CN113325858A - Simulated bat aircraft course control method based on flapping wing amplitude - Google Patents
Simulated bat aircraft course control method based on flapping wing amplitude Download PDFInfo
- Publication number
- CN113325858A CN113325858A CN202110635064.9A CN202110635064A CN113325858A CN 113325858 A CN113325858 A CN 113325858A CN 202110635064 A CN202110635064 A CN 202110635064A CN 113325858 A CN113325858 A CN 113325858A
- Authority
- CN
- China
- Prior art keywords
- course
- control
- cpg
- amplitude
- steering engine
- 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.)
- Withdrawn
Links
- 238000000034 method Methods 0.000 title claims abstract description 21
- 241001331491 Myliobatis californica Species 0.000 claims abstract description 23
- 241001471424 Manta birostris Species 0.000 claims abstract description 10
- 238000010168 coupling process Methods 0.000 claims description 13
- 238000005859 coupling reaction Methods 0.000 claims description 13
- 230000008878 coupling Effects 0.000 claims description 10
- 210000000006 pectoral fin Anatomy 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 7
- 238000013507 mapping Methods 0.000 claims description 3
- 230000009182 swimming Effects 0.000 abstract description 4
- 238000013528 artificial neural network Methods 0.000 abstract description 2
- 230000000694 effects Effects 0.000 description 3
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 239000011664 nicotinic acid Substances 0.000 description 1
- 230000033764 rhythmic process Effects 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/04—Control of altitude or depth
- G05D1/06—Rate of change of altitude or depth
- G05D1/0692—Rate of change of altitude or depth specially adapted for under-water vehicles
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Feedback Control In General (AREA)
Abstract
The invention relates to a simulated bat ray aircraft course control method based on flapping wing amplitude, aiming at a simulated bat ray aircraft, acquiring current course information through an attitude sensor, and calculating a yaw value; designing a course fuzzy controller, and constructing a fuzzy closed-loop control system simulating the course of the bat ray aircraft so as to realize quantitative control of the expected course by establishing a control closed loop; parameters obtained by a fuzzy control algorithm are used as CPG amplitude variables, a CPG controller outputs flapping wing control signals, a CPG phase oscillator model is established, a flapping wing system controlled by a CPG neural network is adjusted, course control of the simulated manta ray aircraft is achieved, and then the task of navigating and swimming is completed.
Description
Technical Field
The invention belongs to a course control method of an underwater vehicle, and relates to a simulated manta ray course control method based on flapping wing amplitude.
Background
The unmanned underwater vehicle is used as an intelligent underwater carrier platform and has wide application in military and civil work tasks such as resource exploration, enemy reconnaissance and the like, such as hydrological information acquisition, underwater and water surface target monitoring and the like. Researchers obtain inspiration from organisms of aquatic organisms, particularly fishes such as a bat ray, and develop an artificial bat ray underwater vehicle based on a bionic propulsion principle.
With the deep ocean exploration, the requirements on the underwater vehicle are higher and higher, and the underwater vehicle is required to be controlled more accurately in course. Due to the fact that the underwater environment is complex, interference of water flow with different intensity and speed exists, and the aircraft can be easily influenced and cannot move according to the set course. The traditional underwater vehicle mostly adopts a propeller propulsion mode, and can obtain larger thrust and higher speed, but has the problems of low efficiency, high energy consumption, large noise, difficult flexible change of navigation attitude and the like. In order to solve the problem of the underwater vehicle moving and yawing in water, the traditional vehicle adopting propeller propulsion generally realizes course control by changing a rudder angle, but the simulated bat ray vehicle and the traditional vehicle have great difference in a driving mode, so that the accurate course control is very difficult to realize by adopting the traditional method, and a new course control method needs to be designed. In the published literature, no example is known of realizing course control of the simulated manta ray aircraft through change of the flapping wing state.
Disclosure of Invention
Technical problem to be solved
In order to avoid the defects of the prior art, the invention provides a simulated bat aircraft course control method based on an flapping amplitude, which realizes the good operation performance and the swimming stability of the simulated bat aircraft in a narrow space.
The basic principle of realizing the control of the simulated bat ray underwater vehicle by adjusting the asymmetric amplitude of the flapping wings is as follows: when the simulated bat ray aircraft navigates, different expected amplitudes of the flapping wings on the two sides are utilized to generate different forward propulsion forces, namely the propulsion force Fl of the flapping wing on the left side is not equal to the propulsion force Fr of the flapping wing on the right side, so that a forward propulsion resultant force and a turning moment are generated, and the larger side of the flapping amplitude of the flapping wing obtains a larger propulsion force, so that the aircraft can turn to the side with smaller flapping amplitude or without flapping to achieve the effect of controlling the course. Therefore, the posture adjustment of the simulated bat underwater vehicle can be realized through the flapping of the flapping wings at the two sides with asymmetric dynamic amplitude.
