Multi-rotor unmanned aerial vehicle paddle breaking fault rapid diagnosis and fault-tolerant stable control system and method

Abstract

The invention discloses a multi-rotor unmanned aerial vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control system and method, belongs to the technical field of unmanned aerial vehicle flight control, and aims to solve the problems that traditional broken propeller detection is high in cost and unreliable, power compensation robustness is insufficient and return flight logic is lacked. According to the system and the method, on the basis of a high-order nonlinear observation theory, rapid and accurate identification of the abnormal state of the unmanned aerial vehicle power system is realized by constructing a multi-modal signal prediction and residual evaluation system; the method effectively prevents the out-of-control, rolling and even crash of the unmanned aerial vehicle caused by power asymmetry, solves the problem that a traditional fixed control strategy is difficult to adapt to fault working conditions, and adapts to dynamic changes under complex working conditions such as hovering and cruising. Finally, closed-loop control from fault detection to safe return can be realized, the autonomous safe return capability of the unmanned aerial vehicle under the condition of the fault of the propulsion system is ensured, and the method is suitable for unmanned aerial vehicle application scenes with high reliability requirements, such as logistics transportation and inspection monitoring.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of unmanned aerial vehicle flight control, and particularly relates to a multi-rotor unmanned aerial vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control system and method based on high-order nonlinear observation theory. BACKGROUND

[0002] Multi-rotor unmanned aerial vehicles have been widely used in aerial photography, logistics, agricultural plant protection, emergency rescue and other fields due to their flexibility, vertical take-off and landing capability and low cost. However, the flight stability of the multi-rotor unmanned aerial vehicle is highly dependent on the integrity of the rotor system. Once a broken propeller fault occurs, the lift distribution will be unbalanced, which will lead to attitude loss of control and even crash, causing equipment damage and safety hazards.

[0003] In recent years, although certain progress has been made in the detection and protection technology of broken propeller fault, there are still the following key technical bottlenecks:

[0004] (1) Traditional broken propeller detection relies on the speed feedback signal of the electronic speed regulator. The fault is identified by judging whether the motor speed is lower than the preset threshold. However, this method has a significant defect: when the propeller is partially broken or falls off, the motor may still maintain a high speed, leading to a false judgment of normal operation;

[0005] (2) The traditional pseudo-inverse method or PID control algorithm does not consider the motor speed saturation limit when power is redistributed, which easily leads to overloading of the remaining rotors and causes secondary faults;

[0006] (3) The logic of emergency return and safe landing is missing. If the broken propeller is directly returned without real-time optimization of the path based on the remaining power, the unmanned aerial vehicle may crash due to motor overload during the return;

[0007] (4) In order to improve the fault tolerance, some solutions use dual-motor redundancy or folding spare propeller design. However, such hardware modification will greatly increase the weight and power consumption of the unmanned aerial vehicle, offsetting the lightweight advantage of the multi-rotor platform, and significantly increasing the manufacturing cost, which makes it difficult to popularize in the civilian market.

[0008] Therefore, how to make the multi-rotor aircraft fly safely after partial propeller failure while being compatible with existing unmanned aerial vehicle architecture and avoiding the cost burden of hardware redundancy is a technical problem to be solved in the prior art. SUMMARY

[0009] The purpose of the present application is to solve the above-mentioned problems in the prior art, and to provide a multi-rotor unmanned aerial vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control system and method. When one or more propellers of the multi-rotor unmanned aerial vehicle fail, the system can quickly respond and adjust to maintain the stable flight of the unmanned aerial vehicle and realize safe return or landing.

[0010] In order to achieve the above object, the present application adopts the technical solutions as follows:

[0011] The present application firstly discloses a multi-rotor unmanned aerial vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control system, comprising:

[0012] The monitoring module: a multi-modal signal prediction and residual evaluation system is constructed to realize accurate identification of abnormal state of the unmanned aerial vehicle power system, and the detected fault diagnosis signal is transmitted to the control module;

[0013] The control module: according to the body parameters and the received fault diagnosis signal, the control distribution matrix is dynamically adjusted, the motor compensation signal is generated, and the broken propeller fault flag is sent to the safe return module;

[0014] The safe return module: based on the multi-constraint optimization autonomous navigation and stability guarantee strategy, combined with the current position and the return point position and the set return height, the safe return route is automatically planned, and the aircraft is controlled to return according to the route.

