CRAFT rectification power supply variable parameter single neuron feed-forward current control method and system

Abstract

The embodiment of the invention provides a CRAFT rectification power supply variable parameter single neuron feed-forward current control method and system, and relates to the technical field of fusion reactor key system comprehensive research facility devices. Comprising the steps of obtaining output current and reference current at a current moment; acquiring a current tracking error value at the current moment according to the output current and the reference current; adjusting a single neuron parameter according to the current tracking error value to obtain a control quantity increment at the current moment; adjusting a reference current feed-forward parameter according to the current tracking error value to obtain a feed-forward quantity at the current moment; acquiring the control quantity at the current moment according to the control quantity increment, the feed-forward quantity and the control quantity at the previous moment; performing mapping control on the control quantity at the current moment to obtain a control square wave of an optimal conduction angle at the current moment; and enabling the control square wave to act on each thyristor of the CRAFT rectification power supply, so as to control the conduction of the thyristors to obtain a target output current. According to the invention, the dynamic response speed and stable tracking control performance of the output current of the CRAFT rectification power supply can be improved.

Description

Technical Field

[0001] This invention relates to the field of Comprehensive Research Facility for Fusion Technology (CRAFT) device technology, specifically to a CRAFT rectifier power supply variable parameter single neuron feedforward current control method and system. Background Technology

[0002] The CRAFT tokamak device is a key instrument for researching controlled nuclear fusion. Multiple magnetic power supplies work in tandem, such as a high-power rectifier power supply capable of bidirectional current and voltage regulation to meet the dynamic magnetic field requirements of the plasma at different operational stages. The high-power rectifier power supply system must possess high-precision control capabilities, along with excellent stability and reliability, to ensure the safe operation of the plasma fusion process. Currently, the research and application of high-power rectifier power supplies are actively being promoted in the CRAFT device. The rectifier power supply employs a three-phase bridge rectifier topology, with six thyristors forming the rectifier branches. The CRAFT rectifier power supply must be capable of outputting large currents, tracking the reference current signal, and rapidly and stably reaching the target value within a short time. The dynamic response performance and stability of the output current are important control indicators for the rectifier power supply; rapidly and stably tracking the reference current to reach the target value ensures the stable control requirements of the plasma at different operational stages.

[0003] The CRAFT rectifier power supply operates on a large inductive load, requiring the output current to reach the target tracking value within a rated time. Currently, CRAFT rectifier power supplies use a fixed-parameter proportional-integral (PI) control method to track the reference current. However, the large inductive load limits the output current growth rate, making fixed-parameter PI control insufficient for rapid output current control. Using larger PI control parameters during the output current growth phase can further improve the growth rate, while using smaller PI control parameters during the output current stabilization phase can further improve tracking stability. Furthermore, reference current feedforward control is an effective method to improve the output current tracking phase, and the selection of feedforward control parameters directly affects the dynamic response performance and stability of the output current.

[0004] Variable parameter proportional-integral (PI) control methods have the advantages of strong parameter adaptability and fast dynamic response, enabling rapid control across the entire range of output current tracking the reference current. They have been applied in numerous current tracking control applications. For example, the paper "Fast Control of Power Supply Current for a Fully Superconducting Tokamak Nuclear Fusion Power Generation Device Based on Improved Grey Prediction Single-Neuron PI" published in the *Journal of Electrical Engineering Technology* in March 2024 proposes a single-neuron variable PI parameter control method. This method allows the proportional-integral parameters to be adjusted in real time according to the error in the output current tracking the reference current, achieving the control objective of rapid and stable tracking of the output current to the reference current in a tokamak device. The paper "Medical Gradient Amplifier Control Based on Feedforward Variable Universe Fuzzy PI" published in the *Heilongjiang Electric Power Journal* in June 2023 proposes a fuzzy variable PI parameter current feedforward control method. In the process of output current tracking the reference current, real-time adjustment of the proportional-integral ratio is achieved according to fuzzy rules. Combined with the reference current feedforward signal, this achieves rapid and stable tracking control of the output current to the reference current in a magnet power supply.

