CN110888451B - Fault-tolerant control method and system for multi-rotor unmanned aerial vehicle - Google Patents

Fault-tolerant control method and system for multi-rotor unmanned aerial vehicle Download PDF

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CN110888451B
CN110888451B CN201911322352.8A CN201911322352A CN110888451B CN 110888451 B CN110888451 B CN 110888451B CN 201911322352 A CN201911322352 A CN 201911322352A CN 110888451 B CN110888451 B CN 110888451B
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原辉
王帅
李劲松
姜敏
芦竹茂
侯少健
晋涛
王琪
白洋
杨虹
刘永鑫
赵亚宁
韩钰
孟晓凯
裴楚
武娜
田赟
郝丽花
郭婷
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State Grid Electric Power Research Institute Of Sepc
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    • G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
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    • G05D1/0816—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft to ensure stability
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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
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Abstract

The invention relates to a fault-tolerant control method and a fault-tolerant control system for a multi-rotor unmanned aerial vehicle, wherein the flight of the unmanned aerial vehicle is controlled by adopting an improved attitude control algorithm of linear active disturbance rejection control so as to ensure the robustness of the unmanned aerial vehicle in the flight process; when detecting that partial motor of unmanned aerial vehicle is unusual, construct trouble matrix R i (ii) a Based on the fault matrix R i Establishing a fault model on line; based on the fault matrix R i Obtaining control distribution information of all motors on the unmanned aerial vehicle; and controlling the flight of the unmanned aerial vehicle under the fault model by adopting the attitude control algorithm of the improved linear active disturbance rejection control, and controlling the unmanned aerial vehicle according to the control distribution information of the motor so as to achieve the required attitude and height. The control method and the control system improve the fault-tolerant capability of the multi-rotor unmanned aerial vehicle, and ensure that the multi-rotor unmanned aerial vehicle has larger load capacity and higher stability.

Description

Fault-tolerant control method and system for multi-rotor unmanned aerial vehicle
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a fault-tolerant control method and system for a multi-rotor unmanned aerial vehicle.
Background
In recent years, with the continuous progress of science and technology, the unmanned aerial vehicle, especially in the field of multi-rotor unmanned aerial vehicles with more than four rotors, has rapidly developed. Many rotor unmanned aerial vehicle is the aircraft that has been equipped with airborne equipment such as data processing and transmission system, sensor, automatic control system and communication system, can carry out certain steady state control and flight, possesses certain autonomous flight ability moreover. At present, many rotor crafts now have the wide application in fields such as agriculture and forestry plant protection, electric power are patrolled and examined, commodity circulation transportation, have made things convenient for people's production life to a very big degree.
When many rotor unmanned vehicles broke down, the flight state can take place the sudden change to cause the consequence that can not estimate, consequently, need design a fault-tolerant control method and improve many rotor unmanned aerial vehicle's fault-tolerant ability, thereby guarantee that many rotor unmanned aerial vehicle have bigger load capacity and higher stability.
Disclosure of Invention
The invention aims to solve the technical problem of providing a multi-rotor unmanned aerial vehicle fault-tolerant control method and system, which improve the fault-tolerant capability of the multi-rotor unmanned aerial vehicle and ensure that the multi-rotor unmanned aerial vehicle has greater load capacity and higher stability.
In order to solve the problems, the technical scheme adopted by the invention is as follows:
in one aspect, a fault-tolerant control method for a multi-rotor unmanned aerial vehicle is provided, which includes:
controlling the flight of the unmanned aerial vehicle by adopting an improved attitude control algorithm of linear active disturbance rejection control so as to ensure the robustness of the unmanned aerial vehicle in the flight process;
when detecting that partial motor of unmanned aerial vehicle is unusual, construct trouble matrix R i I is an integer which is more than or equal to 0 and less than or equal to the number of all motors in the unmanned aerial vehicle;
based on the fault matrix R i Establishing a fault model on line;
based on the fault matrix R i Obtaining control distribution information of all motors on the unmanned aerial vehicle;
and controlling the flight of the unmanned aerial vehicle under the fault model by adopting the attitude control algorithm of the improved linear active disturbance rejection control, and controlling the unmanned aerial vehicle according to the control distribution information of the motor so as to achieve the required attitude and height.
As a further improvement of the present invention, the attitude control algorithm of the improved linear active disturbance rejection control comprises:
arranging a transition process: converting an input abrupt signal into a slowly varying signal through a second-order link by adopting the following formula, and then enabling an output signal to reach an expected input signal:
Figure BDA0002327484090000011
wherein, G(s) represents a transfer function of a second-order link, T represents a time constant of the second-order link, and s represents a variable symbol in the transfer function;
linear extended state observer: the following state space equation and formula are adopted to realize real-time tracking of each variable in the model:
Figure BDA0002327484090000021
wherein x is 1 ,x 2 ,x 3 Respectively represent the state variables of the system being presented,
Figure BDA0002327484090000022
b 0 represents an estimated control gain, w represents an external disturbance, y represents an output of the model, and u represents an input of the model;
Figure BDA0002327484090000023
wherein z is 1 ,z 2 ,z 3 Respectively representing the system state variable, beta, of said linear extended state observer 1 ,β 2 ,β 3 Respectively, representing the gain of the linear extended state observer.
