CN115327906A - Design method and system of fault-tolerant controller of quad-rotor unmanned aerial vehicle - Google Patents
Design method and system of fault-tolerant controller of quad-rotor unmanned aerial vehicle Download PDFInfo
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Abstract
The method comprises the steps of constructing a target motion model for reflecting the flight condition of the unmanned aerial vehicle by combining the fault distribution condition and the rotor rotating speed of the unmanned aerial vehicle under the condition that the influence of faults on a rotor is considered; setting a relative threshold value and a fixed threshold value which synchronously change along with the change of the control input of the model; by combining with the event triggering characteristic, the flight track of the unmanned aerial vehicle approaches to a preset target flight track through the relative threshold and the control input of the fixed threshold adjusting model; in the adjusting process, a corresponding virtual control law and an actual control law are designed in a recursion mode by adopting a backstepping method, so that the model approaches asymptotically stable. The implementation of the method can ensure the accurate tracking control when multiple faults of the quad-rotor unmanned aerial vehicle occur simultaneously.
Description
Technical Field
The application relates to the technical field of unmanned aerial vehicle control, in particular to a design method and a system of a fault-tolerant controller of a quad-rotor unmanned aerial vehicle.
Background
In recent years, with the rapid development of technologies in the fields of communication, computers, networks and the like, the related problems of the quad-rotor unmanned aerial vehicle have become a new research direction in the field of automatic control. Quad-rotor unmanned aerial vehicle can accomplish various tasks under the complex environment on a large scale with lower cost, higher flexibility, and this makes quad-rotor unmanned aerial vehicle constantly improve in military and civilian field's position. Therefore, in order to better utilize quad-rotor drones to assist in performing various tasks, the control problem of quad-rotor drones is receiving increasing attention from researchers.
The existing mainstream attitude stabilization or tracking method for the quad-rotor unmanned aerial vehicle mainly comprises a control structure, a backstepping method, a theory-based control method, self-adaptive control and the like. Although, the existing control method can improve the stability of the unmanned aerial vehicle in the flight process; however, these control methods are based on the control method under the condition that the system of the quad-rotor unmanned aerial vehicle is not in fault, and as the unmanned aerial vehicle runs at a high speed, along with the aging of components or the damage of a driving motor and a propeller, the driving motor-propeller system is easy to be in fault, so that the quad-rotor unmanned aerial vehicle cannot complete a set task, even is out of control, and generates a safety problem, so that the control problem of the quad-rotor unmanned aerial vehicle is discussed, and meanwhile, the quad-rotor unmanned aerial vehicle is required to be ensured to reach ideal performance under normal conditions and fault conditions.
Currently, conventional FDA architectures typically employ a fault detection, isolation and evaluation (FDIE algorithm) mechanism to provide diagnostic information that a fault has occurred. Early fault detection and isolation may help to avoid more serious faults, and detailed fault information generated during fault diagnosis, which is very valuable for state-based maintenance and redundancy management. However, the overall performance of such a fault-tolerant control method is directly affected by the time delay between the occurrence of a fault and the isolation of the fault and the accuracy of the FDIE algorithm, and when a plurality of faults occur simultaneously, the accuracy of the FDIE algorithm is difficult to ensure, so that the problem of low control accuracy exists.
Disclosure of Invention
The purpose of the embodiment of the application is based on providing a design method and a system of a fault-tolerant controller of a quad-rotor unmanned aerial vehicle, and accurate tracking control of the quad-rotor unmanned aerial vehicle during simultaneous occurrence of multiple faults can be guaranteed.
The embodiment of the application also provides a design method of the fault-tolerant controller of the quad-rotor unmanned aerial vehicle, which comprises the following steps:
s1, under the condition that the influence of faults on a rotor is considered, a target motion model for reflecting the flight condition of the unmanned aerial vehicle is constructed by combining the fault distribution condition and the rotor rotating speed of the unmanned aerial vehicle;
s2, setting a relative threshold value and a fixed threshold value which synchronously change along with the control input change of the model;
s3, combining an event trigger characteristic, and adjusting the control input of the model through the relative threshold and the fixed threshold so as to enable the flight trajectory of the unmanned aerial vehicle to approach a preset target flight trajectory;
and S4, in the adjusting process, a corresponding virtual control law and an actual control law are designed in a recursion mode by adopting a backstepping method, so that the model approaches to be gradually stable.
