CN114578691A - Active anti-interference fault-tolerant attitude control method of flying wing unmanned aerial vehicle considering control plane fault - Google Patents

Active anti-interference fault-tolerant attitude control method of flying wing unmanned aerial vehicle considering control plane fault Download PDF

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CN114578691A
CN114578691A CN202210128644.3A CN202210128644A CN114578691A CN 114578691 A CN114578691 A CN 114578691A CN 202210128644 A CN202210128644 A CN 202210128644A CN 114578691 A CN114578691 A CN 114578691A
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赵振华
顾子箫
姜斌
曹东
祖家奎
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Nanjing University of Aeronautics and Astronautics
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Abstract

The invention discloses an active disturbance rejection fault-tolerant attitude control method of a flying wing unmanned aerial vehicle considering control surface faults, which comprises the steps of firstly establishing a disturbed dynamics model of an attitude system of the flying wing unmanned aerial vehicle considering the control surface faults, and converting the control surface fault influence into lumped interference; secondly, designing a rolling, pitching and yawing three-channel observer based on the extended state observer technology to realize estimation of three-channel lumped interference; then, combining lumped interference estimation information, and constructing a composite dynamic inverse controller of the attitude loop based on a nonlinear dynamic inverse algorithm; and finally, converting the expected torque into the deflection of the control surface of the flying wing unmanned aerial vehicle based on a pseudo-inverse method. The method provided by the invention treats the fault influence as interference, obviously improves the anti-interference capability and fault tolerance capability of the system through the estimation and feedforward compensation of the interference, has better anti-interference capability and fault tolerance capability compared with the traditional dynamic inverse control method, and effectively inhibits the influence of multi-source interference and control surface fault on the control performance of the flying wing unmanned aerial vehicle.

Description

Active anti-interference fault-tolerant attitude control method of flying wing unmanned aerial vehicle considering control plane fault
Technical Field
The invention belongs to the technical field of flight control, and particularly relates to an active anti-interference fault-tolerant attitude control method of a flying wing unmanned aerial vehicle considering control plane faults.
Background
Due to the special aerodynamic layout of the flying-wing unmanned aerial vehicle, the flying-wing unmanned aerial vehicle has the advantages of high lift, long endurance time, strong stealth and the like, and is widely applied to military and civil fields. Because the flying wing unmanned aerial vehicle attitude system is a typical strong nonlinear system, a plurality of challenges such as strong coupling, fast time variation and the like are faced when the controller is designed; with the increasing complexity of the task execution, the flying-wing unmanned aerial vehicle is in a worse flying environment and is influenced by multi-source interference and faults such as external environment interference, perturbation of internal pneumatic parameters, faults of an execution mechanism and the like; these model nonlinearities, multi-source interference, faults, and the like pose significant challenges to the design of attitude control systems.
Aiming at the problem of attitude control of the unmanned aerial vehicle affected by multi-source interference and control surface faults, scholars at home and abroad propose various solutions, including dynamic inverse control based on a nonlinear nominal model and sliding mode control depending on self algorithm robustness. However, the interference and fault suppression strategies of these methods are based on passive elimination of the influence of interference by the error signal, and the anti-interference performance of the system is obtained at the expense of the nominal performance. Therefore, a flying wing unmanned aerial vehicle attitude control method capable of rapidly and actively inhibiting multi-source interference and fault influence is needed to be provided.
In addition, because the flying wing drone adopts redundant control surface configuration to ensure the overall reliability of the system, the available control surface is usually larger than the required control surface, and how to allocate the control surface to ensure the minimum required control surface driving energy under the condition of realizing the desired torque is also a concern.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides the active disturbance rejection fault-tolerant attitude control method of the flying wing unmanned aerial vehicle considering the control surface fault, which can realize the estimation of lumped disturbance caused by multi-source disturbance and fault influence, and compensate or offset the adverse influence caused by the multi-source disturbance and the fault by disturbance estimation information in a feedforward mode so as to ensure that the flying wing unmanned aerial vehicle has stronger disturbance resistance and fault-tolerant capability. In addition, by adopting a reasonable control surface distribution control method, the minimum control surface driving energy consumed while the expected torque is realized is ensured.
