CN111650836B - Control method for dynamically gliding and grabbing object based on operation flying robot - Google Patents

Control method for dynamically gliding and grabbing object based on operation flying robot Download PDF

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CN111650836B
CN111650836B CN202010557868.7A CN202010557868A CN111650836B CN 111650836 B CN111650836 B CN 111650836B CN 202010557868 A CN202010557868 A CN 202010557868A CN 111650836 B CN111650836 B CN 111650836B
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force
unmanned aerial
aerial vehicle
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flying robot
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CN111650836A (en
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陈彦杰
张振国
吴杨宁
占巍巍
何炳蔚
林立雄
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Fuzhou University
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Abstract

The invention relates to a control method for dynamically gliding and grabbing an object based on an operation flying robot, which comprises the following steps: step S1: considering the gravity center shift, constructing a four-rotor unmanned aerial vehicle system model carrying a mechanical arm and a two-degree-of-freedom manipulator model; step S2: calculating the contact force and the friction force applied to the tail end of the manipulator by analyzing the instant contact between the manipulator and the object; step S3: decoupling the attitude, and calculating the rolling angle required by the unmanned plane flying according to the target track
Figure DEST_PATH_IMAGE002
And a pitch angle
Figure DEST_PATH_IMAGE004
Lifting force and dynamic model integration are carried out; step S4: introducing a stable reference model, calculating an error dynamic model of the system, designing a robust adaptive controller by considering the rotary inertia of the flying robot as a bounded variable in the controller, and calculating the lifting force and the input moments of rolling, pitching and yawing of the system; step S5: the rotating speeds of the four rotor wings are calculated through the lift force, the rolling moment, the pitching moment and the yawing moment.

Description

Control method for dynamically gliding and grabbing object based on operation flying robot
Technical Field
The invention relates to the technical field of unmanned aerial vehicles, in particular to a control method for dynamically gliding and grabbing an object based on an operation flying robot.
Background
The unmanned aerial vehicle realizes the unmanned mode from remote control driving to the onboard computer automatic control. Unmanned aerial vehicles are mature flight platforms, and can carry different components on the flight platforms to expand the application of the flight platforms in different fields. For example, the fields of aerial survey, pesticide spraying, target tracking and the like have the potential of unmanned aerial vehicle application. Wherein, these applications need not carry on the arm on the unmanned aerial vehicle platform, combine the two just operation type flying robot, and the equipment of so high-end can make industry obtain very big facility. With the deepening of researchers in the field, the application of unmanned aerial vehicles carrying mechanical arms in practice is realized by scholars. The operation type flying robot with the 7-degree-of-freedom mechanical arm can flexibly complete grabbing and assembling operations; visual servo control is added on the operation type flying robot system, and an autonomous grabbing task can be completed; the tail end of a mechanical arm of the operation type flying robot is contacted with an object to replace a force sensor to finish contact force measurement work; and a parallel operation type flying robot system is adopted, so that better bionic work can be realized.
These applications all have a flight grabbing action. And the technical difficulty of grabbing by the command flight needs to be overcome. The grabbing mode is the problem to be solved firstly by the control engineering. The bionic object gliding grabbing object is one of the hot spots of the current research, the gliding grabbing object can generate larger impact force to generate larger influence on a flight platform, and if the flight speed is too high or the grabbed object is too heavy, the flight platform can deviate from a planned position and even be out of control.
For the problem of the work-type flying robot grasping an object, many scholars have made control methods. For example, the tail end of a mechanical arm of a working type flying robot is contacted with an object to replace a force sensor to complete contact force measurement work; separately establishing flight platform and mechanical arm dynamics models, using H∞The control method controls the gripped object. Most of the control methods can only grab objects with smaller mass,larger errors can occur to grab larger objects and even result in loss of control.
Disclosure of Invention
In view of this, the invention aims to provide a control method for dynamically gliding and grabbing an object based on an operation flying robot, which can effectively improve the grabbing control precision of an unmanned aerial vehicle.