[0005] The aforementioned paper improved the fixed-parameter proportional-integral (PI) control method by employing single-neuron and fuzzy control techniques to achieve real-time adjustment of the PI parameters. Combined with reference current feedforward control, it enhanced the dynamic response performance of the control system and achieved good tracking control of the output current to the reference current. However, the designed single-neuron variable PI parameter control gain function lacks differentiability, resulting in insufficient stability in the rapid control of the CRAFT rectifier power supply output current and potentially causing large output current fluctuations. Furthermore, the fuzzy control rules are difficult to tune and the parameter adjustment process is lengthy. The fixed reference current feedforward parameter is also detrimental to rapid tracking control of the output current. Summary of the Invention

[0006] The purpose of this invention is to provide a variable parameter single-neuron feedforward current control method and system for CRAFT rectifier power supplies. This control method and system has an adaptive parameter adjustment function, which can adaptively adjust the control parameters according to the real-time output current error, thus solving the problems of slow dynamic response speed and insufficient stable tracking performance of CRAFT rectifier power supplies.

[0007] To achieve the above objectives, one embodiment of the present invention provides a CRAFT rectified power supply variable parameter single neuron feedforward current control method, comprising: Obtain the current output current and reference current; The current tracking error value at the current moment is obtained based on the output current and the reference current; The parameters of a single neuron are adjusted based on the current tracking error value to obtain the control increment at the current moment; Adjust the reference current feedforward parameter according to the current tracking error value to obtain the feedforward amount at the current moment; The control quantity at the current moment is obtained based on the control quantity increment, the feedforward quantity, and the control quantity at the previous moment; Map the control quantity at the current moment to obtain the control square wave with the optimal conduction angle at the current moment; The control square wave is applied to each thyristor of the CRAFT rectifier power supply to control the thyristor to conduct and obtain the target output current.

[0008] Optionally, adjusting the single neuron parameters based on the current tracking error value to obtain the control increment at the current moment includes: Obtain the current tracking error value from the previous moment; The change in error is obtained by comparing the current tracking error value at the previous moment with the current tracking error value at the current moment. The current tracking error value and error change at the current moment are used as the input to a single neuron; Obtain the weighting coefficient of the input quantity of the single neuron and the output gain coefficient of the single neuron; The weighted coefficients are normalized to obtain normalized coefficients; The control increment at the current moment is obtained based on the normalization coefficient, output gain coefficient, and input of a single neuron.

[0009] Optionally, obtaining the weighting coefficients of the input quantity of the single neuron and the output gain coefficient of the single neuron includes: The proportional coefficient and integral coefficient are obtained according to formulas (1) and (2). (1) (2) in, This is the first weighting coefficient for the current tracking error value. This is the second weighting coefficient for the change in error. The first normalized coefficient is the first weighted coefficient. The second normalized coefficient is the second weighting coefficient. This is the proportionality coefficient. The integral coefficient is... This represents the output gain coefficient of a single neuron.

[0010] Optionally, obtaining the weighting coefficients of the input quantity of the single neuron and the output gain coefficient of the single neuron includes: According to the objective function of formula (3), the output current at the current moment should track the reference current. (3) in, Let be the objective function. For reference current, For the present Output current at any moment For the present The current tracking error value at any given time; The change in weighting coefficients at the current time can be obtained according to formula (4). (4) in, For the present The change in the first weighting coefficient at time 1 For the present The change in the second weighting coefficient at time t. For proportional search parameters, For the integral search parameters; Based on the weighting coefficient at the current moment and the change in the weighting coefficient at the current moment, obtain the weighting coefficient at the next moment; The values ​​of the search parameters are normalized according to formulas (5) and (6). (5) , (6).

[0011] Optionally, obtaining the weighting coefficients of the input quantity of the single neuron and the output gain coefficient of the single neuron includes: The output gain coefficient is obtained based on the current tracking error value at the current moment using formula (7). (7) in, This is the output gain coefficient. This is the upper limit of the output gain coefficient. This is the lower limit of the output gain coefficient. For the present The upper limit of the current tracking error value at any given time. For the present The lower limit of the current tracking error value at any given time.

[0012] Optionally, the control increment at the current moment is obtained based on the normalization coefficient, the output gain coefficient, and the input of a single neuron, including: The control increment at the current moment is obtained according to formula (8). (8) in, For the present Increment of control quantity at any given time, For the present The amount of error change at any given time.