[0015] Preferably, the aforementioned monitoring module is based on high-order nonlinear observation theory, and the adaptive convergence factor and nonlinear saturation function are built-in for filtering pretreatment of the motor original thrust command to suppress amplitude abnormal disturbance and improve fault identification accuracy.

[0016] Preferably, the autonomous navigation and stability guarantee strategy of the aforementioned safe return module includes:

[0017] (1) Based on the number of remaining motors, the maximum allowed tilt angle of the unmanned aerial vehicle after the propeller is broken is calculated according to the attitude envelope linear function ;

[0018] (2) The built-in vertical motion dynamics constraint model ensures the attitude stability under low speed working condition.

[0019] The present application also discloses a multi-rotor unmanned aerial vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control method based on the aforementioned system, comprising the following processes:

[0020] S1, the monitoring module pre-processes each motor command signal based on a discrete-time nonlinear recursive estimator to obtain a filtered thrust command estimation value:

[0021]

[0022] Wherein, is the filtered thrust command estimation value of the i-th motor in the k-th sampling period; is the original thrust command of the i-th motor in the k-th sampling period; is an adaptive convergence factor, ; is the monitoring module running frequency; is a nonlinear saturation function, used to suppress amplitude abnormal disturbances, is a slope parameter;

[0023] S2, compute the sum of filtered thrust commands of all enabled motors and the maximum thrust command while recording the motor index corresponding to the maximum thrust command

[0024]

[0025] where, is the set of enabled motor indices; is the sum of filtered thrust commands of all enabled motors; is the supremum of filtered thrust commands of all enabled motors; is the motor index corresponding to the maximum thrust command; sup(.) is the supremum operator; argsup(.) is the supremum argument index operator; is the thrust of each motor;

[0026] S3, compute the non-equilibrium measure based on information entropy weighting

[0027]

[0028] where, is the dimensionless non-equilibrium measure; is the cardinality of the set , i.e., the number of enabled motors; is the mean of thrust commands, is the variance of thrust distribution, is the natural exponential function;

[0029] S4, compute the system fault state , determined by the following time-varying differential inclusion relation:

[0030]

[0031] where, is the fault state flag, = 1 indicates a fault, = 0 indicates normal; is the time derivative of the fault state flag; is the differential inclusion operator; is the hysteresis coefficient; represents the indicator function of the set A; ​​​​​Fault upper threshold, taking 1.5; Fault lower threshold, taking 1.25; Indicates the number of motors enabled;

[0032] S5, the control module detects the system fault state When 1, first set the idle value of the unmanned aerial vehicle to zero to ensure that the unmanned aerial vehicle can quickly respond and supplement power when one or more propellers lose power, and then redistribute the power output through the control matrix to ensure that the aircraft maintains the current height and attitude stability;

[0033] S6, the safety return module automatically plans a safe return route based on the current position and return point position and the set return height, and controls the aircraft to return according to the route.

[0034] Preferably, the specific steps of the foregoing control matrix redistributing power output are as follows:

[0035] S5.1, input unmanned aerial vehicle body configuration parameters 、 、 、 , calculate the force and torque distribution matrix of the unmanned aerial vehicle :

[0036]

[0037] Wherein, is the pulling force coefficient of the first motor, is the torque coefficient of the first motor, is the distance from the first motor to the body y axis, is the distance from the first motor to the body x axis, ,

[0038] S5.2, obtain the control distribution matrix of the unmanned aerial vehicle control system by pseudo-inverse calculation :

[0039]

[0040] S5.3, calculate the control signal amount of each motor :

[0041]

[0042]

[0043]

[0044] wherein, , , are the moments acting on each axis of the UAV body, , , are the forces acting on each axis of the UAV body; , , , The relationship is:

[0045]

[0046] wherein, is the output of the UAV attitude angle rate and yaw angle rate controller, is the output of the UAV linear velocity controller;

[0047] S5.4, when the monitoring module detects that a certain motor is stalled, set the column corresponding to the motor in the force and moment distribution matrix in step S1 to zero, update the matrix F, and then continue to perform steps S5.2 and S5.3 to obtain the motor signal control quantity after re-distribution.

[0048] Further preferably, in the six-rotor UAV, when the No. 2 motor is stalled, the updated force and moment distribution matrix is:

[0049] .

[0050] This method can also be extended to the case of multiple motor failures, but the actual feasibility depends on the configuration of the UAV (such as the number of motors, layout) and the severity of the failure. For example, in a UAV with redundant motor design (such as a six-rotor or eight-rotor), even if multiple motors fail, as long as the remaining motors can provide sufficient force and moment range, the fault-tolerant control algorithm of the present application can still achieve stable control by updating the force and moment distribution matrix. However, if too many motors fail, it may result in insufficient control capability and be unable to fully restore stability.

[0051] Further preferably, the aforementioned step S6 includes the following sub-steps:

[0052] S6.1, according to the attitude envelope linear function, calculate the maximum allowed tilt angle of the UAV after the propeller is broken ;

[0053] S6.2, calculate the vertical motion dynamics under stability constraints to ensure attitude stability under low speed conditions;

[0054] S6.3, the return path generation is converted into a constrained optimization, through a nonlinear constrained optimization and stability algorithm, to ensure the autonomous safe return capability of the UAV under propulsion system failure, and to realize the unification of fault tolerance and navigation safety.

[0055] Preferably, the aforementioned maximum allowed tilt angle The calculation process is as follows:

[0056]

[0057] wherein, is the nominal maximum attitude angle; Nr represents the number of fault-free motors, and N represents the total number of motors; is the power index, representing the influence of system redundancy; is the fault attenuation coefficient, reflecting the multi-fault effect.

[0058] Further preferably, the aforementioned vertical motion dynamics equation is:

[0059]

[0060]

[0061]

[0062] wherein, is the angular rate related adaptive convergence gain function; is the rate of change of height, which is not more than 0.5 m / s; is the basic convergence rate coefficient; is the angular velocity adjustment gain coefficient; is an S-shaped saturation function, ensuring smooth and bounded output; is the body angular rate vector; is the Euclidean norm; is the minimum angular velocity threshold for maintaining attitude stability; is the angular velocity normalized reference value; is a hyperbolic tangent function, providing smooth saturation characteristics; h is the current flight height; is the target height of the return point; is the height convergence region scale parameter. The dynamics equation ensures that the vertical velocity always satisfies the stability constraint condition through a nonlinear feedback mechanism, and when the angular velocity norm approaches the minimum threshold, the convergence gain is automatically adjusted to avoid the system entering an unstable region.

[0063] Further preferably, the aforementioned constrained optimization is:

[0064]

[0065] wherein, is the three-dimensional trajectory of the UAV; is the instantaneous yaw angle; is the yaw angle at the time of failure occurrence; is the yaw keeping weight coefficient;

[0066] The sufficient condition for the safe return of the UAV is guaranteed by the following simultaneous inequalities:

[0067]

[0068]

[0069]

[0070] wherein, is the maximum flight speed set by the UAV, is the minimum torque required to maintain stability; is the maximum torque provided by the remaining motors; is the air density related parameter; is the moment of inertia tensor of the UAV; , is the design tolerance parameter. The above nonlinear constraint optimization and stability algorithm ensures the autonomous safe return capability of the UAV under the failure of the propulsion system, and realizes the unification of fault tolerance and navigation safety.

