Immersive evaluation method and system for anti-crosswind disturbance flight control efficiency of unmanned aerial vehicle
By constructing a dynamic wind field simulation and navigation deception technology indoors, the controllability problem of crosswind disturbance assessment for UAVs was solved, and high-fidelity assessment and optimization of UAV flight control systems were achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- 浣江实验室
- Filing Date
- 2026-01-28
- Publication Date
- 2026-05-08
AI Technical Summary
Existing technologies lack a means to conduct high-fidelity evaluation of the closed-loop control performance against crosswind disturbances in the free flight state of UAVs under safe, controllable, and repeatable conditions.
Indoor dynamic wind field simulation and multi-sensor deception technology are constructed. Through dynamic disturbance generation unit, perception deception unit and high-precision state perception unit, combined with central integrated control and evaluation unit, the flight environment of UAV under lateral gusts is simulated, and its robustness and trajectory keeping capability are quantified.
It enables accurate and repeatable quantitative testing of UAV flight control systems under crosswind disturbances, provides comprehensive performance evaluation indicators, and supports the optimization and verification of flight control systems.
Smart Images
Figure CN121995901A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of unmanned aerial vehicle (UAV) testing technology, specifically to a UAV anti-crosswind flight control performance evaluation system. Background Technology
[0002] With the widespread application of drones in logistics delivery, urban air transport, and precision inspection, their flight safety and mission reliability face severe challenges. Lateral gusts are a common and significantly hazardous disturbance source in low-altitude airspace, easily causing drones to deviate from their planned routes, increasing the risk of collisions, and even triggering instability. Therefore, assessing and improving the ability of drone flight control systems to resist lateral disturbances is crucial.
[0003] Currently, the assessment of a drone's crosswind resistance mainly relies on the following methods: Natural wind field outdoor testing: Test flights are conducted in outdoor locations with suitable wind conditions. This method has a fundamental flaw: natural wind fields are uncontrollable, non-repeatable, and it is difficult to accurately measure their instantaneous velocity and spatial distribution, resulting in highly random test results that cannot be used as a reliable basis for performance comparison and algorithm optimization.
[0004] Traditional wind tunnel constrained testing involves fixing the UAV to a wind tunnel force measurement platform, applying steady-state or quasi-steady-state crosswinds, and measuring its aerodynamic forces and moments. While this method can obtain some aerodynamic parameters, it completely deprives the UAV of its free flight state and autonomous control response process, making it impossible to evaluate its complete "perception-decision-control" closed-loop dynamic performance, especially its trajectory holding and autonomous recovery capabilities.
[0005] Pure numerical simulation: Evaluation is conducted through coupled computational fluid dynamics and flight mechanics simulation. This method is limited by model fidelity and struggles to accurately reproduce the complex logic of real flight control software, sensor noise, and actuator dynamics. It suffers from the "model confidence" problem, and its conclusions often require physical verification.
[0006] Therefore, existing technologies lack a means to conduct high-fidelity evaluation of the closed-loop control performance against crosswind disturbances in UAVs during free flight under safe, controllable, measurable, and repeatable conditions. Summary of the Invention
[0007] The technical problem solved by this invention is to provide a system for quantitatively evaluating the robustness, trajectory keeping ability and recovery efficiency of UAV flight control system under lateral gust disturbances in a controlled indoor environment by using high dynamic wind field simulation and multi-sensor deception technology, so as to solve the problems mentioned in the background art.
[0008] The technical problem solved by this invention is achieved by the following technical solution: a UAV anti-crosswind flight control performance evaluation system, including a dynamic disturbance generation unit, a perception deception unit, and a high-precision state perception unit for constructing a test space, and a central integrated control and evaluation unit for running core software. The test space constructs a test environment that integrates dynamic wind field simulation, GNSS / inertial navigation deception, and high-precision motion tracking, so that the UAV can completely reproduce the outdoor scenario of encountering crosswinds at the perception and dynamics levels. The aforementioned central integrated control and evaluation unit includes: a test scenario management module and a signal synchronization and mapping engine, and executes synchronization and mapping logic methods, wherein the row synchronization and mapping logic methods include: S1. Generate the desired signal; S2, Disturbance Triggering and Wind Field Control; S3. The performance quantification and evaluation module compares and analyzes the actual trajectory data of the UAV recorded by the high-precision state perception unit with the preset benchmark route to calculate the anti-disturbance performance index.
[0009] As a further aspect of the present invention: The dynamic disturbance generation unit includes a programmable wind field generation device composed of a multi-fan array, which is arranged on one side of the test space. The device can generate a lateral wind field with a set intensity, direction, spatial profile and time sequence (including gusts, gradual winds and turbulence) within a millisecond response time according to control commands.
