast-control power supply is adjusted to be larger to adjust the duty cycle of the power switch tube.

[0097] The grey parameter calculation module includes a grey development coefficient a determination unit, and its specific operation mode is as follows:

[0098] When a>0, the background value sequence Z is retained (1) (k), and retain the calculated gray development coefficient a and gray amount b;

[0099] When a<0, the cumulative sequence X is reconstructed through the transformation operator Δ(1) (k), and based on the reconstructed cumulative sequence X Δ(1) (k) Recalculate the background value sequence Z (1) (k), and then based on the recalculated background value sequence Z (1) (k) Update and calculate the gray development coefficient a and gray amount b.

[0100] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. The improved grey GM(1,1) prediction method for the output current of the EAST fast-control power supply is characterized by: The following steps are involved: S1. Sample the output current of the EAST fast control power supply and obtain the original sequence X of the grey GM (1,1) prediction model composed of the output current sampling data in the last four switching cycles. (0) , the expression is: X (0) =[X (0) (1),X (0) (2),...,X (0) (n)] (1) S2, based on the original sequence X (0) , generate the cumulative sequence X (1) (k), where k represents the switching period, and then combined with the idea of ​​calculus, the cumulative sequence X (1) (k) The background value sequence Z is obtained by segmentation approximation calculation (1) (k); S3, based on the background value sequence Z obtained in step S2 (1) (k) and the original current sampling data, calculate the gray development coefficient a and the gray amount b; judge whether the background value sequence Z needs to be reconstructed according to the size of the gray development coefficient a. (1) (k) and recalculate the gray development coefficient a and gray amount b; S4, based on the gray development coefficient a, gray amount b and original sequence X obtained in step S3 (0) , predict the output current i(k+1) of the next switching cycle, and replace the original sequence X with the output current i(k+1) of the next switching cycle (0) The oldest current sampling value in the original sequence X is obtained (0) ; S5, based on the updated original sequence X (0) , repeat steps S2 to S4 to predict the output current i(k+2) of the next switching cycle again; S6. Take i(k+2) as the latest predicted value of the output current; subtract the signal corresponding to i(k+2) from the reference signal to obtain the output current error; when the output current error is small, adjust the proportional control parameter of the EAST fast-control power supply to be smaller; when the output current error is large, adjust the proportional control parameter of the EAST fast-control power supply to be larger to adjust the duty cycle of the power switch tube.

2. The improved grey GM (1,1) prediction method for output current of the EAST fast-controlled power supply according to claim 1 is characterized in that: The cumulative sequence expression described in step S2 is:

3. The improved grey GM (1,1) prediction method for output current of the EAST fast-controlled power supply according to claim 2 is characterized in that: Step S2 combines the calculus idea to accumulate the sequence X (1) (k) The background value sequence Z is obtained by segmentation approximation calculation (1) (k) Specifically: The accumulated sequence X (1) (k) The curve is divided into l rectangles, and the area of ​​l rectangles is used to approximate the integral value of the curve. The cumulative sequence X (1) (k) After segmentation, the background value sequence Z is approximately calculated (1) (k), the background value sequence expression is: Where k represents the switching period.

4. The improved grey GM (1,1) prediction method for output current of the EAST fast-controlled power supply according to claim 3 is characterized in that: The gray development coefficient a and gray amount b are calculated in step S3. The specific calculation expressions are: X n =[X (0) (2) X (0) (3) X (0) (4)] T (5) 5. The improved grey GM (1,1) prediction method for output current of the EAST fast-controlled power supply according to claim 4 is characterized in that: In step S3, the gray development coefficient a is used to determine whether the background value sequence Z needs to be reconstructed. (1) (k) and update the calculation of the gray development coefficient a and the gray amount b, specifically: When a>0, the background value sequence Z is retained (1) (k), and retain the calculated gray development coefficient a and gray amount b; When a<0, the cumulative sequence X is reconstructed through the transformation operator Δ(1) (k), and based on the reconstructed cumulative sequence X Δ(1) (k) Recalculate the background value sequence Z (1) (k), and then based on the recalculated background value sequence Z (1) (k) Update and calculate the gray development coefficient a and gray amount b.

