A method for power supply and signal switching of CPCI bus test experiment

Abstract

The application provides a CPCI bus test experiment power supply and distribution and signal switching method, relates to the field of analog unmanned aerial vehicle track power supply and distribution technology, acquires power utilization information of multiple power utilization equipment, constructs multiple power supply and distribution feedback control models corresponding to the multiple power utilization equipment, and generates a corresponding power supply and distribution feedback control data set for each power supply and distribution feedback control model; a power supply and distribution adjustment vector matched with each power supply and distribution feedback control model is generated through a feedback control simulator; real-time power supply and distribution is controlled to the corresponding power utilization equipment according to real-time power supply and distribution adjustment parameters; beneficial effects are that real-time adjustment of power supply to multiple power utilization equipment is realized, existing CPCI bus power supply and distribution is improved, different power outputs can be provided, and the demand for real-time control and adjustment of voltage output is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of simulation of unmanned aerial vehicle trajectory experiment power supply and distribution, and particularly relates to a CPCI bus test experiment power supply and distribution and signal switching method. BACKGROUND

[0002] The flight trajectory simulation of unmanned aerial vehicles can optimize flight routes and fuel efficiency: by establishing mathematical models and using advanced algorithms, considering factors such as the initial state of the aircraft, flight speed, direction, atmospheric conditions, power system performance, and flight mission requirements, trajectory modeling helps optimize flight routes, improve fuel efficiency, reduce flight time, and ensure flight safety.

[0003] It can also optimize path planning and trajectory tracking control: after path planning is completed, the aircraft needs to implement trajectory tracking control according to the planned path. Trajectory tracking control refers to the aircraft accurately tracking the planned path in actual flight according to the path planning results. The minimum acceleration trajectory and the minimum capture trajectory are common trajectory tracking control strategies that ensure good dynamic performance of the aircraft and minimize the amplitude of the aircraft's motion under acceleration constraints.

[0004] For flight trajectory simulation of aircraft guided by the guidance system, in addition to the above significance, it can also demonstrate and train the interception of unmanned aerial vehicles and improve the success rate of interception.

[0005] The flight trajectory simulation of unmanned aerial vehicles is performed by sensitive elements and rudders. The sensitive elements can move in the horizontal and vertical dimensions under the control of the embedded ARM main control board. The rudder device control board uses an embedded ARM control board to achieve 1553B bus communication through a control network 1553B module and controls the motor through an RS485 signal to control the rotation of the motion shaft and obtain the angle of the shaft.

[0006] In the present application, the sensitive elements and rudders used for unmanned aerial vehicle simulation are driven by motors. Since the output power of the motor is directly proportional to the voltage, it means that when the simulated trajectory changes, the output power of the motor also needs to change.

[0007] When the voltage increases and the current in the circuit remains unchanged, the output power of the motor also increases. Conversely, when the voltage decreases and the current in the circuit remains unchanged, the output power of the motor also decreases; therefore, in the simulation of unmanned aerial vehicle trajectory experiments, the power supply and distribution of the motor need to be controlled and adjusted at all times, and the existing CPCI bus power supply and distribution, although it can provide a variety of different power outputs, cannot achieve real-time control and adjustment of the output voltage. SUMMARY

[0008] The application provides a CPCI bus test experiment power supply and signal switching method, which is used to solve the technical problem that in the prior art, in the simulation of the trajectory of an unmanned aerial vehicle, the control and adjustment of voltage need to be paid attention to at all times when the power supply of the motor is required, and although the existing CPCI bus power supply can provide a plurality of different power outputs, it cannot realize real-time control and adjustment of the output voltage.

[0009] In view of the above problems, the application provides a CPCI bus test experiment power supply and signal switching system.

