CN111650836A - 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

Info

Publication number
CN111650836A
CN111650836A CN202010557868.7A CN202010557868A CN111650836A CN 111650836 A CN111650836 A CN 111650836A CN 202010557868 A CN202010557868 A CN 202010557868A CN 111650836 A CN111650836 A CN 111650836A
Authority
CN
China
Prior art keywords
force
flying robot
unmanned aerial
aerial vehicle
calculating
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202010557868.7A
Other languages
Chinese (zh)
Other versions
CN111650836B (en
Inventor
陈彦杰
张振国
吴杨宁
占巍巍
何炳蔚
林立雄
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Fuzhou University
Original Assignee
Fuzhou University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fuzhou University filed Critical Fuzhou University
Priority to CN202010557868.7A priority Critical patent/CN111650836B/en
Publication of CN111650836A publication Critical patent/CN111650836A/en
Application granted granted Critical
Publication of CN111650836B publication Critical patent/CN111650836B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance

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_BDA0002544977030000055
Pitch angle thetadLifting 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: by lift, rolling moment, pitching momentAnd the yaw moment calculates the rotating speeds of the four rotors.

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 small mass, and large errors and even out of control can be generated when the objects grab large objects.
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＝k+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, 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；
In step S4, the needleThe method comprises the steps of carrying out integral robust self-adaptive control on the position and the attitude of a flight platform and a two-degree-of-freedom mechanical arm in a dynamic equation, introducing a control parameter k based on an interval matrix for the self-generated rotary inertia change of the flight platform, and introducing the self-adaptive control parameter k 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＝k+k0+k1+τ1(16)
step S46: the lyapunov function is designed as follows:
Figure BDA0002544977030000141
lesion 1 Interval matrix A ∈ [ Am,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
eithe ith column vector of the n × n-dimensional unit matrix Σ is a variable vector and for any 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 required for flight
Figure FDA0002544977020000011
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.
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 FDA0002544977020000012
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 FDA0002544977020000021
meaning that one differentiation is made on omega,
Figure FDA0002544977020000022
represents a pair of r0Carrying out secondary differentiation;
Figure FDA0002544977020000023
wherein M (q),
Figure FDA0002544977020000024
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 1, 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 FDA0002544977020000025
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 FDA0002544977020000026
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 FDA0002544977020000031
step S25: further, the resultant force of the operation type flying robot in the grabbing process is as follows:
Figure FDA0002544977020000032
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 FDA0002544977020000033
wherein: c. C1＝cos(q1),c2＝cos(q2),s1＝sin(q1),s2＝sin(q2)。
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, designing a virtual control quantity according to the stress analysis obtained in the step S2:
Figure FDA0002544977020000034
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 FDA0002544977020000035
Pitch angle thetadAnd lift u1：
Figure FDA0002544977020000041
Step S33: and (3) combining the formulas (1) to (10), obtaining an overall dynamic model of the operation type flying robot as follows:
Figure FDA0002544977020000042
wherein:
Figure FDA0002544977020000043
u＝[v1,v2,v3,u2,u3,u4,τ1,τ2]T，
Figure FDA0002544977020000044
Figure FDA0002544977020000045
Figure FDA0002544977020000051
Figure FDA0002544977020000052
E1＝(c1c2-s1s2)m4,E3＝(-c1s2-c2s1)m4,
Figure FDA0002544977020000053
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,φd,θd,ψd,q1d,q2d]TDefining a stable reference model as follows:
Figure FDA0002544977020000054
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 FDA0002544977020000055
wherein the content of the first and second substances,
Figure FDA0002544977020000056
is a system disturbance;
step S44: definition error
Figure FDA0002544977020000057
The error dynamic model of the system is then:
Figure FDA0002544977020000058
wherein the content of the first and second substances,
Figure FDA0002544977020000059
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＝k+k0+k1+τ1(16)
wherein k is a parameter to be designed,
Figure FDA0002544977020000061
step S46: tau is1In order to design an adaptive controller, the following requirements are met:
Figure FDA0002544977020000062
wherein: f. ofc＝B-1(fb+EΣFk0+EΣFk1)，
Figure FDA0002544977020000063
Is fcIs determined by the estimated value of (c),
Figure FDA0002544977020000064
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:
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。
CN202010557868.7A 2020-06-18 2020-06-18 Control method for dynamically gliding and grabbing object based on operation flying robot Active CN111650836B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010557868.7A CN111650836B (en) 2020-06-18 2020-06-18 Control method for dynamically gliding and grabbing object based on operation flying robot

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010557868.7A CN111650836B (en) 2020-06-18 2020-06-18 Control method for dynamically gliding and grabbing object based on operation flying robot

Publications (2)