In order to achieve the purpose, the invention adopts the following technical scheme:
a control method for dynamically gliding and grabbing an object based on a working flying robot comprises the following steps:
step S1: considering the gravity center shift, constructing a four-rotor unmanned aerial vehicle system model carrying a mechanical arm and a two-degree-of-freedom manipulator model;
step S2: calculating the contact force F borne by the tail end of the manipulator by analyzing the instantaneous contact between the manipulator and the objectsAnd frictional force F2；
Step S3: decoupling the attitude, and calculating the target trajectory d of the unmanned aerial vehicleTRoll angle required for flight
Figure BDA0002544977030000021
Pitch angle thetadAnd lift u1And integrating the dynamic model;
step S4: introducing a stable reference model, calculating an error dynamic model of the system, designing a robust adaptive controller by considering the rotary inertia of the flying robot as a bounded variable in the controller, and calculating the lifting force of the system and the input moments u of rolling, pitching and yawingi，i＝1,2,3,4；
Step S5: by a lifting force u1Rolling moment u2Pitching moment u3Yaw moment u4Solve the rotational speed omega of four rotorsi，i＝1,2,3,4；
Step S6: and controlling the unmanned aerial vehicle through the resolved data.
Further, it specifically is to establish the four rotor unmanned aerial vehicle system models who carries on the arm: modeling a four-rotor unmanned aerial vehicle system carrying the mechanical arm by using a Newton-Euler equation method, and obtaining the model according to force balance and moment balance:
Figure BDA0002544977030000031
wherein F is the external force applied to the system, M is the external moment applied to the system, M is the total mass of the system, and rGFor the position of the centre of gravity offset in the coordinate system of the unmanned aerial vehicle platform, r0The position of the unmanned aerial vehicle platform in the world coordinate system, B is the driving force of the system, omega is the angular velocity vector of the unmanned aerial vehicle platform in the world coordinate system, I is the inertia tensor of the system,
Figure BDA0002544977030000032
meaning that one differentiation is made on omega,
Figure BDA0002544977030000033
represents a pair of r0Carrying out secondary differentiation;
Figure BDA0002544977030000034
wherein M (q),
Figure BDA0002544977030000035
And G (q) are system variables relating to moment of inertia, mass, and rotational speed of the robot, respectively, qiIs the rotational speed, τ, of the robot iiIs the input torque of the manipulator i.
Further, the step S2 is specifically:
step S21, at the moment when the operation type flying robot grabs the object, the following can be obtained by the momentum theorem:
mv1＝(m+m4)v2 (3)
wherein: m is4As mass of object to be gripped, v1Velocity before impact, v2Is the velocity after the collision;
step S22: calculating impulse generated in the motion process by using impulse theorem;
Figure BDA0002544977030000041
wherein t is the time required for a collision;
step S23: the combined type (3) and (4) calculate the contact force generated by collision:
Figure BDA0002544977030000042
wherein xeIs the displacement of the tail end of the manipulator;
step S24: the force generated by friction on the manipulator is derived from newton dynamics of motion:
Figure BDA0002544977030000043
step S25: further, the resultant force of the operation type flying robot in the grabbing process is as follows:
Figure BDA0002544977030000044
step S26: calculating the force F transmitted from the tail end of the mechanical arm to the unmanned aerial vehicle flight platform by adopting a Jacobi matrix methodBSum moment MBComprises the following steps:
Figure BDA0002544977030000045
wherein: c. C1＝cos(q1),c2＝cos(q2),s1＝sin(q1),s2＝sin(q2)。
Further, the step S3 is specifically:
and S31, designing a virtual control quantity according to the stress analysis obtained in the step S2:
Figure BDA0002544977030000051
wherein: phi is ad、θdAnd psidThe expected values of the yaw angle, the roll angle and the pitch angle of the flight platform are obtained;
step S32: according to the virtual control quantity, obtaining a target track dTRoll angle required for flight
