Low-altitude aircraft stability enhancing system based on adaptive control

Abstract

The invention discloses a low-altitude aircraft stability enhancing system based on adaptive control, and belongs to the technical field of aircraft low-altitude control, and the system specifically comprises the steps: collecting the flight data of a low-altitude aircraft in real time, carrying out the preprocessing of the collected flight data of the low-altitude aircraft, and carrying out the deep processing and analysis, adjusting the control parameters of the aircraft in real time by using a self-adaptive control algorithm, outputting a control instruction, converting the control instruction into an actual action, and adjusting the flight attitude and trajectory of the aircraft; flight modes can be automatically switched according to different flight tasks, control parameters are dynamically adjusted according to the real-time state of the aircraft and external disturbance, and it is ensured that the aircraft keeps stable in a complex, dynamic and nonlinear low-altitude flight environment.

Description

Technical Field

[0001] The invention belongs to the technical field of low-altitude aircraft control, and in particular is a low-altitude aircraft stability enhancement system based on adaptive control. Background Art

[0002] Low-altitude aircraft (such as drones, helicopters, small planes, etc.) usually face complex flight environments when performing missions. Compared with high-altitude flights, low-altitude aircraft are more susceptible to factors such as terrain, airflow, weather, wind speed, and airflow turbulence; these factors often manifest as high-frequency disturbances, nonlinear changes, and environmental uncertainties, which seriously affect the flight stability, control accuracy, and mission completion efficiency of the aircraft. During low-altitude flight, the aircraft needs to quickly respond to sudden changes in airflow, changes in climate conditions, and disturbances in the surrounding environment.

[0003] Traditional low-altitude aircraft control methods, such as PID control and LQR control, are usually designed based on the linear dynamics model of the aircraft. These methods can show good control effects when the aircraft is less disturbed and the flight environment is relatively stable. However, when the aircraft encounters complex airflow disturbances, terrain changes, and nonlinear factors, the control effects of these traditional methods are often difficult to meet the requirements. Especially in complex, dynamic, and nonlinear low-altitude flight environments, traditional control methods are prone to slow response, low accuracy, and even system instability.

[0004] Therefore, with the continuous development of aircraft technology, especially the increasing number of application scenarios of low-altitude flight (such as environmental monitoring, agricultural spraying, urban air transportation, etc.), how to improve the stability and control accuracy of low-altitude aircraft in complex flight environments has become a research hotspot in the current field of aircraft control. Existing technologies mostly rely on disturbance compensation, model reference control and other methods to deal with the complex environment in low-altitude flight, but these methods still have certain limitations and are difficult to cope with changes in aircraft dynamic performance and real-time processing of complex nonlinear disturbances.

[0005] Adaptive control technology can adjust control system parameters in real time to adapt to system dynamic changes and uncertainties. In low-altitude aircraft control, adaptive control can adjust parameters according to the different disturbances and changes encountered by the aircraft in complex environments, thereby enhancing the robustness and stability of the system. However, existing adaptive control methods still face many challenges, such as how to quickly respond to sudden disturbances, how to deal with nonlinear aircraft dynamic characteristics, and how to achieve multi-mode aircraft control. These problems need to be solved urgently. Summary of the invention

[0006] In view of the deficiencies of the prior art, the present invention proposes a stability enhancement system for low-altitude aircraft based on adaptive control. By designing an adaptive controller to adjust the control strategy in real time, the stability of the low-altitude aircraft is improved, which can effectively cope with the dynamic changes of the aircraft in different flight stages and different environmental conditions, and achieve precise control and high-efficiency stability of the aircraft in the low-altitude environment.

[0007] To achieve the above object, the present invention provides the following technical solutions: A stability enhancement system for low-altitude aircraft based on adaptive control, comprising: a data acquisition module, a data processing module, an adaptive control module and an execution module; The data acquisition module is used to collect the flight data of the low-altitude aircraft in real time and preprocess the collected flight data of the low-altitude aircraft; The data processing module is used to receive the preprocessed flight data of the low-altitude aircraft from the data acquisition module and process and analyze the flight data received from the data acquisition module; The adaptive control module is used to adjust the control parameters of the low-altitude aircraft in real time by using an adaptive control algorithm and output control instructions; The execution module is used to receive the control instructions from the adaptive control module and convert the control instructions into actual actions to adjust the flight attitude and trajectory of the low-altitude aircraft.