[0010] As a further aspect of the present invention: The perception deception unit includes a programmable multi-constellation GNSS signal simulator and an inertial measurement simulation interface; the GNSS signal simulator is used to generate positioning and velocity signals that reflect the UAV's desired / command trajectory; the inertial measurement simulation interface is optionally used to inject simulated inertial sensor data into the UAV to cooperate with the GNSS signals to form a complete navigation deception environment.
[0011] As a further aspect of the present invention: The high-precision state perception unit consists of a set of high-frame-rate, low-latency optical motion capture cameras arranged around the test space. It is used to measure the real position, attitude and velocity of the UAV in three-dimensional space in real time with sub-millimeter accuracy, as the benchmark true value for performance evaluation.
[0012] As a further aspect of the present invention: The test scenario management module is used to define test cases, including the initial flight state of the UAV (such as level flight speed and altitude), lateral gust disturbance mode (such as start time, wind speed, duration, and spatial gradient), and the baseline flight path to be maintained.
[0013] As a further aspect of the present invention: The signal synchronization and mapping engine is used to receive feedback data from the high-precision state perception unit in real time.
[0014] As a further aspect of the present invention: The generated desired signal is: based on a preset reference route, a continuous desired GNSS / inertial navigation signal is generated and sent to the perception deception unit, so that the UAV flight control system "believes" that it is flying undisturbed along the predetermined route.
[0015] As a further aspect of the present invention: The disturbance triggering and wind field control are as follows: at a preset test time, the engine sends a command to the dynamic disturbance generation unit to trigger a specific mode of lateral gust; at the same time, the engine dynamically calculates and controls the wind field according to the expected forward flight speed of the UAV, so that the relative wind speed vector acting on the physical UAV is completely equivalent to the aerodynamic load under the simulated scenario of "the UAV encountering a sudden crosswind while flying along the flight path".
[0016] As a further aspect of the present invention: The core indicators of the disturbance rejection performance include: Maximum yaw distance, under the influence of disturbance, is the maximum deviation of the UAV's true trajectory from the reference route in the lateral direction. This value directly characterizes the static accuracy of the flight control system in suppressing disturbances. Steady-state recovery error is the remaining lateral deviation between the UAV trajectory and the reference flight path after the disturbance ends and the trajectory tends to stabilize. This value characterizes the steady-state accuracy of the system and its ability to eliminate residual errors. Recovery time is the time elapsed from the start of the disturbance to the point during which the UAV's lateral deviation enters and remains within a specified tolerance band centered on the baseline flight path. This value characterizes the system's dynamic response and rapid recovery capability. Trajectory overshoot and oscillation frequency, the number of times the lateral deviation exceeds the maximum value during the recovery process, and the decay characteristics are used to evaluate the damping characteristics and stability of the system.
[0017] Compared with existing technologies, the beneficial effects of this invention are: an immersive evaluation method and system for the flight control performance of unmanned aerial vehicles (UAVs) against crosswind disturbances. This system constructs an "immersive" test environment indoors that integrates dynamic wind field simulation, GNSS / inertial navigation deception, and high-precision motion tracking, enabling the UAV to completely replicate the outdoor scenario of encountering crosswinds at the perception and dynamics levels. This allows for precise and repeatable quantitative testing of the flight control system's anti-disturbance performance.
[0018] High-fidelity and immersive testing: By generating dynamic wind fields and consistent navigation deception signals that match the flight status in real time, a "perception-dynamics" closed-loop environment that is highly consistent with real outdoor gusts is created for the UAV flight control system, and the test results are real and reliable.
[0019] Excellent repeatability and comparability: Disturbance wind fields and test conditions can be precisely programmed and repeated, completely solving the randomness problem of outdoor testing, and allowing fair and consistent performance comparisons of different control algorithm parameters for the same UAV or different UAV platforms.
[0020] A comprehensive quantitative evaluation system: It not only measures the final yaw distance, but also obtains dynamic process indicators such as recovery time and overshoot, providing multi-dimensional and detailed data support for controller tuning and robustness optimization of the flight control system.
[0021] Safe, efficient, and low-cost: All tests are conducted in a safe and controlled indoor environment, without being restricted by weather or airspace. Tests can be performed quickly and in batches under extreme wind conditions, greatly accelerating R&D iteration and reducing verification costs and risks. Attached Figure Description
[0022] Figure 1 This is a schematic diagram of the UAV anti-crosswind flight test of the present invention. Detailed Implementation
[0023] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below with reference to specific illustrations.
