Improved model-free current prediction control method, device and system based on forgetting factor

Abstract

The application discloses an improved model-free current prediction control method and device and system based on a forgetting factor. The method does not need to acquire system parameters in advance, only needs to collect a load current, and then approximately calculates a current increment from historical current data, and then outputs an optimal inverter switch state from a minimized current value function, and meanwhile, a forgetting factor is introduced to weaken the adverse effect of a sampling error on the system, so that the model-free current prediction control is realized. On the basis of guaranteeing the realization of the parameter-free control, the forgetting factor is introduced to weaken the adverse effect of the sampling error on the system, the current quality is improved while the response speed is faster, and the robustness of the control is improved. The application is suitable for different types of power electronic topological structures, and does not need to separately perform mathematical modeling on different types of power electronic topological structures, has a reference significance for the model-free prediction current control of the power electronic converter, and has a wide application prospect.

Description

Technical Field

[0001] This invention belongs to the field of power electronic control, and particularly relates to an improved model-free current prediction control method, device, and system based on the forgetting factor. Background Technology

[0002] With the rapid development of power electronics technology, power electronic converters are increasingly widely used in various power electronic systems. The control strategy of power electronic converters directly affects the system's performance and efficiency. Traditional control methods typically rely on accurate system parameter models for control design. However, in practical applications, system parameters are often difficult to obtain accurately, and the dynamic changes in system operating conditions make it difficult to guarantee the accuracy of model parameters. This results in insufficient accuracy and robustness of traditional control methods in dealing with system parameter changes and sampling errors.

[0003] While existing model-free predictive current control (MFPCC) methods improve control accuracy and robustness to some extent by relying solely on the detection of load current and current difference without requiring system parameters, their sensitivity to sampling errors still limits their application in high-frequency power electronic systems.

[0004] Therefore, further research into current prediction control methods that do not rely on system parameter models, can effectively reduce the impact of sampling errors, and adapt to changes in operating conditions is of great significance for improving the control performance and system stability of power electronic converters. Summary of the Invention

[0005] The purpose of this invention is to provide an improved model-free current prediction control method, device, and system based on a forgetting factor, to solve the above-mentioned problems.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0007] In a first aspect, the present invention provides an improved model-free current prediction control method based on a forgetting factor, the method comprising:

[0008] The inverter state at time k is collected in real time and saved as historical data; the inverter state includes the three-phase current at time k and the inverter switching state at time k-1; the three-phase current at time k is expressed as...

[0009] The three-phase currents collected at time k are subjected to Clark transformation to obtain the inverter current in the α-β stationary coordinate system;

[0010] Define the current increment at time k as the current difference between time k and time k-1, and approximate the current increments of two adjacent current increments under the same switching state as equal;

[0011] Calculate the current increment using historical current data;

[0012] A forgetting factor is introduced to update the current increment, and the predicted current is calculated from the updated current increment;

[0013] The current value function is derived based on the relationship between the predicted current value and the reference current value.

[0014] Calculate the current value function for all switching states of the inverter, and select the switching state that minimizes the current value function as the output.

[0015] In one implementation, based on the current collected at time k and the defined current increments at time k and k+1, the general mathematical expression for current prediction is derived as follows:

[0016]

[0017] Among them, i=[i α i β ] T V represents the α-axis and β-axis currents; k Let V be the inverter switching state at time k, where V∈{V0,V1,…,V m}; Let be the sampled value of the current at time k; These are the current increments at time k and time k+1, calculated based on historical current data.

[0018] In one implementation, the current increment, the current increment at time k and time k+1 is calculated using historical current data. Its general form is expressed as:

[0019]

[0020] in, These are the current sample values ​​at time k, time k+1, and time k+2, respectively.

[0021] In one implementation, the current increments of two adjacent current increments under the same switching state are approximately equal, and the current increment at time k is... The general form is expressed as:

[0022]

[0023] in, The previous switch state was V k The current increment below, The previous switching state was V. k The current acquisition value at the current acquisition time and the current acquisition value at the previous time.

