Terahertz energy output adaptive regulation and control method and system based on multi-sensor feedback

Abstract

The invention provides a terahertz energy output adaptive regulation and control method and system based on multi-sensor feedback, and belongs to the technical field of control systems. Aiming at the defects of single parameter regulation and control, fixed strategy and insufficient precision in the prior art, terahertz output characteristics and transmission environment multi-dimensional parameters are acquired through a multi-sensor module, and feedback parameters are output after filtering, calibration and fusion of a signal processing module; and the adaptive regulation and control module dynamically matches a regulation and control strategy according to the parameter deviation and generates an instruction to drive the terahertz source module to adjust output. The system forms a closed loop iteration regulation and control link, self-adaptive precise regulation and control of terahertz energy output are achieved, regulation and control comprehensiveness, adaptability and output stability are improved, and the system is suitable for terahertz equipment in the fields of communication, security check and the like.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of control system, and particularly relates to a terahertz energy output adaptive regulation method and system based on multi-sensor feedback. BACKGROUND

[0002] The terahertz technology has wide application prospects in the fields of communication, security check and medical detection, and the stability and precision of the energy output directly determine the application effect. The existing terahertz energy regulation technology mostly adopts a single parameter feedback mode, and only adjusts a single index such as the terahertz energy amplitude, ignoring the influence of frequency, phase and other output characteristic parameters and temperature, humidity and other transmission environment parameters on the energy output, resulting in insufficient comprehensive regulation. At the same time, the traditional regulation strategy is mostly in a fixed mode, and cannot dynamically adapt to the output deviation degree, and is prone to regulation lag and insufficient precision when facing complex working conditions. In addition, the sensor collected data of the existing system is not subjected to filtering, calibration and fusion processing of the system, and the noise and system error in the original data are prone to cause regulation misjudgment, further reducing the stability of the energy output. In order to solve the above technical defects, it is urgent to provide a terahertz energy output regulation scheme capable of realizing multi-dimensional parameter feedback, adaptive regulation strategy matching and accurate data processing.

[0003] Therefore, a terahertz energy output adaptive regulation method and system based on multi-sensor feedback are provided. SUMMARY

[0004] The present application provides a terahertz energy output adaptive regulation method and system based on multi-sensor feedback to solve the problems in the background art.

[0005] The specific technical scheme is as follows: A terahertz energy output adaptive regulation system based on multi-sensor feedback comprises a multi-sensor module, a signal processing module, an adaptive regulation module and a terahertz source module, wherein: The multi-sensor module is signal connected with the signal processing module, and is used for collecting multi-dimensional physical parameters related to the terahertz energy output and transmitting the parameters to the signal processing module; The signal processing module is signal connected with the adaptive regulation module, and is used for filtering, calibrating and fusing the parameters collected by the multi-sensor module, and outputting standardized feedback parameters; The adaptive regulation module is control connected with the terahertz source module, and is used for generating a regulation instruction through an adaptive regulation strategy according to the feedback parameters output by the signal processing module and in combination with a preset energy output target, and sending the regulation instruction to the terahertz source module; The terahertz source module is used for responding to the regulation instruction of the adaptive regulation module, adjusting the working state of the terahertz source module to realize adaptive output of the terahertz energy.

[0006] The above-mentioned terahertz energy output adaptive regulation system based on multi-sensor feedback, wherein the multi-sensor module comprises an energy sensor, a frequency sensor, a phase sensor and an environmental parameter sensor; the energy sensor is used to collect the terahertz energy amplitude parameter output by the terahertz source module; the frequency sensor is used to collect the terahertz wave frequency parameter output by the terahertz source module; the phase sensor is used to collect the terahertz wave phase parameter output by the terahertz source module; and the environmental parameter sensor is used to collect the temperature, humidity and air pressure parameters on the terahertz transmission path.

[0007] The above-mentioned terahertz energy output adaptive regulation system based on multi-sensor feedback, wherein the signal processing module comprises a filtering unit, a calibration unit and a data fusion unit; the filtering unit is used to perform noise suppression processing on the original parameters collected by the multi-sensor module; the calibration unit is used to correct the system error of the filtered parameters based on a preset standard parameter library; and the data fusion unit is used to perform information fusion on the calibrated multi-dimensional parameters by using a multi-source data fusion algorithm, and output comprehensive feedback parameters capable of representing the terahertz energy output state.

[0008] The above-mentioned terahertz energy output adaptive regulation system based on multi-sensor feedback, wherein the adaptive regulation module comprises a target setting unit, a strategy selection unit and an instruction generation unit; the target setting unit is used to store or receive externally input terahertz energy output target parameters; the strategy selection unit is used to adaptively select a corresponding regulation strategy according to the deviation degree of the feedback parameters and the target parameters, the regulation strategy comprising a proportional integral derivative regulation strategy, a model prediction regulation strategy and a neural network adaptive regulation strategy; and the instruction generation unit is used to generate corresponding voltage or current regulation instructions according to the selected regulation strategy and the deviation data.

[0009] The above-mentioned terahertz energy output adaptive regulation system based on multi-sensor feedback, wherein the terahertz source module comprises a terahertz generator, a driving circuit and a matching circuit; the driving circuit is in control connection with the adaptive regulation module, and is used to output a corresponding driving signal in response to the regulation instruction; the terahertz generator is electrically connected with the driving circuit, and is used to generate a terahertz wave under the action of the driving signal; and the matching circuit is connected to the output end of the terahertz generator, and is used to optimize the output impedance matching of the terahertz wave and improve the energy transmission efficiency.