[0008] Specifically, the data processing module includes: a disturbance perception and classification unit and a disturbance model establishment unit; The disturbance perception and classification unit is used to perceive external environmental disturbances and classify external disturbances; The disturbance model establishment unit is used to estimate the state of the aircraft, establish a disturbance source model according to external environmental disturbances, and evaluate the flight risk of the aircraft in combination with the real-time state of the aircraft.

[0009] Specifically, the perception of external environmental disturbances and the classification of external disturbances include: According to the wind speed and wind direction of the environment where the aircraft is located, combined with the ground wind speed data and the real-time flight trajectory of the aircraft, the wind speed distribution around the aircraft is calculated in real time by using wind field modeling technology; Directly sense the airflow in front of and on the side of the aircraft; Identify terrain obstacles and changing landforms, and perceive the terrain features around the aircraft.

[0010] Specifically, the estimation of the state of the aircraft, the establishment of a disturbance source model according to external environmental disturbances, and the evaluation of the flight risk of the aircraft in combination with the real-time state of the aircraft include: Based on the preprocessed flight data of low-altitude aircraft, use a filtering algorithm to calculate the dynamic state of the aircraft and obtain the real-time state of the aircraft; Based on wind speed perception, airflow disturbance, and terrain influence, through analyzing historical data and real-time monitored disturbance information, conduct real-time modeling and identification of external disturbance sources; Based on the established disturbance source model and combined with the real-time state of the aircraft, adopt a simulation method based on adaptive sampling to evaluate the impact of external disturbances on the aircraft.

[0011] Specifically, the real-time modeling and identification of external disturbance sources include: Extract disturbance data features, including time-domain features, frequency-domain features, non-linear dynamic features, and statistical features; Based on the real-time state of the aircraft and the real-time data of the external environment, use a data-driven machine learning method to model the disturbance source and obtain the disturbance source model; Input the extracted disturbance data features into the disturbance source model for identification and classification.

[0012] Specifically, the method of evaluating the impact of external disturbances on the aircraft by adopting a simulation method based on adaptive sampling based on the established disturbance source model and combined with the real-time state of the aircraft includes: Conduct sensitivity analysis on the flight state of the aircraft to evaluate the sensitivity of different disturbance sources to the aircraft state; Based on the identification and classification of the disturbance source, adopt a simulation method based on adaptive sampling to conduct multi-scenario and multi-mode simulations on the behavior of the aircraft under different environmental disturbances, and evaluate the impact range of external disturbances on the aircraft. The adaptive sampling process includes sampling data and verification frames, and the verification frames include sampling frames and data verification frames; Based on factors such as the state response of the aircraft, the intensity and duration of the disturbance source, construct multi-dimensional risk assessment indicators, including: probability of instability, increment of energy consumption, and index of reduced maneuverability; According to the evaluation results, automatically trigger corresponding warnings or emergency measures through the real-time calculated risk assessment indicators.

[0013] Specifically, the adaptive control module includes: a model and desired output unit, a non-linear control and compensation unit, and a multi-mode adaptive control unit; The model and desired output unit is used to establish the motion model of the aircraft and design the desired output based on requirements; The non-linear control and compensation unit is used to control and compensate the non-linear characteristics of the aircraft; The multi-mode adaptive control unit is used to adaptively control the aircraft under different flight conditions and modes.

[0014] Specifically, establishing the motion model of the aircraft and designing the desired output based on requirements includes: Establishing the linear and nonlinear motion equations of the aircraft, and deriving the motion model of the aircraft through parameters such as the mass, moment of inertia, and aerodynamic characteristics of the aircraft; Defining the tolerance range and designing the desired output according to different flight missions.

[0015] Specifically, adaptively controlling the aircraft under different flight conditions and modes includes: Calculating the control error by comparing the actual state of the aircraft with the desired output of the model, and analyzing the dynamic change of the control error; Adopting an adaptive gain adjustment algorithm to adjust the controller gain in real time and adaptively correct the error; Based on the preprocessed flight data of the low-altitude aircraft, real-time detecting the current flight mode of the aircraft, and automatically switching the suitable control strategy according to the flight missions under different modes.

[0016] Compared with the prior art, the beneficial effects of the present invention are: 1. The present invention proposes a stability enhancement system for low-altitude aircraft based on adaptive control. Adaptive control can dynamically adjust the control parameters according to the real-time state of the aircraft and external disturbances, ensuring the stability of the aircraft in a complex, dynamic, and nonlinear low-altitude flight environment.