[0013] Optionally, adjusting the reference current feedforward parameters based on the current tracking error value to obtain the feedforward amount at the current moment includes: The feedforward parameter value at the current time is obtained according to formula (9). (9) in, For feedforward parameter values, This is the lower limit of the error variation of the feedforward parameter value. This represents the upper limit of the error variation in the feedforward parameter value. For the present The current tracking error value at any given time.

[0014] Optionally, adjusting the reference current feedforward parameters based on the current tracking error value to obtain the feedforward amount at the current moment includes: The feedforward quantity at the current moment is obtained according to formula (10). (10) in, For the present Feedforward at time step This is the reference current.

[0015] Optionally, the control quantity at the current moment is obtained based on the control quantity increment, the feedforward quantity, and the control quantity at the previous moment, including: The control quantity at the current moment is obtained according to formula (11). (11) in, For the present The amount of control at any given moment For the present The amount of control at any given moment For the present Increment of control quantity at any given time, For the present Feedforward at any given time.

[0016] On the other hand, the present invention also provides a CRAFT rectifier power supply variable parameter single neuron feedforward current control system, the control system including a processor for executing the control method as described above.

[0017] Through the above technical solution, this invention provides a variable parameter single-neuron feedforward current control method and system for CRAFT rectifier power supplies. It acquires the current output current and reference current at the current moment, obtains the current tracking error value based on the output current and reference current, adjusts the single-neuron parameters based on the current tracking error value to obtain the control increment at the current moment, adjusts the reference current feedforward parameters based on the current tracking error value to obtain the feedforward value at the current moment, obtains the control value at the current moment based on the control increment, feedforward value, and the control value from the previous moment, maps the control value at the current moment to obtain a control square wave with the optimal conduction angle at the current moment, and applies the control square wave to each thyristor of the CRAFT rectifier power supply to control the thyristor conduction and obtain the target output current. This invention, by adjusting the single-neuron parameters, enables the CRAFT rectifier power supply output current to have fast and stable tracking performance of the reference current, as well as good dynamic response and steady-state performance. It can adaptively adjust the control parameters according to the real-time output current error, solving the problems of slow dynamic response speed and insufficient stable tracking performance of the CRAFT rectifier power supply output current.

[0018] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0019] The accompanying drawings are provided to further illustrate embodiments of the present invention and form part of the specification. They are used together with the following detailed description to explain the embodiments of the present invention, but do not constitute a limitation thereof. In the drawings: Figure 1 This is a flowchart of a CRAFT rectifier power supply variable parameter single neuron feedforward current control method according to one embodiment of the present invention. Figure 2 This is a schematic diagram of the CRAFT rectifier power supply output current control structure according to one embodiment of the present invention; Figure 3 This is a flowchart of obtaining the control quantity increment at the current moment according to one embodiment of the present invention; Figure 4 This is a flowchart illustrating the acquisition of weighting coefficients and output gain coefficients according to one embodiment of the present invention; Figure 5 This is a flowchart of obtaining the feedforward quantity at the current moment according to one embodiment of the present invention; Figure 6 This is a schematic diagram of the output current tracking response waveform of a CRAFT rectified power supply according to one embodiment of the present invention. Detailed Implementation

[0020] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the scope of the present invention.

[0021] In the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, they do not mean that the applicant has used or necessarily used the solution.

[0022] like Figure 1 The diagram shown is a flowchart of a CRAFT rectified power supply variable parameter single neuron feedforward current control method according to one embodiment of the present invention. Figure 1 The control method may include the following steps: In step S1, the current output current and reference current are obtained at the current moment; In step S2, the current tracking error value at the current moment is obtained based on the output current and the reference current; In step S3, the parameters of the single neuron are adjusted according to the current tracking error value to obtain the control increment at the current moment; In step S4, the reference current feedforward parameter is adjusted according to the current tracking error value to obtain the feedforward amount at the current moment; In step S5, the control quantity at the current moment is obtained based on the control quantity increment, the feedforward quantity, and the control quantity at the previous moment; In step S6, the control quantity at the current moment is mapped to obtain the control square wave with the optimal conduction angle at the current moment; In step S7, a control square wave is applied to each thyristor of the CRAFT rectifier power supply to control the thyristor to conduct and obtain the target output current.