[0024] like Figure 1 As shown, this embodiment provides a UAV anti-crosswind flight control performance evaluation system, including: Dynamic disturbance generation unit: This includes a programmable wind field generation device consisting of a multi-fan array, which is arranged on one side or the side of the test space. This device can generate a lateral wind field with a set intensity, direction, spatial profile, and timing (including gusts, gradual winds, and turbulence) within a millisecond-level response time according to control commands.
[0025] The perception deception unit includes a programmable multi-constellation GNSS signal simulator and an inertial measurement simulation interface. The GNSS signal simulator is used to generate positioning and velocity signals that reflect the UAV's desired / command trajectory; the inertial measurement simulation interface is optionally used to inject simulated inertial sensor data into the UAV to form a complete navigation deception environment in conjunction with the GNSS signals.
[0026] High-precision state perception unit: It consists of a group of high frame rate, low latency optical motion capture cameras arranged around the test space. It is used to measure the real position, attitude and velocity of the UAV in three-dimensional space in real time with sub-millimeter accuracy, as the benchmark true value for performance evaluation.
[0027] Central Integrated Control and Evaluation Unit: A computer system that runs the core software, including: Test Scenario Management Module: Define test cases, including the initial flight state of the drone (such as level flight speed and altitude), lateral gust disturbance mode (such as start time, wind speed, duration, and spatial gradient), and the baseline flight path to be maintained.
[0028] Signal synchronization and mapping engine: As the core of the system, it receives feedback data from the high-precision state sensing unit in real time and executes the following synchronization and mapping logic: Desired signal generation: Based on a preset reference route, a continuous desired GNSS / inertial navigation signal is generated and sent to the perception deception unit, so that the UAV flight control system "believes" that it is flying undisturbed along the predetermined route.
[0029] Disturbance Triggering and Wind Field Control: At a preset test moment, the engine sends a command to the dynamic disturbance generation unit to trigger a specific mode of lateral gust. Simultaneously, the engine dynamically calculates and controls the wind field based on the desired forward speed of the UAV, ensuring that the relative wind speed vector acting on the physical UAV is completely equivalent to the aerodynamic load under the simulated scenario of "UAV encountering a sudden crosswind while flying along the flight path".
[0030] Performance Quantitative Evaluation Module: Based on the real trajectory data of the UAV recorded by the high-precision state perception unit, it compares and analyzes the data with a preset benchmark route to calculate a series of anti-disturbance performance indicators. The core indicators include: Maximum yaw distance: The maximum lateral deviation of the UAV's actual trajectory from the reference path under disturbance. This value directly characterizes the static accuracy of the flight control system in suppressing disturbances.
[0031] Steady-state recovery error: The remaining lateral deviation between the UAV trajectory and the reference flight path after the disturbance ends and the trajectory tends to stabilize. This value characterizes the system's steady-state accuracy and its ability to eliminate residual errors.
[0032] Recovery time: The time elapsed from the initial application of the disturbance until the UAV's lateral deviation enters and remains within a specified tolerance band centered on the baseline flight path. This value characterizes the system's dynamic response and rapid recovery capability.
[0033] Trajectory overshoot and number of oscillations: During the recovery process, the number of times the lateral deviation exceeds the maximum value and the decay characteristics are used to evaluate the damping characteristics and stability of the system.
[0034] The present invention will now be described with reference to a preferred embodiment; System Implementation: A multi-fan array with a response time of less than 100 milliseconds is used as the dynamic disturbance generation unit, capable of generating instantaneous crosswinds of up to 15 m / s. A high-precision UWB and optical fusion positioning system is employed as the state awareness unit, with a positioning update rate greater than 200 Hz. The GNSS simulator supports real-time trajectory injection.
[0035] Test configuration: The drone was set to fly horizontally forward at a speed of 10 m / s. The lateral gust disturbance was configured as follows: at the 5th second of flight, a step gust with a peak speed of 8 m / s and a duration of 2 seconds was applied 2 meters to the side of the drone.
[0036] Execution process: The UAV enters simulated cruise under the guidance of GNSS signals. At the 5th second, the wind farm device instantly activates the corresponding fan group, generating an 8m / s crosswind. The UAV flight control system relies solely on the received (undisturbed) GNSS signals and the actual airframe IMU data (sensing the angular velocity and acceleration caused by the crosswind) to make stability control decisions.
[0037] Data analysis: Motion capture data shows that after being hit by a crosswind, the maximum lateral yaw distance of the UAV was 2.3 meters. It then began to recover under the control of the flight controller, with a recovery time of 4.5 seconds, and the final steady-state residual error was 0.15 meters. This data can be directly used to evaluate the crosswind resistance performance of the flight control algorithm and guide the optimization of its PID parameters or advanced control laws.
