A model predictive control method based on dual-frequency pre-triggering

Abstract

This invention relates to a model predictive control method based on dual-frequency pre-triggering. It performs sampling and control updates once per switching cycle, advancing the sampling and update times. Furthermore, before sampling the switching cycle, the switch is pre-triggered, advancing the sampling trigger time by a fixed interval, thereby eliminating accumulated errors. This invention achieves an increase in model predictive control bandwidth without increasing the switching frequency of the power electronic converter.

Description

Technical Field

[0001] This invention belongs to the field of power electronic control and model predictive control, and particularly relates to a model predictive control method based on dual-frequency pre-triggering. Background Technology

[0002] Existing model predictive control (MMC) techniques are based on single-frequency triggering, meaning that sampling, control output calculation, and updating are performed only once per switching cycle. Furthermore, sampling and calculation require a certain amount of time, resulting in a delay. A block diagram illustrating the application of MMC in power electronics scenarios is shown below. Figure 1 As shown, it mainly consists of a prediction module and a cost minimization module. The controlled variable is x(k), and its reference value is x. * The output of model predictive control is u(k), where k is a certain control time. Based on the current state of the controlled variable, the prediction module combines all switching states in the power electronic converter to predict the next state of the controlled variable. The controlled variable is generally the voltage or current of the power electronic converter. The cost function of the cost minimization module is generally defined as the difference between the controlled variable and its reference value. The goal of this module is to select an optimal switching state given by the prediction module that minimizes the cost function, thus ensuring that the controlled variable equals its reference value. The flow of model predictive control technology is as follows: Figure 2 As shown.

[0003] Existing model predictive control is based on single-frequency triggering, meaning that sampling, control calculation, and updating are performed only once per switching cycle. Therefore, the control bandwidth is limited by the switching frequency, and the steady-state error is affected by the accuracy of the model used. Figure 3 It can be seen that the calculated new control variable is based on the data at the time of sampling. The updating of the control variable requires time for sampling, calculation, and updating, resulting in a control delay. This delay causes significant fluctuations in the waveform of the controlled variable. Furthermore, the accuracy of model predictive control heavily depends on the accuracy of the model used. If the model used has errors compared to the actual system parameters, it will lead to steady-state errors in the controlled variable, meaning it cannot be controlled to its given reference value. Summary of the Invention

[0004] To address the aforementioned technical problems, the purpose of this invention is to provide a model predictive control method based on dual-frequency pre-triggering.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A model predictive control method based on dual-frequency pre-triggering is proposed, which performs sampling and control update once in each switching cycle, and advances the sampling and control update time.

[0007] Meanwhile, based on the traditional model predictive control model, the two-step prediction is as follows:

[0008] x(k+1)=Ax(k)+Bu(k)+D (1)

[0009] x(k+2)=Ax(k+1)+Bu(k+1)+D (2)

[0010] Where x is the system state variable;

[0011] u is a system input variable;

[0012] A, B, and D are the linear system parameter matrices after system linearization;

[0013] k represents any given moment;

[0014] If the model parameters have errors, i.e., A, B, and D change, then... and Then formulas (1) and (2) become:

[0015]

[0016]

[0017] in, This is for estimating the system state variables when the model has errors;

[0018] Subtracting (1) and (2) from (3) and (4) respectively, we can obtain the error amount as follows:

[0019] Δx(k+1)=ΔAx(k)+ΔBu(k)+ΔD (5)

[0020]

[0021] As can be seen from formula (6), the error caused by the inaccuracy of the model is mainly divided into two parts: the first part is the current error part1 and the second part is the accumulated error part2. Based on the accumulated error of the second part, the switch is pre-triggered so that the sampling trigger time is advanced by a fixed time, so that the accumulated error can be removed.

[0022] Preferably, the model predictive control method based on dual-frequency pre-trigger advances the sampling trigger time by a fixed time. This fixed time should be much less than half of the switching cycle, but at the same time, it should have enough time to complete sampling, control quantity calculation and control update.

[0023] Preferably, in the model predictive control method based on dual-frequency pre-triggering, sampling, control quantity calculation, and control update are all completed within the fixed time period.

[0024] By means of the above-described solution, the present invention has at least the following advantages:

[0025] This invention utilizes a dual-frequency pre-triggering mechanism to effectively increase the control bandwidth and improve the control performance of model predictive control without hardware modifications. Simultaneously, the proposed pre-triggering mechanism can effectively enhance the robustness of model predictive control, reduce its dependence on accurate models, and better control the controlled variable even when there are errors between actual parameters and the model, thereby reducing steady-state errors.

