CN111352447A - Wave compensation method for take-off and landing platform of unmanned aerial vehicle - Google Patents
Wave compensation method for take-off and landing platform of unmanned aerial vehicle Download PDFInfo
- Publication number
- CN111352447A CN111352447A CN201811584774.8A CN201811584774A CN111352447A CN 111352447 A CN111352447 A CN 111352447A CN 201811584774 A CN201811584774 A CN 201811584774A CN 111352447 A CN111352447 A CN 111352447A
- Authority
- CN
- China
- Prior art keywords
- platform
- unmanned aerial
- aerial vehicle
- wave
- compensation method
- 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.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D3/00—Control of position or direction
- G05D3/12—Control of position or direction using feedback
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Feedback Control In General (AREA)
Abstract
The invention relates to a wave compensation method for a take-off and landing platform of an unmanned aerial vehicle, which comprises the steps of determining a six-degree-of-freedom platform kinematics positive solution according to a take-off and landing platform structure of the unmanned aerial vehicle, and calculating a reverse solution according to the kinematics positive solution; resolving each coefficient matrix corresponding to the state space of the h infinite filter; predicting T based on each coefficient matrixpreA wave signal after the time; based on TpreThe wave signals after the time and the kinematics positive and negative solution of the six-degree-of-freedom platform obtain the state of the takeoff and landing platform of the unmanned aerial vehicle; and adjusting the control quantity according to the state of the unmanned aerial vehicle takeoff and landing platform to compensate the action of the sea waves. The method can effectively block the interference of sea waves to the carrier-based unmanned aerial vehicle during taking off and landing under the sea wind condition, and improves the taking off and landing safety and stability of the carrier-based unmanned aerial vehicle.
Description
Technical Field
The invention relates to the field of sea surface take-off and landing of carrier-borne unmanned aerial vehicles, in particular to a sea wave compensation method for a take-off and landing platform of an unmanned aerial vehicle.
Background
The intelligent unmanned aerial vehicle is a complex integrated system and needs support in the aspects of aircraft design, space positioning, path planning, flight control, landing assistance and the like; in recent years, sea surface autonomous mobile platform control technologies represented by unmanned ships and unmanned planes are also mature continuously; in the current war, sea unmanned aerial vehicles play irreplaceable roles, and autonomous take-off and landing undoubtedly become an important item in the problem of unmanned aerial vehicles; taking off and landing an unmanned aerial vehicle at sea is a difficult task, particularly in heavy seas; the lifting and descending device is used on the ship to compensate or eliminate the complex random motion of the ship caused by sea waves, so that the ship motion and the unmanned aerial vehicle motion are decoupled, which is necessary.
Key technologies such as a sliding takeoff technology, an ejection takeoff technology, a ship-entering guiding technology, an LSO technology and the like related to the rise and fall of the fixed wing and the jet carrier-based aircraft are mature day by day; therefore, the carrier-based takeoff of the rotary wing type or small unmanned aerial vehicle becomes an important and troublesome problem due to the characteristics of small volume, light weight, easy interference, poor stability and the like;
the sea waves have strong randomness and time-varying property, so that the longitudinal and transverse swinging and heaving motions generated by the ship bring huge challenges to the safe take-off and landing of the carrier-borne unmanned aerial vehicle; aiming at the problem of complex safety that the launching and landing of a carrier-borne unmanned aerial vehicle are influenced by the interference of a ship under the action of sea waves, the design of a landing platform capable of blocking the interference of the sea waves is of great significance; at present, the sea wave heave compensation platform can be divided into a passive heave compensation Platform (PHC) and an active heave compensation platform (AHC), and in addition, a hybrid active-passive system is provided, which combines the characteristics of the passive and active systems; regardless of the type of the compensator, the heave compensation aims at decoupling the load motion and the ship motion, so as to achieve the aim of weakening the interference effect of sea waves in real time; however, the existing sea wave compensation device has the characteristics of weak self-adaptive capacity and poor robustness of a controller or hardware equipment in both active compensation and passive compensation, cannot automatically adjust control parameters aiming at sea waves in different sea areas and different natural environments, and has low universality; on the other hand, the problem of unsuppressed jitter of the compensation platform caused by high-frequency disturbance of sea waves is solved due to the processing error of a hardware structure or the rapid conversion of a drive in the compensation process; in the past, not only the mechanical structure is easy to generate fatigue to weaken the strength of the platform, but also the load complexity of the motor or the hydraulic pump is increased, and the service life of a driving system is greatly shortened; finally, the robustness of the control system is poor, the strength of the hardware structure is weakened, and the potential safety hazard and reliability of the system are greatly reduced.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a sea wave compensation method for a take-off and landing platform of an unmanned aerial vehicle, and solves the problems that the existing sea wave compensation device is weak in self-adaptive capacity and poor in robustness, cannot automatically adjust control parameters aiming at sea waves in different sea areas and different natural environments, and is low in universality.
