A design method and system for a fault-tolerant controller for a quadrotor drone

Abstract

The embodiment of the present application provides a method and system for designing a fault-tolerant controller for a quad-rotor drone. The method includes building a target motion model for reflecting the flight status of the drone in combination with the fault distribution and the rotor speed of the drone, taking into account the impact of the fault on the rotor; setting a relative threshold and a fixed threshold that change synchronously with the control input of the model; adjusting the control input of the model through the relative threshold and the fixed threshold in combination with the event triggering characteristics, so that the flight trajectory of the drone approaches the preset target flight trajectory; in the adjustment process, the backstepping method is used to recursively design the corresponding virtual control law and the actual control law, so that the model approaches asymptotic stability. The implementation of this method can ensure accurate tracking control of the quad-rotor drone when multiple faults occur simultaneously.

Description

Technical Field

[0001] The present application relates to the field of UAV control technology, and more specifically, to a design method and system for a fault-tolerant controller for a quad-rotor UAV. Background Art

[0002] In recent years, with the rapid development of technologies in the fields of communications, computers, and networks, the related topics of quadrotor drones have become a new research direction in the field of automatic control. Quadrotor drones can complete various tasks in a wide range of complex environments at a low cost and with high flexibility, which has continuously improved the status of quadrotor drones in military and civilian fields. Therefore, in order to better utilize quadrotor drones to assist in completing various tasks, the control issues of quadrotor drones have attracted more and more attention from researchers.

[0003] The current mainstream quadcopter attitude stabilization or tracking methods mainly include control structure, backstepping method, theory-based control method and adaptive control. Although the existing control methods can improve the stability of the drone during flight, these control methods are based on the control method of the quadcopter system without faults. As the drone is running at high speed, with the aging of components or damage to the drive motor and propeller, it is easy to cause the drive motor-propeller system to fail, causing the quadcopter to be unable to complete the specified task, or even lose control and cause safety problems. This requires that when discussing the control issues of the quadcopter, it is necessary to ensure that it can achieve ideal performance under normal conditions and fault conditions.

[0004] At present, the traditional FDA architecture usually adopts the fault detection, isolation and evaluation (FDIE algorithm) mechanism to provide diagnostic information of the faults that have occurred. In the early stage, fault detection and isolation may help to avoid more serious faults, and the detailed fault information generated during the fault diagnosis process is very valuable for state-based maintenance and redundancy management. However, the overall performance of such fault-tolerant control methods is directly affected by the time delay between the occurrence of faults and fault isolation, as well as the accuracy of the FDIE algorithm. When multiple faults occur at the same time, the accuracy of the FDIE algorithm will be difficult to guarantee, and there is a problem of low control accuracy. Summary of the invention

[0005] The purpose of the embodiments of the present application is to provide a design method and system for a fault-tolerant controller for a quad-rotor drone, which can ensure accurate tracking and control of the quad-rotor drone when multiple faults occur simultaneously.

[0006] The present application also provides a method for designing a fault-tolerant controller for a quad-rotor drone, comprising the following steps:

[0007] S1. Considering the impact of the fault on the rotor, combined with the fault distribution and the rotor speed of the UAV, a target motion model is constructed to reflect the flight status of the UAV;

[0008] S2, setting a relative threshold value that changes synchronously with the control input of the model, and a fixed threshold value;

[0009] S3, combining the event triggering characteristics, adjusting the control input of the model through the relative threshold and the fixed threshold, so that the flight trajectory of the UAV approaches the preset target flight trajectory;

[0010] S4. During the adjustment process, the backstepping method is used to recursively design the corresponding virtual control law and the actual control law so that the model approaches asymptotic stability.

[0011] In a second aspect, an embodiment of the present application further provides a design system for a fault-tolerant controller of a quad-rotor drone, characterized in that the system includes a motion model building module, a threshold setting module, a control input adjustment module, and a backstepping recursive design module, wherein:

[0012] The motion model building module is used to build a target motion model for reflecting the flight status of the UAV by combining the fault distribution and the rotor speed of the UAV while considering the impact of the fault on the rotor;

[0013] The threshold setting module is used to set a relative threshold value that changes synchronously with the control input of the model, and a fixed threshold value;

[0014] The control input adjustment module is used to adjust the control input of the model through the relative threshold and the fixed threshold in combination with the event triggering characteristics, so that the flight trajectory of the UAV approaches the preset target flight trajectory;

[0015] The backstepping recursive design module is used to recursively design the corresponding virtual control law and the actual control law using the backstepping method during the adjustment process, so as to make the model approach asymptotic stability.