In a second aspect, the embodiment of the present application further provides a design system for fault-tolerant controller of quad-rotor unmanned aerial vehicle, where the system includes a motion model building module, a threshold setting module, a control input adjusting module, and a backstepping recursive design module, where:
the motion model building module is used for building a target motion model for reflecting the flight condition of the unmanned aerial vehicle by combining the fault distribution condition and the rotor rotating speed of the unmanned aerial vehicle under the condition of considering the influence of the fault on the rotor;
the threshold setting module is used for setting a relative threshold which synchronously changes along with the change of the control input of the model and a fixed threshold;
the control input adjusting module is used for adjusting the control input of the model through the relative threshold and the fixed threshold in combination with an event triggering characteristic so as to enable the flight trajectory of the unmanned aerial vehicle to approach a preset target flight trajectory;
and the backstepping recursion design module is used for recurrently designing a corresponding virtual control law and an actual control law by adopting a backstepping method in the adjustment process so as to enable the model to approach asymptotically stable.
In a third aspect, the present application provides a readable storage medium, which includes a program for a method of designing a fault-tolerant controller for a quad-rotor drone, and when the program is executed by a processor, the method of designing a fault-tolerant controller for a quad-rotor drone implements the steps of the method as described in any one of the above.
Therefore, according to the design method, the system and the readable storage medium of the fault-tolerant controller for the quad-rotor unmanned aerial vehicle, the influence of the fault on the rotor is considered, the fault is simulated through the fault parameters, and an event trigger mechanism integrating relative threshold control and fixed threshold control is adopted. Under the condition of ensuring an event trigger mechanism, a corresponding virtual control law and an actual control law are designed by adopting a backstepping method, so that the system can be gradually stable, and accurate tracking control when multiple faults of the quad-rotor unmanned aerial vehicle occur simultaneously is ensured.
Additional features and advantages of the present application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the present application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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To more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a flowchart of a design method of a fault-tolerant controller for a quad-rotor unmanned aerial vehicle according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of a result of simulation debugging based on a design method of a fault-tolerant controller of a quad-rotor unmanned aerial vehicle;
fig. 3 is a schematic structural diagram of a design system of a fault-tolerant controller for a quad-rotor unmanned aerial vehicle according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for designing a fault-tolerant controller for a quad-rotor drone according to some embodiments of the present disclosure. The method comprises the following steps:
step S1, under the condition that the influence of faults on the rotor is considered, a target motion model for reflecting the flight condition of the unmanned aerial vehicle is constructed by combining the fault distribution condition and the rotor rotating speed of the unmanned aerial vehicle.
And S2, setting a relative threshold value and a fixed threshold value which synchronously change along with the change of the control input of the model.
And S3, combining an event trigger characteristic, and adjusting the control input of the model through the relative threshold and the fixed threshold so as to enable the flight trajectory of the unmanned aerial vehicle to approach a preset target flight trajectory.
And S4, in the adjusting process, a corresponding virtual control law and an actual control law are designed in a recursion mode by adopting a backstepping method, so that the model approaches to be gradually stable.
By last can know, the design method of four rotor unmanned aerial vehicle fault-tolerant controller that this application disclosed has considered the influence of trouble to the rotor, simulates the trouble through the fault parameter, and adopts the event trigger mechanism of synthesizing relative threshold control and fixed threshold control, compares in traditional control mode, and reduction event trigger number of times that can the at utmost is guaranteeing control effect, can also practice thrift communication resources. Under the condition of ensuring an event trigger mechanism, a corresponding virtual control law and an actual control law are designed by adopting a backstepping method, so that the system can be gradually stable, and accurate tracking control when multiple faults of the quad-rotor unmanned aerial vehicle occur simultaneously is ensured.