The technical scheme adopted by the invention for realizing the purpose is as follows:
a wave compensation method for a take-off and landing platform of an unmanned aerial vehicle comprises the following steps:
step 1: determining a six-degree-of-freedom platform kinematics positive solution according to the takeoff and landing platform structure of the unmanned aerial vehicle, and then calculating a reverse solution according to the kinematics positive solution;
step 2: resolving each coefficient matrix corresponding to the state space of the h infinite filter;
and step 3: predicting T based on each coefficient matrixpreA wave signal after the time;
and 4, step 4: based on TpreThe wave signals after the time and the kinematics positive and negative solution of the six-degree-of-freedom platform obtain the state of the takeoff and landing platform of the unmanned aerial vehicle;
and 5: and adjusting the control quantity according to the state of the unmanned aerial vehicle takeoff and landing platform to compensate the action of the sea waves. The inverse kinematics solution of the six-degree-of-freedom platform is as follows:
wherein L isi＝|AiBi|，L＝[L1,L2,...,L6]；LiLength of positive solution for six degree of freedom platform kinematics, J-1For an inverse Jacobian iteration matrix of the pose of the upper platform and 6 driving cylinders, x, y and z represent three-dimensional coordinate values under a corresponding coordinate system, α, β and gamma respectively represent rotation angle values around x, y and z axes under the corresponding coordinate system, and the matrix for resolving each coefficient corresponding to the state space of the h infinite filter comprises the following steps:
firstly, determining the form of a transfer function matrix G of a six-degree-of-freedom platform as follows:
wherein V represents J-1Transfer function of, J-1An inverse Jacobian iteration matrix of the pose of the upper platform and 6 driving cylinders is formed; k represents a fast Fourier transform operator, H represents a wave linear model transfer function,
where s denotes the Laplace transform factor, σwIs the sea wave strength constant, ξ is the damping coefficient, omega0Is the dominant frequency of sea waves; the transfer function matrix G is then decomposed into a state space matrix G' comprising 9 sub-matrices according to the state space:
wherein A ═ 0]；B1＝[0]；B2＝[KV]；C2＝[1]；D11＝[H]；D12＝[-KV]；C1＝[1]；D21＝[H]；D22＝[-KV]；
The coefficient matrixes corresponding to the state space of the h infinite filter obtained by calculation are as follows:
Cf＝C1；
Df＝0；
wherein, X in the formula represents a symmetric matrix solution X corresponding to the minimum gamma value allowed by the equation by solving the following algebraic Riccati equation;
where γ is the characteristic coefficient of the equation.
Predicting T based on each coefficient matrixpreA post-time ocean wave signal comprising:
step 3.1: performing fast Fourier transform on the wave heave signal w (T) within the delta T time before filtering to obtain amplitude-frequency data and phase-frequency data of the input signal;
step 3.2: identifying N harmonic functions with maximum peak values and corresponding amplitude values A by means of a peak value detectorFFTFrequency fFFTPhase of
Step 3.3: amplitude a of each frequency harmonic by using Kalman filteri,tAnd phase
Carrying out prediction;
step 3.4: obtaining a harmonic prediction expression of each harmonic function in the N harmonic functions through a Kalman filter;
step 3.5: superposing the harmonic prediction expressions of each harmonic function in the N harmonic functions to obtain TpreWave signal after time.
The amplitude a of each frequency harmonic wave is measured by adopting a Kalman filteri,tAnd phase
Performing a prediction comprising:
step 3.3.1: carrying out fast Fourier transform on the filtered wave heave signal w (T) within the delta T time to obtain amplitude-frequency data and phase-frequency data of the input signal;
step 3.3.2: identifying the main N harmonic functions and their corresponding amplitudes A by means of a peak detectorFFTFrequency fFFTPhase of
Wherein the time between two peaks is the frequency fFFTThe reciprocal of (1), the peak value is the amplitude AFFTThe first peak is located at the phase
The harmonic prediction expression for each of the N harmonic functions is:
in the formula: xj(t) represents the harmonic value of the jth harmonic, AFFT,j、fFFT,j、
Respectively representing the amplitude, frequency and phase of the jth harmonic.
Based on TpreThe wave signal after the time and the six-degree-of-freedom platform kinematics positive and negative solution are used for obtaining the state of the takeoff and landing platform of the unmanned aerial vehicle, and the method comprises the following processes:
step 4.1: acquiring an Euler angle, a height value and a first-order derivative value of a take-off and landing platform of the unmanned aerial vehicle through a sensor;
step 4.2: transmitting the value obtained in the step 4.1 to a sea wave compensation controller, and outputting expected values of the lengths of 6 driving cylinder bodies by the sea wave compensation controller;
step 4.3: and the platform executing mechanism acquires the lengths of the 6 driving cylinders, adjusts the lengths of the 6 driving cylinders to the expected values, and returns to the step 4.1.
According to the state adjustment control volume of unmanned aerial vehicle landing platform, including following process:
step 5.1: through the Euler angle and the height value of the upper platform for takeoff and landing of the unmanned aerial vehicle, the length value L of 6 driving cylinder bodies is obtained according to a six-degree-of-freedom platform kinematics forward solution formula1,L2,...,L6]Then, acquiring the motion speed values of 6 driving cylinder bodies according to the inverse kinematics of the six-degree-of-freedom platform;
step 5.2: filtering the length values and the speed values of the 6 driving cylinder bodies according to an h infinite filter, and filtering out a high-frequency wave band;
step 5.3: calculating the length value L '[ [ L [ ] of the driving cylinder at the next control period of the takeoff and landing platform of the unmanned aerial vehicle through the self-adaptive fast Fourier prediction algorithm on the filtered value'1,L'2,...,L'6]；
Step 5.4: and controlling the driving cylinder to reach the length at the speed of (L' -L)/T, wherein T represents the execution period of the takeoff and landing platform of the unmanned aerial vehicle.
The six-degree-of-freedom platform kinematics positive solution is as follows:
wherein, i is 1,2, 6 is a number of a corresponding hinge point pair up and down of the six-freedom-degree platform, x, y and z represent three-dimensional coordinate values α, β and gamma respectively representing rotation angle values around x, y and z axes under the corresponding coordinate system, and A is a number representing the rotation angle values around the x, y and z axes under the corresponding coordinate systemiIndicating the point of articulation of the hydraulic cylinder with the upper platform, BiIndicate the pneumatic cylinder and lower platform pin joint, r indicates the effective radius of upper platform, and r ═ A promptlyiw, i ═ 1,2, 6, where w denotes the upper platform center point, aiw denotes starting from w to AiThe vector of (1), wherein | represents the length of the vector;
is represented by Aiw and coordinate axis XwC represents cos and s represents sin; r represents the effective radius of the lower platform, i.e. | Bio |, o denotes the lower platform center point, Bio denotes a transition from o to BiThe vector of (a) is determined,
is represented by Bio and coordinate system axis X0Angle of (A)iBiRepresenting the driving cylinder vector.
The invention has the following beneficial effects and advantages:
the method adopts a self-adaptive Fast Fourier (FFT) prediction algorithm to predict the load of the take-off and landing platform acted by sea waves, and compensates the take-off and landing platform based on a six-degree-of-freedom platform kinematics positive and negative solution and the self-adaptive Fast Fourier (FFT) prediction algorithm;
the method can effectively block the interference of sea waves to the carrier-based unmanned aerial vehicle during taking off and landing under the sea wind condition, and improves the taking off and landing safety and stability of the carrier-based unmanned aerial vehicle.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a schematic view of the unmanned aerial vehicle takeoff and landing platform of the present invention;
FIG. 3 is a block diagram of the LFT of the h-infinity filtering problem of the present invention;
FIG. 4 is a schematic diagram of the prediction algorithm of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, but rather should be construed as modified in the spirit and scope of the present invention as set forth in the appended claims.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.
1. A wave compensation method for a take-off and landing platform of an unmanned aerial vehicle is characterized by comprising the following steps: the method comprises the following steps:
step 1: determining a six-degree-of-freedom platform kinematics positive solution according to the takeoff and landing platform structure of the unmanned aerial vehicle, and then calculating a reverse solution according to the kinematics positive solution;
step 2: resolving each coefficient matrix corresponding to the state space of the h infinite filter;
and step 3: predicting T based on each coefficient matrixpreA wave signal after the time;
and 4, step 4: based on TpreThe wave signals after the time and the kinematics positive and negative solution of the six-degree-of-freedom platform obtain the state of the takeoff and landing platform of the unmanned aerial vehicle;
and 5: and adjusting the control quantity according to the state of the unmanned aerial vehicle takeoff and landing platform to compensate the action of the sea waves. The inverse kinematics solution of the six-degree-of-freedom platform is as follows:
wherein L isi＝|AiBi|，L＝[L1,L2,...,L6]；LiLength of positive solution for six degree of freedom platform kinematics, J-1For an inverse Jacobian iteration matrix of the pose of the upper platform and 6 driving cylinders, x, y and z represent three-dimensional coordinate values under a corresponding coordinate system, α, β and gamma respectively represent rotation angle values around x, y and z axes under the corresponding coordinate system, and the matrix for resolving each coefficient corresponding to the state space of the h infinite filter comprises the following steps:
firstly, determining the form of a transfer function matrix G of a six-degree-of-freedom platform as follows:
wherein V represents J-1Transfer function of, J-1An inverse Jacobian iteration matrix of the pose of the upper platform and 6 driving cylinders is formed; k represents a fast Fourier transform operator, H represents a wave linear model transfer function,
where s denotes the Laplace transform factor, σwIs the sea wave strength constant, ξ is the damping coefficient, omega0Is the dominant frequency of sea waves; the transfer function matrix G is then decomposed into a state space matrix G' comprising 9 sub-matrices according to the state space:
wherein A ═ 0]；B1＝[0]；B2＝[KV]；C2＝[1]；D11＝[H]；D12＝[-KV]；C1＝[1]；D21＝[H]；D22＝[-KV]；
The coefficient matrixes corresponding to the state space of the h infinite filter obtained by calculation are as follows:
Cf＝C1；
Df＝0；
wherein, X in the formula represents a symmetric matrix solution X corresponding to the minimum gamma value allowed by the equation by solving the following algebraic Riccati equation;
where γ is the characteristic coefficient of the equation.
Predicting T based on each coefficient matrixpreA post-time ocean wave signal comprising:
step 3.1: performing fast Fourier transform on the wave heave signal w (T) within the delta T time before filtering to obtain amplitude-frequency data and phase-frequency data of the input signal;
step 3.2: identifying N harmonic functions with maximum peak values and corresponding amplitude values A by means of a peak value detectorFFTFrequency fFFTPhase of
Step 3.3: amplitude a of each frequency harmonic by using Kalman filteri,tAnd phase
Carrying out prediction;
step 3.4: obtaining a harmonic prediction expression of each harmonic function in the N harmonic functions through a Kalman filter;
step 3.5: superposing the harmonic prediction expressions of each harmonic function in the N harmonic functions to obtain TpreWave signal after time.
The amplitude a of each frequency harmonic wave is measured by adopting a Kalman filteri,tAnd phase
Performing a prediction comprising:
step 3.3.1: carrying out fast Fourier transform on the filtered wave heave signal w (T) within the delta T time to obtain amplitude-frequency data and phase-frequency data of the input signal;
step 3.3.2: identifying the main N harmonic functions and their corresponding amplitudes A by means of a peak detectorFFTFrequency fFFTPhase of
Wherein the time between two peaks is the frequency fFFTThe reciprocal of (1), the peak value is the amplitude AFFTThe first peak is located at the phase
The harmonic prediction expression for each of the N harmonic functions is:
in the formula: xj(t) represents the harmonic value of the jth harmonic, AFFT,j、fFFT,j、
Respectively representing the amplitude, frequency and phase of the jth harmonic.