[0071] The present application has the advantages of:

[0072] (1) The broken propeller fault rapid response and attitude stabilization system of the present application is based on high-order nonlinear observation theory. By constructing a multi-modal signal prediction and residual evaluation system, compared with traditional single-mode detection, the present application first eliminates false signals such as electromagnetic interference and load fluctuation through a discrete-time nonlinear recursive estimator combined with an adaptive convergence factor and a nonlinear saturation function, ensuring that the thrust command estimation value is more accurate; then by calculating the thrust sum, the maximum thrust and the corresponding motor index, the abnormal motor can be quickly located, overcoming the problem of difficult identification of fault motor when multiple motors are running in parallel; further, the information entropy weighted non-equilibrium degree measure can realize quantitative evaluation of the fault, finally providing reliable fault basis for subsequent fault-tolerant control, realizing rapid and accurate identification of abnormal state of the UAV power system, avoiding fault missed detection / misdiagnosis, and adapting to dynamic changes under complex working conditions such as hovering and cruising.

[0073] (2) The monitoring module transmits the detected fault signal to the control module, when detecting the failure of a specific motor, the control module can immediately set the corresponding column in the distribution matrix to zero, and recalculate the control signal of the remaining motor, quickly compensate for the power loss, maintain the attitude stability, and lay the foundation for the subsequent safe operation (return / home) of the unmanned aerial vehicle. The system can respond within a very short time when the motor or propeller fails, so that the power output can be optimally distributed according to the state of the remaining healthy motor, actively maintaining the required attitude and height, the whole process does not need human intervention, and is automatically completed by the control algorithm deployed in the flight control system, rather than passive response to loss of control, effectively preventing the unmanned aerial vehicle from losing control, rolling or even crashing due to power asymmetry, which is crucial for sudden failure, greatly reducing the risk of accidents, and solving the problem that the traditional fixed control strategy is difficult to adapt to fault conditions.

[0074] (3) The present application further realizes the safe return of the fault unmanned aerial vehicle based on the autonomous navigation and stability guarantee strategy of multi-constraint optimization, realizes the closed-loop control from fault detection to safe return, the process is coherent and operable, ensures the autonomous safe return ability of the unmanned aerial vehicle under the condition of propulsion system failure, realizes the unification of fault tolerance and navigation safety: avoids the risk of crashing caused by attitude over-limit or too fast descent during return, and realizes autonomous return after failure, greatly improves the control stability and return safety under the condition of broken propeller failure. BRIEF DESCRIPTION OF DRAWINGS

[0075] Figure 1 It is a schematic diagram of the frame structure of the multi-rotor unmanned aerial vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control system of the present application;

[0076] Figure 2 It is a schematic diagram of the logic structure of the multi-rotor unmanned aerial vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control method of the present application;

[0077] Figure 3 It is a motor output PWM signal time history curve diagram after motor failure of the present application;

[0078] Figure 4 It is a desired height and actual height time history curve diagram after motor failure of the present application;

[0079] Figure 5 It is a desired vertical speed and actual vertical speed time history curve diagram after motor failure of the present application;

[0080] Figure 6 It is a desired roll angle and actual roll angle time history curve diagram after motor failure of the present application;

[0081] Figure 7 It is a desired pitch angle and actual pitch angle time history curve diagram after motor failure of the present application; Detailed Implementation

[0082] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0083] Example 1

[0084] See Figure 1 This embodiment discloses a rapid diagnosis and fault-tolerant stability control system for rotor breakage faults in multi-rotor unmanned aerial vehicles (UAVs). The system consists of a monitoring module, a control module, and a safe return-to-home module.

[0085] The monitoring module employs a motor fault detection method based on high-order nonlinear observation theory. By constructing a multimodal signal prediction and residual evaluation system, it achieves accurate identification of abnormal states in the UAV's power system and transmits the detected fault diagnosis signals to the control module. The control module then dynamically adjusts the control allocation matrix based on the airframe parameters and the received fault diagnosis signals, generates motor compensation signals, and sends a propeller failure flag to the safe return-to-home module. Finally, the safe return-to-home module calculates the maximum attitude angle of the UAV during flight using the number of faulty motors and the total number of motors, while limiting the maximum descent rate. Combining the current position, the return-to-home point position, and the set return-to-home altitude, it automatically plans a safe return-to-home route and controls the aircraft to return along the route.