[0016] In a third aspect, the present application provides a readable storage medium, which includes a design method program for a fault-tolerant controller for a quadrotor drone. When the design method program for a fault-tolerant controller for a quadrotor drone is executed by a processor, the steps of the method described in any one of the above items are implemented.

[0017] From the above, it can be seen that the design method, system and readable storage medium of a fault-tolerant controller for a quad-rotor drone provided in the embodiment of the present application take into account the impact of the fault on the rotor, simulate the fault through the fault parameter, and adopt the event trigger mechanism of comprehensive relative threshold control and fixed threshold control. Compared with the traditional control method, it can minimize the number of event triggers, while ensuring the control effect, it can also save communication resources. Under the condition of ensuring the event trigger mechanism, the corresponding virtual control law and actual control law are recursively designed by backstepping method, which can make the system achieve asymptotic stability and ensure accurate tracking control when multiple faults occur simultaneously in the quad-rotor drone.

[0018] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or be understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0020] Figure 1 A flow chart of a method for designing a fault-tolerant controller for a quad-rotor drone provided in an embodiment of the present application;

[0021] Figure 2 This is a schematic diagram of the simulation debugging results based on the design method of the fault-tolerant controller of the quadrotor drone;

[0022] Figure 3 A structural schematic diagram of a design system for a fault-tolerant controller for a quadrotor drone provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0024] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0025] Please refer to Figure 1 , Figure 1 1 is a flow chart of a method for designing a fault-tolerant controller for a quadrotor drone in some embodiments of the present application. The method comprises the following steps:

[0026] Step S1, considering the impact of the fault on the rotor, combining the fault distribution and the rotor speed of the UAV, constructing a target motion model for reflecting the flight status of the UAV.

[0027] Step S2, setting a relative threshold value and a fixed threshold value that change synchronously with the control input of the model.

[0028] Step S3, combining the event triggering characteristics, adjusting the control input of the model through the relative threshold and the fixed threshold, so that the flight trajectory of the UAV approaches the preset target flight trajectory.

[0029] Step S4: During the adjustment process, the backstepping method is used to recursively design the corresponding virtual control law and the actual control law so that the model approaches asymptotic stability.

[0030] From the above, it can be seen that the design method of a fault-tolerant controller for a quad-rotor drone disclosed in the present application takes into account the impact of the fault on the rotor, simulates the fault through the fault parameter, and adopts the event trigger mechanism of comprehensive relative threshold control and fixed threshold control. Compared with the traditional control method, it can minimize the number of event triggers, while ensuring the control effect, it can also save communication resources. Under the condition of ensuring the event trigger mechanism, the corresponding virtual control law and actual control law are recursively designed by backstepping method, which can make the system achieve asymptotic stability and ensure accurate tracking control when multiple faults occur simultaneously in the quad-rotor drone.

[0031] In one embodiment, in step S1, considering the influence of the fault on the rotor, combining the fault distribution and the rotor speed of the UAV, constructing a target motion model for reflecting the flight status of the UAV, including:

[0032] Step S11, defining corresponding fault parameters in combination with the impact of the fault on the rotor, wherein the fault parameters are defined in the following manner:

[0033]

[0034] Among them, α s Indicates the degree of fault. is the defined fault parameter.

[0035] Specifically, when In other cases, it means that the rotor has a fault during operation and will cause a corresponding degree of thrust loss.

[0036] Step S12, determining the thrust and torque generated synchronously according to the fault parameters, the fault distribution and the rotor speed of the drone, wherein the thrust and torque are defined in the following manner:

[0037]

[0038] Where U represents the thrust, which is the control input of the model; τ φ ,τ θ ,τ ψ It represents the angular acceleration of the drone in the three directions of yaw, pitch and roll, I4 represents the 4×4 unit matrix, M represents the mapping matrix between thrust and torque and speed, Λ s represents the preset fault distribution matrix, Ω i (i=1,2,3,4) is the rotation speed of the four rotors of the drone.

[0039] Specifically, and because the thrust and torque of the rotor are proportional to the square of the rotational speed, in the current embodiment, the thrust and torque of the quadrotor drone are further determined in combination with the definition method of the above fault parameters.