Publication Number Publication Date
CN111650836A true CN111650836A (en) 2020-09-11
CN111650836B CN111650836B (en) 2021-08-31

Family

ID=72347540

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010557868.7A Active CN111650836B (en) 2020-06-18 2020-06-18 Control method for dynamically gliding and grabbing object based on operation flying robot

Country Status (1)

Country Link
CN (1) CN111650836B (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112527008A (en) * 2020-12-21 2021-03-19 福州大学 Operation type flying robot control method based on low-complexity specification performance
CN113467501A (en) * 2021-07-20 2021-10-01 福州大学 Dynamic gliding grabbing and force position hybrid control method for operation flying robot

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016111594A1 (en) * 2015-01-09 2016-07-14 주식회사 대한항공 Method for stabilizing mission equipment using unmanned aerial vehicle command and posture information
CN110427043A (en) * 2019-09-04 2019-11-08 福州大学 Pose Control device design method based on operation flying robot's centre-of gravity shift
CN111185907A (en) * 2020-01-13 2020-05-22 福州大学 Pose stability control method for operation type flying robot after grabbing

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2016111594A1 (en) * 2015-01-09 2016-07-14 주식회사 대한항공 Method for stabilizing mission equipment using unmanned aerial vehicle command and posture information
CN110427043A (en) * 2019-09-04 2019-11-08 福州大学 Pose Control device design method based on operation flying robot's centre-of gravity shift
CN111185907A (en) * 2020-01-13 2020-05-22 福州大学 Pose stability control method for operation type flying robot after grabbing

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
孙妙平等: "基于区间矩阵的四旋翼无人机鲁棒跟踪控制", 《控制理论与应用》 *
孟祥冬等: "飞行机械臂系统的接触力控制", 《飞行机械臂系统的接触力控制》 *
钟杭等: "旋翼飞行机械臂建模及动态重心补偿控制", 《控制理论与应用》 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112527008A (en) * 2020-12-21 2021-03-19 福州大学 Operation type flying robot control method based on low-complexity specification performance
CN113467501A (en) * 2021-07-20 2021-10-01 福州大学 Dynamic gliding grabbing and force position hybrid control method for operation flying robot
CN113467501B (en) * 2021-07-20 2023-03-28 福州大学 Dynamic gliding grabbing and force position hybrid control method for operation flying robot

Also Published As

Publication number Publication date
CN111650836B (en) 2021-08-31

Similar Documents

Publication Publication Date Title
Altug et al. Quadrotor control using dual camera visual feedback
CN111185907B (en) Pose stability control method for operation type flying robot after grabbing
CN109625333B (en) Spatial non-cooperative target capturing method based on deep reinforcement learning
CN110427043B (en) Pose controller design method based on gravity center offset of operation flying robot
CN107263466B (en) Base undisturbed control method of space robot based on quadratic programming problem
Raffo et al. MPC with nonlinear ℋ∞ control for path tracking of a quad-rotor helicopter
CN106985139A (en) Robot for space active disturbance rejection control method for coordinating with compensating is observed based on extended mode
CN109606753A (en) A kind of control method of Dual-arm space robot collaboration capture target
Rosaldo-Serrano et al. Observer-based time-varying backstepping control for a quadrotor multi-agent system
CN111650836B (en) Control method for dynamically gliding and grabbing object based on operation flying robot
Hasseni et al. Decentralized PID control by using GA optimization applied to a quadrotor
Dinh et al. Adaptive tracking control of a quadrotor unmanned vehicle
Jithu et al. Quadrotor modelling and control
CN111857165B (en) Trajectory tracking control method of underwater vehicle
Islam et al. Adaptive sliding mode control design for quadrotor unmanned aerial vehicle
Santiaguillo-Salinas et al. Observer-based time-varying backstepping control for parrot’s ar. drone 2.0
CN113467501B (en) Dynamic gliding grabbing and force position hybrid control method for operation flying robot
Rosaldo-Serrano et al. Trajectory tracking for a commercial quadrotor via time-varying backstepping
Jiao et al. Disturbance observer-based backstepping control for quadrotor UAV manipulator attitude system
Bouzgou et al. PD sliding mode controller based decoupled aerial manipulation
CN115229792A (en) Terminal sliding mode self-adaptive control method for dynamic grabbing of flying operation robot
Khebbache Robust control algorithm considering the actuator faults for attitude tracking of an uav quadrotor aircraft
Worrall et al. Autonomous planetary rover control using inverse simulation
CN115826597A (en) Adaptive neural network-based anti-interference control method and device for rotorcraft
CN113580127B (en) Multi-rotor aircraft humanoid double-mechanical-arm system and dynamic self-balancing control design method thereof

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant