A Compound-Wing UAV Rotor Fault Location and Power Reconfiguration System and Method

Abstract

The present invention discloses a system and method for rotor fault location and power reconstruction of a composite wing UAV, which belongs to the technical field of fault-tolerant control of UAVs. The system includes a data acquisition module, a fault verification module, and a power redistribution module. First, according to the relationship between the physical layout of the rotor and the attitude dynamics, a rotor fault-attitude change direction symbol mapping table is established to identify the fault type; after satisfying the symbol matching, a dynamic threshold energy verification function is constructed for judgment, and a fault dual verification model of symbol matching and energy verification is used to determine whether the rotor has actually failed; the control allocation matrix is dynamically reconstructed according to the verified fault rotor position, and power compensation is provided by coordinating the normal rotor to achieve stable flight attitude control. The present invention provides an effective method for reducing the sensor false alarm rate and fault response time, so that the control system can quickly respond to restore the flight attitude when the rotor suddenly fails, ensuring stable attitude control and significantly improving flight safety.

Description

Technical Field

[0001] The present invention relates to a composite-wing UAV rotor fault location and power reconstruction system and method, which is applicable to a six-rotor composite-wing UAV and belongs to the technical field of UAV fault-tolerant control. Background Art

[0002] In recent years, with breakthroughs in flight control technology, composite-wing UAVs, with their unique advantages of combining the characteristics of both rotorcraft and fixed-wing aircraft, have gradually become important application platforms in civilian fields such as logistics and transportation, emergency rescue, and environmental monitoring. Composite-wing UAVs possess dual-mode flight capabilities, including vertical take-off and landing and high-speed cruising, enabling them to flexibly respond to a variety of complex mission scenarios. However, while composite-wing structures offer significant advantages in improving UAV fault tolerance, they also increase the probability of rotor failure. According to statistics, rotor failure accounts for 68% of UAV flight accidents, and traditional fault location methods suffer from high positioning delays and insufficient compensation efficiency when faced with sudden rotor failures, seriously restricting flight safety.

[0003] Chinese invention patent publication number CN108445760A proposes a fault-tolerant control method for a quadrotor drone based on an adaptive fault estimation observer. However, its adaptive fault estimation observer relies on sensor data input. If the sensor noise is large (such as speed signal fluctuations), it may cause fault estimation deviations, reduce the reliability of fault-tolerant control, and further cause position failures or delayed responses, affecting flight stability and safety.

[0004] In view of the above reasons, how to achieve rapid and accurate fault location and power reconstruction when a rotor failure occurs has become a key issue that needs to be urgently solved in the flight control technology of composite-wing UAVs. Summary of the Invention

[0005] In order to address the shortcomings of the existing technology, the purpose of the present invention is to provide a composite wing UAV rotor fault location and power reconstruction system and method. This method addresses the problems in the existing technology such as high false alarm rate and large fault location delay caused by sensor noise interference, which affect the flight safety of the UAV. Through a fault double verification model, the method quickly and accurately identifies the alarm and locates the rotor fault position, and completes adaptive power compensation based on the dynamic reconstruction control allocation matrix, that is, the control allocation matrix is dynamically reconstructed to coordinate other rotors for power compensation, so as to quickly restore the flight attitude when the rotor suddenly fails, ensure the stability of attitude control, and significantly improve flight safety.

[0006] In order to achieve the above objectives, the present invention adopts the following technical solutions:

[0007] The present invention first discloses a composite wing UAV rotor fault location and power reconstruction system, comprising:

[0008] Data acquisition module: responsible for collecting the status data of the UAV and transmitting this data to the fault verification module;

[0009] Fault Verification Module: This module is responsible for organizing the collected status data and calculating the accumulated attitude change and dynamic threshold energy function to implement dual fault verification. Once verified, the module transmits the fault occurrence time and location to the power redistribution module.

[0010] Power redistribution module: Based on the verified fault location, a time-varying attenuation coefficient matrix is introduced to dynamically reconstruct the control distribution matrix, and then power compensation is provided through the normal rotor to ensure stable control under rotor fault conditions.

[0011] Preferably, the aforementioned status data includes rotor speed, torque change and command tracking status.