Figure BDA0002544977030000055
Pitch angle thetadAnd lift u1：
Figure BDA0002544977030000052
Step S33: and (3) combining the formulas (1) to (10), obtaining an overall dynamic model of the operation type flying robot as follows:
Figure BDA0002544977030000053
wherein:
Figure BDA0002544977030000054
u＝[v1,v2,v3,u2,u3,u4,τ1,τ2]T，
Figure BDA0002544977030000061
Figure BDA0002544977030000062
Figure BDA0002544977030000063
Figure BDA0002544977030000064
E1＝(c1c2-s1s2)m4,E3＝(-c1s2-c2s1)m4,
Figure BDA0002544977030000065
Fij＝-Fiajsin(qj),Eij＝-Eiajcos(qj)，i＝1,3,5,j＝1,2。
further, the step S4 specifically includes the following steps:
step S41: defining an expected vector χd＝[xd,yd,zd,φd,θd,ψd,q1d,q2d]TDefining a stable reference model as follows:
Figure BDA0002544977030000066
wherein a and b are defined constants, and r is a system input instruction;
step S42: defining an error tracking vector:
e＝χ-χd (13)
step S43: obtained by the formulae (11) to (13):
Figure BDA0002544977030000071
wherein the content of the first and second substances,
Figure BDA0002544977030000072
is a system disturbance;
step S44: definition error
Figure BDA0002544977030000073
The error dynamic model of the system is then:
Figure BDA0002544977030000074
wherein the content of the first and second substances,
Figure BDA0002544977030000075
step S45: in order to make the lyapunov function positive and the first order differential lyapunov semi-negative, a robust adaptive controller is designed as follows:
u＝kδ+k0+k1+τ1 (16)
wherein k is a parameter to be designed,
Figure BDA0002544977030000076
step S46: tau is1In order to design an adaptive controller, the following requirements are met:
Figure BDA0002544977030000077
wherein: f. ofc＝B-1(fb+EΣFk0+EΣFk1)，
Figure BDA0002544977030000078
Is fcIs determined by the estimated value of (c),
Figure BDA0002544977030000079
further, the step S5 is specifically:
step S51: from equation (16), the system control force and control torque u can be derived, u1、u2、u3And u4The relationship of (1) is:
u1＝C1(ω1 2+ω2 2+ω3 2+ω4 2)
u2＝C1(-ω2 2+ω4 2),u3＝C1(-ω1 2+ω3 2)
u4＝C2(ω1 2-ω2 2+ω3 2-ω4 2)
(17)
step S52: solving the rotation speed omega of four rotorsi，i＝1,2,3,4。
Compared with the prior art, the invention has the following beneficial effects:
the invention constructs a dynamic model based on instantaneous contact force and friction force, adopts an integrated control strategy of a manipulator and a flying robot, and can complete the task of gliding grabbing; in order to eliminate the micro disturbance of the mechanical arm motion and the real-time change of the rotation variable on a dynamic system, a robust control method based on an interval matrix is adopted; aiming at the large disturbance such as contact force and friction force generated in the process of grabbing objects in gliding, a self-adaptive control method is designed, so that the control precision and the grabbing quality range of the unmanned aerial vehicle are improved, and the unmanned aerial vehicle has strong practicability and wide application prospect.
Drawings
Fig. 1 is a schematic view of a flight platform gliding capture according to an embodiment of the invention.
Fig. 2 is a schematic flow structure diagram according to an embodiment of the present invention.
Fig. 3 is a schematic diagram illustrating the control effect of the X-axis component in the position controller according to the embodiment of the present invention.
Fig. 4 is a schematic diagram illustrating the control effect of the Y-axis component in the position controller according to the embodiment of the present invention.
Fig. 5 is a schematic diagram illustrating the control effect of the Z-axis component in the position controller according to the embodiment of the present invention.
FIG. 6 shows the roll angle in the attitude controller according to the embodiment of the present invention
Figure BDA0002544977030000081
The control effect of (1) is shown schematically.
Fig. 7 is a schematic diagram illustrating the effect of controlling the pitch angle θ in the attitude controller according to the embodiment of the present invention.
Fig. 8 is a schematic diagram illustrating the effect of controlling the roll angle ψ in the attitude controller according to the embodiment of the present invention.