[0040] In one embodiment, Λ s represents the fault distribution matrix, s=1...4 represents the rotor number of the fault. For example, when s=1, Λ1=diag{1,0,0,0}; when s=2, Λ2=diag{0,1,0,0}, and other cases can be deduced by analogy, which is not limited in the present embodiment.

[0041] Step S13, substituting the determined thrust and torque into the dynamic model of the UAV to perform model conversion, and obtaining a target motion model for reflecting the flight status.

[0042] Specifically, the definition of the UAV's dynamic model includes:

[0043]

[0044] It should be noted that since the various parameters in the above formula have been defined later, no further explanation will be given at present.

[0045] The above embodiment takes into account the impact of the fault on the rotor, simulates the fault through fault parameters, and adopts adaptive control to eliminate the impact of the fault, thereby ensuring accurate tracking and control of the UAV when multiple faults occur simultaneously, and further improving the control effect.

[0046] In one embodiment, in step S13, the target motion model is defined in the following manner:

[0047]

[0048]

[0049]

[0050]

[0051] in, x1=[p z ,φ,θ,ψ] T ,x2=[v z ,p,q,r] T , [φ,θ,ψ] represent the yaw angle, pitch angle and roll angle respectively, [p,q,r] represent the angular acceleration of the above three angles respectively; p z represents the inertial vertical position, v z Indicates inertial vertical velocity; Rη (φ, ψ) represents the association matrix that relates the generated angular velocity to the Euler angular velocity, m represents the weight of the drone, and g represents the generated gravitational acceleration; J = diag{J x ,J y ,J z} represents the inertia matrix of the body, c d Indicates the drag coefficient of the aircraft; is the derivative of parameter x1, is the derivative of parameter x2.

[0052] In the above embodiment, a second-order Newton-Lagrangian model is used to construct a dynamic model of the UAV, wherein the rotation of the quad-rotor UAV is characterized by a rotation matrix, which can better describe the posture of the UAV and more concisely implement the calculation of the rotation speed of each rotor of the UAV from the control input of the UAV.

[0053] In one embodiment, in step S3, adjusting the control input of the model by the relative threshold and the fixed threshold so that the flight trajectory of the drone approaches a preset target flight trajectory includes:

[0054] Step S31, obtaining the actual control input of the model, and comparing the actual control input with a preset switching threshold control parameter.

[0055] In the current embodiment, the actual control input of the model is further The control strategy is then compared with the preset switching threshold control parameter D to determine when to switch the control strategy.

[0056] For example, in determining , the current strategy will be switched to the relative threshold strategy. By associating the control input of the UAV with the relative threshold, when it is determined that the control input of the UAV is relatively large, it means that the UAV is far away from the target trajectory. Since the main task at this time is to make the UAV catch up to the vicinity of the target flight trajectory first, there is no need for fine control.

[0057] It should be noted that because the value of the control input is large, the corresponding relative threshold value is also large. At this time, the trigger threshold is relatively high and the number of triggers is relatively small. In this way, the drone can track the target at a faster tracking speed.

[0058] In other cases, it will switch to a fixed threshold strategy. When it is determined that the drone is approaching the target flight trajectory, as the control input decreases, a fixed threshold will be used to achieve high-precision control by increasing the number of controls to ensure improved control effects.

[0059] It should be noted that the fixed threshold value can be a positive constant. In the current embodiment, its specific value is not limited. In different embodiments, it can be combined with specific practical conditions and simulated and debugged to determine the appropriate value. The purpose is to ensure the control effect of the drone near the target flight trajectory, while reducing the number of triggers and saving communication resources.

[0060] Step S32, when it is determined that the flight trajectory of the UAV is far away from the target trajectory and the actual control input is greater than or equal to the preset switching threshold control parameter, based on the relative threshold, the actual control input and the interval difference between the control input set at different times, determine whether the first trigger moment is reached.

[0061] Specifically, when determining the actual control input of the model When it is greater than or equal to the preset switching threshold control parameter D, the relative threshold and the interval difference between the actual control input and the control input set at different times will be further compared. The size between.

[0062] In one embodiment, when determining whether the first trigger moment is reached, the implementation method that can be referred to includes: when determining the relative threshold value obtained in the first target moment is greater than or equal to the interval difference existing in the moment When the first target moment is used as the first trigger moment, the actual control input of the model will be adjusted based on the design control input set at the first trigger moment.

[0063] Step S33, when it is determined that the first trigger moment is reached, based on the control input set in the first trigger moment, the actual control input of the model is adjusted so that the UAV quickly approaches the target trajectory.

[0064] Specifically, when it is determined that the first triggering time t k+1 It will be further determined at this time t k+1 The design control input Ω is set in . Then, the actual control input of the model is realized based on the design control input Ω Updates, even if Among them, in the non-triggering time, that is, t∈[t,t k+1 ), the actual control input will remain unchanged, that is, not updated, until the trigger time t k+1 That is, t = t k+1 When the trigger time t k+1 The design control input Ω set in is updated.

[0065] Step S34, when it is determined that the UAV is near the target trajectory and the actual control input is less than the preset switching threshold control parameter, based on the fixed threshold, the actual control input and the interval difference between the control input set at different times, it is determined whether the second trigger moment is reached.

[0066] Specifically, when determining the actual control input of the model When the switching threshold control parameter D is smaller than the preset switching threshold control parameter D, the fixed threshold value and the interval difference between the actual control input and the control input set at different times will be further compared. The size between.

[0067] In one embodiment, when determining whether the second trigger moment is reached, the implementation method that can be referred to includes: when determining the second target moment, the fixed threshold value obtained is greater than or equal to the interval difference existing in the moment. , the second target moment is used as the second trigger moment.

[0068] Step S35: When it is determined that the second triggering moment is reached, the actual control input of the model is adjusted based on the control input set in the second triggering moment.

[0069] Specifically, when it is determined that the second triggering moment is reached, the adjustment method of the actual control input of the model can refer to the aforementioned implementation method, and no further explanation is given in the current embodiment.

[0070] In the current embodiment, the advantages of relative threshold control and fixed threshold control are combined so that the controller will only make changes or updates when the corresponding threshold conditions are met. Compared with the traditional control method, in which the controller changes in real time with the changes of the system, it can minimize the number of event triggering times while improving the control effect.

[0071] In one embodiment, in step S32, judging whether the first triggering moment is reached based on the relative threshold value, the interval difference between the actual control input and the control input set at different moments, includes:

[0072] Step S321: When it is determined that the interval difference is greater than or equal to the relative threshold, determine whether the first triggering moment is reached by the following formula:

[0073]

[0074] Among them, t k+1 represents the first triggering moment reached, t represents time, R represents a preset real number set, represents the actual control input, Ω represents the control input set at time t, m1 and m2 represent preset constants respectively, and “m1Ω+m2” represents a relative threshold value that changes synchronously with the change of Ω.

[0075] In one embodiment, in step S34, judging whether the second triggering moment is reached based on the fixed threshold, the interval difference between the actual control input and the control input set at different moments includes:

[0076] Step S341: When it is determined that the interval difference is greater than or equal to the fixed threshold, determine whether the second triggering moment is reached by the following formula:

[0077]

[0078] Wherein, m represents a fixed threshold.

[0079] In one embodiment, in step S4, during the adjustment process, a corresponding virtual control law is recursively designed using a backstepping method, including:

[0080] Step S41, coordinate changes are performed based on the target motion model to obtain:

[0081]

[0082] Among them, z1 represents the coordinate transformation form of the state variable x1, z2 represents the coordinate transformation form of the state variable x2, c1 represents the preset proportional gain, c2 represents the preset integral gain, x1 represents the system state of the model, x d represents the target state to be achieved, and α represents the virtual control law.

[0083] Specifically, the reason for the current coordinate change is to facilitate the design and processing of the subsequent backstepping method. In the current embodiment, based on the adaptive control principle, a suitable Lyapunov function is selected, then derived, and a corresponding virtual control law is designed.

[0084] Step S42, based on the adaptive control principle, select the corresponding first Lyapunov function V1:

[0085]

[0086] Among them, σ s represents the adaptive parameter, represents the parameter estimate of the fault parameter.

[0087] Step S43, solving the first-order derivative of the first Lyapunov function V1 to obtain the corresponding first-order derivative

[0088] Step S44, based on making the first-order derivative negative definite, that is, The first constraint condition is to design the corresponding virtual control law so that the system approaches asymptotic stability, where:

[0089]

[0090] Among them, α1 represents the virtual control law at the design point, a>0, b>0, 0<δ<1 are all preset positive constants, and k1 represents the preset error gain.