[0010] A CPCI bus test experiment power supply and signal switching method, which is applied to the power supply of the simulation of the trajectory of an unmanned aerial vehicle, and the method comprises the following steps of:

[0011] acquiring power consumption information of a plurality of power consumption devices;

[0012] constructing a plurality of power supply and distribution feedback control models corresponding to the plurality of power consumption devices, each power supply and distribution feedback control model generating a corresponding power supply and distribution feedback control data set;

[0013] The feedback control data set comprises feedback control values of a plurality of variable track points in the simulation of the trajectory of an unmanned aerial vehicle, and the feedback control values comprise first real-time voltage values and first real-time current values of each driving motor at a time point at which the variable track points are located, and second real-time voltage values and second real-time current values of each monitoring device supplied by the CPCI bus;

[0014] Based on a BP neural network, a feedback control simulator is constructed, and a power supply and distribution adjustment vector matched with each power supply and distribution feedback control model is generated through the feedback control simulator;

[0015] The power supply and distribution feedback control data set is input into the feedback control simulator to generate the power supply and distribution adjustment vector;

[0016] standard feedback control parameters corresponding to each power supply and distribution feedback control model are acquired;

[0017] The feedback control parameter setting model is trained using the power supply and distribution adjustment vector and the standard feedback control parameters corresponding to each power supply and distribution feedback control model, and real-time power supply and distribution adjustment parameters of the corresponding device are acquired;

[0018] According to the real-time power supply and distribution adjustment parameters, the CPCI bus test experiment is controlled to supply power to the corresponding power consumption device in real time.

[0019] Preferably, the plurality of power supply and distribution feedback control models corresponding to the plurality of electrical equipment are constructed, each power supply and distribution feedback control model generates a corresponding power supply and distribution feedback control data set, and the method further comprises:

[0020] The plurality of power supply and distribution feedback control models corresponding to the plurality of electrical equipment are constructed, and the feedback control strategies corresponding to the power supply and distribution feedback control models are obtained respectively;

[0021] According to the feedback control strategy corresponding to each power supply and distribution feedback control model, the power supply and distribution feedback control data set corresponding to each power supply and distribution feedback control model is generated respectively;

[0022] The mapping relationship between each power supply and distribution feedback control data set and the corresponding power supply and distribution feedback control sub-data set is established, and the feedback control simulator is constructed based on the BP neural network according to the mapping relationship.

[0023] Preferably, the plurality of power supply and distribution feedback control models corresponding to the plurality of electrical equipment are constructed, each power supply and distribution feedback control model generates a corresponding power supply and distribution feedback control data set, and the method further comprises:

[0024] The plurality of power supply and distribution feedback control models corresponding to the plurality of electrical equipment are constructed using the feedback control simulator, and the feedback control strategies corresponding to each power supply and distribution feedback control model are obtained respectively;

[0025] According to the feedback control strategy corresponding to each power supply and distribution feedback control model, the power supply and distribution feedback control data set corresponding to each power supply and distribution feedback control model is generated respectively;

[0026] Preferably, according to the feedback control strategy corresponding to each power supply and distribution feedback control model, the power supply and distribution feedback control data set corresponding to each power supply and distribution feedback control model is generated respectively, which comprises:

[0027] According to the feedback control strategy corresponding to each power supply and distribution feedback control model, each power supply and distribution feedback control model is executed;

[0028] During the complete feedback control process of each power supply and distribution feedback control model, the feedback control values at each target control time point in the feedback control process of the electrical equipment are collected;

[0029] The feedback control values corresponding to each target control time point in each complete feedback control process are assigned to the power supply and distribution adjustment vector, and the tuning model is trained to obtain the power supply and distribution adjustment parameters corresponding to each target control time point in each complete feedback control process, and the tuning model is trained.

[0030] Preferably, obtaining the standard feedback control parameters corresponding to each power supply and distribution feedback control model comprises:

[0031] Obtaining initial feedback control parameters corresponding to each power supply and distribution feedback control model respectively;

[0032] Using the setting model to optimize each initial feedback control parameter several times to obtain multiple optimized parameters corresponding to each power supply and distribution feedback control model respectively;

[0033] According to the multiple optimized parameters corresponding to each power supply and distribution feedback control model respectively, obtaining multiple power supply and distribution feedback control data sets corresponding to each power supply and distribution feedback control model respectively, and obtaining the response time of the simulated unmanned aerial vehicle trajectory experiment after executing the power supply and distribution feedback control data set, and taking the optimized parameter with the shortest response time as the standard feedback control parameter.

[0034] The technical solutions provided in the present application have at least the following technical effects or advantages:

[0035] The technical solutions provided in the present application obtain the power consumption information of multiple electrical equipment involved in the CPCI bus test experiment in the simulated unmanned aerial vehicle trajectory experiment, construct multiple power supply and distribution feedback control models corresponding to the multiple electrical equipment, each power supply and distribution feedback control model generates a corresponding power supply and distribution feedback control data set, generate a power supply and distribution adjustment vector matched with each power supply and distribution feedback control model through a feedback control simulator, train a feedback control parameter setting model using the power supply and distribution adjustment vector and the standard feedback control parameter corresponding to each power supply and distribution feedback control model, obtain real-time power supply and distribution adjustment parameters of the corresponding equipment, and control the CPCI bus test experiment to supply power to the corresponding electrical equipment in real time according to the real-time power supply and distribution adjustment parameters, thereby realizing feedback monitoring of the real-time power consumption of the multiple electrical equipment, converting these monitoring signals into power supply and distribution control, and realizing real-time adjustment of power supply to the multiple electrical equipment to meet the needs of controlling and adjusting the voltage at all times when supplying power to the motor in the simulated unmanned aerial vehicle trajectory experiment. Although the existing CPCI bus power supply and distribution can provide multiple different power outputs, it cannot meet the demand of real-time control and adjustment of the voltage output. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 A CPCI bus test experiment power supply and distribution and signal switching method process schematic diagram is provided for the present application;

[0037] Figure 2 A CPCI bus test experiment power supply and distribution and signal switching method process schematic diagram is provided for the present application;

[0038] Figure 3 A CPCI bus test experiment power supply and distribution and signal switching method is provided for constructing a plurality of power supply and distribution feedback control models corresponding to a plurality of power-using devices, each power supply and distribution feedback control model generates a corresponding power supply and distribution feedback control data set second flow diagram;

[0039] Figure 4 The application provides a simulation unmanned aerial vehicle trajectory experiment power supply and distribution and signal conversion constitution principle diagram. DETAILED DESCRIPTION

[0040] In order to enable personnel in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor should belong to the scope of protection of the present application.

[0041] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not have to be limited to only those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0042] As Figure 4 shown, a simulation unmanned aerial vehicle trajectory experiment power supply and distribution and signal conversion constitution principle diagram is provided for the application:

[0043] The AC power supply and distribution device and the DC power supply and distribution device respectively connect AC and DC power sources, each of which divides 8 power supply signals to realize the power supply and distribution function; the 24V power supply outputs signals through an adjusted potentiometer, and then adjusts the potentiometer through the panel voltage adjustment knob to realize the adjustment and output function of 8 differential signals or 16 single-ended signals; there are 8 voltage adjustment knobs, each of which outputs 1 differential signal, and each differential signal can be divided into two single-ended signals; that is, 8 differential signal outputs can be simulated, and 16 single-ended signal outputs can be simulated. The 8 knobs are installed on the panel, and the adjustment knob can adjust the output voltage;

[0044] The control method is provided by the application to realize real-time control parameters of voltage or current for power supply and signal conversion of the unmanned aerial vehicle trajectory simulation experiment.

[0045] Embodiment one: as shown in the figure, a flow chart of a CPCI bus test experiment power supply and signal switching method is provided, the method described in the embodiment is applied to power supply of unmanned aerial vehicle trajectory simulation experiment, and the method comprises the following steps: Figure 1

[0046] Step S100: obtaining power consumption information of a plurality of power consumption devices;

[0047] Specifically, the power consumption information of the power consumption information of the power consumption device refers to the value of the voltage or current required by the power consumption device, and also includes the change value of the voltage or current corresponding to the change of the unmanned aerial vehicle trajectory when the output power of the motor is increased or decreased during unmanned aerial vehicle trajectory simulation;

[0048] Step S200: constructing a plurality of power supply feedback control models corresponding to a plurality of power consumption devices, each power supply feedback control model generates a corresponding power supply feedback control data set;

[0049] The feedback control data set includes feedback control values of a plurality of trajectory change points in unmanned aerial vehicle trajectory simulation, and the feedback control values include first real-time voltage values and first real-time current values of each driving motor at the time point where the trajectory change point is located, and second real-time voltage values and second real-time current values of each monitoring device supplied by the CPCI bus;