Based on TpreThe wave signal after the time and the six-degree-of-freedom platform kinematics positive and negative solution are used for obtaining the state of the takeoff and landing platform of the unmanned aerial vehicle, and the method comprises the following processes:
step 4.1: acquiring an Euler angle, a height value and a first-order derivative value of a take-off and landing platform of the unmanned aerial vehicle through a sensor;
step 4.2: transmitting the value obtained in the step 4.1 to a sea wave compensation controller, and outputting expected values of the lengths of 6 driving cylinder bodies by the sea wave compensation controller;
step 4.3: and the platform executing mechanism acquires the lengths of the 6 driving cylinders, adjusts the lengths of the 6 driving cylinders to the expected values, and returns to the step 4.1.
According to the state adjustment control volume of unmanned aerial vehicle landing platform, including following process:
step 5.1: through the Euler angle and the height value of the upper platform for takeoff and landing of the unmanned aerial vehicle, the length value L of 6 driving cylinder bodies is obtained according to a six-degree-of-freedom platform kinematics forward solution formula1,L2,...,L6]Then, acquiring the motion speed values of 6 driving cylinder bodies according to the inverse kinematics of the six-degree-of-freedom platform;
step 5.2: filtering the length values and the speed values of the 6 driving cylinder bodies according to an h infinite filter, and filtering out a high-frequency wave band;
step 5.3: calculating the length value L '[ [ L [ ] of the driving cylinder at the next control period of the takeoff and landing platform of the unmanned aerial vehicle through the self-adaptive fast Fourier prediction algorithm on the filtered value'1,L'2,...,L'6]；
Step 5.4: and controlling the driving cylinder to reach the length at the speed of (L' -L)/T, wherein T represents the execution period of the takeoff and landing platform of the unmanned aerial vehicle.
The six-degree-of-freedom platform kinematics positive solution is as follows:
wherein, i is 1,2, 6 is a number of a corresponding hinge point pair up and down of the six-freedom-degree platform, x, y and z represent three-dimensional coordinate values α, β and gamma respectively representing rotation angle values around x, y and z axes under the corresponding coordinate system, and A is a number representing the rotation angle values around the x, y and z axes under the corresponding coordinate systemiIndicating the point of articulation of the hydraulic cylinder with the upper platform, BiHinge for hydraulic cylinder and lower platformThe joint, r, represents the upper platform effective radius, i.e., r ═ Aiw, i ═ 1,2, 6, where w denotes the upper platform center point, aiw denotes starting from w to AiThe vector of (1), wherein | represents the length of the vector;
is represented by Aiw and coordinate axis XwC represents cos and s represents sin; r represents the effective radius of the lower platform, i.e. | Bio |, o denotes the lower platform center point, Bio denotes a transition from o to BiThe vector of (a) is determined,
is represented by Bio and coordinate system axis X0Angle of (A)iBiRepresenting the driving cylinder vector.
Claims (9)
1. A wave compensation method for a take-off and landing platform of an unmanned aerial vehicle is characterized by comprising the following steps: the method comprises the following steps:
step 1: determining a six-degree-of-freedom platform kinematics positive solution according to the takeoff and landing platform structure of the unmanned aerial vehicle, and then calculating a reverse solution according to the kinematics positive solution;
step 2: resolving each coefficient matrix corresponding to the state space of the h infinite filter;
and step 3: predicting T based on each coefficient matrixpreA wave signal after the time;
and 4, step 4: based on TpreThe wave signals after the time and the kinematics positive and negative solution of the six-degree-of-freedom platform obtain the state of the takeoff and landing platform of the unmanned aerial vehicle;
and 5: and adjusting the control quantity according to the state of the unmanned aerial vehicle takeoff and landing platform to compensate the action of the sea waves.