[0010] The application further provides a terahertz energy output adaptive regulation method based on multi-sensor feedback, which is applied to the above-mentioned terahertz energy output adaptive regulation system based on multi-sensor feedback, and comprises the following steps: Step one, parameter collection, real-time collection of multi-dimensional physical parameters related to terahertz energy output through a multi-sensor module; Step two, signal processing, filtering, calibration and fusion processing of the collected multi-dimensional physical parameters in turn to obtain standardized feedback parameters; Step three, regulation and decision-making, deviation calculation according to the feedback parameters and the preset energy output target parameters, and adaptive selection of regulation strategies and generation of regulation instructions based on the deviation results; Step four, energy regulation, the terahertz source module responds to the regulation instructions, adjusts its working state to adjust the terahertz energy output, and realizes adaptive regulation of the terahertz energy output.

[0011] The above-mentioned terahertz energy output adaptive regulation method based on multi-sensor feedback, wherein the fusion processing in step two is specifically: using a weighted fusion algorithm, according to the measurement accuracy weight of each sensor, weighted calculation is performed on the calibrated multi-dimensional parameters to obtain comprehensive feedback parameters; wherein the measurement accuracy weight is determined by error analysis on the historical measurement data of each sensor.

[0012] The above-mentioned terahertz energy output adaptive regulation method based on multi-sensor feedback, wherein the deviation calculation in step three is specifically: calculating the absolute deviation and relative deviation of the terahertz energy amplitude in the feedback parameters and the target energy amplitude, and simultaneously calculating the deviation of the frequency parameter and the target frequency parameter; when the relative deviation is less than a preset threshold, a proportional-integral-derivative regulation strategy is selected; when the relative deviation is greater than or equal to the preset threshold and less than twice the preset threshold, a model prediction regulation strategy is selected; when the relative deviation is greater than or equal to twice the preset threshold, a neural network adaptive regulation strategy is selected.

[0013] The above-mentioned terahertz energy output adaptive regulation method based on multi-sensor feedback, wherein it further comprises step five, feedback iteration, after the terahertz source module completes the energy regulation, the multi-sensor module collects the terahertz energy output related parameters again, and steps two to four are repeated until the deviation of the feedback parameters and the target parameters is less than a preset stable threshold, realizing stable regulation of the terahertz energy output.

[0014] The above-mentioned terahertz energy output adaptive regulation method based on multi-sensor feedback, wherein the parameter collection in step one adopts a synchronous collection method, and the collection frequency of the multi-sensor module is dynamically adjusted according to the output frequency of the terahertz source module, and the collection frequency is not less than ten times the output frequency of the terahertz source module.

[0015] The present application has the following beneficial effects: 1. Improve the overall regulation and precision: through the multi-sensor module to realize the full-dimensional collection of terahertz output characteristics and transmission environment parameters, combined with the step-by-step optimization processing of the signal processing module, the influence of single parameter collection and original data noise, error on the regulation is avoided, the feedback parameter is more in line with the actual output state, which provides reliable data support for accurate regulation, and significantly improves the regulation precision; 2. Enhance the regulation adaptability and efficiency: the adaptive regulation module dynamically matches the regulation strategy based on the deviation degree, breaks through the adaptation limitation of traditional fixed strategy, can select the optimal regulation mode in different deviation scenes, realizes stable regulation in small deviation scene and rapid response in large deviation scene, improves the adaptation ability and regulation efficiency of the system to complex working conditions; 3. Ensure the stability of energy output: through the closed-loop iterative regulation process, the system can continuously correct the energy output deviation, avoid the problem of insufficient accuracy of single regulation; At the same time, the matching circuit optimizes the impedance matching, reduces the energy transmission loss, ensures that the terahertz energy output is stable in the target range for a long time, and improves the reliability of terahertz technology in various application scenarios; 4. Improve the practicability and operability of the system: the functions of each module of the system are clear, the connection logic is clear, only initial deployment and parameter setting are needed in the use process, and subsequent regulation process can be automatically executed without continuous manual intervention; At the same time, the dynamic adjustment of the collection frequency adapts to the different output frequency requirements of the terahertz source, which further improves the practicability of the system. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 The electrical connection relationship diagram of each module in the terahertz energy output adaptive regulation system based on multi-sensor feedback provided by the embodiment of the present application is shown. Figure 2 The flowchart of the terahertz energy output adaptive regulation method based on multi-sensor feedback provided by the embodiment of the present application is shown. Figure 3 The regulation overall and precision improvement curve is shown. Figure 4 The complex working condition adaptation ability curve is shown. Figure 5 The energy output stability curve is shown. Figure 6 The iteration efficiency curve is shown. DETAILED DESCRIPTION

[0017] The technical solutions of the present application will be further illustrated by specific embodiments in combination with the drawings.

[0018] In the drawings, only for example, the representation is a schematic diagram, not a physical diagram, and cannot be understood as a limitation of the present application; in order to better illustrate the embodiments of the present application, some components in the drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product; for those skilled in the art, it is understandable that some well-known structures and their descriptions in the drawings may be omitted.

[0019] The same or similar reference numerals in the drawings of the embodiments of the present application correspond to the same or similar components; in the description of the present application, it should be understood that if the terms "upper", "lower", "left", "right", "inner", "outer" and the like indicate the orientation or positional relationship shown in the drawings, they are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, therefore the terms describing the positional relationship in the drawings are only for example and cannot be understood as a limitation of the present application, for those skilled in the art, the specific meaning of the above terms can be understood according to the specific circumstances.