An active disturbance rejection fault-tolerant attitude control method of a flying wing unmanned aerial vehicle considering control plane faults is characterized by comprising the following steps:
s1, establishing a flying wing unmanned aerial vehicle attitude system considering control surface faults, wherein the flying wing unmanned aerial vehicle attitude system comprises an attitude system disturbed dynamics model and a control surface model considering control surface faults, and obtaining disturbed attitude system dynamics and attitude system tracking error dynamics according to the models;
s2, constructing an extended state observer based on the disturbed attitude system dynamic state, and obtaining a lumped disturbance estimation by combining an expected moment
Figure BDA0003501662320000021
S3, dynamically constructing a composite nonlinear dynamic inverse attitude controller based on the tracking error of the attitude system, and estimating the lumped interference observed by combining the extended state observer
Figure BDA0003501662320000022
Obtaining a desired moment, i.e. a virtual control quantity gamman；
And S4, converting the expected torque into the control plane deflection of the flying wing unmanned aerial vehicle based on a pseudo-inverse method, forming a control plane deflection instruction and sending the control plane deflection instruction to the attitude system of the flying wing unmanned aerial vehicle.
Has the advantages that:
1. according to the method, the extended state observer is adopted to estimate multisource interference and control surface faults in the attitude system, so that asymptotic estimation of lumped interference is realized;
2. the invention brings the lumped interference estimation information into the nonlinear dynamic inverse controller design, reconstructs the lumped interference estimation information into the composite dynamic inverse controller, and performs dynamic real-time feedforward compensation on the lumped interference, thereby obviously improving the anti-interference and fault-tolerant control performance of the system.
3. The method solves the virtual control quantity through a pseudo-inverse method, realizes that the total deflection quantity of the control surface of the flying wing unmanned aerial vehicle is minimum while the flying wing unmanned aerial vehicle can track the instruction, effectively avoids the saturation condition of the control surface and improves the flight performance of the flying wing unmanned aerial vehicle.
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FIG. 1 is a structural block diagram of an active disturbance rejection fault-tolerant attitude control method of a flying wing unmanned aerial vehicle, which takes control plane faults into consideration and is adopted by the invention;
fig. 2 is a roll angle channel response curve, a roll angle tracking error response curve and a response curve of the channel control quantity under the action of a Composite Nonlinear Dynamic Inverse Controller (CNDIC) and a Nonlinear Dynamic Inverse Controller (NDCI) for comparison, respectively, according to the method provided by the present invention;
FIG. 3 shows a response curve of a pitch angle channel, a response curve of a pitch angle tracking error and a response curve of the channel control quantity of a flying wing unmanned aerial vehicle under the respective actions of a CNDIC and an NDCI according to the method of the present invention;
fig. 4 is a response curve of a yaw angle channel, a response curve of a yaw angle tracking error, and a response curve of a control quantity of the channel of a flying wing drone under respective actions of a CNDIC and an NDCI according to the method of the present invention;
FIG. 5 is a control plane deflection response curve of the flying wing drone under the respective actions of the CNDIC and the NDCI proposed by the present invention;
FIG. 6 is a graph of the observation effect of the extended state observer under the action of the CNDIC according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and do not constitute an undue limitation on the present invention.
The invention discloses an active disturbance rejection fault-tolerant attitude control method of a flying wing unmanned aerial vehicle considering control surface faults, which comprises the steps of firstly establishing a disturbed dynamics model of an attitude system of the flying wing unmanned aerial vehicle considering the control surface faults, and converting the control surface fault influence into lumped interference; secondly, designing a rolling, pitching and yawing three-channel observer based on the extended state observer technology to realize estimation of three-channel lumped interference; then, combining lumped interference estimation information, and constructing a composite dynamic inverse controller of the attitude loop based on a nonlinear dynamic inverse algorithm; and finally, converting the expected torque into the deflection of the control surface of the flying wing unmanned aerial vehicle based on a pseudo-inverse method.