6. The improved grey GM (1,1) prediction method for output current of the EAST fast-controlled power supply according to claim 5 is characterized in that: The cumulative sequence X is reconstructed by the transformation operator Δ(1) (k), specifically: Reconstruct the cumulative sequence X Δ(1) In the process of (k), the original sequence error caused by the inconsistency of concavity and convexity is first calculated as Δ(k+1)=X (1) (n-k)-X (1) (n-k-1),k=0,1,…,n-2 (8) The reconstructed cumulative sequence is 7. The improved grey GM (1,1) prediction method for output current of the EAST fast-controlled power supply according to claim 6 is characterized in that: The output current i(k+1) of the next switching cycle described in step S4 is predicted by 8. The improved grey GM (1,1) prediction method for output current of the EAST fast-controlled power supply according to claim 6 is characterized in that: The updated original sequence X in step S4 (0) The expression is X (0) =[X (0) (2),...,X (0) (n),i(k+1)]。 (11) 9. An improved grey GM (1,1) prediction system for output current of an EAST fast-controlled power supply, characterized in that the system adopts the method described in any one of claims 1 to 8 during operation, and includes the following modules: The sampling module is used to sample the output current of the EAST fast control power supply and obtain the original sequence X of the grey GM (1,1) prediction model composed of the output current sampling data in the last four switching cycles. (0) , the expression is: X (0) =[X (0) (1),X (0) (2),...,X (0) (n)] (1) Background value sequence calculation module is used to calculate the background value sequence based on the original sequence X (0) , generate the cumulative sequence X (1) (k), where k represents the switching period, and then combined with the idea of ​​calculus, the cumulative sequence X (1) (k) The background value sequence Z is obtained by segmentation approximation calculation (1) (k); Gray parameter calculation module, used for background value sequence Z obtained based on background value sequence calculation module (1) (k) and the original current sampling data, calculate the gray development coefficient a and the gray amount b; judge whether the background value sequence Z needs to be reconstructed according to the size of the gray development coefficient a. (1) (k) and recalculate the gray development coefficient a and gray amount b; The first current prediction module is used to calculate the gray development coefficient a, gray quantity b and original sequence X obtained in step S3. (0) , predict the output current i(k+1) of the next switching cycle, and replace the original sequence X with the output current i(k+1) of the next switching cycle (0) The oldest current sampling value in the original sequence X is obtained (0) ; The second current prediction module is used to predict the current based on the updated original sequence X (0) , repeatedly run the background value sequence calculation module, the gray parameter calculation module and the first current prediction module to predict the output current i(k+2) of the next switching cycle again; The control module is used to use i(k+2) as the latest predicted value of the output current; the signal corresponding to i(k+2) is subtracted from the reference signal to obtain the output current error; when the output current error is small, the proportional control parameter of the EAST fast-control power supply is adjusted to be smaller; when the output current error is large, the proportional control parameter of the EAST fast-control power supply is adjusted to be larger to adjust the duty cycle of the power switch tube.

10. The improved grey GM (1,1) prediction system for output current of the EAST fast-controlled power supply according to claim 9 is characterized in that: The grey parameter calculation module includes a grey development coefficient a determination unit, and its specific operation mode is as follows: When a>0, the background value sequence Z is retained (1) (k), and retain the calculated gray development coefficient a and gray amount b; When a<0, the cumulative sequence X is reconstructed through the transformation operator Δ(1) (k), and based on the reconstructed cumulative sequence X Δ(1) (k) Recalculate the background value sequence Z (1) (k), and then based on the recalculated background value sequence Z (1) (k) Update and calculate the gray development coefficient a and gray amount b.

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