[0091] Specifically, after solving the first-order derivative of the first Lyapunov function V1, in order to reduce the amount of calculation, the obtained first-order derivative is Then, on this basis, the virtual control law is designed, and when it is determined that the selected virtual control law can make the first-order derivative negative, it is considered that the currently designed virtual control law can make the UAV system asymptotically stable.

[0092] The above embodiment integrates various system control requirements and recursively designs a virtual control law using the backstepping method, so that the UAV system can achieve asymptotic stability and improve the control effect.

[0093] In one embodiment, in step S4, during the adjustment process, a backstepping method is used to recursively design a corresponding actual control law, including:

[0094] Step S45, based on the adaptive control principle, select the corresponding second Lyapunov function V2, that is:

[0095]

[0096] Specifically, the various parameters in the above formula have been explained above and will not be further explained here.

[0097] Step S46, solving the first-order derivative of the second Lyapunov function V2 to obtain the corresponding first-order derivative

[0098] Specifically, before designing the corresponding actual control law, the first-order derivative obtained can be selectively After simplification, the actual control law is designed based on this, the event-triggered characteristics, and the limiting condition that the first-order derivative is negative.

[0099] Step S47, based on the event triggering characteristics, the first-order derivative is negatively determined, that is, The second constraint condition is to design the corresponding actual control law so that the asymptotic tracking of the target can be completed even under fault conditions, where:

[0100] or Among them, λ i (t), i = 1, ..., 3 represents a continuous time-varying parameter that satisfies λ i (t k )=0,λ i (t k+1 )=±1 and |λ i |≤1; δ represents a preset positive parameter, and m1 represents the relative threshold control input gain.

[0101] Specifically, in the actual control law designed Can make When , it means that the event trigger mechanism currently proposed can still make the system achieve asymptotic stability. In one embodiment, the Lagrange mean value theorem can also be used to verify that the event trigger mechanism can avoid the Zeno phenomenon to ensure control accuracy.

[0102] In one embodiment, please refer to Figure 2 In order to verify that the controller designed in this application can make the system, its various states follow the given reference signal changes, the following parameters will be selected: M = 1kg, g = 9.8m / s 2 , and the reference signal: Perform system simulation.

[0103] Among them, through Figure 2 As can be seen from (d), the event-triggered adaptive fault-tolerant control can quickly and accurately enable the UAV system to track the target estimate (i.e., the target trajectory). Figure 2 (a)- Figure 2 The solid line in (d) is the actual trajectory of the UAV system, and the dotted line is the target trajectory. As can be seen from the figure, the adaptive control based on event triggering can quickly and accurately enable the UAV system to track the target trajectory, with small tracking error and good tracking effect. As can be seen from Table 1 below, the trigger mode is the switching threshold event trigger mechanism, which can greatly reduce the number of triggers compared to the traditional time trigger mechanism, thereby ensuring accurate tracking control of the UAV when multiple faults occur simultaneously, and can also effectively reduce the number of controls and save communication resources.

[0104] Table 1 Comparison of trigger times

[0105] Trigger mode Trigger times Traditional time trigger 10000 Switching threshold event trigger 326

[0106] Please refer to Figure 3, which is a design system 300 of a fault-tolerant controller for a quad-rotor drone disclosed in the present application, the system 300 includes a motion model building module 301, a threshold setting module 302, a control input adjustment module 303 and a backstepping recursive design module 304, wherein:

[0107] The motion model building module 301 is used to build a target motion model that reflects the flight status of the UAV by combining the fault distribution and the rotor speed of the UAV while considering the impact of the fault on the rotor.

[0108] The threshold setting module 302 is used to set a relative threshold and a fixed threshold that change synchronously with the control input of the model.

[0109] The control input adjustment module 303 is used to adjust the control input of the model through the relative threshold and the fixed threshold in combination with the event triggering characteristics, so that the flight trajectory of the UAV approaches the preset target flight trajectory.

[0110] The backstepping recursive design module 304 is used to recursively design corresponding virtual control laws and actual control laws using the backstepping method during the adjustment process, so as to make the model approach asymptotic stability.

[0111] In one of the embodiments, each module in the system is also used to implement the method in any optional implementation of the embodiment, which will not be explained in detail in the current embodiment.