The invention is concretely realized as follows: firstly, a disturbed attitude loop model of the flying wing unmanned aerial vehicle considering control surface faults is built by using a Simulink toolbox in simulation software MATLAB R2021a, and then simulation and experiment are carried out; fig. 1 is a structural block diagram of an active disturbance rejection fault-tolerant attitude control method of a flying wing unmanned aerial vehicle considering control plane faults. The method comprises the following specific steps:
s1, establishing a disturbed dynamics model of the flying wing unmanned aerial vehicle attitude system considering the control plane fault, specifically:
establishing a disturbed dynamics model of an attitude system of a flying wing unmanned aerial vehicle:
Figure BDA0003501662320000031
wherein s isφ，tθ，cφAnd cθDenotes sin phi, tan theta, cos phi and cos theta, respectively; phi, theta and psi respectively represent the roll angle, the pitch angle and the yaw angle of the flying wing unmanned plane,
Figure BDA0003501662320000032
and
Figure BDA0003501662320000033
first derivatives of phi, theta and psi, respectively; p, q and r respectively represent the rotation angular speeds of the flying-wing unmanned aerial vehicle around the x, y and z axes of the body,
Figure BDA0003501662320000041
Figure BDA0003501662320000042
and
Figure BDA0003501662320000043
first derivatives of p, q, and r, respectively; i isx，IyAnd IzRespectively representing the rotational inertia of the flying-wing unmanned aerial vehicle around the x, y and z axes of the body; i isxzRepresenting the product of inertia of the flying wing drone; tau.x，τyAnd τzRespectively representing the aerodynamic moment of the flying wing unmanned aerial vehicle rotating around the x, y and z axes of the body; dx，DyAnd DzRepresenting three axial multisource disturbances.
Establishing a flying wing unmanned plane model considering the fault of a control plane:
Γ＝B[(I-Kf)δ+δf]＝Bδ+B(δf-Kfδ)＝Γn+Γf (8)
wherein r ═ τx τy τz]TIs a moment vector; b is belonged to R3×8Representing a control efficiency matrix of a control surface of the flying wing unmanned aerial vehicle; i is as large as R8×8Is an identity matrix; kf＝diag{kf1,kf2,…,kf8Represents a failure coefficient matrix; delta-is [ delta ]1 δ2 δ3 δ4 δ5 δ6δ7 δ8]TIndicating the deflection angle, delta, of the control surface of the flying-wing dronef＝diag{δf1,δf2,…,δf8Expressing the jamming angle of the control surface; gamma-shapednIndicating nominal aerodynamic moment, Γ, without control surface failurefIndicating a fault-induced aerodynamic moment. In this example Ix＝0.3493，Iy＝0.9234，Iz＝1.3217，Ixz0.0319. For convenience of writing, the following definitions are elicited:
Figure BDA0003501662320000044
Δ＝IxIz-Ixz 2,
Figure DA00035016623251755529
Figure BDA0003501662320000046
equation (1) can be rewritten as follows:
Figure BDA0003501662320000047
wherein
Figure BDA0003501662320000048
Is the first derivative of theta and is,
Figure BDA0003501662320000049
the first derivative of Ω. According to the attitude dynamic equation (3), the simultaneous equation (2) can obtain the disturbed attitude system dynamic, namely the attitude angle second-order dynamic:
Figure BDA0003501662320000051
wherein
Figure BDA0003501662320000052
Is the first derivative of W, DLFor lumped interference in the attitude tracking system, the expression is as follows:
DL＝WD+WGΓf
defining the attitude tracking error of the flying-wing unmanned aerial vehicle:
Figure BDA0003501662320000053
wherein Θ isd＝[φd θd ψd]TFor the desired attitude angle, the tracking error dynamics of the obtained attitude system is:
Figure BDA0003501662320000054
wherein
Figure BDA0003501662320000055
And
Figure BDA0003501662320000056
respectively represent eΘThe second derivative and the first derivative of (a),
Figure BDA0003501662320000057
and
Figure BDA0003501662320000058
respectively represent thetadThe second derivative and the first derivative.
And S2, designing a roll, pitch and yaw three-channel observer based on the extended state observer technology.