[0024] In one implementation, a forgetting factor is introduced to update the current increment, and the updated current increment... The general form is expressed as:

[0025]

[0026] Where η is the forgetting factor, The previous switch state was V j The current increment below, The current increment is updated to incorporate a forgetting factor.

[0027] In one implementation, the predicted current is calculated based on the updated current increment, and its general form is expressed as:

[0028]

[0029] Among them, V j The selected switch state.

[0030] In one implementation, the general form of the current value function is expressed as:

[0031]

[0032] in, These are the reference currents for the α and β axes, respectively. Select switch states V respectively j The predicted currents along the α and β axes at time k+2. To select the switch state as V j The current-time value function, where min is the function for finding the minimum element. V is the minimum value of the current value function. n To output the optimal inverter switching state at time k+1.

[0033] Secondly, the present invention provides an improved model-free current prediction control device based on a forgetting factor, the device comprising:

[0034] The data acquisition and storage module is used to acquire the inverter status at time k in real time and save it as historical data. The inverter status includes the three-phase current at time k and the inverter switching status at time (k-1). The three-phase current at time k is expressed as...

[0035] The mathematical model module in the α-β stationary coordinate system is used to analyze the obtained three-phase current at time k. Perform Clark transformation to obtain the inverter current in the α-β stationary coordinate system;

[0036] The incremental calculation module is used to define the current increment at time k and time k+1 as the current difference between the two times, and to approximate the current increments of two adjacent times under the same switching state as equal; at the same time, it uses historical current data to calculate the current increment.

[0037] The current increment update module is used to introduce a forgetting factor to update the current increment, and to calculate the predicted current from the updated current increment;

[0038] The current value function construction module is used to derive the current value function based on the current prediction value and the current reference value.

[0039] The output module is used to calculate the current value function for all switching states of the inverter and select the switching state that minimizes the current value function as the output.

[0040] Thirdly, the present invention provides an improved model-free current prediction and control system based on a forgetting factor, the system comprising the aforementioned improved model-free current prediction and control device based on a forgetting factor.

[0041] Fourthly, the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the above-described improved model-free current prediction control method based on the forgetting factor.

[0042] Compared with the prior art, the present invention has the following advantages:

[0043] (1) The model-free predictive control method described in this invention does not require prior knowledge of system parameters and only needs historical current data to predict current. Therefore, it has a wider range of applicability compared to traditional model-based predictive control methods and does not require a cumbersome parameter tuning process.

[0044] (2) The model-free predictive control method described in this invention is based on historical current data for prediction, which unifies the current control law of the system. Therefore, it is applicable to different types of power electronic topologies and does not require separate mathematical modeling of different types of power electronic topologies.

[0045] (3) The model-free predictive control method described in this invention uses a forgetting factor to suppress the sampling error caused by the sampling circuit. At the same time, it can adapt to different operating conditions by adjusting the forgetting factor. While the accuracy requirements of the sampling circuit are lower, it can track the current reference value more accurately under changing operating conditions. Therefore, it has better steady-state and dynamic performance. Attached Figure Description

[0046] The accompanying drawings, as part of this invention, are provided to further illustrate the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention, but do not constitute an undue limitation thereof. Clearly, the drawings described below are merely some embodiments, and those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0047] Figure 1 A flowchart of an improved model-free current prediction control method based on a forgetting factor, provided in an embodiment of the present invention;

[0048] Figure 2 This is a block diagram of the three-phase two-level inverter used in the improved model-free current prediction control based on the forgetting factor of this invention.

[0049] Figure 3 A diagram illustrating the implementation process of the improved model-free current predictive control method based on the forgetting factor;

[0050] Figure 4 This is a comparison diagram of the current waveforms of the improved model-free current prediction control method based on the forgetting factor and the traditional model-free FCS method in the embodiments of the present invention.

[0051] Figure 5 This is a dynamic waveform diagram of the current under the condition of sudden change in the peak value of the current reference value in an embodiment of the present invention, using an improved model-free current prediction control method based on the forgetting factor.