As a further improvement of the invention, when part of motors of the unmanned aerial vehicle are detected to be abnormal, a fault matrix R is constructed i The method comprises the following steps:
detecting all motors of the unmanned aerial vehicle in real time;
when detecting that part of motors of the unmanned aerial vehicle are abnormal, calculating the ratio of the output of a fault motor to the output of the unmanned aerial vehicle without faults, and constructing a fault matrix R according to the ratio i 。
As a further improvement of the invention, the fault matrix R is based on i Establishing a fault model on line, comprising:
establishing a fault model on line by adopting the following formula:
Figure BDA0002327484090000024
wherein
Figure BDA0002327484090000025
Respectively represent the position acceleration under the geodetic coordinate system,
Figure BDA0002327484090000026
angular accelerations respectively representing the attitude angles of the unmanned aerial vehicle in the geodetic coordinate system,
Figure BDA0002327484090000027
theta, psi stands for roll, pitch and yaw angle, respectively, I x ,I y ,I z Respectively representing the rotational inertia of the unmanned aerial vehicle body in three directions, m representing the mass of the unmanned aerial vehicle, g representing the gravity acceleration, and U representing the mass of the unmanned aerial vehicle R ,U P ,U Y ,U T Respectively representing roll moment, pitch moment, yaw moment and lift force when the motors of the unmanned aerial vehicle have no faults, f p ,f q ,f r ,f z Respectively representing roll moment error, pitch moment error, yaw moment error and lift error.
As a further improvement of the invention, the fault matrix R is based on i Obtaining control distribution information of all motors on the unmanned aerial vehicle, including:
obtaining an optimized distribution matrix N by adopting the following formula f The optimized distribution matrix N is used f As control distribution information of all motors on the unmanned aerial vehicle:
N f ＝A f-1 ；
N f ＝A fT (A f ·A fT ) -1 (ii) a Wherein A is f Representing the control efficiency matrix after partial motor failure, A fT Represents A f Transposing;
A f ＝AR i (ii) a Wherein A represents a control efficiency matrix before failure;
Figure BDA0002327484090000031
wherein, b is the lift coefficient, and l is unmanned aerial vehicle's wheel base, and d is the reaction torque coefficient.
In another aspect, a fault-tolerant control system for a multi-rotor drone is provided, comprising:
the first control module is used for controlling the flight of the unmanned aerial vehicle by adopting an attitude control algorithm of improved linear active disturbance rejection control so as to ensure the robustness of the unmanned aerial vehicle in the flight process;
a fault matrix construction module for constructing a fault matrix R when detecting that part of the motors of the unmanned aerial vehicle are abnormal i I is an integer which is more than or equal to 0 and less than or equal to the number of all motors in the unmanned aerial vehicle;
a fault model building module for building a fault matrix R based on the fault matrix i Establishing a fault model on line;
a distribution information acquisition module for acquiring distribution information based on the fault matrix R i Obtaining control distribution information of all motors on the unmanned aerial vehicle;
and the second control module controls the flight of the unmanned aerial vehicle under the fault model by adopting the attitude control algorithm of the improved linear active disturbance rejection control, and controls the unmanned aerial vehicle according to the control distribution information of the motor so as to achieve the required attitude and height.
As a further improvement of the present invention, the fault matrix building module comprises:
arranging a transition process unit for converting an input abrupt signal into a slowly varying signal through a second-order link by adopting the following formula, and then enabling an output signal to reach an expected input signal:
Figure BDA0002327484090000032
wherein G(s) represents a transfer function of the second-order element, T represents a time constant of the second-order element, and s representsRepresenting the variable symbols in the transfer function;
the linear extended state observer unit is used for tracking each variable in the model in real time by adopting the following state space equation and formula:
Figure BDA0002327484090000041
wherein x is 1 ,x 2 ,x 3 Respectively represent the state variables of the system being monitored,
Figure BDA0002327484090000042
b 0 represents an estimated control gain, w represents an external disturbance, y represents an output of the model, and u represents an input of the model;
Figure BDA0002327484090000043
wherein z is 1 ,z 2 ,z 3 Respectively representing the system state variable, beta, of said linear extended state observer 1 ,β 2 ,β 3 Respectively, representing the gain of the linear extended state observer.
As a further improvement of the present invention, the fault model building module includes:
the detection unit is used for detecting all motors of the unmanned aerial vehicle in real time;
a fault model establishing unit for calculating the ratio of the output of the fault motor to the output without fault when detecting that part of the motors of the unmanned aerial vehicle are abnormal, and establishing a fault matrix R according to the ratio i 。
As a further improvement of the present invention, the fault model building module includes:
the fault model establishing unit is used for establishing a fault model on line by adopting the following formula:
Figure BDA0002327484090000044
wherein
Figure BDA0002327484090000045
Respectively represent the position acceleration under the geodetic coordinate system,
Figure BDA0002327484090000046
angular accelerations respectively representing the attitude angles of the unmanned aerial vehicle in the geodetic coordinate system,
Figure BDA0002327484090000047
theta, psi stands for roll, pitch and yaw angle, respectively, I x ,I y ,I z Respectively representing the rotational inertia of the unmanned aerial vehicle body in three directions, m representing the mass of the unmanned aerial vehicle, g representing the gravity acceleration, and U representing the mass of the unmanned aerial vehicle R ,U P ,U Y ,U T Respectively representing roll moment, pitch moment, yaw moment and lift force when the motors of the unmanned aerial vehicle have no faults, f p ,f q ,f r ,f z Respectively representing roll moment error, pitch moment error, yaw moment error and lift error.