[0020] In the description of the present application, unless otherwise explicitly specified and limited, if the term "connection" and the like appear to indicate the connection relationship between components, the term should be broadly understood, for example, it can be fixedly connected, or it can be detachably connected, or it can be integrated; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication or interaction relationship between two components. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0021] Referring to Figures 1-6 , the present specific embodiment provides the following embodiments 1 and 2, in which Figure 1 the electrical connection relationship of each module in the system is shown; Figure 2 the flow of the present multi-sensor feedback based terahertz energy output adaptive control method is shown; Figure 3 In the figure, the X-axis represents time / iteration number, and the Y-axis represents control accuracy (deviation), which shows that the curve of the present system quickly decreases and tends to be stable, and the curve of the comparison group system decreases slowly and fluctuates obviously, which reflects the precise control advantage of the multi-sensor feedback system; Figure 4 In the figure, the X-axis represents environmental parameter change (temperature / humidity fluctuation), and the Y-axis represents system output stability, which shows that the present system maintains stable output (curve is smooth) under complex working conditions, and the comparison group system fluctuates significantly, which verifies the adaptability of the system to dynamic environment; Figure 5 In the figure, the X-axis represents time, and the Y-axis represents output energy, which shows that the output of the present system is close to the target energy line (fluctuation ± 0.5%), and the output of the comparison group system fluctuates greatly (± 15%) around the target line, which directly shows the difference in stability of energy output;Figure 6 The X-axis represents the number of iterations, and the Y-axis represents the time when the deviation falls below the threshold value. The system converges quickly through limited iterations, demonstrating the efficiency of the multi-sensor feedback mechanism. Embodiment

[0022] The multi-sensor feedback-based terahertz energy output adaptive regulation system provided in this embodiment includes a multi-sensor module, a signal processing module, an adaptive regulation module, and a terahertz source module. Figures 1-5 As shown in the figure, the multi-sensor module, the signal processing module, the adaptive regulation module, and the terahertz source module are connected in signal. The multi-sensor module is connected to the signal processing module for collecting multi-dimensional physical parameters related to terahertz energy output and transmitting them to the signal processing module. The signal processing module is connected to the adaptive regulation module for filtering, calibrating, and fusing the parameters collected by the multi-sensor module, and outputting standardized feedback parameters. The adaptive regulation module is connected to the terahertz source module for generating regulation instructions based on the feedback parameters output by the signal processing module and combining the preset energy output target, and sending the regulation instructions to the terahertz source module. The terahertz source module is used to respond to the regulation instructions of the adaptive regulation module, adjust its working state, and realize adaptive output of terahertz energy.

[0023] This scheme forms a closed-loop link of multi-dimensional parameter collection-processing-regulation by constructing a collaborative architecture of multi-sensor module, signal processing module, adaptive regulation module, and terahertz source module, breaks through the limitation of single parameter feedback, makes the terahertz energy output regulation more comprehensive and accurate, and ensures that the output state can stably adapt to the preset target demand.

[0024] Specifically, in this embodiment, the multi-sensor module includes an energy sensor, a frequency sensor, a phase sensor, and an environmental parameter sensor. The energy sensor, the frequency sensor, and the phase sensor are all arranged at the output end of the terahertz source module and are connected to the signal processing module in signal. The energy sensor is used to collect the terahertz energy amplitude parameter output by the terahertz source module and transmit it to the signal processing module. The frequency sensor is used to collect the terahertz wave frequency parameter output by the terahertz source module and transmit it to the signal processing module. The phase sensor is used to collect the terahertz wave phase parameter output by the terahertz source module and transmit it to the signal processing module. The environmental parameter sensor is arranged on the terahertz transmission path and is connected to the signal processing module in signal, and is used to collect the temperature, humidity, and air pressure parameters on the terahertz transmission path and transmit them to the signal processing module.

[0025] This scheme arranges energy, frequency, and phase sensors at the output end of the terahertz source, arranges environmental parameter sensors on the transmission path, and establishes signal connections between all sensors and the signal processing module, achieving full-dimensional collection of terahertz output characteristics and transmission environment parameters, supplementing complete data basis, reducing the influence of environmental interference and parameter loss on regulation, and improving the pertinence and reliability of regulation.

[0026] Specifically, in the embodiment, the signal processing module includes a filtering unit, a calibration unit and a data fusion unit; the filtering unit is signal connected with the multi-sensor module, used for noise suppression processing of the original parameters collected by the multi-sensor module, and the filtering unit is also signal connected with the calibration unit, used for transmitting the filtered parameters to the calibration unit; the calibration unit is signal connected with the data fusion unit, used for system error correction of the filtered parameters based on the preset standard parameter library, and transmitting the calibrated parameters to the data fusion unit; the data fusion unit is signal connected with the adaptive control module, used for information fusion of the calibrated multi-dimensional parameters by using a multi-source data fusion algorithm, outputting comprehensive feedback parameters capable of representing the terahertz energy output state and transmitting to the adaptive control module.

[0027] The scheme improves the accuracy and representativeness of the feedback parameters by step-by-step signal connection and step-by-step processing of the filtering unit, the calibration unit and the data fusion unit, suppresses the noise in the original parameters first, corrects the system error, and finally integrates the multi-dimensional parameters, avoids the control misjudgment caused by single parameter deviation or noise, and provides reliable data support for adaptive control.

[0028] Specifically, in the embodiment, the adaptive control module includes a target setting unit, a strategy selection unit and an instruction generation unit; the target setting unit is signal connected with the strategy selection unit, used for storing or receiving the externally input terahertz energy output target parameters and transmitting to the strategy selection unit; the strategy selection unit is also signal connected with the output end of the signal processing module, used for receiving the feedback parameters output by the signal processing module, adaptively selecting the corresponding control strategy according to the deviation degree of the feedback parameters and the target parameters, the control strategy including proportional integral derivative control strategy, model prediction control strategy and neural network adaptive control strategy; the strategy selection unit is signal connected with the instruction generation unit, and the instruction generation unit is also control connected with the terahertz source module, used for generating corresponding voltage or current control instructions according to the selected control strategy and deviation data, and transmitting the control instructions to the terahertz source module.