2. A wave compensation method for an unmanned aerial vehicle take-off and landing platform according to claim 1, wherein the wave compensation method comprises the following steps: the inverse kinematics solution of the six-degree-of-freedom platform is as follows:
wherein L isi＝|AiBi|，L＝[L1,L2,...,L6]；LiLength of positive solution for six degree of freedom platform kinematics, J-1The pose of the upper platform and the inverse Jacobian iteration matrix of the 6 driving cylinder bodies are provided, x, y and z represent three-dimensional coordinate values under the corresponding coordinate system, and α, β and gamma respectively represent rotation angle values around x, y and z axes under the corresponding coordinate system.
3. A wave compensation method for an unmanned aerial vehicle take-off and landing platform according to claim 1, wherein the wave compensation method comprises the following steps: the solving of each coefficient matrix corresponding to the state space of the h infinite filter includes:
firstly, determining the form of a transfer function matrix G of a six-degree-of-freedom platform as follows:
wherein V represents J-1Transfer function of, J-1An inverse Jacobian iteration matrix of the pose of the upper platform and 6 driving cylinders is formed; k represents a fast Fourier transform operator, H represents a wave linear model transfer function,
where s denotes the Laplace transform factor, σwIs the sea wave strength constant, ξ is the damping coefficient, omega0Is the dominant frequency of sea waves; the transfer function matrix G is then decomposed into a state space matrix G' comprising 9 sub-matrices according to the state space:
wherein A ═ 0]；B1＝[0]；B2＝[KV]；C2＝[1]；D11＝[H]；D12＝[-KV]；C1＝[1]；D21＝[H]；D22＝[-KV]；
The coefficient matrixes corresponding to the state space of the h infinite filter obtained by calculation are as follows:
Cf＝C1；
Df＝0；
wherein, X in the formula represents a symmetric matrix solution X corresponding to the minimum gamma value allowed by the equation by solving the following algebraic Riccati equation;
where γ is the characteristic coefficient of the equation.
4. A wave compensation method for an unmanned aerial vehicle take-off and landing platform according to claim 1, wherein the wave compensation method comprises the following steps: predicting T based on each coefficient matrixpreA post-time ocean wave signal comprising:
step 3.1: performing fast Fourier transform on the wave heave signal w (T) within the delta T time before filtering to obtain amplitude-frequency data and phase-frequency data of the input signal;
step 3.2: identifying N harmonic functions with maximum peak values and corresponding amplitude values A by means of a peak value detectorFFTFrequency fFFTPhase of
Step 3.3: amplitude a of each frequency harmonic by using Kalman filteri,tAnd phase
Carrying out prediction;
step 3.4: obtaining a harmonic prediction expression of each harmonic function in the N harmonic functions through a Kalman filter;
step 3.5: superposing the harmonic prediction expressions of each harmonic function in the N harmonic functions to obtain TpreWave signal after time.
5. A wave compensation method for an unmanned aerial vehicle take-off and landing platform according to claim 4, wherein the wave compensation method comprises the following steps: the amplitude a of each frequency harmonic wave is measured by adopting a Kalman filteri,tAnd phase
Performing a prediction comprising:
step 3.3.1: carrying out fast Fourier transform on the filtered wave heave signal w (T) within the delta T time to obtain amplitude-frequency data and phase-frequency data of the input signal;
step 3.3.2: identifying the main N harmonic functions and their corresponding amplitudes A by means of a peak detectorFFTFrequency fFFTPhase of
Wherein the time between two peaks is the frequency fFFTThe reciprocal of (1), the peak value is the amplitude AFFTThe first peak is located at the phase
6. A wave compensation method for an unmanned aerial vehicle take-off and landing platform according to claim 5, wherein the wave compensation method comprises the following steps: the harmonic prediction expression for each of the N harmonic functions is:
in the formula: xj(t) represents the harmonic value of the jth harmonic, AFFT,j、fFFT,j、
Respectively representing the amplitude, frequency and phase of the jth harmonic.
7. A wave compensation method for an unmanned aerial vehicle take-off and landing platform according to claim 1, wherein the wave compensation method comprises the following steps: based on TpreThe wave signal after the time and the six-degree-of-freedom platform kinematics positive and negative solution are used for obtaining the state of the takeoff and landing platform of the unmanned aerial vehicle, and the method comprises the following processes:
step 4.1: acquiring an Euler angle, a height value and a first-order derivative value of a take-off and landing platform of the unmanned aerial vehicle through a sensor;
step 4.2: transmitting the value obtained in the step 4.1 to a sea wave compensation controller, and outputting expected values of the lengths of 6 driving cylinder bodies by the sea wave compensation controller;
step 4.3: and the platform executing mechanism acquires the lengths of the 6 driving cylinders, adjusts the lengths of the 6 driving cylinders to the expected values, and returns to the step 4.1.