As a further improvement of the present invention, the allocation information obtaining module includes:
an allocation information obtaining unit for obtaining the optimized allocation matrix N by using the following formula f The optimized distribution matrix N is used f As control distribution information of all motors on the unmanned aerial vehicle:
N f ＝A f-1 ；
N f ＝A fT (A f ·A fT ) -1 (ii) a Wherein A is f Representing the control efficiency matrix after partial motor failure, A fT Represents A f Transposing;
A f ＝AR i (ii) a Wherein A represents a control efficiency matrix before failure;
Figure BDA0002327484090000051
wherein b is literAnd the force coefficient, i, is the wheelbase of the unmanned aerial vehicle, and d, is the reaction torque coefficient.
Adopt the produced beneficial effect of above-mentioned technical scheme to lie in:
according to the fault-tolerant control method and the fault-tolerant control system for the multi-rotor unmanned aerial vehicle, which are provided by the embodiment of the invention, the flight of the unmanned aerial vehicle is controlled by adopting an improved attitude control algorithm of linear active disturbance rejection control, so that the robustness of the unmanned aerial vehicle in the flight process is ensured; when detecting that partial motors of the unmanned aerial vehicle are abnormal, constructing a fault matrix R i (ii) a Based on the fault matrix R i Establishing a fault model on line; based on the fault matrix R i Obtaining control distribution information of all motors on the unmanned aerial vehicle; and controlling the flight of the unmanned aerial vehicle under the fault model by adopting the attitude control algorithm of the improved linear active disturbance rejection control, and controlling the unmanned aerial vehicle according to the control distribution information of the motor so as to achieve the required attitude and height. When the motor of the unmanned aerial vehicle does not break down, the selected basic control law is an improved attitude control algorithm of linear active disturbance rejection control, and the control algorithm has strong robustness to disturbance. Moreover, when part of motors of the unmanned aerial vehicle have faults, a new flight model-fault model and control distribution information of all the motors can be obtained based on a fault matrix after the faults occur, so that the unmanned aerial vehicle can fly in the fault mode, and meanwhile, the use of the fault motors can be reduced, and the unmanned aerial vehicle can reach a stable flight state.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a fault-tolerant control method for a multi-rotor unmanned aerial vehicle according to an embodiment of the present invention.
Fig. 2 is a response graph of roll angle of a system without distribution optimization when a first fault occurs according to an embodiment of the present invention.
Fig. 3 is a response graph of a pitch angle of a system without allocation optimization when a first fault occurs according to an embodiment of the present invention.
Fig. 4 is a response graph of yaw angle of a system without optimization allocation when a first fault occurs according to an embodiment of the present invention.
Fig. 5 is a comparison graph of the roll angle when the system performs the distribution optimization in the first failure and when no failure occurs according to the embodiment of the present invention.
Fig. 6 is a diagram of pitch angle comparison between the first failure and the non-failure of the system for allocation optimization according to the embodiment of the present invention.
Fig. 7 is a diagram comparing the yaw angle when the system performs the allocation optimization in the case of the first failure and the yaw angle when the system does not perform the failure according to the embodiment of the present invention.
Fig. 8 is a response graph of roll angle of a system without distribution optimization when a second fault occurs according to an embodiment of the present invention.
Fig. 9 is a response curve of a pitch angle of a system without optimization of allocation when a second fault occurs according to an embodiment of the present invention.
Fig. 10 is a response graph of yaw angle of a system without optimization of allocation when a second fault occurs according to an embodiment of the present invention.
Fig. 11 is a comparison graph of the roll angle when the system performs the distribution optimization when the second failure occurs and when the second failure does not occur according to the embodiment of the present invention.
Fig. 12 is a diagram of pitch angle comparison between the system performing assignment optimization in the case of a second fault and the system performing no fault, according to an embodiment of the present invention.
Fig. 13 is a diagram comparing the yaw angle of a system performing allocation optimization when a second fault occurs and when no fault occurs according to an embodiment of the present invention.
Fig. 14 is a structural diagram of a fault-tolerant control system for a multi-rotor drone according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail and fully with reference to the accompanying drawings and specific embodiments.
At present, many rotor unmanned aerial vehicle mainly divide into: four rotor unmanned aerial vehicle and the many rotor unmanned aerial vehicle more than four rotors, four rotor unmanned aerial vehicle lack the redundancy of rotor subassembly, in case send the trouble, the sudden change takes place for the flight gesture, can cause the consequence that can not estimate in some application. And to many rotor unmanned aerial vehicle more than four rotors, can make many rotor unmanned aerial vehicle have fine fault-tolerant ability, bigger load capacity and higher stability through the optimal control algorithm to guarantee that unmanned aerial vehicle still has good stability and security when running into strong external force interference or partial motor impaired, thereby can carry more task equipment, accomplish more complicated task.
Based on this, the multi-rotor unmanned aerial vehicle related to the invention refers to a multi-rotor unmanned aerial vehicle with more than four rotors.
Fig. 1 and fig. 2 are flowcharts of a fault-tolerant control method for a multi-rotor drone, according to the present invention, as shown in fig. 1 and fig. 2, the fault-tolerant control method includes:
s101: and controlling the flight of the unmanned aerial vehicle by adopting an attitude control algorithm of improved linear active disturbance rejection control so as to ensure the robustness of the unmanned aerial vehicle in the flight process.
The attitude control algorithm of the improved linear active disturbance rejection control comprises the following steps:
(1) Arranging a transition process: converting an input abrupt change signal into a slowly changing signal through a second-order link by adopting the following formula, and enabling an output signal to reach an expected input signal:
Figure BDA0002327484090000071
wherein G(s) represents a transfer function of the second order element, T represents a time constant of the second order element, and T can be taken as an expected transition time
Figure BDA0002327484090000072
s represents the sign of the variable in the transfer function and is a complex parameter.