[0050] The power supply feedback control model refers to a feedback control mathematical model established by a plurality of mathematical formulas on the basis of feedback control theory in order to achieve the expected feedback control target under the set unmanned aerial vehicle trajectory simulation condition, and to ensure unmanned aerial vehicle trajectory simulation. The unmanned aerial vehicle trajectory simulation condition can be understood as the specific execution condition of the feedback control task. For example, the unmanned aerial vehicle accelerates, decelerates, changes direction, accelerates or decelerates in the direction change, and triggers the random avoidance action, etc.

[0051] ​Specifically, the voltage or current variable value for each power supply and distribution feedback control model during trajectory change can be obtained, that is, the change value of the corresponding voltage or current when the UAV trajectory is changed by increasing or decreasing the output power of the motor, and the corresponding feedback control strategy is used respectively, and the power supply and distribution feedback control data set corresponding to each power supply and distribution feedback control model is generated according to the feedback control strategy of each power supply and distribution feedback control model. For example, when the unmanned aerial vehicle encounters an obstacle during acceleration simulation, one motor provides the torque for acceleration, and another motor or two motors provide the torque for acceleration and steering. Therefore, at least two voltage increments need to be provided, and the distance from the obstacle, the time for steering, and the duration of the steering process need to be calculated to ensure the smooth completion of the entire steering avoidance process. The calculation formula of the voltage increment size, the voltage increment supply time point, and the voltage increment supply duration constitutes the power supply and distribution feedback control model. Due to the randomness of the UAV trajectory simulation, the feedback control method emphasized in this embodiment is not specific to a certain trajectory simulation feedback control form. When this embodiment is tried, a specific power supply and distribution feedback control model can be made according to the feedback control method of this embodiment based on the specific trajectory simulation.

[0052] The feedback control strategy can be understood as a specific strategy for determining the control amount of feedback control in each feedback control process at each time point for the voltage or current variable value and the expected value of the UAV trajectory change. Specifically, the feedback control strategy can include calculating whether the motor output power provided by the current voltage can meet the requirement of changing the UAV trajectory simulation to the expected trajectory, and the compensation amount required to change the trajectory to the expected trajectory. This compensation amount can be calculated by combining proportional control, integral control, and differential control.

[0053] Step S300: based on the BP neural network, a feedback control simulator is constructed, and a power supply and distribution adjustment vector matched with each power supply and distribution feedback control model is generated through the feedback control simulator;

[0054] The feedback control simulator is used to distinguish the power supply and distribution adjustment vectors of different trajectory change scenarios. The input of the feedback control simulator is the power supply and distribution feedback control data set generated after the execution of the power supply and distribution feedback control model, and the output is the power supply and distribution adjustment vector matched with each power supply and distribution feedback control model.

[0055] Since the final purpose of the present application is to obtain real-time power supply and distribution adjustment parameters through a feedback control parameter setting model, the role of the feedback control parameter setting model is to obtain the standard feedback control parameters of the feedback control system by inputting the power supply and distribution adjustment vector matched with each power supply and distribution feedback control model, therefore, in the training process, the power supply and distribution adjustment vector used is obtained in real time by executing the corresponding feedback control strategy and is corrected, that is, the voltage or current required for the trajectory change is compensated in real time.

[0056] Step S400: inputting the power supply and distribution feedback control data set into the feedback control simulator to generate the power supply and distribution adjustment vector;

[0057] The power supply and distribution feedback control data set should be understood as the power supply and distribution feedback control data set obtained in step S200, and specifically, taking the example of changing direction when encountering an obstacle during the acceleration of the unmanned aerial vehicle, one motor provides the torque for acceleration, and the other motor or two motors provide the torque for acceleration and turning, so at least two voltage increments need to be provided at the same time, and the distance from the obstacle, the time for changing direction, and the duration of the changing direction process need to be calculated to ensure the smooth completion of the entire changing direction avoidance process, and the calculation results of the calculation formula of the voltage increment size, the voltage increment supply time point, and the voltage increment supply duration form a data set, which is the power supply and distribution feedback control data set, and after these power supply and distribution feedback control data sets are input into the feedback control simulator, the power supply and distribution adjustment vector of the corresponding feedback control strategy is generated.

[0058] Step S500: obtaining the standard feedback control parameters corresponding to each power supply and distribution feedback control model;

[0059] Preferably, the standard feedback control parameters are the standard feedback control parameters of the feedback control under the same or similar trajectory conditions of the simulated unmanned aerial vehicle trajectory pre-implanted in the database.

[0060] Step S600: training the feedback control parameter setting model using the power supply and distribution adjustment vector and the standard feedback control parameters corresponding to each power supply and distribution feedback control model to obtain the real-time power supply and distribution adjustment parameters of the corresponding equipment;

[0061] Specifically, in the present embodiment, the power supply and distribution adjustment vector is used to match the standard feedback control parameters for multiple rounds of setting training.

[0062] The feedback control parameters used by the feedback control parameter setting model refer to a group of important parameters in the control system, which are used to describe the dynamic characteristics and performance indicators of the system; these parameters usually include proportional coefficient Kp, integral time Ti, and differential time Td, etc., and the feedback control parameters include that they can be determined by analyzing and optimizing the input and output signals of the system. Generally, the optimization of the setting model parameters can make the system have better stability and response speed, and improve the control performance of the system. In this embodiment, the feedback control parameters refer to the power supply and distribution adjustment vector and the standard feedback control parameters corresponding to each power supply and distribution feedback control model;

[0063] In this embodiment, by using the power supply and distribution adjustment vector and the standard feedback control parameters corresponding to each power supply and distribution feedback control model, the PD controller is used to differentiate the power supply and distribution adjustment vector and the standard feedback control parameters corresponding to each power supply and distribution feedback control model in time, to obtain the feedback control parameters at each time point in the variable orbit time period, and to set and train the feedback control parameters in this time period, to give the proportional coefficient for adjustment control, and to obtain the real-time power supply and distribution adjustment parameters of the corresponding equipment;

[0064] Step S700: According to the real-time power supply and distribution adjustment parameters, the CPCI bus test experiment is controlled to supply real-time power to the corresponding electrical equipment.

[0065] Embodiment two: on the basis of embodiment one, preferably, a plurality of power supply and distribution feedback control models corresponding to a plurality of electrical equipment are constructed, each power supply and distribution feedback control model generates a corresponding power supply and distribution feedback control data set, and the method further comprises:

[0066] Step S211: a plurality of power supply and distribution feedback control models corresponding to a plurality of electrical equipment are constructed, and feedback control strategies corresponding to the power supply and distribution feedback control models respectively are obtained;

[0067] Step S212: according to the feedback control strategies corresponding to each power supply and distribution feedback control model respectively, power supply and distribution feedback control sub-data sets corresponding to each power supply and distribution feedback control model respectively are generated;

[0068] Step S213: a mapping relationship between each power supply and distribution feedback control data set and the corresponding power supply and distribution feedback control sub-data set is established, and according to the mapping relationship, a feedback control simulator is constructed based on a BP neural network.

[0069] Embodiment three:

[0070] On the basis of embodiment one, preferably, a plurality of power supply and distribution feedback control models corresponding to a plurality of electrical equipment are constructed, each power supply and distribution feedback control model generates a corresponding power supply and distribution feedback control data set, and the method further comprises:

[0071] Step S221: using the feedback control simulator to construct a plurality of power supply and distribution feedback control models corresponding to a plurality of power consuming devices, and obtaining a feedback control strategy corresponding to each power supply and distribution feedback control model respectively;

[0072] Step S222: generating a power supply and distribution feedback control data set corresponding to each power supply and distribution feedback control model according to the feedback control strategy corresponding to each power supply and distribution feedback control model respectively;

[0073] Preferably, generating a power supply and distribution feedback control data set corresponding to each power supply and distribution feedback control model according to the feedback control strategy corresponding to each power supply and distribution feedback control model respectively comprises:

[0074] According to the feedback control strategy corresponding to each power supply and distribution feedback control model, each power supply and distribution feedback control model is executed;

[0075] During the complete feedback control process of each power supply and distribution feedback control model, the feedback control values at each target control time point in the power consumption device feedback control process are collected;

[0076] The feedback control values corresponding to each target control time point in each complete feedback control process are assigned to the power supply and distribution adjustment vector, and the setting model is trained to obtain the power supply and distribution adjustment parameters corresponding to each target control time point in each complete feedback control process, and the setting model is trained.