[0023] In such Figure 1 The method shown, step S1 can be used to obtain the output current at the current moment. and reference current The specific methods for obtaining the output current and the reference current can be various those known to those skilled in the art. In one example of the present invention, the current sensor for sampling the output current can be a Hall current sensor with a sampling ratio of 10000:1. After the reference current passes through the sampling circuit, it is converted into a voltage value of 0~10V, and the reference current value corresponding to the converted 0~10V voltage value is 0~60kA.

[0024] Step S2 can be used to obtain the current tracking error value at the current moment based on the output current and the reference current. Step S3 can be used to adjust the single neuron parameters based on the current tracking error value to obtain the control increment at the current moment. The method for obtaining the control increment can further include, for example... Figure 3 The steps are shown. Specifically: In step S11, the current tracking error value of the previous moment is obtained; In step S12, the error change is obtained based on the current tracking error value at the previous moment and the current tracking error value at the current moment; In step S13, the current tracking error value and error change at the current moment are used as the input of a single neuron; In step S14, the weighting coefficient of the input of a single neuron and the output gain coefficient of a single neuron are obtained; In step S15, the weighted coefficients are normalized to obtain normalized coefficients; In step S16, the control increment at the current moment is obtained based on the normalization coefficient, the output gain coefficient, and the input of a single neuron.

[0025] In Figure 3 In the steps shown, the error change is obtained by acquiring the current tracking error value at the previous moment and the current tracking error value at the current moment. This error change and the current tracking error value at the current moment are used as the input to a single neuron. The weighting coefficient of the single neuron input and the output gain coefficient of the single neuron are then obtained. The method for obtaining the output gain coefficient is similar to that of traditional incremental proportional-integral control. Further steps for obtaining the output gain coefficient of a single neuron may include... Figure 4 The steps are shown. Specifically: In step S21, the proportional coefficient and integral coefficient are obtained according to formulas (1) and (2). (1) (2) in, This is the first weighting coefficient for the current tracking error value. This is the second weighting coefficient for the change in error. The first normalized coefficient is the first weighted coefficient. The second normalized coefficient is the second weighting coefficient. This is the proportionality coefficient. The integral coefficient is... This represents the output gain coefficient of a single neuron. In step S22, the output current at the current moment is made to track the reference current according to the target tracking function of formula (3). (3) in, Let be the objective function. For reference current, For the present Output current at any moment For the present The current tracking error value at any given time; In step S23, the change in weighting coefficients at the current time is obtained according to formula (4). (4) in, For the present The change in the first weighting coefficient at time 1 For the present The change in the second weighting coefficient at time t. For proportional search parameters, For the integral search parameters; In step S24, the weighting coefficients for the next time step are obtained based on the weighting coefficients at the current time and the change in the weighting coefficients at the current time. In step S25, the values ​​of the search parameters are normalized according to formulas (5) and (6). (5) (6); In step S26, the output gain coefficient is obtained based on the current tracking error value at the current moment using formula (7). (7) in, This is the output gain coefficient. This is the upper limit of the output gain coefficient. This is the lower limit of the output gain coefficient. For the present The upper limit of the current tracking error value at any given time. For the present The lower limit of the current tracking error value at any given time.

[0026] In Figure 4 In the steps shown, the proportional coefficient and integral coefficient are obtained through formulas (1) and (2), and the weighting coefficients are normalized to make the current Output current at any time To enable rapid tracking of the reference current, a target tracking function is introduced in step S22. To accelerate the tracking speed of the output current, the first and second weighting coefficients are searched in the direction of the negative gradient of the target tracking function. At this time, the current current obtained in step S23 according to formula (4) is... The weighting coefficient change at time step S24 is calculated, and the weighting coefficient at the current time step S25 is added to the weighting coefficient change at the current time step S26 to obtain the weighting coefficient at the next time step S24.

[0027] Proportional search parameters in traditional single neurons and integral search parameters The proportionality coefficient is determined by a fixed value. and integral coefficient The value of is prone to getting trapped in local optima. The current output current of the CRAFT rectifier power supply, during the tracking of the reference current, is currently... Current tracking error value at time It is in a dynamic state of change, therefore, according to the current Current tracking error value at time Adjusting the search parameters and integral search parameters The value can avoid the proportionality coefficient and integral coefficient The value of gets trapped in a local optimum, and the proportional search parameter and integral search parameters The normalized expression for the value can be shown in formulas (5) and (6), and the proportional search parameter. and integral search parameters According to the current Current tracking error value at time The size varies, when Greater than 5% Value Time Characterization and There is a large error between them, therefore and For parameters with larger values ​​and larger proportions, the search rate should be faster to ensure fast tracking performance. Less than 5% Value Time Characterization and The error between them is small, therefore and Smaller values ​​and a slower search rate for integral search parameters are preferred to ensure stable tracking performance.