In one embodiment, in step S1, the constructing a target motion model for reflecting the flight condition of the drone by combining the fault distribution and the rotor speed of the drone under the condition of considering the influence of the fault on the rotor includes:
step S11, defining corresponding fault parameters by combining the influence of the fault on the rotor, wherein the definition mode of the fault parameters comprises the following steps:
wherein alpha is s The degree of the failure is indicated by the number of the sensors,
are defined fault parameters.
In particular, when
Time indicates that the current rotor is operating normally; otherwise, it indicates that the rotor is in failure during operation, and a corresponding degree of thrust loss occurs.
Step S12, determining the thrust and the torque synchronously generated according to the fault parameters, the fault distribution condition and the rotor rotating speed of the unmanned aerial vehicle, wherein the definition mode of the thrust and the torque comprises the following steps:
wherein U represents thrust, i.e. the control input of the model; tau is φ ,τ θ ,τ ψ Represents the angular acceleration I generated by the unmanned aerial vehicle in the yaw direction, the pitch direction and the roll direction respectively 4 Representing a 4 x 4 identity matrix, M representing a mapping matrix between thrust and torque and rotational speed, Λ s Representing a predetermined fault distribution matrix, Ω i (i =1,2,3,4) is the rotational speed of the four rotors of the drone.
Specifically, since the thrust and the torque of the rotor are proportional to the square of the rotation speed, in the current embodiment, the thrust and the torque of the quad-rotor drone are further determined by combining the above definition manner of the fault parameters.
In one embodiment, Λ s The representation is a fault distribution matrix, and s =1.. 4 represents the rotor number where the fault occurs. Exemplarily, when s =1, then there is Λ 1 = diag {1, 0}; when s =2, then there is Λ 2 And = diag {0,1,0,0}, and the rest can be analogized, which is not limited in the embodiments of the present application.
And S13, substituting the determined thrust and torque into a dynamic model of the unmanned aerial vehicle for model conversion to obtain a target motion model for reflecting the flight condition.
Specifically, the definition mode of the dynamics model of the unmanned aerial vehicle includes:
it should be noted that, since the parameters in the above formula are defined in the following, no excessive description is made at present.
Above-mentioned embodiment has considered the influence of trouble to the rotor, simulates the trouble through the fault parameter to and need adopt adaptive control to eliminate the influence of trouble, accurate tracking control when having guaranteed that many troubles of unmanned aerial vehicle take place simultaneously has further improved control effect.
In one embodiment, in step S13, the target motion model is defined in a manner including:
wherein,
x 1 ＝[p z ,φ,θ,ψ] T ,x 2 ＝[v z ,p,q,r] T ，[φ,θ,ψ]respectively, the yaw angle, pitch angle and roll angle [ p, q, r ] generated]Angular accelerations respectively corresponding to the three angles; p is a radical of z Representing inertial vertical position, v z Representing inertial vertical velocity; r η (phi, psi) represents a correlation matrix that correlates the generated angular velocity with the euler angular velocity, m represents the body weight of the drone, and g represents the generated gravitational acceleration; j = diag { J } x ,J y ,J z Denotes the inertia matrix of the body, c d Representing the resistance coefficient of the body;
is a parameter x 1 The derivative of (a) of (b),
is a parameter x 2 The derivative of (c).
Above-mentioned embodiment has adopted second order Newton Lagrange's model to establish unmanned aerial vehicle's dynamics model, and wherein, the rotation through four rotor unmanned aerial vehicle of rotation matrix representation, description unmanned aerial vehicle's gesture that can be better, more succinct realization unmanned aerial vehicle control inputs the resolving of every rotor speed of unmanned aerial vehicle.
In one embodiment, in step S3, adjusting the control input of the model through the relative threshold and the fixed threshold to make the flight trajectory of the drone approach to a preset target flight trajectory includes:
step S31, obtaining the actual control input of the model, and comparing the actual control input with the preset switching threshold control parameter.
In the present embodiment, the actual control input of the model is further inputted
And comparing with a preset switching threshold control parameter D to determine when to switch the control strategy.