The method is characterized in that an extended state observer is designed for disturbed attitude system dynamics (4) of the flying wing unmanned aerial vehicle considering control surface faults so as to realize estimation of lumped disturbance, and the design method specifically comprises the following steps:
Figure BDA0003501662320000059
wherein
Figure BDA00035016623200000510
And
Figure BDA00035016623200000511
and in order to extend the state observer dynamics,
Figure BDA00035016623200000512
to interfere with DLIs determined by the estimated value of (c),
Figure BDA00035016623200000513
and
Figure BDA00035016623200000514
are each Z1And Z2Derivative of, L1And L2Observer gain, in the form:
Figure BDA00035016623200000515
wherein
Figure BDA00035016623200000516
And
Figure BDA00035016623200000517
they are all normal numbers. In this example
Figure BDA00035016623200000518
Figure BDA00035016623200000519
And S3, designing a composite nonlinear dynamic inverse attitude controller of the flying wing unmanned aerial vehicle.
Aiming at the tracking error dynamics (5) of the flying wing unmanned aerial vehicle attitude system and combining the interference estimation information of the extended state observer
Figure BDA0003501662320000061
Constructing a composite nonlinear dynamic inverse attitude controller, wherein the design method comprises the following specific steps:
aiming at the tracking error dynamics (5) of the flying wing unmanned aerial vehicle attitude system, a composite nonlinear dynamic inverse attitude controller is designed:
Figure BDA0003501662320000062
wherein the information is estimated
Figure BDA0003501662320000063
Is obtained by an extended state observer (6),
Figure BDA0003501662320000064
is a controller parameter and has the following specific form:
Figure BDA0003501662320000065
wherein
Figure BDA0003501662320000066
And
Figure BDA0003501662320000067
is a normal number. In the present embodiment, the first and second electrodes are,
Figure BDA0003501662320000068
Figure BDA0003501662320000069
and S4, converting the expected torque into the deflection amount of the control surface of the flying wing unmanned aerial vehicle based on a pseudo-inverse method.
Based on virtual control quantity Γ obtained in S3nNamely, the control plane equation (2) of the flying wing unmanned aerial vehicle with the expected moment and the control plane fault considered is inversely solved based on a pseudo-inverse method to obtain the actual control quantity delta of the attitude system of the flying wing unmanned aerial vehicle:
δ＝B+Γn,
wherein, B+Is the generalized inverse matrix of B. In this embodiment:
Figure BDA00035016623200000610
in order to verify the anti-interference performance, the tracking error rapid convergence and the fault-tolerant performance of the method, the control algorithm is subjected to simulation verification based on an MATLAB simulation environment under the condition of considering multi-source interference and control surface faults. The initial values of the three attitude angular velocities in the simulation process are respectively set as:
φ(0)＝0，θ(0)＝0，ψ(0)＝0，p(0)＝0，q(0)＝0，r(0)＝0
to make the control task more challenging, the attitude angle command is set to a time-varying form as follows:
φd(t)＝5°，
Figure BDA00035016623200000611
ψd(t)＝3
wherein t is time. The external interference in the simulation process is set as follows:
Dx＝Dy＝Dz＝sin(t)
and consider the following fault scenario: the control surface has no fault in 0-5 seconds, the 8 # control surface is damaged by 20% after 5 seconds, the 4 # control surface is damaged by 20% after 10 seconds, and the 1 # control surface is blocked by 10% after 15 seconds.
The form and Controller parameters of the proposed Composite Nonlinear Dynamic Inverse Controller (CNDIC) have been given in the design examples. The form of a Nonlinear Dynamic Inverse Controller (NDCI) used for comparison and Controller parameters were designed as follows:
Figure BDA0003501662320000071
wherein the controller parameter
Figure BDA0003501662320000072
And
Figure BDA0003501662320000073
the value of (d) is the same as that of step S3.