[0028] In traditional single neurons, the output gain coefficient is fixed or the adaptive change formula is not differentiable, which may cause large local errors in the output current of the CRAFT rectifier power supply during the tracking of the reference current. Therefore, step S25 is used to adaptively change the output gain coefficient with the current tracking error value at the current moment.

[0029] exist Figure 3In the steps shown, step S15 can be used to normalize the weighting coefficients to obtain normalized coefficients. These weighting coefficients are the weighting coefficients obtained in step S24 at the current time. Normalizing the newly obtained weighting coefficients yields the normalized coefficients. Step S16 can be used to obtain the control increment at the current time based on the normalized coefficients, the output gain coefficient, and the single neuron input. The specific method for obtaining the control increment can be of various forms known to those skilled in the art. In one example of the present invention, the control increment at the current time can be obtained according to formula (8). (8) in, For the present Increment of control quantity at any given time, For the present The amount of error change at any given time.

[0030] Step S4 can be used to adjust the reference current feedforward parameters based on the current tracking error value to obtain the feedforward amount at the current moment. In one example of the present invention, the method for obtaining the feedforward amount at the current moment may include, for example... Figure 5 The steps are shown. In this Figure 5 In this context, the method for obtaining the feedforward quantity at the current moment may include the following steps: In step S31, the feedforward parameter value at the current time is obtained according to formula (9). (9) in, For feedforward parameter values, This is the lower limit of the error variation of the feedforward parameter value. This represents the upper limit of the error variation in the feedforward parameter value. For the present The current tracking error value at any given time.

[0031] In step S32, the feedforward quantity at the current time is obtained according to formula (10). (10) in, For the present Feedforward at time step This is the reference current.

[0032] In Figure 5 In the method shown, formula (9) This is the lower limit of the error variation of the feedforward parameter value. As an upper limit for the error variation of the feedforward parameter value, in one example of the present invention, The value can be 0.2 , The value of is generally between 1 and 3. When the output current tracking error is large, the feedforward coefficient value... A larger value can further improve the dynamic response speed of the output current tracking the reference current. When the output current tracking error value is small, the feedforward coefficient value is larger. Smaller values, or even close to zero, cause the feedforward component to exit the control system to ensure stable tracking performance.

[0033] Step S5 can be used to obtain the control quantity at the current moment based on the control quantity increment, the feedforward quantity, and the control quantity at the previous moment. The specific method for obtaining the control quantity at the current moment can be of various forms known to those skilled in the art. In one example of the present invention, the control quantity at the current moment can be obtained according to formula (11). (11) in, For the present The amount of control at any given moment For the present The amount of control at any given moment For the present Increment of control quantity at any given time, For the present The feedforward quantity at any given time will have a reduced effect as the output current tracks the reference current error, thus ensuring the speed and stability of the output current response.

[0034] Step S6 can be used to map the control quantity at the current moment to obtain a control square wave with the optimal conduction angle at the current moment. Step S7 can be used to apply the control square wave to each thyristor of the CRAFT rectifier power supply to control the thyristor to conduct and obtain the target output current. In one example of the present invention, the control quantity at the current moment is mapped to obtain a control square wave with the optimal conduction angle, which is then applied to each thyristor of the CRAFT rectifier power supply to obtain the target output current. The normalized value is a number between 0 and 10. The value linearly corresponds to a conduction angle of 0~135° in a 100Hz square wave, therefore based on different It is worthwhile to obtain square waves with different conduction angles to drive and control the 6 thyristors, and the 6 thyristors are controlled by different signals at different times. Controlling the on and off states will output the target current across the load inductor of the CRAFT rectifier power supply.