[0017] 2. The present invention proposes a stability enhancement system for low-altitude aircraft based on adaptive control. By integrating various sensor data, it can real-time identify the type, intensity, and possible impacts of external disturbances, and can automatically adjust the control strategy according to the changes of the disturbance sources, compensating for the deviations caused by factors such as airflow disturbances and terrain impacts, so that the aircraft is always in a stable control state throughout the flight process.

[0018] 3. The present invention proposes a stability enhancement system for low-altitude aircraft based on adaptive control. Through nonlinear control and compensation, it designs a control strategy suitable for the nonlinear dynamic characteristics of the aircraft, dealing with the nonlinear response of the aircraft when encountering strong airflow disturbances or rapid maneuvers. In addition, it can automatically switch the flight mode (such as cruising, maneuvering, descending, etc.) according to different flight missions, ensuring that the aircraft can maintain good stability and control accuracy in various flight stages. Description of the Drawings

[0019] Figure 1 It is an architecture diagram of a stability enhancement system for low-altitude aircraft based on adaptive control provided by the present invention; Figure 2 It is a data processing flow chart provided by the present invention; Figure 3 Schematic diagram of adaptive sampling provided by the present invention; Figure 4 Flowchart of adaptive control provided by the present invention. Detailed implementation manners

[0020] The present application will be described in detail below with reference to specific embodiments. The following embodiments will help those skilled in the art to further understand the present application, but do not limit the present application in any form. It should be noted that those of ordinary skill in the art can make several modifications and improvements without departing from the concept of the present application. These all fall within the protection scope of the present application.

[0021] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0022] It should be noted that if there is no conflict, the various features in the embodiments of the present application can be combined with each other, and all are within the protection scope of the present application. In addition, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order from the module division in the device or the flowchart. In addition, the terms "first", "second", "third", etc. used in the present application do not limit the data and execution order, but only distinguish the same items or similar items with basically the same functions and effects.

[0023] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used in this specification in the description of the present application are only for the purpose of describing specific embodiments and are not used to limit the present application. The term "and / or" used in this specification includes any and all combinations of one or more of the related listed items.

[0024] Please refer to Figures 1-4 , an embodiment provided by the present invention: a low-altitude aircraft stability enhancement system based on adaptive control, including: a data acquisition module, a data processing module, an adaptive control module, and an execution module; The data acquisition module is used to collect the flight data of the low-altitude aircraft in real time and preprocess the collected flight data of the low-altitude aircraft; The flight data of the low-altitude aircraft includes information such as the attitude angles (pitch angle, roll angle, yaw angle), acceleration, angular velocity, altitude, airspeed, etc. of the aircraft; It also includes: the airflow conditions in the low-altitude environment, the atmospheric density, terrain, and temperature in the low-altitude area where the aircraft is located, etc.; The preprocessing, such as filtering, ensures the stability and reliability of the data by removing noise interference, providing high-quality data input for subsequent control algorithms.

[0025] The data processing module is used to receive the flight data of the low-altitude aircraft preprocessed by the data acquisition module, and deeply process and analyze the flight data received from the data acquisition module; The data processing module includes: a disturbance perception and classification unit and a disturbance model establishment unit; The disturbance perception and classification unit is used to perceive external environmental disturbances and classify external disturbances; The steps of perceiving external environmental disturbances and classifying external disturbances specifically include: Step A1: According to the wind speed and direction of the environment where the aircraft is located, combined with the ground wind speed data and the real-time flight trajectory of the aircraft, use wind field modeling technology to calculate the real-time wind speed distribution around the aircraft; This helps to identify wind shear or strong airflow areas encountered during flight, providing an early warning for subsequent control strategies.

[0026] Step A2: Directionally perceive the airflow in front of and on the side of the aircraft; Through the airflow disturbance model, instantaneous airflow changes caused by external factors can be identified, and the position and intensity of the disturbance source can be deduced, providing a basis for the controller's reaction.

[0027] Step A3: Identify terrain obstacles and changing landforms, and perceive the terrain features around the aircraft.

[0028] Especially when flying near the ground, lidar can generate a high-precision ground height map to predict potential hazards in the flight path in advance.

[0029] The disturbance model establishment unit is used to estimate the state of the aircraft, establish a disturbance source model based on external environmental disturbances, and evaluate the flight risk of the aircraft in combination with the real-time state of the aircraft.

[0030] The steps of estimating the state of the aircraft, establishing a disturbance source model based on external environmental disturbances, and evaluating the flight risk of the aircraft in combination with the real-time state of the aircraft specifically include: Step B1: Based on the flight data of the low-altitude aircraft after preprocessing, use a filtering algorithm to calculate the dynamic state of the aircraft to obtain the real-time state of the aircraft; Step B2: Based on wind speed perception, airflow disturbance, and terrain influence, through analyzing historical data and real-time monitored disturbance information, conduct real-time modeling and identification of external disturbance sources; The specific steps of Step B2 are as follows: Step B21: Extract the characteristics of disturbance data. The disturbance data includes data such as wind speed, airflow, and terrain, including time-domain characteristics, frequency-domain characteristics, non-linear dynamic characteristics, and statistical characteristics; In this embodiment, the time-domain characteristics are obtained by analyzing the time-domain waveforms of signals such as wind speed and air pressure, extracting basic characteristics such as the start time, duration, peak value, and change rate of the disturbance, and determining whether the disturbance is a sudden disturbance (such as thunderstorm, sudden airflow change) or a continuous disturbance (such as continuous wind speed change); the frequency-domain characteristics use the fast Fourier transform (FFT) to perform frequency-domain analysis on the time-domain signal, extracting the frequency components of the disturbance. For example, turbulence usually shows high-frequency fluctuations, while crosswind shows relatively stable low-frequency changes. Through spectrum analysis, different types of disturbance sources can be effectively distinguished; the non-linear dynamic characteristics, such as the non-linear response characteristics of the aircraft, such as sharp changes in control input and non-linear fluctuations in attitude, can be extracted by introducing non-linear dynamics analysis tools such as Lyapunov exponents and Fractal dimensions, helping to reveal the response mode of the aircraft when encountering complex disturbances (such as complex turbulence, strong airflow changes); the statistical characteristics are obtained by statistical analysis to extract characteristics such as the mean, variance, skewness, and kurtosis of the disturbance signal, identify the type of disturbance source (such as airflow disturbance, sudden crosswind, etc.), and provide input for subsequent model learning.

[0031] Step B22: Based on the real-time state of the aircraft and the real-time data of the external environment, use a data-driven machine learning method to model the disturbance source to obtain a disturbance source model; Data-driven machine learning methods such as support vector machine (SVM), neural network, etc.; Step B23: Input the extracted disturbance data characteristics into the disturbance source model for identification and classification; Through identification and classification, it is possible to automatically distinguish whether it is crosswind, airflow turbulence, terrain effect, or other sudden disturbances.

[0032] Step B3: Based on the established disturbance source model, combined with the real-time state of the aircraft, use an adaptive sampling-based simulation method to evaluate the impact of external disturbances on the aircraft.

[0033] The specific steps of Step B3 are as follows: Step B31: Conduct a sensitivity analysis of the flight state of the aircraft to evaluate the sensitivity of different disturbance sources to the aircraft state; Exemplarily, analyze the effects of crosswind, lift changes, and airflow turbulence on the aircraft's attitude and trajectory, identify which disturbance sources pose the greatest threats to the aircraft's stability and safety, and the disturbance sources with higher sensitivity should be given priority for weighting in the risk assessment.

[0034] Step B32: Based on the identification and classification of disturbance sources, use a simulation method based on adaptive sampling to perform multi-scenario and multi-mode simulations on the behavior of the aircraft under different environmental disturbances, and evaluate the scope of the impact of external disturbances on the aircraft. The adaptive sampling process includes sampling data and verification frames, and the verification frames include sampling frames and data verification frames. See Figure 3 , for example: During the steady flight phase, since the flight is relatively stable, the sampling frame will provide a larger sampling interval. During the takeoff phase, the pitch angle and roll angle are sampled at 100 samples per second to ensure that the aircraft maintains a stable horizontal takeoff. The data verification frame is used to verify which flight phase the aircraft is in and whether the data is correct. After the data verification frame corrects the flight phase of the aircraft, it automatically generates a sampling frame. By setting a dynamic threshold comparison based on the real-time sampled data and the key parameters of each flight phase, it can be determined whether the data is correct.