[0012] The present invention also discloses a method for locating rotor faults and reconfiguring power of a composite wing UAV, which is used to implement the aforementioned system and includes the following steps:

[0013] S1. Based on the relationship between the rotor physical layout and attitude dynamics, a rotor fault-attitude change direction symbol mapping table is established. The accumulated attitude change symbols within the window period are calculated in real time and matched with the symbol mapping table to identify the fault type.

[0014] S2. After the symbol matching is satisfied, a dynamic threshold energy verification function is constructed to determine whether the rotor has actually failed, using a fault dual verification model of symbol matching and energy verification.

[0015] S3. Dynamically reconstruct the control allocation matrix based on the verified faulty rotor position, provide power compensation by coordinating the normal rotor, and thus achieve stable control of the flight attitude.

[0016] Preferably, the aforementioned compound wing UAV is a six-rotor UAV, and the rotor layout is a four-in-front and two-in-rear configuration, wherein rotors 1-4 are symmetrically distributed in front of the center of gravity, and rotors 5 and 6 are located on both sides behind the center of gravity.

[0017] More preferably, the aforementioned rotor fault and attitude change direction sign matching process includes:

[0018] In the case of rotor failure, the dynamic relationship between torque change and attitude change is established:

[0019] ,

[0020] ,

[0021] in, for The cumulative change of the UAV's roll angle, pitch angle and yaw angle within a cycle; is the inverse matrix of the moment of inertia matrix, 、 、 are the moments of inertia of the three axes respectively; For the The change of three-axis torque when a rotor fails; For the front The cumulative attitude angle of each cycle; is the maximum continuous detection time window, is the calculation period;

[0022] Each rotor fault corresponds to a unique three-axis attitude angle change direction symbol combination. The cumulative three-axis attitude change during the rotor failure window is matched with the symbol table:

[0023] ,

[0024] ,

[0025] ,

[0026] in, is a symbolic function; is the Kronecker function. When the three axis symbols match at the same time, the symbol matching flag is ,otherwise .

[0027] As a preference, a rotor fault is confirmed only when full symbol matching is satisfied within a time window of at least five consecutive sampling cycles; otherwise, it is considered a sensor false alarm, which can improve the accuracy of fault prediction.

[0028] Preferably, when the attitude change after the rotor failure is detected and matches the symbol mapping table, dynamic threshold energy verification is also required:

[0029] ,

[0030] ,

[0031] ,

[0032] ,

[0033] in, is the Euclidean norm; It is the instruction tracking status flag. When the posture deviation exceeds the threshold When is 1; is the adaptive threshold coefficient; is the benchmark for attitude angle change; is the maximum allowed attitude angle of the UAV; is the target attitude angle of the current control instruction; is the sensitivity coefficient; is the fault rotor speed; is the maximum speed.

[0034] More preferably, in the aforementioned step S2, when it is detected that any rotor speed is lower than or exceeds 15% of the target speed for 150 ms, the fault double verification process is started.

[0035] Further preferably, in step S3, the control allocation matrix represents a mapping relationship between the control instructions and the rotor speed, which satisfies:

[0036] ,

[0037] ,

[0038] Among them, each constant is the coefficient obtained by cubic fitting of the relationship between rotor throttle and thrust. is the rotational speed of the six rotors; is the functional relationship between the control command and the total pitch / torque; is the rotor collective pitch, rolling moment, pitching moment and yaw moment; It is the rotor collective pitch control command, roll control command, pitch control command and yaw control command; is the Moore-Penrose pseudo-inverse of the control allocation matrix, expressed as:

[0039] ,

[0040] Time decay coefficient matrix ,

[0041] ,

[0042] in, For the The time when the rotor failure occurred; is the fault time constant.

[0043] The present invention is beneficial in that:

[0044] (1) The rotor fault location and power reconstruction system and method of the composite wing UAV of the present invention constructs a dual fault verification model based on a symbol mapping table and a dynamic threshold energy function. The model identifies the fault type by matching the accumulated attitude angle changes within a time window with a preset symbol mapping table. At the same time, the dynamic threshold energy function is combined to quantify the fault degree, which can effectively reduce the sensor false alarm rate and realize fault detection and precise positioning of the six-rotor composite wing UAV under complex working conditions.

[0045] (2) The present invention introduces a piecewise linear continuous attenuation mechanism to dynamically reconstruct the entire control allocation matrix in the event of a sudden fault. It can effectively identify the alarm information, quickly locate the rotor fault position, and promptly coordinate other rotors for power compensation to ensure the stability of attitude control.