8. A wave compensation method for an unmanned aerial vehicle take-off and landing platform according to claim 1, wherein the wave compensation method comprises the following steps: according to the state adjustment control volume of unmanned aerial vehicle landing platform, including following process:
step 5.1: through the Euler angle and the height value of the upper platform for takeoff and landing of the unmanned aerial vehicle, the length value L of 6 driving cylinder bodies is obtained according to a six-degree-of-freedom platform kinematics forward solution formula1,L2,...,L6]Then, acquiring the motion speed values of 6 driving cylinder bodies according to the inverse kinematics of the six-degree-of-freedom platform;
step 5.2: filtering the length values and the speed values of the 6 driving cylinder bodies according to an h infinite filter, and filtering out a high-frequency wave band;
step 5.3: the filtered value is calculated out by a self-adaptive fast Fourier prediction algorithmDriving cylinder length value L ' ═ L ' at next control period of aircraft takeoff and landing platform '1,L'2,...,L'6]；
Step 5.4: and controlling the driving cylinder to reach the length at the speed of (L' -L)/T, wherein T represents the execution period of the takeoff and landing platform of the unmanned aerial vehicle.
9. A wave compensation method for an unmanned aerial vehicle take-off and landing platform according to claim 1 or 8, wherein the wave compensation method comprises the following steps: the six-degree-of-freedom platform kinematics positive solution is as follows:
wherein, i is 1,2, 6 is a number of a corresponding hinge point pair up and down of the six-freedom-degree platform, x, y and z represent three-dimensional coordinate values α, β and gamma respectively representing rotation angle values around x, y and z axes under the corresponding coordinate system, and A is a number representing the rotation angle values around the x, y and z axes under the corresponding coordinate systemiIndicating the point of articulation of the hydraulic cylinder with the upper platform, BiIndicate the pneumatic cylinder and lower platform pin joint, r indicates the effective radius of upper platform, and r ═ A promptlyiw, i ═ 1,2, 6, where w denotes the upper platform center point, aiw denotes starting from w to AiThe vector of (1), wherein | represents the length of the vector;
is represented by Aiw and coordinate axis XwC represents cos and s represents sin; r represents the effective radius of the lower platform, i.e. | Bio |, o denotes the lower platform center point, Bio denotes a transition from o to BiThe vector of (a) is determined,
is represented by Bio and coordinate system axis X0Angle of (A)iBiRepresenting the driving cylinder vector.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811584774.8A CN111352447A (en) | 2018-12-24 | 2018-12-24 | Wave compensation method for take-off and landing platform of unmanned aerial vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811584774.8A CN111352447A (en) | 2018-12-24 | 2018-12-24 | Wave compensation method for take-off and landing platform of unmanned aerial vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111352447A true CN111352447A (en) | 2020-06-30 |
Family
ID=71192004
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811584774.8A Pending CN111352447A (en) | 2018-12-24 | 2018-12-24 | Wave compensation method for take-off and landing platform of unmanned aerial vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111352447A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112611382A (en) * | 2020-11-27 | 2021-04-06 | 哈尔滨工程大学 | Strapdown inertial navigation system heave measurement method with phase compensation |
| CN113093770A (en) * | 2021-03-30 | 2021-07-09 | 华南理工大学 | Wave evaluation-based multi-rotor unmanned spacecraft water surface takeoff control method |
| CN115079576A (en) * | 2022-07-20 | 2022-09-20 | 西南科技大学 | Amplitude-frequency characteristic parameter acquisition method based on unmanned aerial vehicle recovery landing under ship shaking |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104199456A (en) * | 2014-09-04 | 2014-12-10 | 中国科学院自动化研究所 | Water-surface operating control method and system for water unmanned aerial vehicle |
| CN107357170A (en) * | 2017-07-14 | 2017-11-17 | 山东大学 | A kind of Wave Model Forecasting Methodology based on active disturbance rejection state observer |