[0086] The typical workflow of this system is as follows: when the monitoring module detects a fault in the motor power system through flight status feedback, it sends a fault diagnosis signal to the control module; the control module automatically performs a control matrix reconstruction process based on the fault diagnosis signal, outputs compensation commands to maintain attitude stability, and notifies the safe return module to update the number of remaining motors; the safe return module calculates the maximum tilt angle and feeds back the attitude constraints to the control module, enabling the UAV to safely return and land, ending the flight mission.

[0087] Example 2

[0088] See Figure 2 This embodiment discloses the application of the rapid diagnosis and fault-tolerant stable control method for propeller breakage based on the aforementioned system in a hexarotor unmanned aerial vehicle (UAV). The specific method includes the following steps:

[0089] S1. The monitoring module preprocesses the command signals of each motor based on a discrete-time nonlinear recursive estimator to obtain the filtered thrust command estimate:

[0090]

[0091] in, The filtered thrust command estimate for the i-th motor in the k-th sampling period; This represents the original thrust command for the i-th motor during the k-th sampling period; is an adaptive convergence factor, ; is a monitoring module running frequency; is a nonlinear saturation function for suppressing abnormal amplitude disturbance, , is a slope parameter.

[0092] S2, compute the sum of filtered thrust commands of all enabled motors and the maximum thrust command while recording the motor index corresponding to the maximum thrust command :

[0093]

[0094] where, is the set of enabled motor indices; is the sum of filtered thrust commands of all enabled motors; is the supremum of filtered thrust commands of all enabled motors; is the motor index corresponding to the maximum thrust command; sup(.) is the supremum operator; argsup(.) is the supremum argument index operator; is the thrust command of each motor.

[0095] S3, compute the non-equilibrium degree measure based on information entropy weighting :

[0096]

[0097] where, is the dimensionless non-equilibrium degree measure; is the cardinality of the set , i.e., the number of enabled motors; is the mean of thrust commands, ; is the variance of thrust distribution, ; is the natural exponential function.

[0098] S4, compute the system fault state , determined by the following time-varying differential inclusion relation:

[0099]

[0100] where, is the fault state flag, =1 indicates a fault, =0 indicates normal; is the time derivative of the fault state flag; is the differential inclusion operator; is a hysteresis coefficient; denotes the indicator function of the set A; denotes the upper threshold of failure, and takes 1.5; denotes the lower threshold of failure, and takes 1.25; denotes the number of enabled motors.

[0101] S5, the control module detects a system failure state is 1, first set the idle value of the unmanned aerial vehicle to zero to ensure that the unmanned aerial vehicle can quickly respond and supplement power when one or more propellers lose power, and then redistribute the power output through the control matrix to ensure that the aircraft maintains the current height and attitude stability.

[0102] Specifically, the specific steps of the control matrix to redistribute the power output are as follows:

[0103] S5.1, input the unmanned aerial vehicle body configuration parameters , , , , calculate the force and torque distribution matrix of the unmanned aerial vehicle :

[0104]

[0105] wherein, is the tension coefficient of the i th motor, is the torque coefficient of the i th motor, is the distance from the i th motor to the y axis of the body, is the distance from the i th motor to the x axis of the body, . Specific to the embodiment, the No. 2 motor fails to rotate, and the updated force and torque distribution matrix is:

[0106] .

[0107] .