[0026] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, the preferred embodiments of the present invention are described in detail below with reference to the accompanying drawings. Attached Figure Description

[0027] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a block diagram of the application of the existing model predictive control of the present invention to a power electronic converter;

[0029] Figure 2 This is a flowchart of the existing model predictive control process of the present invention;

[0030] Figure 3 This is a sampled diagram of the existing model predictive control in this invention;

[0031] Figure 4 This is the dual-frequency pre-triggered sampling diagram of the present invention;

[0032] Figure 5a The waveform diagram is for model predictive control without the application of this invention;

[0033] Figure 5b The waveform diagram is obtained by applying the present invention to model predictive control. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0035] Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of the application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0036] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0037] In the description of this application, it should be noted that the terms "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship commonly used when the product is in use. They are used only for the convenience of describing this application and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application. Furthermore, the terms "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0038] Furthermore, terms such as "horizontal" and "vertical" do not imply that components must be absolutely horizontal or vertical, but rather that they can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0039] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "set up," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0040] Example

[0041] A comparison between traditional sampling schemes and the dual-frequency pre-triggered method proposed in this invention: Figure 3 and Figure 4 As shown, the control delay using the traditional sampling scheme is 1.5Ts, where Ts is the switching frequency of the power electronic equipment, i.e., the frequency of the PWM triangular wave. However, using the dual-frequency pre-triggered sampling scheme, the control delay is only 0.25Ts + Ta, where Ta is the pre-triggered advance time, which is generally much smaller than Ts. Therefore, the control delay is reduced by 4-5 times, meaning the control bandwidth is increased by 4-5 times.

[0042] A model predictive control method based on dual-frequency pre-triggering is proposed, which performs sampling and control update once in each switching cycle, and advances the sampling and control update time.

[0043] Meanwhile, based on the traditional model predictive control model, the two-step prediction is as follows:

[0044] x(k+1)=Ax(k)+Bu(k)+D (1)

[0045] x(k+2)=Ax(k+1)+Bu(k+1)+D (2)

[0046] Where x is the system state variable;

[0047] u is the system input variable;

[0048] A, B, and D are the linear system parameter matrices after system linearization;

[0049] k represents any given moment;

[0050] If the model parameters have errors, i.e., A, B, and D change, then... and Then formulas (1) and (2) become:

[0051]

[0052]

[0053] in, This is for estimating the system state variables when the model has errors;

[0054] Subtracting (1) and (2) from (3) and (4) respectively, we can obtain the error amount as follows:

[0055] Δx(k+1)=ΔAx(k)+ΔBu(k)+ΔD (5)

[0056]

[0057] As can be seen from formula (6), the error caused by the inaccuracy of the model is mainly divided into two parts: the first part is the current error (part1) and the second part is the accumulated error (part2). Based on the accumulated error of the second part, the switch is pre-triggered so that the sampling trigger time is advanced by a fixed time, so that the accumulated error can be removed.

[0058] Depend on Figure 4As can be seen, pre-triggering advances the sampling trigger time by a fixed time, that is, the sampling start time is advanced from point A to point B. Since the advanced time is much less than half of the switching cycle, the value sampled at point B can be considered as the value at point A. Therefore, sampling, control quantity calculation, and control update are completed within this advanced fixed time, allowing control updates and applications to be completed in the current cycle, thus avoiding control delay. Therefore, model predictive control is transformed from the original two-step prediction to one-step prediction, effectively avoiding the accumulation of errors, that is, the second part in formula (6) is removed.

[0059] like Figure 5a This is a waveform diagram showing the application of model predictive control to the direct-axis and quadrature-axis current control of a motor, with a load change occurring in the middle of the graph. Without the solution proposed in this invention, a large steady-state error will occur due to an inaccurate model, leading to inaccurate control. However, after adopting the solution proposed in this invention, see... Figure 5b The steady-state error was greatly suppressed and basically consistent with the reference value.

[0060] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the technical principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A model predictive control method based on dual-frequency pre-triggering, characterized in that, Sampling and control updates are performed once in each switching cycle, and the timing of sampling and control updates is advanced. The two-step prediction method based on traditional model predictive control is as follows: x(k+1)=Ax(k)+Bu(k)+D (1) x(k+2)=Ax(k+1)+Bu(k+1)+D (2) Where x is the system state variable; u is a system input variable; A, B, and D are the linear system parameter matrices after system linearization; k is any time interval If the model parameters have errors, i.e., A, B, and D change, then... and Then formulas (1) and (2) become: in, This is for estimating the system state variables when the model has errors; Subtracting (1) and (2) from (3) and (4) respectively, we can obtain the error amount as follows: Δx(k+1)=ΔAx(k)+ΔBu(k)+ΔD (5) From formula (6), it can be concluded that the error caused by the inaccuracy of the model is mainly composed of two parts: the first part is the current error and the second part is the accumulated error. Based on the accumulated error of the second part, the switch is pre-triggered so that the sampling trigger time is advanced by a fixed time, so that the accumulated error can be removed. In this process, the sampling start time is advanced by a fixed time. This fixed time should be much less than half of the switching cycle, but at the same time, there should be enough time to complete sampling, control quantity calculation and control update.

2. The model predictive control method based on dual-frequency pre-triggering according to claim 1, characterized in that: Sampling, control quantity calculation, and control update are all completed within the specified fixed time.

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