For example, in determining
When the unmanned aerial vehicle is close to the target flight path, the unmanned aerial vehicle can track the target flight path, and therefore fine control is not needed.
It should be noted that, because the value of the control input is large, the value of the corresponding associated relative threshold is also large, the trigger threshold at this time is relatively high, and the number of times of triggering is relatively small, so that the unmanned aerial vehicle can track the target at a fast tracking speed.
Under other circumstances, will switch to fixed threshold value strategy, when confirming that unmanned aerial vehicle approaches target flight path, along with control input's reduction, will adopt fixed threshold value, realize high accuracy control through increasing the control number of times to guarantee the promotion of control effect.
It should be noted that the fixed threshold may be a positive constant. In the current embodiment, specific values are not limited, and in different embodiments, specific practical conditions can be combined, and a proper value can be determined by simulation debugging, so that the control effect of the unmanned aerial vehicle near the target flight trajectory is ensured, the triggering times are reduced, and the communication resources are saved.
And S32, when the fact that the distance between the flight track of the unmanned aerial vehicle and the target track is far and the actual control input is greater than or equal to a preset switching threshold control parameter is determined, whether the first trigger time is reached is judged based on the relative threshold and the interval difference between the actual control input and the control input set at different moments.
In particular, the actual control input at the determined model
When the switching threshold value is larger than or equal to the preset switching threshold value control parameter D, the relative threshold value and the interval difference value between the actual control input and the control input set in different moments are further compared, namely
The size of (c) between.
In one embodiment, when determining whether the first trigger time is reached, reference may be made to the following embodiments: the relative threshold value obtained in determining the first target time is greater than or equal to the interval difference existing in that time
Then, the first target time is used as a first trigger time, and then the design control input set based on the first trigger time is used for adjusting the actual control input of the model.
And step S33, when the first trigger moment is determined to be reached, adjusting the actual control input of the model based on the control input set in the first trigger moment so that the unmanned aerial vehicle quickly approaches the target track.
In particular, at the first trigger time t k+1 Will further determine at that time t k+1 The design control input Ω set in (1). Then, the actual control input of the model is realized based on the design control input omega
Is updated, i.e. is
Wherein in the non-triggering time instant, i.e. t ∈ [ t, t ∈ [ ] k+1 ) The actual control input will remain unchanged, i.e. not updated, until the trigger time t is reached k+1 I.e. t = t k+1 Then based on the trigger time t k+1 The design control input Ω set in (1) is updated.
And S34, when the unmanned aerial vehicle is determined to be near the target track and the actual control input is smaller than a preset switching threshold control parameter, judging whether a second trigger moment is reached or not based on the fixed threshold, the actual control input and an interval difference between the control inputs set in different moments.
In particular, the actual control input at the determined model
When the switching threshold control parameter D is smaller than the preset switching threshold control parameter D, the fixed threshold and the interval difference between the actual control input and the control input set in different moments are further compared, namely
The size of (c) between.
In one embodiment, when determining whether the second trigger time is reached, reference may be made to the following embodiments: the fixed threshold taken in determining the second target moment is largeAt, or equal to, the interval difference existing in that moment
And taking the second target time as a second trigger time.
Step S35, when it is determined that the second trigger time is reached, adjusting the actual control input of the model based on the control input set in said second trigger time.
Specifically, when it is determined that the second trigger time is reached, the adjustment manner of the actual control input of the model may refer to the foregoing embodiment, and is not described in detail in the current embodiment.
In the current embodiment, advantages of relative threshold control and fixed threshold control are integrated, so that the controller is changed or updated only when corresponding threshold conditions are met, and compared with a traditional control mode that the controller is changed in real time along with changes of a system, the control effect can be improved while the number of event triggers is reduced to the maximum extent.