[0108] S5.2, obtain the control distribution matrix of the unmanned aerial vehicle control system by pseudo-inverse calculation :

[0109]

[0110] S5.3, calculate the control signal amount of each motor :

[0111] ​​​

[0112]

[0113]

[0114] wherein, , , are the moments acting on the UAV body along each axis respectively, , , are the forces acting on the UAV body along each axis respectively; , , , The relationship is:

[0115]

[0116] wherein, is the output of the UAV attitude angle rate and yaw angle rate controller, is the output of the UAV linear velocity controller;

[0117] S5.4, when the monitoring module detects that a certain motor is stalled, the force and moment distribution matrix in step S1 is set to zero in the column corresponding to the motor, the matrix F is updated, and then steps S5.2 and S5.3 are continued to obtain the motor signal control quantity after re-distribution.

[0118] S6, the safety return module automatically plans a safe return route based on the multi-constraint optimization autonomous navigation and stability guarantee strategy, combines the current position and the return point position, and sets the return height to automatically plan a safe return route, and controls the aircraft to return according to the route.

[0119] Specifically, step S6 includes the following sub-steps:

[0120] S6.1, according to the attitude envelope linear function, the maximum allowed tilt angle of the UAV after the propeller is broken is calculated according to the remaining motor quantity :

[0121]

[0122] wherein, is the nominal maximum attitude angle; Nr represents the number of fault-free motors, and N represents the total number of motors; is the power index, which represents the influence of system redundancy; is the fault attenuation coefficient, which reflects the multi-fault effect.

[0123] ​S6.2, calculate the vertical motion dynamics under stability constraints to ensure attitude stability in low speed conditions:

[0124]

[0125]

[0126]

[0127] where, is an angular rate dependent adaptive convergence gain function; is the rate of change of altitude, maximum not more than 0.5 m / s; is the basic convergence rate coefficient; is the angular velocity adjustment gain coefficient; is an S-shaped saturation function to ensure smooth and bounded output; is the body angular rate vector; is the Euclidean norm; is the minimum angular velocity threshold to maintain attitude stability; is the angular velocity normalized reference value; is the hyperbolic tangent function, providing smooth saturation characteristics; h is the current flight altitude; is the target altitude of the home point; is the altitude convergence region scale parameter.

[0128] S6.3, convert the return path generation into a constrained optimization, through nonlinear constraint optimization and stability algorithm, to ensure the autonomous safe return ability of the unmanned aerial vehicle in the case of propulsion system failure, realize the unification of fault tolerance and navigation safety.

[0129] Specifically, the constrained optimization is:

[0130]

[0131] where, is the three-dimensional trajectory of the unmanned aerial vehicle; is the instantaneous heading angle; is the heading angle at the time of failure; is the heading keeping weight coefficient;

[0132] The sufficient condition for the safe return of the unmanned aerial vehicle is guaranteed by the following simultaneous inequalities:

[0133]

[0134]

[0135]

[0136] wherein, the minimum torque required to maintain stability; the maximum torque provided by the remaining motors; the air density related parameters; the UAV moment of inertia tensor; , the design tolerance parameters.

[0137] The method of the present application is verified: Figure 3 the motor output PWM signal time history curve after motor failure, Figure 4 the expected height and actual height time history curve after motor failure, Figure 5 the expected vertical speed and actual vertical speed time history curve after motor failure, combined with the three graphs, it can be seen that the multi-rotor UAV of the embodiment can maintain stable height and vertical speed after the failure of the No. 2 motor. Figure 6 the expected roll angle and actual roll angle time history curve after motor failure, Figure 7 the expected pitch angle and actual pitch angle time history curve after motor failure, combined with the two graphs, it can be seen that the multi-rotor UAV can maintain stable pitch angle and roll angle after the failure of the motor.

[0138] In summary, the multi-rotor fault rapid response and attitude stabilization system and method of the present application can respond within a very short time after the motor or propeller fails, so that the power output can be optimally distributed according to the state of the remaining healthy motor, actively maintaining the required attitude and height. The entire process does not require human intervention and is completely automatic, completed by the control algorithm deployed in the flight control system, rather than passive response to loss of control, effectively preventing loss of control, rolling or even crashing of the UAV due to power asymmetry. It is crucial for sudden failure and greatly reduces the risk of accidents, solving the problem that traditional fixed control strategies are difficult to adapt to fault conditions. And realize the closed-loop control from fault detection to safe return, the process is coherent and operable, ensuring the autonomous safe return capability of the UAV under the condition of propulsion system failure, realizing the unity of fault tolerance and navigation safety: avoiding the risk of crashing due to attitude exceeding limit or descending too fast during return, and realizing autonomous return after failure, greatly improving the control stability and return safety under the condition of broken propeller failure.