[0046] (3) Compared with the traditional method that relies on iterative correction of the controller, the method of the present invention can greatly reduce the amount of calculation, further improve the fault response speed, shorten the fault location time, and improve the accuracy of positioning, thereby improving flight safety; it overcomes the problems of the existing technology such as the lack of practicality of complex optimization algorithms under the condition of limited onboard resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a module division diagram of a composite wing UAV rotor fault location and power reconstruction system according to embodiment 1 of the present invention;

[0048] Figure 2 Schematic diagram of a method for rapid rotor positioning and power reconstruction based on a fault dual verification model according to embodiment 2 of the present invention;

[0049] Figure 3 This is a rotor distribution diagram of the six-rotor composite-wing UAV according to Example 2 of the present invention;

[0050] Figure 4 Graphs showing fault determination results under three conditions: normal maneuvering, external disturbance, and rotor failure according to Example 2 of the present invention;

[0051] Figure 5 This is a diagram showing the rotational speed changes of the six rotors after rotor 1 fails in Example 2 of the present invention;

[0052] Figure 6 2 is a schematic diagram comparing attitude control when the rotor of the UAV of Example 2 of the present invention fails and only relies on controller iterative correction and reconstruction control allocation. DETAILED DESCRIPTION

[0053] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] Example 1

[0055] This embodiment discloses a composite wing UAV rotor fault location and power reconstruction system, the structure of which is as follows: Figure 1 As shown in the figure, the system includes an acquisition module, a fault verification module and a power redistribution module, wherein the acquisition module is responsible for collecting the status data of the UAV, including the rotor speed, torque change and command tracking status, and transmitting these data to the fault verification module; the fault verification module is responsible for organizing the collected status data, calculating the accumulated attitude change and the dynamic threshold energy function, and implementing double verification of the fault. When the verification is passed, the module transmits the fault occurrence time and fault location to the power redistribution module; and the power redistribution module introduces the time-varying attenuation coefficient matrix according to the fault location obtained by verification to dynamically reconstruct the control distribution matrix, and then provides power compensation through the normal rotor to ensure stable control under rotor fault conditions.

[0056] Example 2

[0057] This embodiment discloses a method for quickly locating rotor failures and reconstructing power of a composite wing UAV, which is used to implement the above-mentioned system. The composite wing UAV is a six-rotor UAV with a structure such as Figure 3 As shown, the rotor layout is a four-in-front and two-in-back configuration, where rotors 1-4 are symmetrically distributed in front of the center of gravity, and rotors 5 and 6 are located on both sides behind the center of gravity. The relevant physical parameters of the drone are as follows: , the number of time windows , calculation cycle , maximum speed , the maximum allowable attitude angle , attitude deviation threshold , sensitivity coefficient , fault time constant .

[0058] like Figure 2 As shown, the present invention uses a fault dual verification model to identify faults in the speed measurement information of the ESC, quickly locates the rotor position after the fault is detected, and achieves stable attitude control by dynamically reconstructing the control allocation matrix. Specifically, the following steps are included:

[0059] S1. Based on the relationship between the rotor physical layout and attitude dynamics, a rotor fault-attitude change direction symbol mapping table is established. The attitude change symbols accumulated during the real-time calculation window period are matched with the symbol mapping table to identify the fault type.

[0060] The specific process of matching rotor faults with attitude change direction signs includes:

[0061] In the case of rotor failure, the dynamic relationship between torque change and attitude change is established:

[0062] ,

[0063] ,

[0064] in, for The cumulative change of the UAV's roll angle, pitch angle and yaw angle within a cycle; is the inverse matrix of the moment of inertia matrix, 、 、 are the moments of inertia of the three axes respectively; For the The change of three-axis torque when a rotor fails; For the front The cumulative attitude angle of each cycle; is the maximum continuous detection time window; is the calculation cycle.

[0065] Each rotor fault corresponds to a unique three-axis attitude angle change direction symbol combination. The cumulative three-axis attitude change during the rotor failure window is matched with the symbol table:

[0066] ,

[0067] ,

[0068] , ,

[0069] in, is a symbolic function; For the Kronecker function, when the three axis symbols match at the same time, the symbol matching flag is ,otherwise .

[0070] Because composite-wing drones have large moments of inertia and delayed attitude responses, a rotor fault is confirmed only when full symbol matching is achieved within a time window of five consecutive sampling cycles; otherwise, the sensor is considered to have issued a false alarm. This reduces the impact of environmental factors on the results.