[0035] Using the sampling frame can effectively save system resources and reduce the number of data transmissions. The verification function of the data verification frame for the flight phase greatly enhances the fault tolerance. If the flight phase is misjudged due to external interference, sensor failures, etc., the verification frame can detect and correct it in time to avoid the incorrect execution of subsequent sampling strategies.

[0036] In this embodiment, the present application proposes an adaptive sampling method, which improves the simulation efficiency and enhances the accuracy of disturbance simulation by dynamically adjusting the sampling strategy, including: importance sampling, according to the probability distribution of disturbance sources and the dynamic response model of the aircraft, using the importance sampling method to increase the sampling frequency when high-risk disturbances (such as sudden changes in wind speed, airflow turbulence, etc.) occur. By increasing the sampling density of high-impact disturbance sources, it is ensured that low-probability but high-risk situations are not overlooked, and the representativeness of the simulation results is ensured; adaptive resampling, during each round of simulation, according to the disturbance impact evaluation results obtained from the previous round of simulation, the sampling strategy is adjusted in real time. If the impact of some disturbance sources is large, the sampling of the disturbance sources is increased. Conversely, if the impact of some disturbance sources on the aircraft is small, their sampling density will be reduced. Through adaptive adjustment, the simulation efficiency is significantly improved, and more accurate simulations can be provided in local "high-risk areas".

[0037] Multi-scenario and multi-mode simulation includes: multi-flight scenario simulation, simulating the performance of the aircraft under various flight environments and mission conditions, including complex terrains such as urban areas, mountainous areas, and forest areas, as well as different meteorological conditions (such as strong winds, heavy rains, lightning, etc.). In each scenario, the nature and intensity of the disturbances received by the aircraft are different. Therefore, simulations need to be carried out separately, and statistical analysis of the aircraft's responses in each environment is required; mission mode switching simulation, the mission modes of the aircraft usually include multiple stages such as climbing, cruising, descending, and maneuvering. The flight environment and disturbance characteristics in each stage are different. By setting different mission modes and flight stages, it is possible to predict and evaluate the impact of disturbances in different flight states, ensuring that the simulation covers various flight situations; extreme scenario simulation, to ensure flight safety, extreme disturbance scenario simulation is designed. For example, the performance of the aircraft when encountering strong airflows, sudden thunderstorms, or extreme wind speeds. Although the occurrence probability is low, it poses a great threat to the aircraft. Therefore, sufficient simulations are required to evaluate the aircraft's response capabilities.

[0038] Step B33: Based on factors such as the state response of the aircraft, the intensity and duration of the disturbance source, construct a multi-dimensional risk assessment index system, including: Instability probability: Calculate the probability of the aircraft becoming unstable or deviating from its trajectory in a specific environment according to the impact of the disturbance on the aircraft; Increment of energy consumption: Evaluate the impact of the disturbance on the aircraft's energy consumption, especially the additional power required by the aircraft during high-intensity airflow changes; Reduction index of controllability: Evaluate the impact of the disturbance on the accuracy and response speed of the aircraft's control system, and give a quantitative index of the reduction in controllability; Step B34: According to the evaluation results, automatically trigger corresponding warnings or emergency measures through the real-time calculated risk assessment index.

[0039] When the risk is high, the aircraft can adjust its flight path or altitude according to the control strategy to avoid entering high-risk areas; when the risk reaches the preset threshold, the system will automatically adjust the control parameters of the aircraft or recommend that the pilot take emergency measures.

[0040] The adaptive control module is used to use the adaptive control algorithm to adjust the control parameters of the aircraft in real time and output control commands; The adaptive control module includes: a model and desired output unit, a non-linear control and compensation unit, and a multi-mode adaptive control unit; The model and desired output unit is used to establish the motion model of the aircraft and design the desired output based on requirements; The establishment of the motion model of the aircraft and the design of the desired output based on requirements include: Establish the linear and nonlinear motion equations of the aircraft, and derive the motion model of the aircraft through parameters such as the mass, moment of inertia, and aerodynamic characteristics of the aircraft; In this embodiment, when flying at low altitude, considering factors such as airflow interference and terrain effects, the model design should be able to handle significant changes in altitude, flight speed, and attitude; Define a tolerance range and design the desired output according to different flight missions.