[0139] The basic principles, main features and advantages of the present application are shown and described above. Those skilled in the art should understand that the above examples do not limit the present application in any form, and any technical solution obtained by equivalent substitution or equivalent transformation falls within the scope of the present application.

Claims

1. A multi-rotor unmanned aerial vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control system, characterized in that, Comprise: Monitoring module: build a multimodal signal prediction and residual evaluation system, realize the accurate identification of abnormal state of unmanned aerial vehicle power system, and deliver the detected fault diagnosis signal to the control module; Control module: dynamically adjust the control distribution matrix according to the machine parameters and the received fault diagnosis signal, generate motor compensation signal, and send the fault flag of broken propeller to the safe return module; Safe return module: based on the autonomous navigation and stability guarantee strategy of multi-constraint optimization, combined with the current position and the position of the return point and the set return height, automatically plan a safe return route, and control the aircraft to return according to the route.

2. The multi-rotor unmanned vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control system according to claim 1, characterized in that, The monitoring module is based on high-order nonlinear observation theory, and the module is built-in with adaptive convergence factor and nonlinear saturation function, which is used to filter and pretreat the original thrust instruction of motor, so as to suppress the amplitude abnormal disturbance and improve the fault identification accuracy.

3. The multi-rotor unmanned vehicle broken propeller fault rapid diagnosis and fault-tolerant stable control system according to claim 1, characterized in that, The autonomous navigation and stability guarantee strategy of the safe return module includes: (1) Based on the remaining number of motors, the maximum allowed tilt angle of the unmanned aerial vehicle after the propeller is broken is calculated according to the attitude envelope linear function ; (2) Built-in vertical motion dynamics constraint model to ensure the attitude stability under low speed working condition.

4. A method for quick diagnosis and fault-tolerant stable control of a multi-rotor unmanned aerial vehicle based on the system of claim 1, characterized in that, The process includes the following steps: S1, the monitoring module based on discrete time nonlinear recursive estimator pretreats each motor instruction signal to obtain the filtered thrust instruction estimation value: ， wherein, is the filtered thrust command estimate for the ith motor in the kth sample period; is the raw thrust command for the ith motor in the kth sample period; is an adaptive convergence factor, ; is the monitoring module operating frequency; is a non-linear saturation function used to dampen amplitude anomalies, , is a slope parameter; S2, calculate the sum of all current filter thrust instructions of enabled motors and the maximum thrust instruction while recording the motor index corresponding to the maximum thrust instruction : ， wherein, is the set of enabled motor indices; is the sum of filtered thrust commands for the enabled motors; is the upper bound of filtered thrust commands for all enabled motors; is the motor index corresponding to the maximum thrust command; sup(.) is the upper bound operator; argsup(.) is the upper bound argument index operator; is the thrust of each motor; S3、calculating a non-equilibrium degree measure based on information entropy weighting : ， wherein, is a dimensionless non-equilibrium measure; is the cardinality of the set of active motors, i.e. the number of motors enabled; is the mean of the thrust commands, ; is the variance of the thrust profile, ; is the natural exponential function; S4, computing system failure state is determined by the following time-varying differential inclusion: ， wherein is a fault status flag, = 1 indicates a fault, = 0 indicates normal; is a time derivative of the fault status flag; is a differential inclusion operator; is a hysteresis coefficient; denotes an indicator function of the set A; denotes a fault upper threshold, taken as 1.5; denotes a fault lower threshold, taken as 1.25; denotes the number of active motors; S5、control module detects system fault state When the value is 1, first set the idle value of the unmanned aerial vehicle to zero to ensure that when the unmanned aerial vehicle loses the power of one or more propellers, other motors can quickly respond and supplement power, and then redistribute the power output through the control matrix to ensure that the aircraft maintains the current height and attitude stability; S6, the safe return module based on the autonomous navigation and stability guarantee strategy of multi-constraint optimization, combined with the current position and the position of the return point and the set return height, automatically plans a safe return route, and controls the aircraft to return according to the route.