[0029] The scheme breaks through the adaptation limitation of single control strategy by signal linkage of the target setting unit, the strategy selection unit and the instruction generation unit, adaptively matches the control strategy according to the deviation degree, quickly selects the optimal control mode in different deviation scenarios, improves the control efficiency and adaptability, and ensures that the generated control instructions accurately match the adjustment requirements of the terahertz source.

[0030] Specifically, in the embodiment, the terahertz source module includes a terahertz generator, a driving circuit, and a matching circuit; the driving circuit is in control connection with the adaptive control module, is used for receiving the control instruction output by the adaptive control module and outputting a corresponding driving signal in response to the control instruction; the terahertz generator is electrically connected with the driving circuit, and is used for generating terahertz waves under the action of the driving signal; the input end of the matching circuit is connected with the output end of the terahertz generator, and the output end of the matching circuit is the terahertz wave output end of the terahertz source module, and is used for optimizing the output impedance matching of the terahertz waves and improving the energy transmission efficiency.

[0031] In the scheme, the driving circuit is in control connection with the adaptive control module, the terahertz generator is electrically connected with the driving circuit, and the matching circuit is connected with the output end of the generator, forming a complete instruction response-energy generation-output optimization link, so that the terahertz source can accurately respond to the control instruction, while reducing energy transmission loss and improving the effectiveness and utilization of energy output. Embodiment

[0032] The embodiment provides a terahertz energy output adaptive control method based on multi-sensor feedback, which is applied to the terahertz energy output adaptive control system based on multi-sensor feedback in embodiment 1, and the method comprises the following steps: step one, parameter acquisition, real-time acquisition of multi-dimensional physical parameters related to terahertz energy output through a multi-sensor module; step two, signal processing, filtering, calibration and fusion processing of the collected multi-dimensional physical parameters in sequence to obtain standardized feedback parameters; step three, control decision, deviation calculation according to the feedback parameters and preset energy output target parameters, adaptive selection of a control strategy based on the deviation result and generation of a control instruction; step four, energy adjustment, the terahertz source module responds to the control instruction, adjusts its working state to adjust the terahertz energy output, and realizes adaptive control of the terahertz energy output.

[0033] The scheme converts the system architecture into an orderly process of parameter acquisition-signal processing-control decision-energy adjustment, clearly defines the execution logic and connection relationship of each link, makes the adaptive control operable, guarantees the orderly cooperation of the functions of each module of the system, realizes the standardization of the terahertz energy output control, and ensures that the adaptive control target is stably landed.

[0034] Specifically, in the embodiment, the fusion processing in step two is specifically: a weighted fusion algorithm is used, the calibrated multi-dimensional parameters are weighted calculated according to the measurement accuracy weights of each sensor, and a comprehensive feedback parameter is obtained; wherein the measurement accuracy weight is determined by error analysis on the historical measurement data of each sensor.

[0035] The scheme adopts a weighted fusion algorithm, integrates the calibrated parameters according to the measurement accuracy weights of the sensors, fully considers the measurement reliability differences of different sensors, makes the integrated feedback parameters more consistent with the actual output state of the terahertz, improves the reliability of the feedback data, and further ensures the rationality of the control decision.

[0036] Specifically, in the embodiment, the deviation calculation in step three is specifically: calculating the absolute deviation and the relative deviation of the terahertz energy amplitude in the feedback parameter and the target energy amplitude, and simultaneously calculating the deviation of the frequency parameter and the target frequency parameter; when the relative deviation is less than a preset threshold, a proportional-integral-derivative control strategy is selected; when the relative deviation is greater than or equal to the preset threshold and less than twice the preset threshold, a model prediction control strategy is selected; and when the relative deviation is greater than or equal to twice the preset threshold, a neural network adaptive control strategy is selected.

[0037] The scheme avoids the blindness of strategy selection by clearly defining the deviation calculation dimensions of the terahertz energy amplitude and frequency, and the corresponding rules of different deviation ranges and control strategies, ensures stable control in a small deviation scenario and efficient control in a large deviation scenario, and improves the adaptation ability of the system to different output deviations.

[0038] Specifically, in the embodiment, step five, feedback iteration, is further included. After the energy adjustment of the terahertz source module is completed, the terahertz energy output related parameters are collected again by the multi-sensor module, and steps two to four are repeated until the deviation of the feedback parameter and the target parameter is less than a preset stable threshold, so as to realize stable control of the terahertz energy output.

[0039] The scheme increases the iterative collection and repeated control steps after energy adjustment to form a closed-loop control for continuous optimization, gradually corrects the residual deviation after single control, avoids the problem of insufficient control accuracy, further improves the long-term stability of the terahertz energy output, and ensures that the output deviation is always controlled within a stable range.

[0040] Specifically, in the embodiment, the parameter collection in step one adopts a synchronous collection mode, and the collection frequency of the multi-sensor module is dynamically adjusted according to the output frequency of the terahertz source module, and the collection frequency is not less than ten times the output frequency of the terahertz source module.

[0041] The scheme adopts a synchronous collection mode and dynamically adjusts the collection frequency to ensure the timing consistency of the multi-sensor parameter collection, avoid control lag caused by collection delay or asynchronization, adapt to the collection needs of different output frequencies of the terahertz source, and ensure the timeliness and integrity of the collected data, thereby providing a guarantee for the timeliness of subsequent processing and control.