[0041] For example, in the cruise flight mode, the output of the model should maintain a stable flight state; when performing maneuvering flight or emergency obstacle avoidance tasks, the model should provide more flexible attitude control requirements. By setting the reference trajectories for different flight modes, the controller can adaptively adjust the flight behavior of the aircraft. The tolerance range is used to handle small deviations that occur during the actual flight process, ensuring the robustness and adaptability of the system.

[0042] The non-linear control and compensation unit is used to control and compensate for the non-linear characteristics of the aircraft; During low-altitude flight, the dynamic model of the aircraft often exhibits obvious non-linear characteristics, such as the non-linear relationship between lift and angle of attack, and the non-linear influence of wind speed on the flight trajectory. Non-linear factors need to be processed through specialized non-linear compensation strategies. A common non-linear compensation method is to linearize the non-linear dynamic model of the aircraft through appropriate control inputs using feedback linearization technology, and use sliding mode control technology to compensate for the control error of the aircraft or use neural networks for compensation; The multi-mode adaptive control unit is used to adaptively control the aircraft under different flight conditions and modes.

[0043] The adaptive control of the aircraft under different flight conditions and modes includes: By comparing the actual state of the aircraft with the desired output of the model, calculate the control error and analyze the dynamic changes of the control error; For example, errors in multiple dimensions such as position error, speed error, and attitude error can be calculated to comprehensively evaluate the deviation of the aircraft; Adopt adaptive gain adjustment algorithms such as L1 adaptive control and gain scheduling methods to adjust the controller gain in real time and adaptively correct the error to ensure that the aircraft can still respond quickly when subjected to disturbances or dynamic environmental changes; For example, in the presence of strong crosswinds or airflow changes, the system will increase the pitch angle control gain to enhance the stability of the aircraft; while during steady flight, the control gain can be appropriately reduced to reduce energy consumption; When a large error or unstable trend is detected, the adaptive mechanism will initiate the correction process. This process adjusts the control commands of the aircraft (such as rudder surface angle, thrust, etc.) to gradually reduce the error and restore the aircraft to the desired state. When encountering sudden disturbances, the system will quickly adjust the control strategy to minimize the adverse effects brought by the disturbances.

[0044] Based on the preprocessed flight data of the low-altitude aircraft, the current flight mode of the aircraft is detected in real time. According to the flight tasks in different modes, the appropriate control strategy is automatically switched, and control commands are output.

[0045] For example, when the aircraft is performing complex maneuvering tasks, the controller will activate the high-gain control mode, while during cruise, a stable control mode with a lower gain is adopted. Under sudden airflow disturbances, the controller needs to automatically adjust the flight path to maintain flight stability; in an emergency obstacle avoidance task, the controller of the aircraft will quickly enter a more aggressive maneuvering mode to avoid obstacles.

[0046] The execution module is used to receive the control commands from the adaptive control module, convert the control commands into actual actions, and adjust the flight attitude and trajectory of the low-altitude aircraft.

[0047] In addition, the parts of the above technical solutions provided in the embodiments of the present application that are consistent with the corresponding technical solutions in the prior art in terms of implementation principles are not described in detail to avoid excessive elaboration.

[0048] As described above in the specific embodiments, the purpose, technical solutions, and beneficial effects of the present invention are further described in detail. It should be understood that the above is only the specific embodiments of the present invention and is not used to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A low-altitude aircraft stability enhancement system based on adaptive control, characterized in that: include: Data acquisition module, data processing module, adaptive control module and execution module; The data acquisition module is used to collect the flight data of the low-altitude aircraft in real time and pre-process the collected flight data of the low-altitude aircraft; The data processing module is used to receive the flight data of the low-altitude aircraft pre-processed by the data acquisition module, and process and analyze the flight data received from the data acquisition module; The adaptive control module is used to use an adaptive control algorithm to adjust the control parameters of the low-altitude aircraft in real time and output control instructions; The execution module is used to receive control instructions from the adaptive control module and convert the control instructions into actual actions to adjust the flight attitude and trajectory of the low-altitude aircraft.

2. A low-altitude aircraft stability enhancement system based on adaptive control as claimed in claim 1, characterized in that: The data processing module includes: a disturbance perception and classification unit and a disturbance model establishment unit; The disturbance sensing and classification unit is used to sense external environmental disturbances and classify the external disturbances; The disturbance model building unit is used to estimate the state of the aircraft, and to build a disturbance source model according to the external environmental disturbance, and to evaluate the flight risk of the aircraft in combination with the real-time state of the aircraft.