[0071] S2. After satisfying the symbol matching, a dynamic threshold energy verification function is constructed for judgment. Through the fault dual verification model of symbol matching and energy verification, it is determined whether the rotor has actually failed.

[0072] The specific process of dynamic threshold energy verification is as follows:

[0073] ,

[0074] ,

[0075] ,

[0076] ,

[0077] in, is the Euclidean norm; It is the instruction tracking status flag. When the posture deviation exceeds the threshold When is 1; is the adaptive threshold coefficient; is the benchmark for attitude angle change; is the maximum allowed attitude angle of the UAV; is the target attitude angle of the current control instruction; is the sensitivity coefficient; is the fault rotor speed; is the maximum speed.

[0078] In step S2, if any rotor speed is detected to be below or above 15% of the target speed for a sustained period of 150 ms, the fault double verification process is initiated. This fault double verification model, which uses symbol matching to identify the fault type and dynamic thresholds to quantify the fault intensity, can effectively reduce sensor false alarm rates and enable fault detection and precise location in complex operating conditions for hexacopter composite wing drones.

[0079] S3. Dynamically reconstruct the control allocation matrix based on the verified faulty rotor position, provide power compensation by coordinating the normal rotor, and thus achieve stable control of the flight attitude.

[0080] The control allocation matrix specifically represents the mapping relationship between the control command and the rotor speed, which satisfies:

[0081] ,

[0082] ,

[0083] Among them, each constant is the coefficient obtained by cubic fitting of the relationship between rotor throttle and thrust. is the rotational speed of the six rotors; is the functional relationship between the control command and the total pitch / torque; is the rotor collective pitch, rolling moment, pitching moment and yaw moment; It is the rotor collective pitch control command, roll control command, pitch control command and yaw control command; is the Moore-Penrose pseudo-inverse of the control allocation matrix, expressed as:

[0084] ,

[0085] Time decay coefficient matrix ,

[0086] ,

[0087] For the The time when the rotor failure occurred; is the fault time constant. Time-varying attenuation coefficient matrix In the event of a sudden failure, the entire control allocation matrix can be dynamically reconstructed by introducing a piecewise linear continuous decay mechanism. This method effectively avoids the control variable mutation problem caused by traditional Boolean switching strategies, while also overcoming the lack of practicality of complex optimization algorithms when onboard resources are limited.

[0088] Finally, the stability control performance after the failure of rotor 1 is simulated and verified using the Simulink simulation environment to verify the effectiveness of the method of the present invention and ensure its robustness and safety. Figure 4 The fault judgment results of three different situations, namely, UAV maneuvering flight, external interference and rotor failure, are given. The results show that the method of the present invention can quickly and accurately identify rotor failure. Figure 5 The changes in the rotational speed of each rotor after rotor 1 fails are given. Figure 6 The changes in attitude control after rotor 1 fails, which are achieved by relying solely on iterative adjustment of the controller and reconstruction of the control allocation mechanism, are compared, further proving that the method of the present invention can achieve rapid attitude stabilization within a few seconds of rotor failure, and that the system and method are effective in improving the response speed to rotor failures.

[0089] In summary, the present invention constructs a dual fault verification model based on a symbol mapping table and a dynamic threshold energy function. By actively reconstructing the control allocation mechanism and introducing a piecewise linear continuous attenuation mechanism, the response speed after rotor failure is further improved without changing the controller structure, thereby realizing fault detection and precise positioning of the six-rotor composite wing UAV under complex working conditions, and timely coordinating other rotors for power compensation to ensure the stability of attitude control, thereby improving flight safety.

[0090] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the above embodiments do not limit the present invention in any form, and any technical solutions obtained by equivalent replacement or equivalent transformation fall within the scope of protection of the present invention.