[0035] like Figure 2 The diagram shown is a schematic representation of the CRAFT rectifier power supply output current control structure according to one embodiment of the present invention. The control structure controls the output current of the CRAFT rectifier power supply. and reference current Sampling is performed based on the rectified power supply output current. With reference current Obtain the current tracking error value sum of error change As the input to a single neuron, based on the current tracking error value Adaptive adjustment of the first weighting coefficient Proportional search parameters Second weighting coefficient Integral search parameters Adaptive adjustment of the output gain coefficient of a single neuron This allows us to obtain the current control increment Δu(k); based on the current tracking error e, we adaptively adjust the feedforward parameter q to ensure that the q value changes adaptively within a reasonable range. The current feedforward quantity is obtained by multiplying the q value by the reference current value. Control increment and feedforward quantity and the control quantity at the previous moment The sum is the control quantity at the current moment. , as the output of a variable parameter single neuron feedforward control system; After the value is normalized to the range of 0~10, the control square wave with the optimal conduction angle is obtained through the mapping control unit. The conduction control of the six thyristors VT1~VT6 in the three-phase thyristor rectifier circuit is performed to convert the three-phase AC power supply. The rectified DC power supply powers the load inductor. Six thyristors VT1~VT6 are controlled by a square wave with optimal conduction angle to output the target current through the load inductor. The designed variable parameter single neuron feedforward control system has an adaptive parameter adjustment function, which can adaptively adjust the control parameters according to the real-time output current error, thus solving the problems of slow dynamic response speed and insufficient stable tracking performance of the CRAFT rectified power supply output current.

[0036] In one example of this invention, a simulation of the CRAFT rectifier power supply variable parameter single-neuron feedforward current control method and system is performed. The simulation parameters are as follows: The CRAFT magnet power supply consists of a three-phase rectifier bridge composed of six thyristors; the input three-phase AC supply voltage is 197V; the load inductance is 2.5mH; the reference current is a trapezoidal wave with an amplitude of 30kA; and the output current needs to track and control the reference current. A schematic diagram of the CRAFT rectifier power supply output current tracking response waveform is shown below. Figure 6As shown in the simulation waveform diagram, analysis reveals that within a complete output current cycle, the CRAFT magnet power supply can track the reference current signal with an amplitude of 30kA trapezoidal wave, and can reach the peak output current within 30 seconds. The waveform tracking stability is good, and the output current exhibits fast dynamic response and tracking stability. The simulation waveform demonstrates that this invention enables the CRAFT rectifier power supply to quickly and stably track the reference current and output the corresponding target current. The output current has the advantages of fast dynamic response, good tracking accuracy, and good stability, meeting the balance control requirements of different stages of plasma processing.

[0037] On the other hand, the present invention also provides a CRAFT rectifier power supply variable parameter single neuron feedforward current control system, the control system including a processor for executing the control method as described above.

[0038] Through the above technical solution, this invention provides a variable parameter single-neuron feedforward current control method and system for CRAFT rectifier power supplies. It acquires the current output current and reference current at the current moment, obtains the current tracking error value based on the output current and reference current, adjusts the single-neuron parameters based on the current tracking error value to obtain the control increment at the current moment, adjusts the reference current feedforward parameters based on the current tracking error value to obtain the feedforward value at the current moment, obtains the control value at the current moment based on the control increment, feedforward value, and the control value from the previous moment, maps the control value at the current moment to obtain a control square wave with the optimal conduction angle at the current moment, and applies the control square wave to each thyristor of the CRAFT rectifier power supply to control the thyristor conduction and obtain the target output current. This invention, by adjusting the single-neuron parameters, enables the CRAFT rectifier power supply output current to have fast and stable tracking performance of the reference current, as well as good dynamic response and steady-state performance. It can adaptively adjust the control parameters according to the real-time output current error, solving the problems of slow dynamic response speed and insufficient stable tracking performance of the CRAFT rectifier power supply output current.

[0039] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0040] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0041] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0042] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0043] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0044] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0045] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0046] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0047] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A CRAFT rectified power supply variable parameter single neuron feedforward current control method, characterized in that, The control method includes: Obtain the current output current and reference current; The current tracking error value at the current moment is obtained based on the output current and the reference current; The parameters of a single neuron are adjusted based on the current tracking error value to obtain the control increment at the current moment; Adjust the reference current feedforward parameter according to the current tracking error value to obtain the feedforward amount at the current moment; The control quantity at the current moment is obtained based on the control quantity increment, the feedforward quantity, and the control quantity at the previous moment; Map the control quantity at the current moment to obtain the control square wave with the optimal conduction angle at the current moment; The control square wave is applied to each thyristor of the CRAFT rectifier power supply to control the thyristor to conduct and obtain the target output current.