Fig. 9 is a schematic diagram illustrating the control effect of the robot arm 1 in the robot controller according to the embodiment of the present invention.
Fig. 10 is a schematic view of the effect of controlling the robot arm 2 in the robot controller according to the embodiment of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings and the embodiments.
Referring to fig. 2, the present invention provides a control method for dynamically gliding and grabbing an object based on a flying robot, comprising the following steps:
step S1: considering the gravity center shift, constructing a four-rotor unmanned aerial vehicle system model carrying a mechanical arm and a two-degree-of-freedom manipulator model;
in this embodiment the construction of a quadrotor unmanned aerial vehicle system model carrying a robot arm specifically comprises: modeling a four-rotor unmanned aerial vehicle system carrying the mechanical arm by using a Newton-Euler equation method, and obtaining the model according to force balance and moment balance:
Figure BDA0002544977030000091
wherein F is the external force applied to the system, M is the external moment applied to the system, M is the total mass of the system, and rGFor the position of the centre of gravity offset in the coordinate system of the unmanned aerial vehicle platform, r0The position of the unmanned aerial vehicle platform in the world coordinate system, B is the driving force of the system, omega is the angular velocity vector of the unmanned aerial vehicle platform in the world coordinate system, I is the inertia tensor of the system,
Figure BDA0002544977030000101
meaning that one differentiation is made on omega,
Figure BDA0002544977030000102
represents a pair of r0A second differentiation is performed.
Step S2: calculating the contact force F borne by the tail end of the manipulator by analyzing the instantaneous contact between the manipulator and the objectsAnd frictional force F2；
Step S21: as shown in fig. 1, the moment when the working flying robot grabs the object can be obtained by the momentum theorem:
mv1＝(m+m4)v2 (3)
wherein: m is m0+m1+m2+m3，m4As mass of object to be gripped, v1Velocity before impact, v2Is the velocity after the collision.
Step S22: calculating impulse generated in the motion process by using impulse theorem;
Figure BDA0002544977030000103
where t is the time required for the collision.
Step S23: the contact force generated by collision can be calculated by the joint type (3) and (4):
Figure BDA0002544977030000104
wherein xeIs the displacement of the end of the robot.
Step S24: from newton dynamics of motion, the force generated by friction on the manipulator can be found as:
Figure BDA0002544977030000105
step S25: therefore, the resultant force of the operation type flying robot in the grabbing process is as follows:
Figure BDA0002544977030000106
step S26: calculating the force F transmitted from the tail end of the mechanical arm to the unmanned aerial vehicle flight platform by adopting a Jacobi matrix methodBSum moment MBComprises the following steps:
Figure BDA0002544977030000111
wherein: c. C1＝cos(q1),c2＝cos(q2),s1＝sin(q1),s2＝sin(q2)。
Step S3: decoupling the attitude, and calculating the target trajectory d of the unmanned aerial vehicleTRoll angle required for flight
Figure BDA0002544977030000112
Pitch angle thetadAnd lift u1And integrating the dynamic model; the method comprises the following specific steps:
step S31: when the operation type flight platform is in the moment of gliding and grabbing the object, the virtual control quantity is designed according to the stress analysis obtained in the step S2 as follows:
Figure BDA0002544977030000113
wherein: phi is ad、θdAnd psidThe expected values of the yaw angle, the roll angle and the pitch angle of the flight platform.