[0112] From the above, it can be seen that the design system of a fault-tolerant controller for a quad-rotor drone disclosed in the present application takes into account the impact of the fault on the rotor, simulates the fault through the fault parameter, and adopts the event trigger mechanism of comprehensive relative threshold control and fixed threshold control. Compared with the traditional control method, it can minimize the number of event triggers, while ensuring the control effect, it can also save communication resources. Under the condition of ensuring the event trigger mechanism, the corresponding virtual control law and actual control law are recursively designed by backstepping method, which can make the system achieve asymptotic stability and ensure accurate tracking control when multiple faults of the quad-rotor drone occur simultaneously.

[0113] The embodiment of the present application provides a readable storage medium, and when the computer program is executed by the processor, the method in any optional implementation of the above embodiment is executed. Wherein, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, disk or optical disk.

[0114] The above-mentioned readable storage medium takes into account the impact of the fault on the rotor, simulates the fault through the fault parameters, and adopts the event triggering mechanism of comprehensive relative threshold control and fixed threshold control. Compared with the traditional control method, it can minimize the number of event triggering times, while ensuring the control effect, it can also save communication resources. Under the condition of ensuring the event triggering mechanism, the corresponding virtual control law and actual control law are recursively designed by backstepping method, which can make the system achieve asymptotic stability and ensure accurate tracking control when multiple faults occur simultaneously in the quadrotor drone.

[0115] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0116] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0117] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0118] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0119] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A design method for a fault-tolerant controller of a quadrotor drone, characterized in that: The following steps are involved: S1. Considering the influence of the fault on the rotor, combining the fault distribution and the rotor speed of the UAV, constructing a target motion model for reflecting the flight status of the UAV; including: defining corresponding fault parameters in combination with the influence of the fault on the rotor; determining the thrust and torque generated synchronously according to the fault parameters, the fault distribution and the rotor speed of the UAV; substituting the determined thrust and torque into the dynamic model of the UAV for model conversion to obtain a target motion model for reflecting the flight status; S2, setting a relative threshold value that changes synchronously with the control input of the model, and a fixed threshold value; S3, obtaining the actual control input of the model, and comparing the actual control input with the preset switching threshold control parameter; when it is determined that the flight trajectory of the UAV is far away from the target flight trajectory, and the actual control input is greater than or equal to the preset switching threshold control parameter, based on the relative threshold, the actual control input and the interval difference between the control input set at different times, determine whether the first trigger moment is reached; when it is determined that the first trigger moment is reached, based on the control input set at the first trigger moment, adjust the actual control input of the model so that the UAV quickly approaches the target flight trajectory; when it is determined that the UAV is near the target flight trajectory, and the actual control input is less than the preset switching threshold control parameter, based on the fixed threshold, the actual control input and the interval difference between the control input set at different times, determine whether the second trigger moment is reached; when it is determined that the second trigger moment is reached, based on the control input set at the second trigger moment, adjust the actual control input of the model so that the flight trajectory of the UAV approaches the preset target flight trajectory; S4. During the adjustment process, the backstepping method is used to recursively design the corresponding virtual control law and the actual control law so that the model approaches asymptotic stability.

2. The method according to claim 1, characterized in that The fault parameter is defined in the following ways: ； in, Indicates the degree of fault. is the defined fault parameter; The thrust and torque are defined in the following ways: ； Among them, U represents the thrust, which is the control input of the model; It indicates the angular acceleration of the drone in the three directions of yaw, pitch and roll. I 4 means The identity matrix of M Represents the mapping matrix between thrust and torque and speed, represents the preset fault distribution matrix, is the rotation speed of the four rotors of the drone.

3. The method according to claim 2, characterized in that In step S13, the target motion model is defined in the following manner: ； in, , , Respectively represent the generated yaw angle, pitch angle and roll angle, They correspond to the angular accelerations of the three angles mentioned above respectively; p z represents the inertial vertical position, v z represents the inertial vertical velocity; represents the association matrix that relates the generated angular velocity to the Euler angular velocity, m Indicates the weight of the drone, and g indicates the gravitational acceleration generated; represents the inertia matrix of the body, c d Indicates the drag coefficient of the aircraft; For parameters x The derivative of 1, For parameters x The derivative of 2.

4. The method according to claim 3, characterized in that In step S32, judging whether the first triggering moment is reached based on the relative threshold value, the interval difference between the actual control input and the control input set at different moments includes: S321. When it is determined that the interval difference is greater than or equal to the relative threshold, determine whether the first triggering moment is reached by the following formula: ； in, represents the first triggering moment reached, t represents time, R represents a preset real number set, represents the actual control input, Indicates at time t The control inputs set in m 1. m 2 respectively represent the preset constants, " " The relative threshold value that changes synchronously with the change.