-
2018
- 2018-12-24 CN CN201811584774.8A patent/CN111352447A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104199456A (en) * | 2014-09-04 | 2014-12-10 | 中国科学院自动化研究所 | Water-surface operating control method and system for water unmanned aerial vehicle |
| CN107357170A (en) * | 2017-07-14 | 2017-11-17 | 山东大学 | A kind of Wave Model Forecasting Methodology based on active disturbance rejection state observer |
Non-Patent Citations (1)
| Title |
|---|
| MINGXI ZHANG，等: "Wave Compensator Design Based on Adaptive FFT Prediction Algorithm and H∞ filtering", 《PROCEEDINGS OF 2018 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112611382A (en) * | 2020-11-27 | 2021-04-06 | 哈尔滨工程大学 | Strapdown inertial navigation system heave measurement method with phase compensation |
| CN112611382B (en) * | 2020-11-27 | 2022-06-21 | 哈尔滨工程大学 | Strapdown inertial navigation system heave measurement method with phase compensation |
| CN113093770A (en) * | 2021-03-30 | 2021-07-09 | 华南理工大学 | Wave evaluation-based multi-rotor unmanned spacecraft water surface takeoff control method |
| CN113093770B (en) * | 2021-03-30 | 2022-03-29 | 华南理工大学 | Wave evaluation-based multi-rotor unmanned spacecraft water surface takeoff control method |
| CN115079576A (en) * | 2022-07-20 | 2022-09-20 | 西南科技大学 | Amplitude-frequency characteristic parameter acquisition method based on unmanned aerial vehicle recovery landing under ship shaking |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111352447A (en) | Wave compensation method for take-off and landing platform of unmanned aerial vehicle | |
| Cao et al. | Review of antiswing control of shipboard cranes | |
| CN110937510A (en) | Offshore crane stability control method and system with double-pendulum characteristic | |
| CN110937076B (en) | Ship comfort control system based on model prediction design of two-channel parameters and control method thereof | |
| CN103895831B (en) | A kind of boats and ships fin/wing fin rollstabilization anti-saturation controls device and control method thereof | |
| CN204490370U (en) | Active heave compensation experimental installation | |
| Hervas et al. | Automatic landing control of unmanned aerial vehicles on moving platforms | |
| CN110568814A (en) | Wave signal simulation device suitable for active heave compensation | |
| CN109240289A (en) | Wave glider yawing information self-adapting filtering method | |
| Quan et al. | A geometrically exact formulation for three-dimensional numerical simulation of the umbilical cable in a deep-sea ROV system | |
| CN107160400B (en) | Robot system with initiative wave compensation function | |
| Qian et al. | Dynamics analysis of an offshore ship-mounted crane subject to sea wave disturbances | |
| CN117105096B (en) | Sliding mode control method suitable for rope-length-variable double-swing type ship crane | |
| CN117163219B (en) | Shipborne trestle feedforward fuzzy control method considering constraint between long rods | |
| Brizzolara et al. | Design of an Unconventional ASV for Underwater Vehicles Recovery: Simulation of the motions for operations in rough seas | |
| CN210864401U (en) | Wave signal simulation device suitable for active heave compensation | |
| CN111392051B (en) | Self-adaptive landing deck control system and method for rotor type aircraft | |
| CN114879504B (en) | Self-adaptive nonlinear control method of four-degree-of-freedom marine rotary crane | |
| CN114296449B (en) | Water surface unmanned ship track rapid tracking control method based on fixed time H-infinity control | |
| CN113608440B (en) | Marine suspended boat system pendulum reduction control method considering rope length change | |
| CN114527647B (en) | Marine crane swing reduction control method based on self-adaptive sliding mode variable structure | |
| Zhang et al. | Rope-hook recovery system of fixed wing UAV based on FFT prediction algorithm and adaptive fuzzy PID control | |
| Ding et al. | Research on static fault-tolerant control method of UUV based on MPC in two dimension | |
| Zhang et al. | Wave Compensator Design Based on Adaptive FFT Prediction Algorithm and H∞ filtering | |
| Lv et al. | Design and control of cable-drive parallel robot with 6-dof active wave compensation |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200630 |
|
| RJ01 | Rejection of invention patent application after publication |