3. A low-altitude aircraft stability enhancement system based on adaptive control as claimed in claim 2, characterized in that: The sensing of external environmental disturbances and classification of external disturbances include: According to the wind speed and direction of the aircraft's environment, combined with ground wind speed data and the aircraft's real-time flight trajectory, the wind field modeling technology is used to calculate the wind speed distribution around the aircraft in real time; Directional perception of airflow in front of and to the sides of the aircraft; Identify terrain obstacles and changing landforms, and sense the terrain features around the aircraft.

4. A low-altitude aircraft stability enhancement system based on adaptive control as claimed in claim 2, characterized in that: The state of the aircraft is estimated, and a disturbance source model is established according to the external environmental disturbance, and the flight risk of the aircraft is evaluated in combination with the real-time state of the aircraft, including: Based on the pre-processed flight data of the low-altitude aircraft, the dynamic state of the aircraft is calculated using a filtering algorithm to obtain the real-time state of the aircraft; Based on wind speed perception, air flow disturbance and terrain influence, external disturbance sources are modeled and identified in real time by analyzing historical data and real-time monitoring disturbance information; Based on the established disturbance source model and the real-time status of the aircraft, a simulation method based on adaptive sampling is used to evaluate the impact of external disturbances on the aircraft.

5. A low-altitude aircraft stability enhancement system based on adaptive control as claimed in claim 4, characterized in that: The real-time modeling and identification of external disturbance sources includes: Extract disturbance data features, including time domain features, frequency domain features, nonlinear dynamic features and statistical features; Based on the real-time status of the aircraft and the real-time data of the external environment, the disturbance source is modeled using a data-driven machine learning method to obtain a disturbance source model; The extracted disturbance data features are input into the disturbance source model for identification and classification.

6. A low-altitude aircraft stability enhancement system based on adaptive control as claimed in claim 4, characterized in that: Based on the established disturbance source model and in combination with the real-time status of the aircraft, a simulation method based on adaptive sampling is used to evaluate the impact of external disturbances on the aircraft, including: Conduct sensitivity analysis on the flight state of the aircraft to evaluate the sensitivity of different disturbance sources to the aircraft state; Based on the identification and classification of disturbance sources, a simulation method based on adaptive sampling is used to perform multi-scenario and multi-mode simulations on the behavior of the aircraft under different environmental disturbances to evaluate the impact range of external disturbances on the aircraft. The adaptive sampling process includes sampling data and verification frames, and the verification frames include sampling frames and data verification frames. Based on the aircraft's state response, the intensity and duration of the disturbance source, a multi-dimensional risk assessment index is constructed, including: instability probability, energy consumption increment and controllability reduction index; Based on the assessment results, corresponding warnings or emergency measures are automatically triggered through real-time calculated risk assessment indicators.

7. A low-altitude aircraft stability enhancement system based on adaptive control as claimed in claim 1, characterized in that: The adaptive control module includes: a model and expected output unit, a nonlinear control and compensation unit and a multi-mode adaptive control unit; The model and expected output unit is used to establish a motion model of the aircraft and design the expected output based on the requirements; The nonlinear control and compensation unit is used to control and compensate for the nonlinear characteristics of the aircraft; The multi-mode adaptive control unit is used to adaptively control the aircraft under different flight conditions and modes.

8. A low-altitude aircraft stability enhancement system based on adaptive control as claimed in claim 7, characterized in that: The said establishing the motion model of the aircraft and designing the expected output based on the requirements include: Establish the linear and nonlinear motion equations of the aircraft, and derive the aircraft's motion model through the aircraft's mass, moment of inertia, and aerodynamic characteristic parameters; Define tolerance ranges and design expected outputs based on different flight missions.

9. A low-altitude aircraft stability enhancement system based on adaptive control as claimed in claim 7, characterized in that: The method of adaptively controlling the aircraft under different flight conditions and modes includes: By comparing the actual state of the aircraft with the expected output of the model, the control error is calculated and the dynamic changes of the control error are analyzed; Adopt adaptive gain adjustment algorithm to adjust controller gain in real time and adaptively correct error; Based on the pre-processed flight data of the low-altitude aircraft, the current flight mode of the aircraft is detected in real time, and the appropriate control strategy is automatically switched according to the flight missions in different modes.

Images