5. The method according to claim 4, characterized in that In step S34, judging whether the second triggering moment is reached based on the fixed threshold, the interval difference between the actual control input and the control input set at different moments includes: S341: When it is determined that the interval difference is greater than or equal to the fixed threshold, determine whether a second triggering moment is reached by the following formula: ； in, m Indicates a fixed threshold.

6. The method according to claim 5, characterized in that In step S4, during the adjustment process, the corresponding virtual control law is recursively designed using the backstepping method, including: S41, coordinate changes are performed based on the target motion model to obtain: ； in, z 1 indicates a state variable x 1 coordinate transformation form, z 2 represents the state variable x 2 coordinate transformation form, c 1 indicates the preset proportional gain, c 2 represents the preset integral gain, x 1 indicates the system state of the model, x d Indicates the target state to be achieved. represents the virtual control law; S42, based on the principle of adaptive control, select the corresponding first Lyapunov function V 1: ； in, represents the adaptive parameter, Represent parameter estimates of fault parameters; S43, for the first Lyapunov function V 1 Solve the first-order derivative and get the corresponding first-order derivative ; S44, based on making the first-order derivative negative, that is, The first constraint condition is to design the corresponding virtual control law so that the system approaches asymptotic stability, where: ； in, represents the virtual control law of the design, are all preset normal numbers. k 1 indicates the preset error gain.

7. The method according to claim 6, characterized in that In step S4, during the adjustment process, the corresponding actual control law is recursively designed using the backstepping method, including: S45, based on the principle of adaptive control, select the corresponding second Lyapunov function V 2, namely: ； S46. Regarding the second Lyapunov function V 2 Solve the first-order derivative and get the corresponding first-order derivative ; S47, based on the event triggering characteristics, the first-order derivative is negative definite, that is, The second constraint condition is to design the corresponding actual control law so that the asymptotic tracking of the target can be completed even under fault conditions, where: ,or ; in, represents a continuous time-varying parameter that satisfies and ; represents the preset positive parameter, m 1 means relative threshold control input gain.

8. A design system for a fault-tolerant controller of a quad-rotor drone, characterized in that: The system includes a motion model building module, a threshold setting module, a control input adjustment module and a backstepping recursive design module, wherein: The motion model building module is used to build a target motion model for reflecting the flight status of the UAV in combination with the fault distribution and the rotor speed of the UAV, taking into account the impact of the fault on the rotor; including: defining corresponding fault parameters in combination with the impact of the fault on the rotor; determining the thrust and torque generated synchronously according to the fault parameters, the fault distribution and the rotor speed of the UAV; substituting the determined thrust and torque into the dynamics model of the UAV for model conversion to obtain a target motion model for reflecting the flight status; The threshold setting module is used to set a relative threshold value that changes synchronously with the control input of the model, and a fixed threshold value; The control input adjustment module is used to obtain the actual control input of the model and compare the actual control input with the preset switching threshold control parameter; when it is determined that the flight trajectory of the UAV is far away from the target flight trajectory and the actual control input is greater than or equal to the preset switching threshold control parameter, based on the relative threshold and the interval difference between the actual control input and the control input set at different times, it is judged whether the first trigger moment is reached; when it is determined that the first trigger moment is reached, based on the control input set at the first trigger moment, the actual control input of the model is adjusted so that the UAV quickly approaches the target flight trajectory; when it is determined that the UAV is near the target flight trajectory and the actual control input is less than the preset switching threshold control parameter, based on the fixed threshold and the interval difference between the actual control input and the control input set at different times, it is judged whether the second trigger moment is reached; when it is determined that the second trigger moment is reached, based on the control input set at the second trigger moment, the actual control input of the model is adjusted so that the flight trajectory of the UAV approaches the preset target flight trajectory; The backstepping recursive design module is used to recursively design the corresponding virtual control law and the actual control law using the backstepping method during the adjustment process, so as to make the model approach asymptotic stability.

9. A readable storage medium, characterized in that: The readable storage medium includes a design method program for a fault-tolerant controller for a quadrotor drone. When the design method program for a fault-tolerant controller for a quadrotor drone is executed by a processor, the steps of the method described in any one of claims 1 to 7 are implemented.

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