(2) Linear extended state observer: the following state space equation and formula are adopted to realize real-time tracking of each variable in the model:
Figure BDA0002327484090000073
wherein x is 1 ,x 2 ,x 3 Respectively represent the state variables of the system,
Figure BDA0002327484090000074
b 0 represents the estimated control gain, w represents the external disturbance, y represents the output of the model, and u represents the input of the model;
Figure BDA0002327484090000075
wherein z is 1 ,z 2 ,z 3 Respectively representing the system state variable, beta, of a linear extended state observer 1 ,β 2 ,β 3 Respectively, represent the gain of the linear extended state observer.
It should be noted that, the multi-rotor unmanned aerial vehicle mainly changes the flying attitude of the unmanned aerial vehicle by changing the rotating speed of the motor corresponding to each rotor, the rotating speed of the motor is changed by changing the duty ratio of the PWM signal, after the rotating speed of the motor is changed, the lift force and the torque generated by the motor are changed, and meanwhile, the torque in the roll direction and the pitch direction and the counter torque in the yaw direction are determined according to the position distribution of the motor of the multi-rotor unmanned aerial vehicle. The changes of the rolling direction and the pitching direction generate linear speeds of the X-axis direction and the Y-axis direction of the airplane, the change of the yaw angle is the change of the heading of the airplane, and the change of the lifting force generates the change of the Z-axis, namely the height of the airplane.
Wherein, the body coordinate system is defined as: the origin is taken at the mass center of the unmanned aerial vehicle, and a coordinate system is fixedly connected with the body; the X axis is parallel to the longitudinal axis designed for the machine body, is positioned in the symmetrical plane of the unmanned aerial vehicle and points to the front; the Y axis is vertical to the symmetry plane of the unmanned aerial vehicle and points to the right; the Z axis is in the unmanned aerial vehicle symmetry plane, and perpendicular to X axis point down. The entire coordinate system conforms to the euler coordinate system right hand rule. The ground coordinate system, i.e., the inertial coordinate system, is defined as: using the North-east-Earth coordinate system, the XE axis points to the North, the YE axis points to the east, and the ZE axis points to the Earth's center. The ground coordinate system is a coordinate system in the environment of the simulation experiment.
And the unmanned aerial vehicle distributes actual control instructions of each motor to the control distribution information according to virtual control instructions generated by user operation. Under the condition that the four motors are normal, the control distribution information is a fixed value and is not changed. However, when some motors of the unmanned aerial vehicle are out of order, the motors cannot correctly respond to the actual distributed control instructions, that is, the motors cannot adjust the same control instructions to the corresponding rotating speeds, and cannot meet the control requirements, so that the control distribution information needs to be optimally redistributed.
S102: when detecting that part of motors of the unmanned aerial vehicle are abnormal, constructing a fault matrix Ri, wherein i is an integer which is more than or equal to 0 and less than or equal to the number of all the motors in the unmanned aerial vehicle.
Wherein, this step includes:
s1021: all motors of the unmanned aerial vehicle are detected in real time.
S1022: when detecting that part of motors of the unmanned aerial vehicle are abnormal, calculating the ratio of the output of the fault motor to the output of the fault-free motor, and constructing a fault matrix according to the ratio.
Regarding the mode of judging that some motors are unusual, in a possible implementation mode, in unmanned aerial vehicle flight in-process, the user accessible promotes the rocker of remote controller in order to send control command to unmanned aerial vehicle flight control system, unmanned aerial vehicle flight control system receives behind the control command, solve link and attitude control link through inside gesture and export certain controlled variable to every electricity accent, later every electricity accent output with the rotational speed of the motor that this controlled variable corresponds with the control, promptly, every PWM value of electricity accent output corresponds with control command. Therefore, when the PWM value output by a certain electric regulation does not correspond to the control command, the motor corresponding to the electric regulation is determined to have a fault.
When detecting that unmanned aerial vehicle's part motor is unusual, unmanned aerial vehicle flight control system acquires the output value of all motors, promptly, the efficiency of motor. In the embodiment of the invention, the efficiency of the motor without faults is set to be 1; the motor efficiency in the case of a failure is a quantized value of the output of the failed motor with respect to the normal output. The efficiency of each motor is respectively expressed by k 1 ,k 2 …k i Expressing, then constructing the obtained fault matrix R i Comprises the following steps:
R i ＝diag[k 1 ,k 2 …k i ]。
for example: this many rotor unmanned aerial vehicle is six rotor unmanned aerial vehicle, and with six motors on this six rotor unmanned aerial vehicle respectively the reference numeral be 1-6, the efficiency that leads to its motor when No. 1 motor and No. 2 motor because breaking down is k respectively 1 ,k 2 In time, this six rotor unmanned aerial vehicle's trouble matrix does:
Figure BDA0002327484090000091
s103: based on fault matrix R i And establishing a fault model on line.
Establishing a fault model on line by adopting the following formula:
Figure BDA0002327484090000092
wherein, the first and the second end of the pipe are connected with each other,
Figure BDA0002327484090000093
respectively represent the position acceleration under the geodetic coordinate system,
Figure BDA0002327484090000094
respectively representing the angular acceleration of the attitude angle of the unmanned aerial vehicle under the geodetic coordinate system,
Figure BDA0002327484090000095
theta, psi representing roll angle, pitch angle and yaw, respectivelyNavigation angle, I x ,I y ,I z Respectively represent the rotary inertia of the unmanned aerial vehicle body in three directions, m represents the mass of the unmanned aerial vehicle, g represents the gravity acceleration, and U represents R ,U P ,U Y ,U T Respectively representing roll moment, pitch moment, yaw moment and lift force when the motors of the unmanned aerial vehicle have no faults, f p ,f q ,f r ,f z Respectively representing roll moment error, pitch moment error, yaw moment error and lift error.