[0077] Preferably, obtaining the standard feedback control parameters corresponding to each power supply and distribution feedback control model comprises:

[0078] Obtaining initial feedback control parameters corresponding to each power supply and distribution feedback control model respectively;

[0079] Using the setting model, the initial feedback control parameters are optimized several times to obtain a plurality of optimization parameters corresponding to each power supply and distribution feedback control model respectively;

[0080] According to the plurality of optimization parameters corresponding to each power supply and distribution feedback control model respectively, a plurality of power supply and distribution feedback control data sets corresponding to each power supply and distribution feedback control model are obtained, and the response time of the unmanned aerial vehicle trajectory experiment after executing the power supply and distribution feedback control data set is simulated, and the optimization parameter with the shortest response time is taken as the standard feedback control parameter.

[0081] Preferably, the method further comprises:

[0082] According to the preset power supply and distribution feedback control parameters, a pre-feedback control operation is performed on each power consuming device to obtain the initial power supply and distribution parameters of each power consuming device under the control of the preset power supply and distribution feedback control parameters.

[0083] generating, by using the feedback control simulator, a power supply adjustment vector matched with the initial power supply parameter;

[0084] inputting the power supply adjustment vector into the feedback control parameter setting model trained by the method, and taking the feedback control parameter output by the feedback control parameter setting model as the feedback control parameter of the power utilization equipment.

[0085] The technical scheme provided in the present application obtains the power utilization information of a plurality of power utilization equipment involved in a CPCI bus test experiment in a simulation of unmanned aerial vehicle trajectory experiment, constructs a plurality of power supply feedback control models corresponding to the plurality of power utilization equipment, each power supply feedback control model generates a corresponding power supply feedback control data set; generates, by using a feedback control simulator, a power supply adjustment vector matched with each power supply feedback control model; uses the power supply adjustment vector and the standard feedback control parameter corresponding to each power supply feedback control model to train a feedback control parameter setting model, and obtains real-time power supply adjustment parameters of the corresponding equipment; controls the CPCI bus test experiment to supply power to the corresponding power utilization equipment in real time according to the real-time power supply adjustment parameters, realizes feedback monitoring of the real-time power utilization of the plurality of power utilization equipment, and converts the monitoring signals into power supply control, realizes real-time adjustment of power supply of the plurality of power utilization equipment, so as to meet the needs of controlling and adjusting voltage at all times in the simulation of unmanned aerial vehicle trajectory experiment, while the existing CPCI bus power supply can provide a plurality of different power supply outputs, but cannot meet the needs of real-time control and adjustment of voltage output.