Technical scheme
A topology network structure controlled by a simulated manta ray aircraft CPG is characterized by comprising 6 driving steering engines and 6 CPG units; the 6 driving steering engines respectively correspond to 6 pectoral fin lines, the left pectoral fins are sequentially connected with a first steering engine 1, a second steering engine 2 and a third steering engine 3 from front to back, and the right pectoral fin steering engines are sequentially connected with a fourth steering engine 4, a fifth steering engine 5 and a second steering engine 6 from front to back; each steering engine is controlled by a phase oscillator model to form a unit, the mutual connection among the steering engines is realized through a coupling item, and the connection between the left and right pectoral fins is established through the pectoral fin middle units 2 and 5.
A simulated bat aircraft course control method based on flapping amplitude is adopted for the topological network structure, and is characterized by comprising the following steps:
step 1: obtaining the current course angle delta and the set course delta by the attitude sensordThe difference is used as the input of the deviation e of the course fuzzy controller, and the differential of the deviation is used as the input of the course angular change rate ec;
wherein, course angle deviation:
e＝δ-δd
course angle rate of change:
δtrepresenting the course angle at the previous moment, wherein delta t is the time difference from the previous moment to the current moment;
step 2, parameter fuzzification: mapping the course deviation e and the course deviation rate ec to a fuzzy subset, and constructing a course fuzzy control lookup table: according to the deviation e and the course angle change rate ec, inquiring a course fuzzy control inquiry table to obtain a control parameter obtained through fuzzy control processing
Wherein the fuzzy subset is { NB, NM, NS, ZO, PS, PM, PB }, and the elements in the subset represent negative big, negative middle, negative small, zero, positive small, positive middle, positive big, respectively;
and step 3: initializing the coupling weight and constant coefficient value of each CPG unit, and setting the following control parameters: including the desired phase difference
Coupling weight wijMaximum desired amplitude Ri max；
CPG phase oscillator model:
νiin order to be the frequency of the radio,
to expect a phase difference, wijTo couple the weights, aiRepresenting the amplitude gain, xiTo be offset, uiTo output, [ phi ]iDenotes the phase, riDenotes the amplitude, RiRepresenting the desired amplitude, i j representing the order cell;
and 4, step 4: the control parameter R obtained by fuzzy control processingiAs the input of the CPG topology network, the CPG topology network outputs the control output u of the ith steering enginei；
And 5: required rotation angle theta of ith steering engineiAnd the control output uiThe size of (A) is linear:
θi＝Cθui+θi0
wherein, CθIs a proportionality coefficient; thetai0The angle of the ith steering engine zero position is shown;
step 6: the angle is input into a controller to control the rotation angle of a steering engine, so that the amplitude of the flapping wings of the simulated bat ray aircraft on two sides in the navigation process is asymmetrically changed, a yawing moment capable of correcting the course is generated, the course angle of the simulated bat ray aircraft is changed, the angle deviation between the actual course angle and the expected course angle of the simulated bat ray aircraft is 0, and the course control of the simulated bat ray aircraft based on the amplitude of the flapping wings is realized.
Coupling weights w in the CPG phase oscillator modelijPresence of only omega12、ω23、ω45、ω56、ω25Five forms, take the value of omega12＝ω23＝ω34＝ω45＝3、ω25＝2。
Advantageous effects
The simulated bat aircraft course control method based on the flapping-wing amplitude, provided by the invention, aims at the simulated bat aircraft, acquires current course information through an attitude sensor, and calculates a yaw value; designing a course fuzzy controller, and constructing a fuzzy closed-loop control system simulating the course of the bat ray aircraft so as to realize quantitative control of the expected course by establishing a control closed loop; parameters obtained by a fuzzy control algorithm are used as CPG amplitude variables, a CPG controller outputs flapping wing control signals, a CPG phase oscillator model is established, a flapping wing system controlled by a CPG neural network is adjusted, course control of the simulated manta ray aircraft is achieved, and then the task of navigating and swimming is completed.