[0052] It should be noted that these accompanying drawings and textual descriptions are not intended to limit the scope of the invention in any way, but rather to illustrate the concept of the invention to those skilled in the art by referring to specific embodiments. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] like Figure 1 As shown in the embodiments of this disclosure, the improved model-free current prediction control method based on the forgetting factor includes the following specific steps:

[0055] Step S100: Collect the inverter status at time k in real time and save it as historical data.

[0056] Specifically, the inverter's state includes the three-phase current at time k and the inverter's switching state at time k-1. The three-phase current at time k is expressed as... At time k-1, the inverter switching state is V. k-1 Current sampling value The data is acquired by the sampling circuit and recorded as historical current data.

[0057] Step S200: Perform Clark transformation on the collected three-phase current at time k to obtain the inverter current in the α-β stationary coordinate system.

[0058] Specifically, the general expression for the two-phase current in the α-β stationary coordinate system at time k is:

[0059]

[0060] in, Let be the two-phase currents at time k in the α-β stationary coordinate system. Let T be the three-phase current at time k. αβ Given the Clark transform matrix, T is used when performing the Clark transform according to the principle of magnitude invariance. αβ The general expression is:

[0061]

[0062] Step S300: Define the current increment at time k as the current difference between time k and time k-1, and approximate the current increments of two adjacent current increments under the same switching state as equal.

[0063] Based on the inverter's current in the α-β stationary coordinate system and the defined current increments at time k and k+1 as two consecutive times, the model-free current prediction result can be expressed in the following general form:

[0064]

[0065] Among them, i=[i α i β ] T V represents the α-axis and β-axis currents; k Let V be the inverter switching state at time k, where V∈{V0,V1,…,V m}; Let be the sampled value of the current at time k; These are the current increments at time k and time k+1, calculated based on historical current data.

[0066] Step S400: Calculate the current increment using historical current data.

[0067] Specifically, the current increment at time k and time k+1 It was approximately calculated from historical current data.

[0068] Calculate the current increment using historical current data, including the current increment at time k and time k+1. Its general form can be expressed as:

[0069]

[0070] in, These are the current sample values ​​at time k, time k+1, and time k+2, respectively.

[0071] Considering It is impossible to sample at time k. Furthermore, under the same switching state, when the sampling interval is fixed and short enough, the current increments of two adjacent current increments under the same switching state can be approximately equal. Therefore, the current increment under the previous same switching state is used to approximate the current increment.

[0072] Furthermore, in equation (4) above, the time k and the current increment... The general form is further expressed as:

[0073]

[0074] in, The previous switch state was V k The current increment below, The previous switching state was V. k The current acquisition value at the current acquisition time and the current acquisition value at the previous time.

[0075] Step S500: Introduce a forgetting factor to update the current increment, and calculate the predicted current from the updated current increment.

[0076] The forgetting factor η∈(0,1) is used to forget earlier historical current data, based on sampling error and operating conditions.

[0077] Furthermore, the updated current increment The general form can be expressed as:

[0078]

[0079] in, The previous switch state was V j The current increment below, The current increment is updated to incorporate a forgetting factor.

[0080] Historical data is used to enhance the algorithm's robustness against interference by exponentially decaying earlier historical current data, thereby improving dynamic performance. This is achieved by introducing a forgetting factor η to update the current increment, predicting future currents from the updated current increment, and calculating the current value function. The forgetting factor η is set based on the following:

[0081] For systems with large sampling errors, the forgetting factor should be appropriately increased to improve the current prediction system's ability to resist sampling error interference; for systems with large changes in operating conditions, the forgetting factor should be appropriately decreased to improve the dynamic performance of the current prediction system.

[0082] Furthermore, the predicted current is calculated based on the updated current increment, and its general form can be expressed as:

[0083]

[0084] Among them, V j The selected switch state.

[0085] Step S600: Derive the current value function based on the relationship between the predicted current value and the reference current value.