As described above
Figure BDA0002327484090000096
Available through sensors including tri-axial accelerometers to measure acceleration and tri-axial gyroscopes to measure angular velocity.
f p ,f q ,f r ,f z Can be derived from the fault matrix R i Obtained, wherein f is p ,f q ,f r ,f z In relation to the number of rotors of the drone and the type of layout of the rotors, f can be obtained, in general, once the number of rotors and the type of rotors of the drone are determined p ,f q ,f r ,f z 。
In a possible implementation mode, when the multi-rotor unmanned aerial vehicle is an X-shaped six-rotor unmanned aerial vehicle, six motors on the six-rotor unmanned aerial vehicle are respectively marked as 1-6, the included angle between each shaft is 60 degrees, and the following mode can be adopted to obtain the roll moment U when the motors of the unmanned aerial vehicle are not in fault R Pitching moment U P Yaw moment U Y And a lift force U T ：
Figure BDA0002327484090000101
The motor efficiency of the No. 1 motor is k after the No. 1 motor fails 1 When other motors are not in fault, the fault matrix R 6 Comprises the following steps:
Figure BDA0002327484090000102
the following method can be adopted to obtain the roll moment when part of motors of the unmanned aerial vehicle have faults
Figure BDA0002327484090000103
Pitching moment
Figure BDA0002327484090000104
Yawing moment
Figure BDA0002327484090000105
And lift force
Figure BDA0002327484090000106
Figure BDA0002327484090000107
Wherein, the above
Figure BDA0002327484090000108
Respectively represent the corresponding rotating speed of each motor when the motors No. 1-6 are not in fault.
Then, the following formula is adopted to obtain the rolling moment error f p Pitching moment error f q Yaw moment error f r And lift error f z ：
Figure BDA0002327484090000109
S104: based on a fault matrix R i And obtaining control distribution information of all motors on the unmanned aerial vehicle.
Obtaining an optimized distribution matrix N by adopting the following formula f The optimized distribution matrix N f As control distribution information of all motors on the unmanned aerial vehicle:
N f ＝A f-1 ；
N f ＝A fT (A f ·A fT ) -1 (ii) a Wherein, A f Representing partial motor failureThe latter control efficiency matrix, A fT Represents A f Transposing;
A f ＝AR i (ii) a Wherein A represents a control efficiency matrix before failure;
Figure BDA0002327484090000111
wherein, b is the lift coefficient, and l is unmanned aerial vehicle's wheel base, and d is the reaction torque coefficient.
S105: and controlling the flight of the unmanned aerial vehicle under the fault model by adopting an improved attitude control algorithm of linear active disturbance rejection control, and controlling the unmanned aerial vehicle according to control distribution information of the motor so as to achieve the required attitude and height.
And adjusting the rotating speed of each motor according to the actual control instruction, and further driving the unmanned aerial vehicle to reach the required posture and height by each motor. Attitude includes pitch, roll and yaw.
For example, the rotational speed of each motor may be adjusted using the following equation:
τ f ＝[U R U P U Y U T ] T (ii) a Wherein, tau f A representative moment matrix;
Figure BDA0002327484090000112
wherein the content of the first and second substances,
Figure BDA0002327484090000113
the partial motor of the unmanned aerial vehicle is abnormal, and the rotating speed corresponding to each motor is represented.
In the embodiment of the invention, the unmanned aerial vehicle flight control system distributes virtual control instructions to the actuating mechanism according to user operation, and when the rotating speed of the motor in the actuating mechanism changes, the unmanned aerial vehicle flight control system optimizes the control distribution information of each motor based on new control distribution information in the process of controlling the unmanned aerial vehicle to fly by adopting an attitude control algorithm of improved linear active disturbance rejection control; the rolling moment error f generated by the motor fault is compensated according to the established fault model p Pitching momentError f q Yaw moment error f r And lift error f z Therefore, the height and the attitude of the unmanned aerial vehicle are changed, and the height and the attitude which are required to be reached by the unmanned aerial vehicle are reached.
In addition, the embodiment of the invention adopts a six-rotor unmanned aerial vehicle as an object, and simulation verification is carried out on the fault-tolerant control method, as shown in fig. 2-13, and fig. 2-13 are all graphs obtained under the condition that the expected roll angle, the pitch angle and the yaw angle are given as 15 degrees, and the expected height is given as 1 m.
Fig. 2-4 are response graphs of roll angle, pitch angle and yaw angle of the system without distribution optimization when the efficiency of the motor 1 is 1/5. As can be seen from fig. 2 to 4, when the force effect of the motor 1 is 1/5 and the fault-tolerant control method for the unmanned aerial vehicle provided by the embodiment of the present invention is not adopted, the three attitude angles cannot be stabilized along with the input expected attitude angle.
Fig. 5-7 are graphs comparing roll angle, pitch angle and yaw angle when the system performs distribution optimization and has no fault when the efficiency of the motor number 1 is 1/5, wherein (a) lines represent three attitude angles when the system performs distribution optimization, and (b) lines represent three attitude angles when the system has no fault. As can be seen from fig. 5 to 7, after the fault-tolerant control method for the unmanned aerial vehicle provided by the embodiment of the present invention is adopted, compared with a flight condition without a fault, although the flight condition is not stable for a long time, the flight condition still can track an expected value well and reach final stability.