In one embodiment, the determining whether the first trigger time is reached based on the relative threshold and the difference between the actual control input and the control input set in different times in step S32 includes:
step S321, when it is determined that the interval difference is greater than or equal to the relative threshold, determining whether the first trigger time is reached by the following formula:
wherein, t k+1 Representing the first trigger moment reached, t representing the time, R representing a preset set of real numbers,
representing said actual control input, omega representing the control input set in time t, m 1 、m 2 Respectively represent preset constants, "m 1 Ω+m 2 "indicates the relative threshold that changes synchronously with changes in Ω.
In one embodiment, the determining whether the second trigger time is reached based on the fixed threshold and the interval difference between the actual control input and the control input set in different times in step S34 includes:
step S341, when it is determined that the interval difference is greater than or equal to the fixed threshold, determining whether a second trigger time is reached according to the following formula:
where m represents a fixed threshold.
In one embodiment, in step S4, in the adjusting process, a corresponding virtual control law is recursively designed by using a back-stepping method, including:
step S41, coordinate change is carried out based on the target motion model, and the following results are obtained:
wherein z is 1 Represents a state variable x 1 Form of coordinate transformation of (1), z 2 Represents a state variable x 2 Coordinate transformation form of (c) 1 Represents a predetermined proportional gain, c 2 Representing a predetermined integral gain, x 1 Representing the system state of the model, x d Indicating the target state reached and alpha indicating the virtual control law.
Specifically, the coordinate change is performed at present, so as to facilitate the design and processing of the subsequent back stepping method. In the current embodiment, based on an adaptive control principle, a proper Lyapunov function is selected, then derivation is performed on the function, and a corresponding virtual control law is designed.
Step S42, based on the self-adaptive control principle, selecting a corresponding first Lyapunov function V 1 ：
Wherein σ s The adaptive parameters are represented by a number of parameters,
a parameter estimate representing a fault parameter.
Step S43, aiming at the first Lyapunov function V 1 Solving the first derivative to obtain the corresponding first derivative
Step S44, based on making the first derivative negative, i.e. determining
Designing a corresponding virtual control law so that the system approaches asymptotic stability, wherein:
wherein alpha is 1 Representing a virtual control law at a design position, wherein a is more than 0, b is more than 0, delta is more than 0 and less than 1, the values are all preset normal numbers, k 1 Indicating a preset error gain.
Specifically, the first Lyapunov function V is applied 1 After solving the first derivative, the first derivative will be calculated to reduce the amount of calculation
And simplifying the process. And then, on the basis, designing the virtual control law, and determining that the selected virtual control law can enable the first derivative to be negative, namely, the currently designed virtual control law is considered to enable the unmanned aerial vehicle system to realize asymptotic stability.
Above-mentioned embodiment synthesizes various system control requirements, utilizes the backstepping method to design out the virtual control law recurrently for the unmanned aerial vehicle system can realize asymptotic stability, has promoted control effect.
In one embodiment, in step S4, in the adjusting process, a corresponding actual control law is designed by recursion using a back-stepping method, including:
step S45, based on the self-adaptive control principle, selecting a corresponding second Lyapunov function V 2 Namely:
specifically, the parameters in the above formula are explained in the foregoing, and are not explained in an excessive way at present.
Step S46, aiming at the second Lyapunov function V 2 Solving the first derivative to obtain the corresponding first derivative
In particular, the first derivative obtained can be optionally selected before designing the corresponding actual control law
And simplifying, and then designing the actual control law based on the event trigger characteristic and a limiting condition that the first derivative is negative.
Step S47, based on the event trigger characteristic, making the first derivative negative, i.e. determining
Designing a corresponding actual control law so as to complete asymptotic tracking of the target under the fault condition, wherein:
In particular, at the actual control law designed
Can enable
In time, it shows that the event trigger mechanism proposed currently still enables the system to achieve asymptotic stability. In one embodiment, the lagrangian median theorem can be further utilized to verify that the event triggering mechanism can avoid the sesno phenomenon, so as to ensure the control accuracy.
In one embodiment, referring to fig. 2, to verify that the controller designed by the present application enables the system to have its states follow the given reference signal, the following parameters are chosen: m =1kg, g =9.8m/s 2 And reference signal:
and carrying out system simulation.
As can be seen from fig. 2 (d), the adaptive fault-tolerant control based on event triggering can quickly and accurately make the unmanned aerial vehicle system track the target estimation (i.e., the target trajectory). It should be noted that the solid line in fig. 2 (a) -2 (d) is the actual trajectory of the drone system, and the dotted line is the target trajectory. As can be seen from the figure, the self-adaptive control based on event triggering can quickly and accurately enable the unmanned aerial vehicle system to track the target track, and is small in tracking error and good in tracking effect. As can be seen from table 1 below, the trigger mode is a switching threshold event trigger mechanism, which can greatly reduce the number of triggers compared to the conventional time trigger mechanism, thereby ensuring accurate tracking control when multiple faults of the unmanned aerial vehicle occur simultaneously, effectively reducing the number of controls, and saving communication resources.
TABLE 1 comparison of number of triggers
| Triggering mode | Number of triggers |
| Conventional time triggering | 10000 |
| Handover threshold event triggering | 326 |
Please refer to fig. 3, which is a design system 300 for a fault tolerant controller of a quad-rotor unmanned aerial vehicle disclosed in the present application, the system 300 includes a motion model building module 301, a threshold setting module 302, a control input adjusting module 303, and a backstepping recursive design module 304, wherein:
the motion model building module 301 is configured to build a target motion model for reflecting the flight condition of the unmanned aerial vehicle, in combination with the fault distribution condition and the rotor speed of the unmanned aerial vehicle, under the condition that the influence of the fault on the rotor is considered.
The threshold setting module 302 is configured to set a relative threshold that changes synchronously with a change in the control input of the model, and a fixed threshold.
The control input adjusting module 303 is configured to adjust the control input of the model through the relative threshold and the fixed threshold in combination with an event trigger characteristic, so that the flight trajectory of the unmanned aerial vehicle approaches a preset target flight trajectory.
The backstepping recursion design module 304 is configured to recursively design a corresponding virtual control law and an actual control law by using a backstepping method in the adjustment process, so that the model approaches asymptotic stability.
In one embodiment, each module in the system is further configured to implement the method in any optional implementation manner of the embodiment, which is not described in detail in the current embodiment.
By last knowing, the design system of four rotor unmanned aerial vehicle fault-tolerant controller that this application disclosed has considered the influence of trouble to the rotor, simulates the trouble through the fault parameter, and adopts the event trigger mechanism of synthesizing relative threshold control and fixed threshold control, compares in traditional control mode, and reduction event trigger number of times that can the at utmost is when guaranteeing the control effect, can also practice thrift communication resources. Under the condition of ensuring an event trigger mechanism, a corresponding virtual control law and an actual control law are designed by adopting a backstepping method, so that the system can be gradually stable, and accurate tracking control when multiple faults of the quad-rotor unmanned aerial vehicle occur simultaneously is ensured.
The embodiment of the present application provides a readable storage medium, and the computer program, when executed by a processor, performs the method in any optional implementation manner of the above embodiment. The storage medium may be implemented by any type of volatile or nonvolatile storage device or combination thereof, such as a Static Random Access Memory (SRAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), an Erasable Programmable Read-Only Memory (EPROM), a Programmable Read-Only Memory (PROM), a Read-Only Memory (ROM), a magnetic Memory, a flash Memory, a magnetic disk, or an optical disk.
The readable storage medium considers the influence of the fault on the rotor, simulates the fault through fault parameters, and adopts an event trigger mechanism integrating relative threshold control and fixed threshold control, compared with the traditional control mode, the readable storage medium can reduce the event trigger times to the greatest extent, and can save communication resources while ensuring the control effect. Under the condition of ensuring an event trigger mechanism, a corresponding virtual control law and an actual control law are designed by adopting a backstepping method, so that the system can be gradually stable, and accurate tracking control when multiple faults of the quad-rotor unmanned aerial vehicle occur simultaneously is ensured.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the 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.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A design method of a fault-tolerant controller of a quad-rotor unmanned aerial vehicle is characterized by comprising the following steps:
s1, under the condition that the influence of faults on a rotor is considered, a target motion model for reflecting the flight condition of the unmanned aerial vehicle is constructed by combining the fault distribution condition and the rotor rotating speed of the unmanned aerial vehicle;
s2, setting a relative threshold value and a fixed threshold value which synchronously change along with the control input change of the model;
s3, combining an event trigger characteristic, and adjusting the control input of the model through the relative threshold and the fixed threshold so as to enable the flight trajectory of the unmanned aerial vehicle to approach a preset target flight trajectory;
and S4, in the adjusting process, a corresponding virtual control law and an actual control law are designed in a recursion mode by adopting a backstepping method, so that the model approaches to be gradually stable.