Step S32: the target track d can be obtained by the virtual control quantity obtained by the controllerTRoll angle required for flight
Figure BDA0002544977030000114
Pitch angle thetadAnd lift u1：
Figure BDA0002544977030000115
Step S33: by combining the formulas (1) to (10), the overall dynamic model of the operation type flying robot can be obtained as follows:
Figure BDA0002544977030000116
wherein:
Figure BDA0002544977030000121
u＝[v1,v2,v3,u2,u3,u4,τ1,τ2]T，
Figure BDA0002544977030000122
Figure BDA0002544977030000123
Figure BDA0002544977030000124
Figure BDA0002544977030000125
E1＝(c1c2-s1s2)m4,E3＝(-c1s2-c2s1)m4,
Figure BDA0002544977030000126
Fij＝-Fiajsin(qj),Eij＝-Eiajcos(qj)，i＝1,3,5,j＝1,2
step S4: introducing a stable reference model, calculating an error dynamic model of the system, taking into account the flight in the controllerThe rotary inertia of the robot is a bounded variable, a robust self-adaptive controller is designed, and the lifting force of the system and the input moments u of rolling, pitching and yawing are solvedi，i＝1,2,3,4；
In step S4, integral robust adaptive control is carried out on the position and the attitude of the flight platform and the two-degree-of-freedom mechanical arm in the dynamic equation, a control parameter k based on an interval matrix is introduced for the moment of inertia change generated by the flight platform, and the adaptive control parameter k is introduced in the gliding grabbing process0、k1And τ1The method specifically comprises the following steps:
step S41: defining an expected vector χd＝[xd,yd,zd,φd,θd,ψd,q1d,q2d]TDefining a stable reference model as follows:
Figure BDA0002544977030000131
where a and b are defined constants and r is a system input command.
Step S42: defining an error tracking vector:
e＝χ-χd (13)
step S43: obtained by the formulae (11) to (13):
Figure BDA0002544977030000132
wherein the content of the first and second substances,
Figure BDA0002544977030000133
for system disturbance
Step S44: definition error
Figure BDA0002544977030000134
The error dynamic model of the system is then:
Figure BDA0002544977030000135
wherein the content of the first and second substances,
Figure BDA0002544977030000136
step S45: in order to make the lyapunov function positive and the first order differential lyapunov semi-negative, a robust adaptive controller is designed as follows:
u＝kδ+k0+k1+τ1 (16)
step S46: the lyapunov function is designed as follows:
Figure BDA0002544977030000141
introduction 1: the interval matrix A ∈ [ A ]m,AM]Then a can be described as:
A＝A0+EaΣFa
wherein:
Figure BDA0002544977030000142
Figure BDA0002544977030000143
Figure BDA0002544977030000144
ζij＝(aij M-aij m)/2,i,j＝1,…，n
eiΣ is a variable vector and for an arbitrary Σ there is ΣTΣ≤1.
Lemma 2, assuming X and Y are real matrices of suitable dimensions, for any given normal number α, the following inequality holds:
XTY+YTX≤α-1XTX+αYTY.
lesion 3 for a suitable matrix G < 0, Z < 0, X-YZ-1YT< 0, which is equivalent to the following matrix:
Figure BDA0002544977030000145
step S47: the first derivative of the Lyapunov function is obtained:
Figure BDA0002544977030000151
step S48: let B be B0+ E Σ F, according to theorem 1 and 2:
Figure BDA0002544977030000152
step S49: setting: rho is less than or equal to | br | |0，
Figure BDA0002544977030000153
Law of design control
Figure BDA0002544977030000154
Figure BDA0002544977030000155
Designing adaptive control rates
Figure BDA0002544977030000156
It can be derived that:
Figure BDA0002544977030000157
wherein: f. ofc＝B-1(fb+EΣFk0+EΣFk1)，
Figure BDA0002544977030000158
Step S5: by a lifting force u1Rolling moment u2Pitching moment u3Yaw moment u4Solve the rotational speed omega of four rotorsiI is 1,2,3, 4; the method specifically comprises the following steps:
step S51: from equation (16), the system control force and control torque u can be derived, u1、u2、u3And u4The relationship of (1) is:
u1＝C1(ω1 2+ω2 2+ω3 2+ω4 2)
u2＝C1(-ω2 2+ω4 2),u3＝C1(-ω1 2+ω3 2)
u4＝C2(ω1 2-ω2 2+ω3 2-ω4 2)
(21)
wherein all constant terms except angular velocity collect a positive scalar parameter C1、C2；
Step S52: solving the rotation speed omega of four rotorsi，i＝1,2,3,4。
Step S6: and controlling the unmanned aerial vehicle through the resolved data.