[0086] Furthermore, the current value function is the relationship between the predicted current value and the reference current value at time k+2, and its general form can be expressed as:

[0087]

[0088] in, These are the reference currents for the α and β axes, respectively. Select switch states V respectively j The predicted currents along the α and β axes at time k+1. To select the switch state as V j The current-time value function, where min is the function for finding the minimum element. V is the minimum value of the current value function. n To output the optimal inverter switching state at time k+1.

[0089] Step S700: Calculate the current value function for all switching states of the inverter, and select the switching state that minimizes the current value function as the output.

[0090] In one specific embodiment, taking a three-phase two-level inverter system (hereinafter referred to as inverter) as an example, such as... Figure 2 The diagram shows the basic structure of an inverter, where each phase consists of two power devices, the output filtering stage is a single L-type filter, and the resistor R is the equivalent resistance of the internal resistance of the power switching devices and the internal resistance of the inductor. Each phase of the inverter has two switches, and different combinations of switch states can yield two... 3=8 basic switching states, represented by V k ∈{V0,V1,…,V7} represents the inverter switching state at time k, as shown in Table 1.

[0091] Table 1 Switching Status of Three-Phase Two-Level Inverter

[0092]

[0093] Now, combining the eight switching states of the inverter and the current collected by the sampling circuit, a current prediction method is used to select the inverter switching state at time k+1. For example... Figure 2 As shown, when using a three-phase two-level inverter, the specific process of the improved model-free current prediction control method based on the forgetting factor is as follows:

[0094] Collect the three-phase current at time k And the inverter switching status at time k-1, refer to Table 1 to determine the inverter switching state V at time k-1. k-1 The three-phase currents obtained at time k are then subjected to Clark transformation to obtain the two-phase currents in the α-β stationary coordinate system at time k.

[0095] The two-phase currents in the α-β stationary coordinate system at time k can be obtained from the three-phase currents at time k using the Clark transformation, and its general expression is:

[0096]

[0097] in, Let be the two-phase currents at time k in the α-β stationary coordinate system. Let T be the three-phase current at time k. αβ Given the Clark transform matrix, T is used when performing the Clark transform according to the principle of magnitude invariance. αβ The general expression is:

[0098]

[0099] Define the current increment at time k and time k+1. The current difference between two consecutive moments can be expressed in a general form as:

[0100]

[0101] in, These are the current sample values ​​at time k, time k+1, and time k+2, respectively.

[0102] because Since it is impossible to sample at time k, and under the same switching state, when the sampling interval is fixed and sufficiently short, two consecutive current increments under the same switching state can be approximately equal. Therefore, the current increment under the previous same switching state is used to approximate the current increment. In the above (revised) equation, time k and current increment... The general form is further expressed as:

[0103]

[0104] in, The previous switch state was V k The current increment below, The previous switching state was V. k The current acquisition value at the current acquisition time and the current acquisition value at the previous time.

[0105] To mitigate the adverse effects of sampling errors and ensure the method functions correctly under varying operating conditions, a forgetting factor η∈(0,1) is introduced to cause older historical current data to decay exponentially over time, updating the current increments accordingly. Its general form can be expressed as:

[0106]

[0107] At this point, the general expression for the predicted current at time k+1 can be expressed as:

[0108]

[0109] Among them, V j ∈{V0,V1,…,V7} represents the selected inverter switching state.

[0110] The current value function is expressed as:

[0111]

[0112] in, These are the reference currents for the α and β axes, respectively. Select switch states V respectively j The predicted currents along the α and β axes at time k+1. To select the switch state as V j The current-time value function, where min is the function for finding the minimum element. V is the minimum value of the current value function. n To output the optimal inverter switching state at time k+1.

[0113] The implementation process of the improved model-free current prediction control method based on the forgetting factor for three-phase two-level inverters is described in the following description. Figure 3 As shown, from Figure 3 The specific execution process of data acquisition, calculation, storage update, and switch state selection in the embodiments of the present invention can be seen from the example.