[0038] This invention provides a revolutionary, standardized, laboratory-level testing solution for evaluating the disturbance rejection performance of UAV flight control systems, which is of great significance for promoting UAV airworthiness certification and performance improvement.
[0039] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection of the present invention is defined by the appended claims and their equivalents. It should be noted that, in this document, the use of relational terms such as "first" and "second" is merely used to distinguish one entity or operation from another, and does not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
Claims
1. A system for evaluating the flight control effectiveness of unmanned aerial vehicles (UAVs) against crosswind disturbances, characterized in that: It includes a dynamic disturbance generation unit, a perception deception unit, and a high-precision state perception unit for constructing the test space, as well as a central integrated control and evaluation unit for running the core software. The test space constructs a test environment that integrates dynamic wind field simulation, GNSS / inertial navigation deception, and high-precision motion tracking, enabling the UAV to completely reproduce the outdoor scenario of encountering lateral gusts at the perception and dynamics levels. The aforementioned central integrated control and evaluation unit includes: a test scenario management module and a signal synchronization and mapping engine, and executes synchronization and mapping logic methods, wherein the row synchronization and mapping logic methods include: S1. Generate the desired signal; S2, Disturbance Triggering and Wind Field Control; S3. The performance quantification and evaluation module compares and analyzes the actual trajectory data of the UAV recorded by the high-precision state perception unit with the preset benchmark route to calculate the anti-disturbance performance index.
2. The UAV anti-crosswind flight control performance evaluation system according to claim 1, characterized in that: The dynamic disturbance generation unit includes a programmable wind field generation device composed of a multi-fan array, which is arranged on one side of the test space; the device can generate a lateral wind field with a set intensity, direction, spatial profile and timing in a millisecond-level response time according to control commands.
3. The UAV anti-crosswind flight control performance evaluation system according to claim 1, characterized in that: The perception deception unit includes a programmable multi-constellation GNSS signal simulator and an inertial measurement simulation interface; the GNSS signal simulator is used to generate positioning and velocity signals that reflect the UAV's desired / command trajectory; the inertial measurement simulation interface is optionally used to inject simulated inertial sensor data into the UAV to cooperate with the GNSS signals to form a complete navigation deception environment.
4. The UAV anti-crosswind flight control performance evaluation system according to claim 1, characterized in that: The high-precision state perception unit consists of a set of high-frame-rate, low-latency optical motion capture cameras arranged around the test space. It is used to measure the real position, attitude and velocity of the UAV in three-dimensional space in real time with sub-millimeter accuracy, as the benchmark true value for performance evaluation.
5. The UAV anti-crosswind flight control performance evaluation system according to claim 1, characterized in that: The test scenario management module is used to define test cases, including the initial flight state of the UAV, the lateral gust disturbance mode, and the baseline flight path to be maintained.
6. The UAV anti-crosswind flight control performance evaluation system according to claim 5, characterized in that: The signal synchronization and mapping engine is used to receive feedback data from the high-precision state perception unit in real time.
7. The UAV anti-crosswind flight control performance evaluation system according to claim 6, characterized in that: The generated desired signal is: based on a preset reference route, a continuous desired GNSS / inertial navigation signal is generated and sent to the perception deception unit, so that the UAV flight control system "believes" that it is flying undisturbed along the predetermined route.
8. The UAV anti-crosswind flight control performance evaluation system according to claim 7, characterized in that: The disturbance triggering and wind field control are as follows: at a preset test time, the engine sends a command to the dynamic disturbance generation unit to trigger a specific mode of lateral gust; at the same time, the engine dynamically calculates and controls the wind field according to the expected forward flight speed of the UAV, so that the relative wind speed vector acting on the physical UAV is completely equivalent to the aerodynamic load under the simulated scenario of "the UAV encountering a sudden crosswind while flying along the flight path".
9. The UAV anti-crosswind flight control performance evaluation system according to claim 8, characterized in that: The disturbance rejection performance indicators include: Maximum yaw distance, under the influence of disturbance, is the maximum deviation of the UAV's true trajectory from the reference route in the lateral direction. This value directly characterizes the static accuracy of the flight control system in suppressing disturbances. Steady-state recovery error is the remaining lateral deviation between the UAV trajectory and the reference flight path after the disturbance ends and the trajectory tends to stabilize. This value characterizes the steady-state accuracy of the system and its ability to eliminate residual errors. Recovery time is the time elapsed from the start of the disturbance to the point during which the UAV's lateral deviation enters and remains within a specified tolerance band centered on the baseline flight path. This value characterizes the system's dynamic response and rapid recovery capability. Trajectory overshoot and oscillation frequency, the number of times the lateral deviation exceeds the maximum value during the recovery process, and the decay characteristics are used to evaluate the damping characteristics and stability of the system.