Fig. 8-10 are graphs of response curves of roll angle, pitch angle and yaw angle of the system without distribution optimization when the efficiency of the motor No. 1 is 1/2 respectively. As can be seen from fig. 8 to 10, when the force effect of the motor 1 is 1/2 and the fault-tolerant control method for the unmanned aerial vehicle provided by the embodiment of the present invention is not adopted, the three attitude angles cannot be stable and vibrate obviously along with the input expected attitude angle.
Fig. 11-13 are graphs comparing roll angle, pitch angle and yaw angle for the system with assignment optimization and without failure for motor number 1 with efficiency of 1/2, respectively, where (a) lines represent the three attitude angles for the system with assignment optimization, and (b) lines represent the three attitude angles without failure. As can be seen from fig. 11 to fig. 13, after the fault-tolerant control method for the unmanned aerial vehicle provided by the embodiment of the present invention is adopted, compared with a flight condition without a fault, although the flight condition is not stable for a long time, the flight condition can still track an expected value well and reach final stability.
According to the fault-tolerant control method for the multi-rotor unmanned aerial vehicle, the flight of the unmanned aerial vehicle is controlled by adopting an improved attitude control algorithm of linear active disturbance rejection control, so that the robustness of the unmanned aerial vehicle in the flight process is ensured; when part of motors of the unmanned aerial vehicle are detected to be abnormal, a fault matrix R is constructed i (ii) a Based on a fault matrix R i Establishing a fault model on line; based on fault matrix R i Obtaining control distribution information of all motors on the unmanned aerial vehicle; and controlling the flight of the unmanned aerial vehicle under the fault model by adopting an improved attitude control algorithm of linear active disturbance rejection control, and controlling the unmanned aerial vehicle according to control distribution information of the motor so as to achieve the required attitude and height. When the motor of the unmanned aerial vehicle does not break down, the selected basic control law is an improved attitude control algorithm of linear active disturbance rejection control, and the control algorithm has strong robustness to disturbance. Moreover, when part of motors of the unmanned aerial vehicle have faults, a new flight model-fault model and control distribution information of all the motors can be obtained based on a fault matrix after the faults occur, so that the unmanned aerial vehicle can fly in the fault mode, and meanwhile, the use of the fault motors can be reduced, and the unmanned aerial vehicle can reach a stable flight state.
Fig. 14 is a structural diagram of a fault-tolerant control system for a multi-rotor drone according to an embodiment of the present invention, as shown in fig. 14, the fault-tolerant control system includes:
the first control module 1401 is configured to control the flight of the unmanned aerial vehicle by using an attitude control algorithm of improved linear active disturbance rejection control, so as to ensure the robustness of the unmanned aerial vehicle in the flight process;
a fault matrix constructing module 1402 for constructing a fault matrix R when detecting that part of the motors of the unmanned aerial vehicle are abnormal i I is an integer which is more than or equal to 0 and less than or equal to the number of all motors in the unmanned aerial vehicle;
a fault model building block 1403 for fault-based modelingBarrier matrix R i Establishing a fault model on line;
an assignment information obtaining module 1404 for obtaining a distribution matrix R based on the fault matrix i Obtaining control distribution information of all motors on the unmanned aerial vehicle;
the second control module 1405 controls the flight of the unmanned aerial vehicle under the fault model by adopting an attitude control algorithm of the improved linear active disturbance rejection control, and controls the unmanned aerial vehicle according to the control distribution information of the motor so as to achieve the required attitude and height.
The first control module 1401 and the second control module 1405 may be the same control module.
In one possible implementation, the fault matrix building module 1402 includes:
arranging a transition process unit for converting an input abrupt signal into a slowly varying signal through a second-order link by adopting the following formula, and then enabling an output signal to reach an expected input signal:
Figure BDA0002327484090000131
wherein, G(s) represents a transfer function of a second-order link, T represents a time constant of the second-order link, and s represents a variable symbol in the transfer function;
the linear extended state observer unit is used for tracking each variable in the model in real time by adopting the following state space equation and formula:
Figure BDA0002327484090000132
wherein x is 1 ,x 2 ,x 3 Respectively represent the state variables of the system being monitored,
Figure BDA0002327484090000133
b 0 represents the estimated control gain, w represents the external disturbance, y represents the output of the model, and u represents the input of the model;
Figure BDA0002327484090000134
wherein z is 1 ,z 2 ,z 3 Respectively, representing the system state variable, beta, of a linear extended state observer 1 ,β 2 ,β 3 Respectively, represent the gain of the linear extended state observer.
In one possible implementation, the fault model building module 1403 includes:
the detection unit is used for detecting all motors of the unmanned aerial vehicle in real time;
a fault model establishing unit for calculating the ratio of the output of the fault motor to the output without fault when detecting the abnormity of partial motor of the unmanned aerial vehicle, and establishing a fault matrix R according to the ratio i 。
In one possible implementation, the fault model building module 1403 includes:
the fault model establishing unit is used for establishing a fault model on line by adopting the following formula:
Figure BDA0002327484090000135
wherein
Figure BDA0002327484090000136
Respectively represent the position acceleration under the geodetic coordinate system,
Figure BDA0002327484090000137
respectively representing the angular acceleration of the attitude angle of the unmanned aerial vehicle under the geodetic coordinate system,
Figure BDA0002327484090000138
theta, psi stands for roll, pitch and yaw angle, respectively, I x ,I y ,I z Respectively represent the inertia of unmanned aerial vehicle fuselage in three directions, and m represents unmanned aerial vehicle's quality, and g represents acceleration of gravity, U R ,U P ,U Y ,U T Respectively representing roll moment, pitch moment, yaw moment and lift force when the motors of the unmanned aerial vehicle have no faults, f p ,f q ,f r ,f z Respectively representing roll moment error, pitch moment error, yaw moment error and lift error.