The active disturbance rejection fault-tolerant control method of the flying wing unmanned aerial vehicle considering the control plane fault provided by the invention realizes the asymptotic tracking of the three-channel attitude angle reference instructions of rolling, pitching and yawing of the flying wing unmanned aerial vehicle under the simultaneous action of disturbance and fault. Fig. 2-4 are a three-channel tracking effect response curve, a three-channel tracking error response curve and a three-channel control quantity curve of the disturbed flying wing unmanned aerial vehicle of the Nonlinear Dynamic Inverse Controller (NDIC) and the proposed composite dynamic inverse controller (CNDIC), respectively. Therefore, the composite dynamic inverse attitude control method provided by the invention can realize higher-precision tracking of the attitude instruction. Figure 5 is a response curve of the control plane deflection angle of the flying wing drone. Fig. 6 is a response curve of the extended state observer to the disturbance estimation, and it can be seen that the extended state observer can achieve a high precision estimation of the lumped disturbance.
Compared with the traditional dynamic inverse control method, the method has better anti-interference capability and fault-tolerant capability, and effectively inhibits the influence of multi-source interference and control surface faults on the control performance of the flying wing unmanned aerial vehicle.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (5)

1. An active disturbance rejection fault-tolerant attitude control method of a flying wing unmanned aerial vehicle considering control plane faults is characterized by comprising the following steps:
s1, establishing a flying wing unmanned aerial vehicle attitude system considering control surface faults, wherein the flying wing unmanned aerial vehicle attitude system comprises an attitude system disturbed dynamics model and a control surface model considering control surface faults, and obtaining disturbed attitude system dynamics and attitude system tracking error dynamics according to the models;
s2, constructing an extended state observer based on the disturbed attitude system dynamic state, and obtaining a lumped disturbance estimation by combining an expected moment
Figure FDA0003501662310000011
S3, dynamically constructing a composite nonlinear dynamic inverse attitude controller based on the tracking error of the attitude system, and estimating the lumped interference observed by combining an extended state observer
Figure FDA0003501662310000012
Obtaining expected torque;
and S4, converting the expected torque into the control plane deflection of the flying wing unmanned aerial vehicle based on a pseudo-inverse method, forming a control plane deflection instruction and sending the control plane deflection instruction to the attitude system of the flying wing unmanned aerial vehicle.
2. The active disturbance rejection fault-tolerant attitude control method for flying wing drones considering control plane faults as claimed in claim 1, wherein step S1 specifically includes: :
s1.1, establishing an attitude system disturbed dynamics model of the flying wing unmanned aerial vehicle:
Figure FDA0003501662310000013
wherein s isφ，tθ，cφAnd cθDenotes sin phi, tan theta, cos phi and cos theta, respectively; phi, theta and psi respectively represent the roll angle, pitch angle and yaw angle of the flying wing drone,
Figure FDA0003501662310000014
and
Figure FDA0003501662310000015
denotes the first derivatives of phi, theta and psi, respectively; p, q and r respectively represent the rotation angular speeds of the flying-wing unmanned aerial vehicle around the x, y and z axes of the body,
Figure FDA0003501662310000016
Figure FDA0003501662310000017
and
Figure FDA0003501662310000018
first derivatives of p, q, and r, respectively; i isx，IyAnd IzRespectively representing the rotational inertia of the flying-wing unmanned aerial vehicle around the x, y and z axes of the body; i isxzRepresenting the product of inertia of the flying-wing drone; tau isx，τyAnd τzRespectively representing aerodynamic moments of the flying-wing unmanned aerial vehicle around x, y and z axes of the flying-wing unmanned aerial vehicle; dx，DyAnd DzRepresenting multi-source interference in three axial directions;
s1.2, establishing a flying wing unmanned aerial vehicle rudder surface model considering rudder surface faults:
Γ＝B[(I-Kf)δ+δf]＝Bδ+B(δf-Kfδ)＝Γn+Γf (2)
wherein Γ is a moment vector; b represents a control efficiency matrix of the control surface of the flying wing unmanned aerial vehicle; i is an identity matrix; kfRepresenting a fault coefficient matrix; delta denotes the deflection angle of the control surface of the flying wing drone, deltafRepresenting the dead angle of the control surface; gamma-shapednIndicating nominal aerodynamic moment, Γ, without control surface failurefIndicating a fault-induced aerodynamic moment;
s1.3, the following parameters are defined:
Figure FDA0003501662310000021
Δ＝IxIz-Ixz 2,
Figure FDA0003501662310000022
Figure FDA0003501662310000023
obtaining disturbed attitude system dynamics according to an attitude system disturbed dynamics model and a control surface model considering control surface faults:
Figure FDA0003501662310000024
wherein
Figure FDA0003501662310000025
Is the first derivative of W, DLLumped interference including multisource interference and control surface fault influence;
s1.4, defining the attitude tracking error of the flying wing unmanned aerial vehicle:
Figure FDA0003501662310000026
wherein Θ isd＝[φd θd ψd]TFor the expected attitude angle, the attitude system tracking error dynamics is:
Figure FDA0003501662310000027
wherein
Figure FDA0003501662310000028
And
Figure FDA0003501662310000029
respectively represent eΘThe second derivative and the first derivative of (a),
Figure FDA00035016623100000210
and
Figure FDA00035016623100000211
respectively represent thetadThe second derivative and the first derivative.