[0042] Specifically, in the embodiment, the deviation calculation further adopts a multi-dimensional weighted fusion control error evaluation equation for comprehensive control error evaluation, and the equation is represented as: ; Where: is the comprehensive regulation error; are the measured and target energy amplitudes, respectively; are the measured and target frequencies, respectively; are the measured and target phases (in radians), respectively; is the measured value of the i-th environmental parameter; is the standard value of the i-th environmental parameter; α, β, γ, δ are the weight coefficients of energy, frequency, phase, and environmental parameters, respectively, and satisfy α + β + γ + δ = 1; is the weight coefficient within each environmental parameter, reflecting its influence on energy output; All error terms are normalized to ensure is a dimensionless evaluation index.

[0043] Derivation process of the equation: The equation is constructed based on the actual needs of multi-sensor feedback regulation, considering four major factors affecting the stability of terahertz output: energy, frequency, phase, and environmental parameters. The derivation process is as follows: 1. Normalization: To eliminate the influence of different physical dimensions on error evaluation, each error is in the form of relative error or normalized error; 2. Weighted fusion: According to the influence of each parameter on the stability of the output, different weight coefficients α, β, γ, δ are given, and the weights can be dynamically adjusted according to historical data or expert experience; 3. Environmental parameter integration: Environmental parameters (such as temperature, humidity, and air pressure) are introduced through weighted accumulation, reflecting their comprehensive influence on terahertz propagation; 4. Dimensionless output: The final output is a dimensionless index, which is convenient for comparison with the preset threshold and used for adaptive strategy selection.

[0044] Example: Suppose the current system collects the following parameters: = 102 mW, = 100 mW; = 2.01 THz, = 2.00 THz; =0.52rad, =0.50 rad; Environmental parameters: temperature =26℃, =25℃; Humidity =55%, =50%; Weighting coefficients are set as follows: α=0.5, β=0.2, γ=0.2, δ=0.1, representing the weights within the environment. =0.6, =0.4.

[0045] Substitute into the equation to calculate: ; The system according to The value is compared with the preset threshold, and the corresponding control strategy is selected.

[0046] Parameter description: α, β, γ, δ: can be dynamically optimized through learning algorithms or experimental calibration, reflecting the importance of each parameter under the current working conditions; The internal weights of environmental parameters can be determined through correlation analysis or transfer function models.

[0047] All sensor data must be filtered and calibrated by the signal processing module to ensure the reliability of the input data.

[0048] Technical effects: 1. Improve the comprehensiveness and scientific nature of error assessment: Integrate multi-dimensional parameters to avoid the one-sidedness of assessment based on a single indicator; 2. Enhance the accuracy of adaptive regulation: Through quantitative evaluation, provide more refined decision-making basis for strategy selection; 3. Adaptability to complex operating conditions: The dynamic weighting of environmental parameters enhances the system's robustness in controlling changes under varying environments; 4. Facilitates system integration and debugging: The equation structure is clear and the parameters are adjustable, which facilitates the implementation and optimization of the actual system.

[0049] Working principle and process: In the "regulation decision-making" step: 1. Obtain standardized feedback parameters from the signal processing module; 2. Call the target parameters; 3. Substitute into the multi-dimensional weighted fusion control error evaluation equation to calculate. ; 4. According to Compare with the preset threshold range and select the appropriate control strategy (such as PID, MPC, neural network). 5. outputting a regulation instruction to the terahertz source module; 6. continuously updating the weight coefficient in the iteration process to achieve dynamic optimization.

[0050] In summary, the terahertz energy output adaptive regulation method and system based on multi-sensor feedback provided by the embodiment has the following advantages: 1. Improve the comprehensiveness and accuracy of regulation: Through the multi-sensor module, the terahertz output characteristics and transmission environment parameters are collected in all dimensions, and combined with the step-by-step optimization processing of the signal processing module, the influence of single parameter collection and original data noise and error on regulation is avoided, the feedback parameters are more in line with the actual output state, and reliable data support is provided for accurate regulation, significantly improving the regulation accuracy; 2. Enhance the adaptability and efficiency of regulation: The adaptive regulation module dynamically matches the regulation strategy based on the deviation degree, breaking through the adaptation limitations of traditional fixed strategies, and can select the optimal regulation mode in different deviation scenarios, achieving stable regulation in small deviation scenarios and rapid response in large deviation scenarios, improving the adaptation ability and regulation efficiency of the system to complex working conditions; 3. Ensure the stability of energy output: Through the closed-loop iterative regulation process, the system can continuously correct the energy output deviation, avoiding the problem of insufficient accuracy of single regulation; at the same time, the matching circuit optimizes the impedance matching, reduces the energy transmission loss, and ensures that the terahertz energy output is stable in the target range for a long time, improving the reliability of terahertz technology in various application scenarios; 4. Improve the practicality and operability of the system: The functions of each module of the system are clear, and the connection logic is clear. During use, only initial deployment and parameter setting need to be completed, and subsequent regulation process can be automatically executed without continuous manual intervention; at the same time, the dynamic adjustment of the collection frequency adapts to the different output frequency requirements of the terahertz source, further improving the practicality of the system.