2. The control method according to claim 1, characterized in that, Adjusting the single neuron parameters based on the current tracking error value to obtain the control increment at the current moment includes: Obtain the current tracking error value from the previous moment; The change in error is obtained by comparing the current tracking error value at the previous moment with the current tracking error value at the current moment. The current tracking error value and error change at the current moment are used as the input to a single neuron; Obtain the weighting coefficient of the input quantity of the single neuron and the output gain coefficient of the single neuron; The weighted coefficients are normalized to obtain normalized coefficients; The control increment at the current moment is obtained based on the normalization coefficient, output gain coefficient, and input of a single neuron.

3. The control method according to claim 2, characterized in that, Obtaining the weighting coefficients of the input quantities of the single neuron and the output gain coefficients of the single neuron includes: The proportional coefficient and integral coefficient are obtained according to formulas (1) and (2). ，（1） ，（2） in, This is the first weighting coefficient for the current tracking error value. This is the second weighting coefficient for the change in error. The first normalized coefficient is the first weighted coefficient. The second normalized coefficient is the second weighting coefficient. This is the proportionality coefficient. The integral coefficient is... This represents the output gain coefficient of a single neuron.

4. The control method according to claim 3, characterized in that, Obtaining the weighting coefficients of the input quantities of the single neuron and the output gain coefficients of the single neuron includes: According to the objective function of formula (3), the output current at the current moment should track the reference current. ，（3） in, Let be the objective function. For reference current, For the present Output current at any moment For the present The current tracking error value at any given time; The change in weighting coefficients at the current time can be obtained according to formula (4). ，（4） in, For the present The change in the first weighting coefficient at time 1 For the present The change in the second weighting coefficient at time t. For proportional search parameters, For the integral search parameters; Based on the weighting coefficient at the current moment and the change in the weighting coefficient at the current moment, obtain the weighting coefficient at the next moment; The values ​​of the search parameters are normalized according to formulas (5) and (6). ，（5） ，（6）。 5. The control method according to claim 4, characterized in that, Obtaining the weighting coefficients of the input quantities of the single neuron and the output gain coefficients of the single neuron includes: The output gain coefficient is obtained based on the current tracking error value at the current moment using formula (7). ，（7） in, This is the output gain coefficient. This is the upper limit of the output gain coefficient. This is the lower limit of the output gain coefficient. For the present The upper limit of the current tracking error value at any given time. For the present The lower limit of the current tracking error value at any given time.

6. The control method according to claim 5, characterized in that, The control increment at the current moment is obtained based on the normalization coefficient, output gain coefficient, and single neuron input, including: The control increment at the current moment is obtained according to formula (8). ，（8） in, For the present Increment of control quantity at any given time For the present The amount of error change at any given time.

7. The control method according to claim 1, characterized in that, Adjusting the reference current feedforward parameters based on the current tracking error value to obtain the feedforward amount at the current moment includes: The feedforward parameter value at the current time is obtained according to formula (9). ，（9） in, For feedforward parameter values, This is the lower limit of the error variation of the feedforward parameter value. This represents the upper limit of the error variation in the feedforward parameter value. For the present The current tracking error value at any given time.

8. The control method according to claim 7, characterized in that, Adjusting the reference current feedforward parameters based on the current tracking error value to obtain the feedforward amount at the current moment includes: The feedforward quantity at the current moment is obtained according to formula (10). ，（10） in, For the present Feedforward at time step This is the reference current.

9. The control method according to claim 1, characterized in that, Based on the control increment, the feedforward, and the control quantity from the previous time step, the control quantity at the current time step is obtained, including: The control quantity at the current moment is obtained according to formula (11). ，（11） in, For the present The amount of control at any given moment For the present The amount of control at any given moment For the present Increment of control quantity at any given time For the present Feedforward at any given time.

10. A CRAFT rectified power supply variable parameter single neuron feedforward current control system, characterized in that, The control system includes a processor for executing the control method as described in any one of claims 1 to 9.

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