In one possible implementation, the allocation information obtaining module 1404 includes:
an allocation information obtaining unit for obtaining the optimized allocation matrix N by using the following formula f The optimized distribution matrix N f As control distribution information of all motors on the unmanned aerial vehicle:
N f ＝A f-1 ；
N f ＝A fT (A f ·A fT ) -1 (ii) a Wherein A is f Representing the control efficiency matrix after partial motor failure, A fT Represents A f Transposing;
A f ＝AR i (ii) a Wherein A represents a control efficiency matrix before failure;
Figure BDA0002327484090000141
wherein, b is the lift coefficient, and l is unmanned aerial vehicle's wheel base, and d is the reaction torque coefficient.
According to the fault-tolerant control system for the multi-rotor unmanned aerial vehicle, the flight of the unmanned aerial vehicle is controlled by adopting an improved attitude control algorithm of linear active disturbance rejection control, so that the robustness of the unmanned aerial vehicle in the flight process is ensured; when part of motors of the unmanned aerial vehicle are detected to be abnormal, a fault matrix R is constructed i (ii) a Based on fault matrix R i Establishing a fault model on line; based on fault matrix R i Obtaining control distribution information of all motors on the unmanned aerial vehicle; and controlling the flight of the unmanned aerial vehicle under the fault model by adopting an improved attitude control algorithm of linear active disturbance rejection control, and controlling the unmanned aerial vehicle according to control distribution information of the motor so as to achieve the required attitude and height. When the motor of the unmanned aerial vehicle does not break down, the selected basic control law is an attitude control algorithm of improved linear active disturbance rejection control, and the control algorithm has strong robustness to disturbance. Moreover, when unmanned aerial vehicle's partial motor broke down, can also be based on the event after breaking downAnd the barrier matrix is used for obtaining a new flight model-fault model and control distribution information of all motors, so that the unmanned aerial vehicle can fly in the fault mode, and meanwhile, the use of fault motors can be reduced, and the unmanned aerial vehicle can reach a stable flight state.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (8)

1. A fault-tolerant control method for a multi-rotor unmanned aerial vehicle is characterized by comprising the following steps:
controlling the flight of the unmanned aerial vehicle by adopting an improved attitude control algorithm of linear active disturbance rejection control so as to ensure the robustness of the unmanned aerial vehicle in the flight process;
when detecting that partial motor of unmanned aerial vehicle is unusual, construct trouble matrix R i I is an integer which is more than or equal to 0 and less than or equal to the number of all motors in the unmanned aerial vehicle;
based on the fault matrix R i Establishing a fault model on line;
based on the fault matrix R i Obtaining control distribution information of all motors on the unmanned aerial vehicle;
controlling the flight of the unmanned aerial vehicle under the fault model by adopting the attitude control algorithm of the improved linear active disturbance rejection control, and controlling the unmanned aerial vehicle according to the control distribution information of the motor so as to achieve the required attitude and height;
based on the fault matrix R i Establishing a fault model on line, comprising:
establishing a fault model on line by adopting the following formula:
Figure FDA0003886206230000011
wherein
Figure FDA0003886206230000012
Respectively represent the position acceleration under the geodetic coordinate system,
Figure FDA0003886206230000013
angular accelerations respectively representing the attitude angles of the unmanned aerial vehicle in the geodetic coordinate system,
Figure FDA0003886206230000014
theta, psi stands for roll, pitch and yaw angle, respectively, I x ,I y ,I z Respectively represent the rotational inertia of the unmanned aerial vehicle body in three directions, m represents the mass of the unmanned aerial vehicle, g represents the gravity acceleration, and U represents R ,U P ,U Y ,U T Respectively representing roll moment, pitch moment, yaw moment and lift force when the motors of the unmanned aerial vehicle have no faults, f p ,f q ,f r ,f z Respectively representing roll moment error, pitch moment error, yaw moment error and lift error.
2. The fault-tolerant control method for multi-rotor unmanned aerial vehicles according to claim 1, wherein the attitude control algorithm of the improved linear active disturbance rejection control comprises:
arranging a transition process: converting an input abrupt signal into a slowly varying signal through a second-order link by adopting the following formula, and then enabling an output signal to reach an expected input signal:
Figure FDA0003886206230000015
wherein, G(s) represents a transfer function of a second-order link, T represents a time constant of the second-order link, and s represents a variable symbol in the transfer function;
linear extended state observer: the following state space equation and formula are adopted to realize real-time tracking of each variable in the model:
Figure FDA0003886206230000021
wherein x is 1 ,x 2 ,x 3 Respectively represent the state variables of the system being monitored,
Figure FDA0003886206230000022
b 0 represents the estimated control gain, w represents the external disturbance, y represents the output of the model, and u represents the input of the model;
Figure FDA0003886206230000023
wherein z is 1 ,z 2 ,z 3 Respectively representing the system state variable, beta, of said linear extended state observer 1 ,β 2 ,β 3 Respectively, representing the gain of the linear extended state observer.