[0051] Working principle: The system realizes adaptive regulation of terahertz energy output based on the logic of multi-dimensional collection-accurate processing-adaptive regulation-closed-loop optimization, and the modules work cooperatively to form a complete closed-loop link: 1. Parameter collection stage: The multi-sensor module serves as the data input end, and the energy, frequency, and phase sensors are deployed at the output end of the terahertz source to collect real-time output characteristic parameters such as terahertz energy amplitude, frequency, and phase; environmental parameter sensors are deployed on the transmission path to collect environmental parameters such as temperature, humidity, and air pressure, and all sensors synchronously transmit the collected raw parameters to the signal processing module; 2. Signal processing stage: The signal processing module optimizes the original parameters step by step. The filtering unit first filters out the noise of the original parameters and removes the interference signals. The calibration unit corrects the systematic errors of the filtered parameters based on the standard parameter library to improve the data accuracy. The data fusion unit uses a weighted fusion algorithm to integrate the multi-dimensional parameters based on the measurement accuracy weights of each sensor, outputs comprehensive feedback parameters that can fully represent the state of terahertz energy output, and transmits them to the adaptive control module; 3. Control decision stage: The target setting unit in the adaptive control module provides preset energy output target parameters. After receiving the feedback parameters and target parameters, the strategy selection unit calculates the deviation between them and adaptively matches the control strategy according to the deviation size. The instruction generation unit generates corresponding voltage or current control instructions based on the selected strategy and deviation data, and transmits them to the terahertz source module. 4. Energy output stage: After receiving the control instructions, the drive circuit of the terahertz source module outputs corresponding drive signals to drive the terahertz generator to generate terahertz waves. The matching circuit optimizes the impedance matching of terahertz wave output to reduce energy transmission loss and achieve precise energy output. At the same time, the multi-sensor module continuously collects the adjusted output parameters, and the above process is repeated to form a closed loop iteration, ensuring stable energy output to meet the target requirements.

[0052] Method of use: 1. System deployment: Install each module according to the preset position, fix the energy, frequency, and phase sensors on the output end of the terahertz source module, and deploy the environmental parameter sensors at the key nodes of the terahertz transmission path. Complete the signal and control connection between the multi-sensor module, the signal processing module, the signal processing module, the adaptive control module, and the terahertz source module to ensure smooth link; 2. Parameter setting: Input or call the preset terahertz energy output target parameters, including energy amplitude, frequency, and other core indicators, through the target setting unit of the adaptive control module. At the same time, confirm the key parameters such as the standard parameter library of the signal processing module, the filtering and fusion algorithm parameters, and the deviation threshold of the adaptive control strategy; 3. Start running: Start the terahertz source module, the system automatically enters the working state, and the multi-sensor module synchronously collects multi-dimensional physical parameters at the dynamically adjusted sampling frequency and transmits them to the signal processing module; 4. Adaptive control: The signal processing module filters, calibrates, and fuses the collected parameters to output comprehensive feedback parameters. The adaptive control module calculates the deviation between the feedback parameters and the target parameters, matches the corresponding control strategy, and generates control instructions to drive the terahertz source module to adjust the working state. 5. Closed-loop maintenance: The system continuously collects the adjusted output parameters through the multi-sensor module, repeatedly processes the signals, makes control decisions, and adjusts the energy, until the deviation of the feedback parameters from the target parameters is less than the stability threshold, achieving stable control; in subsequent operation, the system automatically responds to parameter fluctuations and continuously executes the closed-loop control process without human intervention.

[0053] In addition, the present application also provides the following examples: Based on the control system of Embodiment 1 and the control method of Embodiment 2, the specific selection and connection of each module are as follows: 1. Multi-sensor module: InGaAs terahertz energy sensor (adapted to 0.1-10 THz frequency band), terahertz frequency counter (measurement accuracy up to one thousandth of the frequency band), and terahertz phase detector are selected as output characteristic acquisition components, all of which are connected to the signal input end of the signal processing module through the SMA interface and physically fixed to the flange plate at the output end of the terahertz source; a temperature and humidity integrated sensor (measurement range covering conventional indoor and outdoor environments) is selected as an environmental parameter acquisition component, connected to the signal processing module through the I2C interface, and deployed at the middle node position of the terahertz transmission path; 2. Signal processing module: an FPGA chip (model XC7K325T) is used as the core processing unit, integrating a filtering unit, a calibration unit, and a data fusion unit; the filtering unit realizes noise suppression through the Kalman filtering algorithm, the calibration unit has a built-in preset standard parameter library (covering error correction coefficients of each sensor under different working conditions), and the data fusion unit uses a weighted fusion algorithm; the signal processing module is connected to the adaptive control module through the SPI interface for transmitting integrated feedback parameters; 3. Adaptive control module: an ARM processor (model STM32H743) is selected to build a target setting unit, a strategy selection unit, and an instruction generation unit; the target setting unit supports inputting terahertz energy amplitude and frequency target parameters through the upper computer software and storing them; the strategy selection unit presets a deviation threshold (small deviation threshold, twice small deviation threshold), and internally builds proportional-integral-derivative control algorithm, model predictive control algorithm, and neural network adaptive control algorithm; the instruction generation unit outputs 0-5V adjustable voltage control instructions through the DAC interface and is connected to the drive circuit control of the terahertz source module; 4. Terahertz source module: a quantum cascade terahertz generator (output frequency band 1-5 THz) is used as the core component, a high-speed operational amplifier is selected to form an adjustable drive circuit, and a microstrip impedance matching network (adapted to 50Ω characteristic impedance) is used as the matching circuit; the drive circuit input end is connected to the DAC output end of the adaptive control module, the drive circuit output end is electrically connected to the terahertz generator, the matching circuit input end is welded to the output end of the terahertz generator, and the matching circuit output end is used as the terahertz wave output port; 5. Regulation process adaptation: The parameter acquisition adopts a synchronous acquisition method, and the timing of the FPGA chip is used to synchronously control the acquisition timing of each sensor. The acquisition frequency is dynamically adjusted according to the output frequency of the terahertz generator, and the acquisition frequency is ensured to be not less than ten times the output frequency. The measurement accuracy weights of each sensor in the fusion processing are determined based on historical measurement error analysis through multiple calibration experiments on each sensor in the early stage. In the feedback iteration process, the stability threshold is set as the allowed deviation range of the target parameter to ensure that the energy output is stable after iteration termination.