Compared with the prior art, the invention has the following beneficial technical effects:
1. the traditional craft adopting propeller propulsion generally realizes course control by changing rudder angles, but the simulated manta ray craft and the traditional craft have great difference on driving modes, so that the traditional method is difficult to realize accurate course control. The simulated manta ray underwater vehicle is controlled by using the asymmetric amplitude of the flapping wings on the two sides in the navigation process, the course of the vehicle can be accurately controlled, and a reliable method is found for the navigation control of the underwater vehicle with the flapping wing layout.
2. The course control of the simulated bat aircraft can be realized only by adjusting the rotation angle of the flapping wing steering engine, the method is simple, the adopted fuzzy control algorithm can better adapt to the complex variability of the working environment of the aircraft, the calculation amount of a lower computer system is reduced, the purpose of real-time control is achieved, the yaw control precision is obviously improved, and the stability and the reliability of the navigation of the simulated bat aircraft in a complex sea area are improved;
3. for a simulated manta ray aircraft with each CPG unit used for controlling the motion angle of a driving steering engine, establishing a CPG model for constructing the aircraft based on a plurality of CPG units, adjusting the amplitude to realize rhythm motion control of the aircraft, and when the parameters suddenly change, the yaw speed of the simulated manta ray underwater aircraft continuously changes along with the increase of the flapping wing amplitude difference at two sides, so that the transition is more gradual;
4. and a CPG network structure topological graph is constructed according to the CPG model, so that the model complexity can be reduced, and the solution is convenient.
5. Because the control output u to the ith steering engineiLinear functional processing is carried out to control the rotation angle of the steering engine, so that the rotation angle theta of the steering engine at the current momentiAngle theta of steering engine rotation from last momenti0Establish a relation to prevent the steering engine from rotating by a complete angle of uiIs instead determined at θi0The method solves the problem that course control is not accurate enough due to the fact that the rotation angle of a steering engine cannot be adjusted in place due to overlarge output control quantity change of the conventional underwater vehicle.
Drawings
FIG. 1 is a schematic view of a CPG-based simulated bat-ray aircraft network topology of the present invention
FIG. 2 is a fuzzy closed-loop feedback control schematic diagram of simulated bat ray aircraft
FIG. 3 is a graph of course control curves obtained from the experiment of the present invention
Detailed Description
The invention will now be further described with reference to the following examples and drawings:
referring to fig. 1, a simulated bat aircraft course control method based on flapping wing amplitude comprises the following steps:
1. obtaining the current course angle delta and the set course delta sent by the upper computer by the attitude sensordThe difference is used as the deviation e input of course fuzzy controller, the differential of deviationInputting as course angle change rate ec;
calculating course angle deviation:
e＝δ-δd (1)
delta denotes the current heading angle, deltadIndicating a desired heading angle
Calculating a course angle change rate:
δtindicating the course angle at the previous moment, and delta t is the time difference from the previous moment to the current moment.
2. The parameters are obfuscated. And mapping the course deviation e and the course deviation rate ec to corresponding fuzzy subsets to realize the fuzzification processing of the input parameters. Wherein the fuzzy subset is { -6, -5, -4, -3, -2, -1,0,1,2,3,4,5,6 }.
Specifically, the course fuzzy controller is mainly composed of a fuzzy control table, and the query table is obtained through offline iterative computation in advance. The course fuzzy lookup table adopted by the invention is shown in an attached table 2, wherein e represents deviation, and ec represents deviation conversion rate.
The fuzzy control parameter U can be obtained by the following table query, and accordingly, the control parameter required to be input by the CPG control network can be obtained.
3. Initializing the coupling weight and constant coefficient value of each CPG unit; setting input parameters; obtaining the output theta of each CPG unit in the simulated bat ray aircraft through equation operationi；
The specific CPG phase oscillator model is represented as follows:
wherein each equation is a phase equation, an amplitude equation and an output equation. V isiIn order to be the frequency of the radio,
to expect a phase difference, wijTo couple the weights, aiRepresenting the amplitude gain, xiTo be offset, uiTo output, [ phi ]iDenotes the phase, riDenotes the amplitude, RiIndicating the desired amplitude.
4. And constructing a topological network structure controlled by the CPG. Each CPG unit adopts a simplest connection coupling relation strategy. Referring to fig. 2, the application constructs a topology network of the simplest connection form of the simulated bat ray aircraft. The simulated bat ray aircraft comprises 8 driving steering engines which respectively correspond to 6 pectoral fin-fin lines and 2 tail fin-fin lines. The tail fin usually only plays a role in the pitching attitude, and most of the swimming attitudes can be completed only by the participation of the pectoral fin. The application only relates to motion attitude control with participation of pectoral fins, and only a topological network structure among 6 CPG units needs to be constructed.