In this embodiment, referring to fig. 3 to fig. 10, the operation of the present invention will be described in detail with a specific application example, and the controller according to the control method of the present invention is further designed to mainly study the control and tracking effect when gliding and grasping the object under the influence of the friction force and the contact force.
The specific settings are as follows:
1) set to grab 0.5kg of object in the presence of friction and contact forces, and set the contact impact time short, 0.02 s:
2) in the simulation process, the time constant change of the moment of inertia is considered, and the influence of external disturbance on the flying platform is considered:
3) hardware parameters are shown in table 1:
TABLE 1 hardware parameters
Figure BDA0002544977030000161
Figure BDA0002544977030000171
As shown in fig. 3 to 10, the controller further designed according to the control method of the present embodiment can make the respective components of the position and attitude of the working type aircraft robot and the rotational speed of the robot follow the target trajectory with small fluctuations. And then the operation type flying robot moves under a small steady-state error. As can be seen in fig. 7, the pitch angle is clearly buffeting within 0.5 s. But the overshoot is small and the response time is short. The controller is still considered to be effective. Figures 3-10 demonstrate the effectiveness and advantages of the present invention.
The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in accordance with the claims of the present invention should be covered by the present invention.

Claims (6)

1. A control method for dynamically gliding and grabbing an object based on an operation flying robot is characterized by comprising the following steps:
step S1: considering the gravity center shift, constructing a four-rotor unmanned aerial vehicle system model carrying a mechanical arm and a two-degree-of-freedom manipulator model;
step S2: calculating the contact force F borne by the tail end of the manipulator by analyzing the instantaneous contact between the manipulator and the objectsAnd frictional force F2；
Step S3: decoupling the attitude, and calculating the target trajectory d of the unmanned aerial vehicleTRoll angle psi required for flightdAngle of pitch thetadAnd lift u1And integrating the dynamic model;
step S4: introducing stable reference model, calculatingAn error dynamic model of the system, which takes the rotary inertia of the flying robot as a bounded variable in a controller, designs a robust self-adaptive controller and calculates the lifting force of the system and the input moments u of rolling, pitching and yawingi，i＝1,2,3,4；
Step S5: by a lifting force u1Rolling moment u2Pitching moment u3Yaw moment u4Solve the rotational speed omega of four rotorsi，i＝1,2,3,4；
Step S6: and controlling the unmanned aerial vehicle through the resolved data.
2. The control method for dynamically gliding and grabbing an object based on a working flying robot according to claim 1, wherein the building of the robot-mounted quadrotor unmanned aerial vehicle system model is specifically as follows: modeling a four-rotor unmanned aerial vehicle system carrying the mechanical arm by using a Newton-Euler equation method, and obtaining the model according to force balance and moment balance:
Figure FDA0003175879040000011
wherein F is the external force applied to the system, M is the external moment applied to the system, M is the total mass of the system, and rGFor the position of the centre of gravity offset in the coordinate system of the unmanned aerial vehicle platform, r0The position of the unmanned aerial vehicle platform in the world coordinate system, S is the driving force of the system, omega is the angular velocity vector of the unmanned aerial vehicle platform in the world coordinate system, I is the inertia tensor of the system,
Figure FDA0003175879040000021
meaning that one differentiation is made on omega,
Figure FDA0003175879040000022
represents a pair of r0Carrying out secondary differentiation;
Figure FDA0003175879040000023
wherein M (q),
Figure FDA0003175879040000024
And G (q) are system variables relating to moment of inertia, mass, and rotational speed of the robot, respectively, qiIs the rotational speed, τ, of the robot iiIs the input torque of the manipulator i.