[0114] Figure 4 This figure shows a comparison of the current waveforms in the circuit when using the improved model-free current prediction control method based on the forgetting factor (the method part on the left of the figure, with the forgetting factor set to 0.95) under high-frequency sampling (sampling period of 20µs) provided in this embodiment of the invention, and when using the traditional FCS model-free method (the traditional method part on the right of the figure). Compared with the traditional method, the current waveform in the circuit using the method proposed in this invention is more sinusoidal, indicating that the method proposed in this invention can reduce the impact of sampling error on system performance and improve the accuracy and robustness of control to a certain extent.

[0115] Figure 5 The dynamic performance of the circuit current under the abrupt change in the peak value of the current reference value provided in the embodiments of the present invention is shown. It can be seen that when using the method proposed in the present invention, when the peak value of the current reference value suddenly decreases or increases, the current in the circuit tracks the reference value within 0.5ms and 1.5ms respectively, indicating that the method proposed in the present invention has good dynamic performance.

[0116] The following are embodiments of the improved model-free current prediction control device based on the forgetting factor of the present invention, which can be used to execute the improved model-free current prediction control method based on the forgetting factor of the present invention. For details not disclosed in the embodiments of the improved model-free current prediction control device based on the forgetting factor of the present invention, please refer to the embodiments of the improved model-free current prediction control method based on the forgetting factor of the present invention.

[0117] In one embodiment, an improved model-free current prediction control device based on a forgetting factor is proposed, the device comprising:

[0118] The data acquisition and storage module is used to acquire the inverter status at time k in real time and save it as historical data. The inverter status includes the three-phase current at time k and the inverter switching status at time (k-1). The three-phase current at time k is expressed as...

[0119] The mathematical model module in the α-β stationary coordinate system is used to analyze the obtained three-phase current at time k. Perform Clark transformation to obtain the inverter current in the α-β stationary coordinate system;

[0120] The incremental calculation module is used to define the current increment at time k and time k+1 as the current difference between the two times, and to approximate the current increments of two adjacent times under the same switching state as equal; at the same time, it uses historical current data to calculate the current increment.

[0121] The current increment update module is used to introduce a forgetting factor to update the current increment, and to calculate the predicted current from the updated current increment;

[0122] The current value function construction module is used to derive the current value function based on the relationship between the predicted current value and the reference current value.

[0123] The output module is used to calculate the current value function for all switching states of the inverter and select the switching state that minimizes the current value function as the output.

[0124] It should be noted that the improved model-free current prediction control device based on the forgetting factor provided in the above embodiments is only illustrated by the division of the functional modules described above when executing the improved model-free current prediction control method based on the forgetting factor. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the improved model-free current prediction control device based on the forgetting factor and the improved model-free current prediction control method embodiment based on the forgetting factor provided in the above embodiments belong to the same concept, and its implementation process is detailed in the improved model-free current prediction control method embodiment based on the forgetting factor, which will not be repeated here.

[0125] In one embodiment, an improved model-free current prediction control system based on a forgetting factor is proposed, the system including the aforementioned improved model-free current prediction control device based on a forgetting factor.

[0126] The description of the improved model-free current predictive control based on the forgetting factor is the same as or similar to the description above, and will not be repeated here.

[0127] In one embodiment, a computer program product is provided that, when executed by a processor, causes one or more processors to perform the following steps: real-time acquisition of the inverter state at time k and storage as historical data; the inverter state includes the three-phase current at time k and the inverter switching state at time k-1; the three-phase current at time k is expressed as... The three-phase currents collected at time k are subjected to Clark transformation to obtain the inverter current in the α-β stationary coordinate system; the current increment at time k is defined as the current difference between time k and time k-1, and two adjacent current increments under the same switching state are approximately equal; the current increment is calculated using historical current data; a forgetting factor is introduced to update the current increment, and the predicted current is calculated from the updated current increment; the current value function is derived based on the relationship between the current predicted value and the current reference value; the current value function is calculated for all switching states of the inverter, and the switching state corresponding to the minimum current value function is selected as the output.