2. The method according to claim 1, wherein in step S1, the building a target motion model for reflecting the flight condition of the drone by combining the fault distribution and the rotor speed of the drone under the condition of considering the influence of the fault on the rotor includes:
s11, defining corresponding fault parameters by combining the influence of the fault on the rotor, wherein the fault parameters are defined in a mode comprising:
wherein alpha is s It is indicated that the degree of the failure,
is a defined fault parameter;
s12, determining a thrust and a torque which are synchronously generated according to the fault parameters, the fault distribution condition and the rotor rotating speed of the unmanned aerial vehicle, wherein the thrust and the torque are defined in a mode comprising:
wherein U represents thrust, i.e. the control input of the model; tau is φ ,τ θ ,τ ψ Represents the angular acceleration I generated by the unmanned aerial vehicle in the yaw direction, the pitch direction and the roll direction respectively 4 Representing a 4 x 4 identity matrix, M representing a mapping matrix between thrust and torque and rotational speed, Λ s Represents a predetermined fault distribution matrix, Ω i (i =1,2,3,4) is the rotational speed of the four rotors of the drone;
and S13, substituting the determined thrust and torque into a dynamic model of the unmanned aerial vehicle for model conversion to obtain a target motion model for reflecting the flight condition.
3. The method according to claim 2, wherein in step S13, the object motion model is defined in a manner including:
wherein,
x 1 ＝[p z ,φ,θ,ψ] T ,x 2 ＝[v z ,p,q,r] T ，[φ,θ,ψ]respectively representing the yaw angle, pitch angle and roll angle, [ p, q, r ] generated]Angular accelerations respectively corresponding to the three angles; p is a radical of formula z Representing inertial vertical position, v z Representing inertial vertical velocity; r is η (phi, psi) represents a correlation matrix that correlates the generated angular velocity with the euler angular velocity, m represents the body weight of the drone, and g represents the generated gravitational acceleration; j = diag { J } x ,J y ,J z Denotes the inertia matrix of the body, c d Representing the resistance coefficient of the body;
is a parameter x 1 The derivative of (a) of (b),
is a parameter x 2 The derivative of (c).
4. The method according to claim 3, wherein in step S3, the adjusting the control input of the model through the relative threshold and the fixed threshold to make the flight trajectory of the drone approach to the preset target flight trajectory includes:
s31, acquiring actual control input of the model, and comparing the actual control input with a preset switching threshold control parameter;
s32, when the fact that the distance between the flight track of the unmanned aerial vehicle and the target track is far and the actual control input is larger than or equal to a preset switching threshold control parameter is determined, whether a first trigger moment is reached is judged based on the relative threshold, and the interval difference between the actual control input and the control input set at different moments;
s33, when the first trigger moment is determined to be reached, adjusting the actual control input of the model based on the control input set in the first trigger moment so that the unmanned aerial vehicle quickly approaches the target track;
s34, when the unmanned aerial vehicle is determined to be near the target track and the actual control input is smaller than a preset switching threshold control parameter, judging whether a second trigger moment is reached or not based on the fixed threshold, the actual control input and an interval difference value between the control input set in different moments;
and S35, when the second trigger time is determined to be reached, adjusting the actual control input of the model based on the control input set in the second trigger time.