3. The control method for dynamically gliding and grabbing an object based on a flying robot as claimed in claim 2, wherein said step S2 is specifically:
step S21, at the moment when the operation type flying robot grabs the object, the following can be obtained by the momentum theorem:
mv1＝(m+m4)v2 (3)
wherein: m is4As mass of object to be gripped, v1Velocity before impact, v2Is the velocity after the collision;
step S22: calculating impulse generated in the motion process by using impulse theorem;
Figure FDA0003175879040000025
wherein t is the time required for a collision;
step S23: coupled (3) and (4), calculating the contact force generated by the collision:
Figure FDA0003175879040000026
wherein xeDisplacement of the end of the manipulator;
step S24: the force generated by friction on the manipulator is derived from newton dynamics of motion:
Figure FDA0003175879040000031
step S25: further, the resultant force of the operation type flying robot in the grabbing process is as follows:
Figure FDA0003175879040000032
step S26: calculating the force F transmitted from the tail end of the mechanical arm to the unmanned aerial vehicle flight platform by adopting a Jacobi matrix methodBSum moment MBComprises the following steps:
Figure FDA0003175879040000033
wherein: c. C1＝cos(q1),c2＝cos(q2),s1＝sin(q1),s2＝sin(q2)，q1The rotational speed q of the robot arm 12The rotational speed of the robot 2.
4. The control method for dynamically gliding and grabbing an object based on a flying robot as claimed in claim 3, wherein said step S3 is specifically:
and S31, respectively designing the speed virtual control quantity corresponding to the x axis, the y axis and the z axis according to the stress analysis obtained in the step S2:
Figure FDA0003175879040000034
wherein: phi is ad、ψdAnd thetadRespectively obtaining expected values of a yaw angle, a roll angle and a pitch angle of the flight platform;
step S32: according to the virtual control quantity, obtaining a target track dTRoll angle psi required for flightdAngle of pitch thetadAnd lift u1：
Figure FDA0003175879040000041
Step S33: and (3) combining the formulas (1) to (10), obtaining an overall dynamic model of the operation type flying robot as follows:
Figure FDA0003175879040000042
wherein:
Figure FDA0003175879040000043
ue＝[Vx,Vy,Vz,u2,u3,u4,τ1,τ2]T，
Figure FDA0003175879040000044
Figure FDA0003175879040000045
Figure FDA0003175879040000051
Figure FDA0003175879040000052
Figure FDA0003175879040000053
E1＝(c1c2-s1s2)m4,E3＝(-c1s2-c2s1)m4,
Figure FDA0003175879040000054
Fij＝-Fiajsin(qj),Eij＝-Eiajcos(qj)，i＝1,3,5,j＝1,2。
5. the control method for dynamically gliding and grabbing an object based on a work flying robot as claimed in claim 4, wherein said step S4 specifically comprises the steps of:
step S41: defining an expected vector χd＝[xd,yd,zd,ψd,θd,φd,q1d,q2d]TDefining a stable reference model as follows:
Figure FDA0003175879040000055
wherein, alpha and beta are defined constants, and r is a system input instruction;
step S42: defining an error tracking vector:
e＝χ-χd (13)
step S43: obtained by the formulae (11) to (13):
Figure FDA0003175879040000056
wherein the content of the first and second substances,
Figure FDA0003175879040000057
is a system disturbance;
step S44: definition error
Figure FDA0003175879040000058
The error dynamic model of the system is then:
Figure FDA0003175879040000059
wherein the content of the first and second substances,
Figure FDA0003175879040000061
a is a long matrix of 8 x 8,
step S45: in order to make the lyapunov function positive and the first order differential lyapunov semi-negative, a robust adaptive controller is designed as follows:
u＝kδ+k0+k1+τ1 (16)
wherein k is a parameter to be designed,
Figure FDA0003175879040000062
step S46: tau is1In order to design an adaptive controller, the following requirements are met:
Figure FDA0003175879040000063
wherein: f. ofc＝B-1(fb+RΣHk0+RΣHk1)，
Figure FDA0003175879040000064
Is fcIs determined by the estimated value of (c),
Figure FDA0003175879040000065
6. the control method for dynamically gliding and grabbing an object based on a flying robot as claimed in claim 5, wherein said step S5 is specifically:
step S51: from equation (16), the system control force and control torque u can be derived, u1、u2、u3And u4The relationship of (1) is:
Figure FDA0003175879040000066
step S52: solve the rotational speed omega of four rotorsi，i＝1,2,3,4。
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