[0054] Working principle of this example: This example follows the logic of multi-dimensional acquisition-precise processing-self-adaptive regulation-closed-loop optimization, and the specific working process is as follows: 1. Parameter acquisition stage: After the terahertz generator is started, the energy sensor, frequency counter, and phase detector synchronously acquire the terahertz energy amplitude, frequency, and phase parameters output by the terahertz generator. The temperature, humidity, and pressure integrated sensor synchronously acquires the environmental parameters of the transmission path. All raw parameters are transmitted in real time to the FPGA chip through the corresponding interface. 2. Signal processing stage: The filter unit in the FPGA chip suppresses noise of the raw parameters through the Kalman filter algorithm, and eliminates environmental interference and random noise of the sensor itself. The calibration unit calls the built-in standard parameter library to correct the system error of the filtered parameters, and compensates for the temperature drift error and installation error of the sensor. The data fusion unit integrates the multi-dimensional calibrated parameters through the weighted fusion algorithm according to the preset measurement accuracy weights of each sensor, generates comprehensive feedback parameters that can fully represent the terahertz energy output state, and transmits them to the ARM processor through the SPI interface. 3. Regulation decision stage: The target setting unit of the ARM processor calls the preset energy output target parameters, the strategy selection unit calculates the deviation (including the relative deviation of the energy amplitude and the frequency deviation) between the comprehensive feedback parameters and the target parameters, and matches the regulation strategy according to the deviation size - when the relative deviation is less than the small deviation threshold, select the proportional integral derivative regulation strategy; when the relative deviation is greater than or equal to the small deviation threshold and less than twice the small deviation threshold, select the model prediction regulation strategy; when the relative deviation is greater than or equal to twice the small deviation threshold, select the neural network self-adaptive regulation strategy; the instruction generation unit outputs the corresponding voltage regulation instruction to the driving circuit through the DAC interface according to the selected strategy and deviation data. 4. Energy regulation and closed-loop iteration stage: After the driving circuit receives the voltage regulation instruction, it adjusts the amplitude of the output driving signal, thereby regulating the operating current of the terahertz generator, and realizes the adjustment of the terahertz energy output; the matching circuit optimizes the output impedance through the microstrip line impedance matching network, reduces the energy loss in the process of terahertz wave transmission; at the same time, the multi-sensor module continuously collects the adjusted output parameters and environmental parameters, and repeats the above signal processing, regulation decision, energy regulation process until the deviation of the comprehensive feedback parameters and the target parameters is less than the stable threshold, realizing the stable output of the terahertz energy.

[0055] Experimental data: Two working conditions are set up for verification: working condition one is the conventional indoor environment (temperature 25℃, humidity 50%, atmospheric pressure standard atmospheric pressure), the target energy amplitude is the preset conventional value, and the target frequency is 2THz; working condition two is a complex environment condition (temperature fluctuation range 15-35℃, humidity fluctuation range 30%-70%, atmospheric pressure slightly lower than standard atmospheric pressure), the target energy amplitude and frequency are consistent with working condition one; at the same time, a traditional single parameter regulation system is set as a comparison group (only collecting energy amplitude parameters, using a fixed proportional integral derivative regulation strategy).

[0056] The experimental results show that: under working condition one, the example system can quickly make the terahertz energy output reach the target state, and the output state is stable and maintained without obvious fluctuation; the comparison group system takes longer to reach the target state, and there is a small amplitude fluctuation. Under working condition two, the example system can maintain stable terahertz energy output through environmental parameter collection and adaptive strategy matching; the comparison group system cannot maintain the target output state stably due to not considering the influence of environmental parameters. During the feedback iteration process, the example system can reduce the deviation to below the stable threshold within a limited number of iterations, and the output state remains stable after termination of iteration.

[0057] The technical effects of this example are: 1. Improve the comprehensiveness and accuracy of regulation: By selecting multiple types of sensors to cooperatively collect output characteristic parameters and environmental parameters, and combining Kalman filtering and weighted fusion algorithm to process data, the limitations of single parameter collection and original data noise interference are avoided, making the feedback parameters more consistent with the actual output state, providing reliable data support for accurate regulation, and thereby improving the comprehensiveness and accuracy of regulation; 2. Enhance the adaptability to complex working conditions: By pre-setting multiple regulation strategies and deviation matching rules, the system can adaptively select the optimal regulation method according to the output deviation degree, and at the same time, combined with environmental parameter collection to compensate for environmental interference, it breaks through the adaptation limitations of traditional fixed strategies in complex working conditions, ensuring stable regulation in both conventional and complex environmental conditions; 3. Ensure the stability of energy output: Through the closed-loop iterative control process, the system can continuously correct the energy output deviation, avoiding the problem of insufficient accuracy of single control; at the same time, the impedance matching design of the matching circuit reduces the energy transmission loss, so that the control command can be effectively converted into stable energy output, ensuring that the terahertz energy is long-term stable within the target range; 4. Improve the practicability of the system: The selection of each module considers performance and universality, and the connection interface is standardized, which is convenient for installation and deployment; after the system is started, it can automatically complete the whole process of acquisition, processing, control and iteration without continuous manual intervention, and is suitable for terahertz sources with different output frequencies, further improving the practicability and generalizability of the system.

[0058] The above is only the preferred embodiment of the present application, and does not limit the implementation and protection scope of the present application. For those skilled in the art, it should be realized that any equivalent replacement and obvious change made by applying the content of the present application should be included in the protection scope of the present application.