[0128] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0129] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0130] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. An improved model-free current predictive control method based on a forgetting factor, characterized in that: The method includes: Real-time data collection The inverter status is recorded at all times and saved as historical data; the inverter status includes the first... Three-phase current at time and the first Inverter switching state at all times; the first Three-phase current representation at any moment , , ; The collected first The three-phase currents are subjected to Clark transformation at any given time to obtain the inverter current in the α-β stationary coordinate system; Definition of the first The current increment at time t is the first Time and the The current difference at any given time, and approximate the current increments of two adjacent currents under the same switching state to be equal; Calculate the current increment using historical current data; A forgetting factor is introduced to update the current increment, and the predicted current is calculated from the updated current increment; Introducing a forgetting factor to update the current increment, the updated current increment The general form is expressed as: in, Forgetting factor, The previous switch state was The current increment below, The selected switch state; The current value function is derived based on the relationship between the predicted current value and the reference current value. Calculate the current value function for all switching states of the inverter, and select the switching state that minimizes the current value function as the output.

2. The improved model-free current prediction control method based on the forgetting factor according to claim 1, characterized in that: According to the obtained number Current at time and the definition of the first Time, Number Based on the current increment at each time step, the general mathematical expression for current prediction is derived as follows: in, Represents the α-axis and β-axis currents; The inverter switching state at time k. For the first The sampled value of the current at any given time; , These are the numbers calculated based on historical current data. Time and the first The current increment at any given moment.

3. The improved model-free current prediction control method based on the forgetting factor according to claim 2, characterized in that: Calculate the current increment using historical current data, the first Time and the first Increment of current at time , Its general form is expressed as: in, , , The first Time, Number Time and the first The current sample value at time t.

4. The improved model-free current prediction control method based on the forgetting factor according to claim 3, characterized in that: If two adjacent current increments are approximately equal under the same switching state, then the... Increment of current at time The general form is expressed as: in, The previous switch state was The current increment below, , The previous switch state was respectively The current acquisition value at the current acquisition time and the current acquisition value at the previous time.

5. The improved model-free current prediction control method based on the forgetting factor according to claim 4, characterized in that: The predicted current is calculated based on the updated current increment, and its general form is expressed as: 。 6. The improved model-free current prediction control method based on the forgetting factor according to claim 3, characterized in that: The general form of the current value function is expressed as: in, , These are the reference currents for the α and β axes, respectively. , The selected switch state is as follows: Time Predicted currents along the α and β axes at time t. To select the switch state as Time-current value function To select the minimum element function, This represents the minimum value of the current value function. For the first Always output the optimal inverter switching state.

7. An improved model-free current prediction control device based on a forgetting factor, characterized in that: The device includes: The data acquisition and storage module is used to acquire data in real time. The inverter status is recorded at all times and saved as historical data; the inverter status includes the first... Three-phase current at time and the first Inverter switching state at all times; the first Three-phase current representation at any moment , , ; The mathematical model module in the α-β stationary coordinate system is used to analyze the three-phase currents acquired at time k. , , Perform Clark transformation to obtain the inverter current in the α-β stationary coordinate system; Incremental calculation module, used to define the first Time and the first The current increment at any given moment is the difference between the currents at two consecutive moments, and the current increments of two adjacent moments under the same switching state are approximately equal; at the same time, the current increment is calculated using historical current data. The current increment update module is used to introduce a forgetting factor to update the current increment, and to calculate the predicted current from the updated current increment; Introducing a forgetting factor to update the current increment, the updated current increment The general form is expressed as: in, Forgetting factor, The previous switch state was The current increment below, The selected switch state; The current value function construction module is used to derive the current value function based on the relationship between the predicted current value and the reference current value. The output module is used to calculate the current value function for all switching states of the inverter and select the switching state that minimizes the current value function as the output.

8. A computer program product comprising a computer program / instructions, characterized in that: When the computer program / instructions are executed by the processor, they implement the improved model-free current prediction control method based on the forgetting factor as described in any one of claims 1 to 6.

9. An electronic device, characterized in that: It includes a processor and a memory; wherein, when the processor executes a computer program stored in the memory, it implements the improved model-free current prediction control method based on the forgetting factor as described in any one of claims 1 to 6.

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