3. The fault-tolerant control method for multi-rotor unmanned aerial vehicle of claim 1, wherein a fault matrix R is constructed when part of motors of the unmanned aerial vehicle are detected to be abnormal i The method comprises the following steps:
detecting all motors of the unmanned aerial vehicle in real time;
when detecting that part of motors of the unmanned aerial vehicle are abnormal, calculating the ratio of the output of a fault motor to the output of the unmanned aerial vehicle without faults, and constructing a fault matrix R according to the ratio i 。
4. The fault-tolerant control method for multi-rotor unmanned aerial vehicle of claim 1, wherein the fault matrix R is based on i Obtaining control distribution information of all motors on the unmanned aerial vehicle, including:
obtaining an optimized distribution matrix N by adopting the following formula f The optimized distribution matrix N is used f As control distribution information of all motors on the unmanned aerial vehicle:
N f ＝A f-1 ；
N f ＝A fT (A f ·A fT ) -1 (ii) a Wherein, A f Representing the control efficiency matrix after partial motor failure, A fT Represents A f Transposing;
A f ＝AR i (ii) a Wherein A represents a control efficiency matrix before failure;
Figure FDA0003886206230000024
wherein, b is the lift coefficient, l is unmanned aerial vehicle's wheel base, and d is the reaction torque coefficient.
5. The utility model provides a many rotor unmanned aerial vehicle fault-tolerant control system which characterized in that, it includes:
the first control module is used for controlling the flight of the unmanned aerial vehicle by adopting an attitude control algorithm of improved linear active disturbance rejection control so as to ensure the robustness of the unmanned aerial vehicle in the flight process;
a fault matrix construction module for constructing a fault matrix R when detecting that part of the motors of the unmanned aerial vehicle are abnormal i I is an integer which is more than or equal to 0 and less than or equal to the number of all motors in the unmanned aerial vehicle;
a fault model building module for building a fault matrix R based on the fault matrix i Establishing a fault model on line;
an allocation information acquisition module for acquiring the allocation information based on the fault matrix R i Obtaining control distribution information of all motors on the unmanned aerial vehicle;
the second control module controls the flight of the unmanned aerial vehicle under the fault model by adopting the attitude control algorithm of the improved linear active disturbance rejection control, and controls the unmanned aerial vehicle according to the control distribution information of the motor so as to achieve the required attitude and height;
the fault model building module comprises: the fault model establishing unit is used for establishing a fault model on line by adopting the following formula:
Figure FDA0003886206230000031
wherein
Figure FDA0003886206230000032
Respectively represent the position acceleration under the geodetic coordinate system,
Figure FDA0003886206230000033
angular accelerations respectively representing the attitude angles of the unmanned aerial vehicle in the geodetic coordinate system,
Figure FDA0003886206230000034
theta, psi stands for roll, pitch and yaw angle, respectively, I x ,I y ,I z Respectively represent the rotational inertia of the unmanned aerial vehicle body in three directions, m represents the mass of the unmanned aerial vehicle, g represents the gravity acceleration, and U represents R ,U P ,U Y ,U T Respectively representing roll moment, pitch moment, yaw moment and lift force when the motors of the unmanned aerial vehicle have no faults, f p ,f q ,f r ,f z Respectively representing roll moment error, pitch moment error, yaw moment error and lift force error.
6. The fault-tolerant control system for multi-rotor drones according to claim 5, wherein the fault matrix building module comprises:
arranging a transition process for converting an input abrupt signal into a slowly varying signal through a second-order link and then making an output signal reach a desired input signal by using the following formula:
Figure FDA0003886206230000041
wherein G(s) representsT represents a time constant of the second-order link, and s represents a variable symbol in the transfer function;
the linear extended state observer unit is used for tracking each variable in the model in real time by adopting the following state space equation and formula:
Figure FDA0003886206230000042
wherein x is 1 ,x 2 ,x 3 Respectively represent the state variables of the system being presented,
Figure FDA0003886206230000043
b 0 represents the estimated control gain, w represents the external disturbance, y represents the output of the model, and u represents the input of the model;
Figure FDA0003886206230000044
wherein z is 1 ,z 2 ,z 3 Respectively representing the system state variable, beta, of said linear extended state observer 1 ,β 2 ,β 3 Respectively, representing the gain of the linear extended state observer.
7. The fault-tolerant control system for multi-rotor drones of claim 5, wherein the fault modeling module comprises:
the detection unit is used for detecting all motors of the unmanned aerial vehicle in real time;
a fault model establishing unit for calculating the ratio of the output of the fault motor to the output without fault when detecting that part of the motors of the unmanned aerial vehicle are abnormal, and establishing a fault matrix R according to the ratio i 。
8. The fault-tolerant control system for multi-rotor unmanned aerial vehicles of claim 5, wherein the distribution information acquisition module comprises:
distribution letterAn information obtaining unit for obtaining the optimized distribution matrix N by using the following formula f The optimized distribution matrix N is used f As control distribution information of all motors on the unmanned aerial vehicle:
N f ＝A f-1 ；
N f ＝A fT (A f ·A fT ) -1 (ii) a Wherein A is f Representing the control efficiency matrix after partial motor failure, A fT Represents A f Transposing;
A f ＝AR i (ii) a Wherein A represents a control efficiency matrix before failure;
Figure FDA0003886206230000051
wherein, b is the lift coefficient, l is unmanned aerial vehicle's wheel base, and d is the reaction torque coefficient.
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