Claims

1. A terahertz energy output adaptive control system based on multi-sensor feedback, characterized in that, It includes a multi-sensor module, a signal processing module, an adaptive control module, and a terahertz source module, among which: The multi-sensor module is connected to the signal processing module and is used to collect multi-dimensional physical parameters related to terahertz energy output and transmit them to the signal processing module. The signal processing module is connected to the adaptive control module and is used to filter, calibrate and fuse the parameters collected by the multi-sensor module to output standardized feedback parameters. The adaptive control module is connected to the terahertz source module and is used to generate control commands and send them to the terahertz source module based on the feedback parameters output by the signal processing module and the preset energy output target through an adaptive control strategy. The terahertz source module is used to respond to the control commands of the adaptive control module and adjust its own working state to achieve adaptive output of terahertz energy.

2. The terahertz energy output adaptive control system based on multi-sensor feedback according to claim 1, characterized in that, The multi-sensor module includes an energy sensor, a frequency sensor, a phase sensor, and an environmental parameter sensor; the energy sensor is used to collect the terahertz energy amplitude parameter output by the terahertz source module; the frequency sensor is used to collect the terahertz wave frequency parameter output by the terahertz source module; the phase sensor is used to collect the terahertz wave phase parameter output by the terahertz source module; and the environmental parameter sensor is used to collect temperature, humidity, and air pressure parameters along the terahertz transmission path.

3. The terahertz energy output adaptive control system based on multi-sensor feedback according to claim 1, characterized in that, The signal processing module includes a filtering unit, a calibration unit, and a data fusion unit. The filtering unit is used to suppress noise in the raw parameters collected by the multi-sensor module. The calibration unit is used to correct system errors in the filtered parameters based on a preset standard parameter library. The data fusion unit is used to fuse information from the calibrated multi-dimensional parameters using a multi-source data fusion algorithm, and output a comprehensive feedback parameter that can characterize the terahertz energy output state.

4. The terahertz energy output adaptive control system based on multi-sensor feedback according to claim 1, characterized in that, The adaptive control module includes a target setting unit, a strategy selection unit, and an instruction generation unit; the target setting unit is used to store or receive externally input terahertz energy output target parameters; the strategy selection unit is used to adaptively select the corresponding control strategy according to the degree of deviation between the feedback parameters and the target parameters, and the control strategy includes proportional-integral-derivative control strategy, model prediction control strategy, and neural network adaptive control strategy. The instruction generation unit is used to generate corresponding voltage or current control instructions based on the selected control strategy and deviation data.

5. The terahertz energy output adaptive control system based on multi-sensor feedback according to claim 1, characterized in that, The terahertz source module includes a terahertz generator, a drive circuit, and a matching circuit; the drive circuit is controlled and connected to the adaptive control module, and is used to output a corresponding drive signal in response to the control command; the terahertz generator is electrically connected to the drive circuit, and is used to generate terahertz waves under the action of the drive signal. The matching circuit is connected to the output of the terahertz generator to optimize the output impedance matching of the terahertz wave and improve energy transmission efficiency.

6. A terahertz energy output adaptive control method based on multi-sensor feedback, characterized in that, The method, applied to the terahertz energy output adaptive control system based on multi-sensor feedback as described in any one of claims 1 to 5, comprises the following steps: Step 1: Parameter acquisition. Multi-dimensional physical parameters related to terahertz energy output are acquired in real time through a multi-sensor module. Step two, signal processing: the collected multi-dimensional physical parameters are filtered, calibrated and fused sequentially to obtain standardized feedback parameters; Step 3, control decision-making: Calculate the deviation between the feedback parameters and the preset energy output target parameters, adaptively select the control strategy based on the deviation results, and generate control instructions. Step four: Energy regulation. The terahertz source module responds to the regulation command and adjusts its own working state to adjust the terahertz energy output, thereby achieving adaptive regulation of the terahertz energy output.

7. The terahertz energy output adaptive control method based on multi-sensor feedback according to claim 6, characterized in that, The fusion process described in step two is as follows: a weighted fusion algorithm is used to calculate the calibrated multi-dimensional parameters by weighting them according to the measurement accuracy weights of each sensor, so as to obtain the comprehensive feedback parameters; wherein, the measurement accuracy weights are determined by error analysis of the historical measurement data of each sensor.

8. The terahertz energy output adaptive control method based on multi-sensor feedback according to claim 6, characterized in that, The deviation calculation in step three specifically involves: calculating the absolute and relative deviations between the terahertz energy amplitude and the target energy amplitude in the feedback parameters, and simultaneously calculating the deviation between the frequency parameters and the target frequency parameters; when the relative deviation is less than a preset threshold, a proportional-integral-derivative control strategy is selected. When the relative deviation is greater than or equal to the preset threshold and less than twice the preset threshold, the model prediction control strategy is selected. When the relative deviation is greater than or equal to twice the preset threshold, the neural network adaptive control strategy is selected.

9. The terahertz energy output adaptive control method based on multi-sensor feedback according to claim 6, characterized in that, It also includes step five, feedback iteration. After the terahertz source module completes energy regulation, the multi-sensor module collects the relevant parameters of terahertz energy output again, and steps two to four are repeated until the deviation between the feedback parameters and the target parameters is less than the preset stability threshold, so as to achieve stable control of terahertz energy output.

10. The terahertz energy output adaptive control method based on multi-sensor feedback according to claim 6, characterized in that, The parameter acquisition described in step one adopts a synchronous acquisition method. The acquisition frequency of the multi-sensor module is dynamically adjusted according to the output frequency of the terahertz source module, and the acquisition frequency is not less than ten times the output frequency of the terahertz source module.

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