5. The method of claim 4, wherein, The specific steps of the control matrix re-distribution power output are as follows: S5.1, inputting unmanned aerial vehicle body configuration parameters , , , , calculating the force and moment distribution matrix of the unmanned aerial vehicle : ， wherein, is the drag coefficient of the th motor, is the torque coefficient of the th motor, is the distance from the th motor to the body y-axis, is the distance from the th motor to the body x-axis, , S5.2, obtain the control allocation matrix of the UAV control system by pseudo-inverse calculation : ， S5.3, determining the control signal quantity for each motor : ， ， ， wherein, , , are the moments acting on the respective axes of the UAV body, , , are the forces acting on the respective axes of the UAV body; , , , the relationship is: ， wherein, is an output of the UAV attitude angle rate and yaw angle rate controller, is an output of the UAV linear velocity controller; S5.4, when the monitoring module detects that a certain motor is stalled, the force and torque distribution matrix in step S1 is set to zero in the column corresponding to the motor, the matrix F is updated, and then steps S5.2 and S5.3 are continued to obtain the motor signal control quantity after the redistribution. S5.4, when the monitoring module detects that a certain motor is stalled, the force and torque distribution matrix in step S1 is set to zero in the column corresponding to the motor, the matrix F is updated, and then steps S5.2 and S5.3 are continued to obtain the motor signal control quantity after the redistribution.

6. The method of claim 5, wherein, When the 2nd motor is stopped, the updated force and torque distribution matrix is: 。 7. The method of claim 4, wherein, The step S6 includes the following sub-steps: S6.1, in combination with the remaining motor quantity, the maximum allowed tilt angle of the UAV after the propeller is broken is calculated according to the attitude envelope linear function ; S6.2, calculate the vertical motion dynamics under stability constraint to ensure the attitude stability under low speed working condition; S6.3, convert the return path generation into a constrained optimization, and through the nonlinear constraint optimization and stability algorithm, ensure the autonomous safe return ability of unmanned aerial vehicle under the condition of propulsion system failure, realize the unification of fault tolerance and navigation safety.

8. The method of claim 7, wherein, the maximum allowed tilt angle The calculation process is as follows: ， wherein, is the nominal maximum attitude angle; Nr denotes the number of fault-free motors, N denotes the total number of motors; is the power exponent, which characterizes the influence of the system redundancy; is the fault attenuation coefficient, which reflects the multiple fault effect.

9. The method of claim 7, wherein, The vertical motion dynamics equation is: ， ， ， wherein, is an angular rate dependent adaptive convergence gain function; is a height rate of change, maximum not exceeding 0.5 m / s; is a base convergence rate coefficient; is an angular velocity regulation gain coefficient; is a sigmoid saturation function, ensuring smooth bounded output; is the body angular rate vector; is the Euclidean norm; is a minimum angular velocity threshold to maintain attitude stability; is an angular velocity normalized reference value; is a hyperbolic tangent function, providing a smooth saturation characteristic; h is the current flight height; is the home point target height; is a height convergence region scale parameter.

10. The method of claim 7, wherein, The constrained optimization is: ， wherein, is a three-dimensional trajectory of the UAV; is an instantaneous yaw angle; is a yaw angle at the time of failure occurrence; is a yaw keeping weight coefficient; The sufficient condition of unmanned aerial vehicle safe return is guaranteed by the following simultaneous inequalities: ， ， ， wherein, maximum flight speed of the drone, minimum torque required to maintain stability; maximum torque provided to the remaining motors; air density related parameters; moment of inertia tensor of the drone; , design tolerance parameters.

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