5. The method of claim 4, wherein the determining whether the first trigger time is reached based on the relative threshold, the difference in the interval between the actual control input and the control input set in the different time in step S32 comprises:
s321, when the interval difference is determined to be larger than or equal to the relative threshold, judging whether the first trigger time is reached through the following formula:
wherein, t k+1 Representing the first trigger moment reached, t representing the time, R representing a preset set of real numbers,
representing the actual control input, omega representing the control input set in time t, m 1 、m 2 Respectively represent preset constants, "m 1 Ω+m 2 "denotes the relative threshold that changes synchronously with changes in Ω.
6. The method of claim 5, wherein the determining whether a second trigger time is reached based on the fixed threshold, the difference in the interval between the actual control input and the control input set in the different time in step S34 comprises:
s341, when the interval difference is determined to be greater than or equal to the fixed threshold, judging whether a second trigger time is reached or not according to the following formula:
where m represents a fixed threshold.
7. The method according to claim 6, wherein in step S4, in the adjusting process, a corresponding virtual control law is designed by recursion using a back-stepping method, and the method includes:
s41, changing coordinates based on the target motion model to obtain:
wherein z is 1 Represents a state variable x 1 Form of coordinate transformation of (1), z 2 Represents a state variable x 2 Coordinate transformation form of (c) 1 Representing a preset proportional gain, c 2 Representing a predetermined integral gain, x 1 Representing the system state of the model, x d Representing the achieved target state, and alpha represents a virtual control law;
s42, selecting a corresponding first Lyapunov function V based on a self-adaptive control principle 1 ：
Wherein σ s The adaptive parameters are represented by a number of parameters,
a parameter estimate representing a fault parameter;
s43, aiming at the first Lyapunov function V 1 Solving the first derivative to obtain the corresponding first derivative
S44, based on making the first derivative negative, i.e.
Designing a corresponding virtual control law so that the system approaches asymptotic stability, wherein:
wherein alpha is 1 Representing a virtual control law at a design position, wherein a is more than 0, b is more than 0, delta is more than 0 and less than 1, the values are all preset normal numbers, k 1 Indicating a preset error gain.
8. The method according to claim 7, wherein in step S4, in the adjusting process, a corresponding actual control law is designed by recursion using a back-stepping method, and the method includes:
s45, selecting a corresponding second Lyapunov function V based on a self-adaptive control principle 2 Namely:
s46, aiming at the second Lyapunov function V 2 Solving the first derivative to obtain the corresponding first derivative
S47, based on the event trigger characteristic, making the first derivative negative, namely
Designing a corresponding actual control law so as to complete asymptotic tracking of the target under the fault condition, wherein:
Wherein λ is i (t), i =1.., 3 denotes a continuous time-varying parameter, which satisfies λ i (t k )＝0,λ i (t k+1 ) = ± 1 and | λ i The | < 1; δ represents a preset positive parameter, m 1 Indicating that the relative threshold controls the input gain.
9. The utility model provides a design system of four rotor unmanned aerial vehicle fault-tolerant controller, its characterized in that, the system includes motion model construction module, threshold setting module, control input adjustment module and backstepping recursion design module, wherein:
the motion model building module is used for building a target motion model for reflecting the flight condition of the unmanned aerial vehicle by combining the fault distribution condition and the rotor rotating speed of the unmanned aerial vehicle under the condition of considering the influence of the fault on the rotor;
the threshold setting module is used for setting a relative threshold which synchronously changes along with the change of the control input of the model and a fixed threshold;
the control input adjusting module is used for adjusting the control input of the model through the relative threshold and the fixed threshold in combination with an event trigger characteristic so as to enable the flight trajectory of the unmanned aerial vehicle to approach a preset target flight trajectory;
and the backstepping recursion design module is used for recurrently designing a corresponding virtual control law and an actual control law by adopting a backstepping method in the adjustment process so as to enable the model to approach asymptotically stable.
10. A readable storage medium, wherein the readable storage medium includes a program for a method of designing a fault-tolerant controller for a quad-rotor drone, and wherein the program for a method of designing a fault-tolerant controller for a quad-rotor drone when executed by a processor implements the steps of the method as recited in any one of claims 1 to 8.
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