[0086] The above description of disclosed embodiments enables one of ordinary skill in the art to make or use the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein can be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for power supply and signal switching of a CPCI bus test experiment, characterized in that, The method is applied to simulate unmanned aerial vehicle trajectory experiment power supply and distribution, and the method comprises: Obtaining power consumption information of a plurality of power consumption devices; Constructing a plurality of power supply and distribution feedback control models corresponding to the plurality of power consumption devices, each power supply and distribution feedback control model generating a corresponding power supply and distribution feedback control data set; Wherein, the feedback control data set comprises feedback control values of a plurality of variable trajectory points in the unmanned aerial vehicle simulation trajectory, the feedback control values comprising first real-time voltage values and first real-time current values of each driving motor at a time point where the variable trajectory point is located, and second real-time voltage values and second real-time current values of each monitoring device delivered by the CPCI bus; Based on the BP neural network, a feedback control simulator is constructed, and a power supply and distribution adjustment vector matched with each power supply and distribution feedback control model is generated through the feedback control simulator; The power supply and distribution feedback control data set is input into the feedback control simulator to generate the power supply and distribution adjustment vector; Obtaining standard feedback control parameters corresponding to each power supply and distribution feedback control model; Using the power supply and distribution adjustment vector and the standard feedback control parameters corresponding to each power supply and distribution feedback control model, a feedback control parameter tuning model is trained to obtain real-time power supply and distribution adjustment parameters of the corresponding device; According to the real-time power supply and distribution adjustment parameters, the CPCI bus test experiment controls the real-time power supply and distribution to the corresponding power consumption device; Wherein; the construction of a plurality of power supply and distribution feedback control models corresponding to a plurality of power consumption devices, each power supply and distribution feedback control model generating a corresponding power supply and distribution feedback control data set, further comprises: Constructing a plurality of power supply and distribution feedback control models corresponding to a plurality of power consumption devices, and obtaining feedback control strategies corresponding to each power supply and distribution feedback control model respectively; According to the feedback control strategy corresponding to each power supply and distribution feedback control model respectively, a power supply and distribution feedback control sub-data set corresponding to each power supply and distribution feedback control model is generated respectively; Each power supply and distribution feedback control data set and the corresponding power supply and distribution feedback control sub-data set are mapped, and according to the mapping relationship, a feedback control simulator is constructed based on the BP neural network; Wherein, obtaining standard feedback control parameters corresponding to each power supply and distribution feedback control model comprises: Obtaining initial feedback control parameters corresponding to each power supply and distribution feedback control model respectively; Using the tuning model, each initial feedback control parameter is optimized for several times to obtain a plurality of optimized parameters corresponding to each power supply and distribution feedback control model respectively; According to the plurality of optimized parameters corresponding to each power supply and distribution feedback control model respectively, a plurality of power supply and distribution feedback control data sets corresponding to each power supply and distribution feedback control model are obtained, and the response time of the simulation unmanned aerial vehicle trajectory experiment after executing the power supply and distribution feedback control data set is obtained, and the optimized parameter with the shortest response time is taken as the standard feedback control parameter; According to the preset power supply and distribution feedback control parameter, each power consumption device is subjected to pre-feedback control operation, and initial power supply and distribution parameters of each power consumption device under the control of the preset power supply and distribution feedback control parameter are obtained; Using the feedback control simulator to generate a power supply and distribution adjustment vector matched with the initial power supply and distribution parameters.

2. The method for providing power and signal switching of a CPCI bus test bench according to claim 1, wherein, The method comprises the following steps: constructing a plurality of power supply and distribution feedback control models corresponding to a plurality of electrical equipment, each power supply and distribution feedback control model generating a corresponding power supply and distribution feedback control data set, and further comprising: using a feedback control simulator to construct a plurality of power supply and distribution feedback control models corresponding to a plurality of electrical equipment, and obtaining a feedback control strategy corresponding to each power supply and distribution feedback control model respectively; 3. The method for providing power and signal switching of a CPCI bus test bench according to claim 2, wherein, generating a power supply and distribution feedback control data set corresponding to each power supply and distribution feedback control model respectively according to the feedback control strategy corresponding to each power supply and distribution feedback control model respectively. According to the feedback control strategy corresponding to each power supply and distribution feedback control model respectively, a power supply and distribution feedback control data set corresponding to each power supply and distribution feedback control model respectively is generated. According to the feedback control strategy corresponding to each power supply and distribution feedback control model respectively, a power supply and distribution feedback control data set corresponding to each power supply and distribution feedback control model respectively is generated. According to the feedback control strategy corresponding to each power supply and distribution feedback control model, each power supply and distribution feedback control model is executed; 4. The method for providing power and signal switching for a CPCI bus test bench of claim 1, wherein, During the complete feedback control process of each power supply and distribution feedback control model, feedback control values at each target control time point in the feedback control process of the electrical equipment are collected; The feedback control values corresponding to each target control time point in each complete feedback control process are respectively assigned to the power supply and distribution adjustment vector, and the setting model is trained to obtain the power supply and distribution adjustment parameters corresponding to each target control time point in each complete feedback control process, and the setting model is trained. The method further comprises: inputting the power supply and distribution adjustment vector into the feedback control parameter setting model trained by the method of any one of claims 1 to 3, and taking the feedback control parameter output by the feedback control parameter setting model as the feedback control parameter of the electrical equipment.

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