Claims

1. A method for rotor fault location and power reconstruction of a composite wing UAV, characterized in that: The steps include: S1. Based on the relationship between the rotor physical layout and attitude dynamics, a rotor fault-attitude change direction symbol mapping table is established. The accumulated attitude change symbols within the window period are calculated in real time and matched with the symbol mapping table to identify the fault type. S2. After satisfying the symbol match, a dynamic threshold energy verification function is constructed for judgment. Through the fault dual verification model of symbol matching and energy verification, if it is detected that any rotor speed is lower than or higher than 15% of the target speed for 150 ms continuously, the fault dual verification process is initiated to determine whether the rotor has actually failed. The specific process of the dynamic threshold energy verification is as follows: ， ， ， ， in, is the Euclidean norm; It is the instruction tracking status flag. When the posture deviation exceeds the threshold When is 1; is the adaptive threshold coefficient; is the benchmark for attitude angle change; is the maximum allowed attitude angle of the UAV; is the target attitude angle of the current control instruction; is the sensitivity coefficient; is the fault rotor speed; is the maximum speed; S3. Dynamically reconstruct the control allocation matrix based on the verified faulty rotor position, provide power compensation by coordinating with the normal rotor, and thus achieve stable control of the flight attitude; The control allocation matrix represents the mapping relationship between the control command and the rotor speed, which satisfies: ， ， Among them, each constant is the coefficient obtained by cubic fitting of the relationship between rotor throttle and thrust. is the rotational speed of the six rotors; is the functional relationship between the control command and the total pitch / torque; is the rotor collective pitch, rolling moment, pitching moment and yaw moment; It is the rotor collective pitch control command, roll control command, pitch control command and yaw control command; is the Moore-Penrose pseudo-inverse of the control allocation matrix, expressed as: ， Time attenuation coefficient matrix , ， in, For the The time when the rotor failure occurred; is the fault time constant.

2. The method for locating rotor faults and reconfiguring power for a composite-wing UAV according to claim 1, characterized in that: The composite wing UAV is a six-rotor UAV with a rotor layout of four in front and two in the back, wherein rotors 1-4 are symmetrically distributed in front of the center of gravity, and rotors 5 and 6 are located on both sides behind the center of gravity.

3. The method for locating rotor faults and reconfiguring power for a composite-wing UAV according to claim 1, characterized in that: The rotor fault and attitude change direction sign matching process includes: In the case of rotor failure, the dynamic relationship between torque change and attitude change is established: ， ， in, for The cumulative change of the UAV's roll angle, pitch angle and yaw angle within a cycle; is the inverse matrix of the moment of inertia matrix, 、 、 are the moments of inertia of the three axes respectively; For the The change of three-axis torque when a rotor fails; For the front The cumulative attitude angle of each cycle; is the maximum continuous detection time window, is the calculation period; Each rotor fault corresponds to a unique three-axis attitude angle change direction symbol combination. The cumulative three-axis attitude change during the rotor failure window is matched with the symbol table: ， ， ， ， in, is a symbolic function; is the Kronecker function. When the three axis symbols match at the same time, the symbol matching flag is ,otherwise .

4. The method for locating rotor faults and reconfiguring power for a composite-wing UAV according to claim 3, characterized in that: A rotor fault is confirmed only if full symbol matching is satisfied within a time window of at least five consecutive sampling cycles; otherwise, it is considered a sensor false alarm.

5. The method for locating rotor faults and reconfiguring power for a composite-wing UAV according to claim 1, characterized in that: When the attitude change after detecting rotor failure matches the symbol mapping table, dynamic threshold energy verification is also required: ， ， ， ， in, is the Euclidean norm; It is the instruction tracking status flag. When the posture deviation exceeds the threshold When is 1; is the adaptive threshold coefficient; is the benchmark for attitude angle change; is the maximum allowed attitude angle of the UAV; is the target attitude angle of the current control instruction; is the sensitivity coefficient; is the fault rotor speed; is the maximum speed.

6. A composite wing UAV rotor fault location and power reconstruction system, characterized in that: The method for locating rotor faults and reconfiguring power of a composite wing UAV according to any one of claims 1 to 5 is implemented, comprising: Data acquisition module: responsible for collecting the status data of the UAV and transmitting this data to the fault verification module; Fault Verification Module: This module is responsible for organizing the collected status data and calculating the accumulated attitude change and dynamic threshold energy function to implement dual fault verification. Once verified, the module transmits the fault occurrence time and location to the power redistribution module. Power redistribution module: Based on the verified fault location, a time-varying attenuation coefficient matrix is introduced to dynamically reconstruct the control distribution matrix, and then power compensation is provided through the normal rotor to ensure stable control under rotor fault conditions.

7. The composite wing UAV rotor fault location and power reconstruction system according to claim 6, characterized in that: The status data includes rotor speed, torque change and command tracking status.

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