3. The active disturbance rejection fault-tolerant attitude control method of the flying wing drone considering the control surface fault as claimed in claim 2, wherein the step S2 specifically includes:
designing an extended state observer based on disturbed attitude system dynamics (4), estimating lumped disturbance:
Figure FDA0003501662310000031
wherein Z1And Z2In order to extend the dynamics of the state observer,
Figure FDA0003501662310000032
to interfere with DLIs determined by the estimated value of (c),
Figure FDA0003501662310000033
and
Figure FDA0003501662310000034
are each Z1And Z2Derivative of, L1And L2Is the observer gain.
4. The active disturbance rejection fault-tolerant attitude control method for flying wing drones considering control plane faults as claimed in claim 3, wherein step S3 specifically comprises:
based on the attitude angle tracking error dynamics (5) of the flying wing unmanned aerial vehicle considering the fault of the control surface and combined with the interference estimation information of the extended state observer, a composite dynamic inverse controller is constructed:
Figure FDA0003501662310000035
wherein, gamma isnEstimating information for virtual control quantities, i.e. desired moments
Figure FDA0003501662310000036
Is obtained by an extended state observer (6),
Figure FDA0003501662310000037
and
Figure FDA0003501662310000038
are controller parameters.
5. The active disturbance rejection fault-tolerant attitude control method for flying wing drones considering control plane faults as claimed in claim 4, wherein step S4 specifically includes:
based on virtual control quantity Γ obtained in S3nAnd considering a control plane equation (2) of the flying wing unmanned aerial vehicle with the control plane fault, and obtaining the actual control quantity delta of the attitude system of the flying wing unmanned aerial vehicle based on inverse solution of a pseudo-inverse method:
δ＝B+Γn,
wherein B is+Is the generalized inverse matrix of B.
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CN115903539B (en) * 2022-11-14 2023-08-01 南京航空航天大学 Aircraft rudder loop fault simulation method combining physical simulation platform
CN115629547A (en) * 2022-12-08 2023-01-20 西北工业大学 Airplane airborne fault-tolerant control method and system for control plane fault
CN115629547B (en) * 2022-12-08 2023-04-25 西北工业大学 Control surface fault-oriented aircraft airborne fault-tolerant control method and system
CN116088549A (en) * 2022-12-30 2023-05-09 西北工业大学 Tailstock type vertical take-off and landing unmanned aerial vehicle attitude control method
CN116339140B (en) * 2023-02-24 2023-09-12 大连理工大学 Composite fault-tolerant control method based on instantaneous active disturbance rejection and adaptive dynamic inversion
CN116185057A (en) * 2023-03-24 2023-05-30 西北工业大学 Attitude fault-tolerant control method for wing body fusion flying unmanned aerial vehicle
CN116185057B (en) * 2023-03-24 2023-09-01 西北工业大学 Attitude fault-tolerant control method for wing body fusion flying unmanned aerial vehicle
CN116203848A (en) * 2023-04-28 2023-06-02 西北工业大学 Fault sensing and protecting integrated driving method for aircraft elevator

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