A CPG phase oscillator model which is connected most simply is adopted, the left pectoral fin of the simulated bat aircraft comprises 3 steering engines which are named as steering engines 1,2 and 3 respectively, and the right pectoral fin steering engines are named as steering engines 3,4 and 5. Each steering engine is controlled by a phase oscillator model, and the mutual connection among the steering engines is realized through a coupling item.
The steering engines 1,2,3,4,5 and 6 are respectively controlled by units 1,2,3,4,5 and 6 of the CPG oscillator model, and the letters i and j simultaneously represent unit numbers, namely, the letter i is 1 or the letter j is 1, and both the letter i and the letter j can represent 1 unit.
The unit connection in the oscillator model is that the unit 1 is connected with the unit 2; unit 2 is connected with unit 3; unit 4 is connected with unit 5; unit 5 is connected with unit 6; unit 2 is connected to unit 5.
Coupling weight wijValue of omega12＝ω23＝ω34＝ω45＝3、ω25＝2。
And inputting preset control parameters obtained through fuzzy control into the CPG topological network. The preset control parameters comprise expected phase difference
Coupling weight wijMaximum desired amplitude Rimax(ii) a The control parameter obtained by the fuzzy control processing is a desired amplitude Ri. Inputting the parameters into a CPG topological network, and outputting the control output u of the ith steering engine by the CPG topological networki。
5. Required rotation angle theta of ith steering engineiAnd the control output uiThe size of (A) is linear:
θi＝Cθui+θi0 (4)
wherein, CθFor the scale factor, this example takes Cθ＝5；θi0The angle of the ith steering engine zero position.
The controller controls the rotation angle of the steering engine, different flapping wing amplitude changes are implemented on the current course angle change, so that the flapping wings on two sides generate asymmetric amplitude, a yaw moment capable of correcting the course is generated, the course control of the simulated bat navigation device based on the flapping wing amplitude is realized, and the navigation device advances according to the set course.
The simulated bat aircraft course control method based on the flapping amplitude is tested in a real environment by using a prototype, and a course control curve graph of the simulated bat aircraft obtained by the test is shown in fig. 3.
Claims (3)
1. A topology network structure controlled by a simulated manta ray aircraft CPG is characterized by comprising 6 driving steering engines and 6 CPG units; the 6 driving steering engines respectively correspond to 6 pectoral fin fins, the left pectoral fin is sequentially connected with a first steering engine (1), a second steering engine (2) and a third steering engine (3) from front to back, and the right pectoral fin is sequentially connected with a fourth steering engine (4), a fifth steering engine (5) and a second steering engine (6) from front to back; each steering engine is controlled by a phase oscillator model to form a unit, mutual connection among the steering engines is achieved through coupling terms, and connection between the left and right pectoral fins is established through the pectoral fin middle units (2) and (5).
2. A method for controlling the course of a simulated bat ray aircraft by adopting the flapping amplitude-based flapping-wing amplitude for the topological network structure of claim 1, which is characterized by comprising the following steps:
step 1: obtaining the current course angle delta and the set course delta by the attitude sensordThe difference is used as the input of the deviation e of the course fuzzy controller, and the differential of the deviation is used as the input of the course angular change rate ec;
wherein, course angle deviation:
e＝δ-δd
course angle rate of change:
δtrepresenting the course angle at the previous moment, wherein delta t is the time difference from the previous moment to the current moment;
step 2, parameter fuzzification: mapping the course deviation e and the course deviation rate ec to a fuzzy subset, and constructing a course fuzzy control lookup table: according to the deviation e and the course angle change rate ec, inquiring a course fuzzy control inquiry table to obtain a control parameter obtained through fuzzy control processing
Wherein the fuzzy subset is { NB, NM, NS, ZO, PS, PM, PB }, and the elements in the subset represent negative big, negative middle, negative small, zero, positive small, positive middle, positive big, respectively;
and step 3: initializing the coupling weight and constant coefficient value of each CPG unit, and setting the following control parameters: including the desired phase difference
Coupling weight wijMaximum desired amplitude Rimax；
CPG phase oscillator model:
νiin order to be the frequency of the radio,
to expect a phase difference, wijTo couple the weights, aiRepresenting the amplitude gain, xiTo be offset, uiTo output, [ phi ]iDenotes the phase, riDenotes the amplitude, RiRepresenting the desired amplitude, i j representing the order cell;
and 4, step 4: the control parameter R obtained by fuzzy control processingiAs the input of the CPG topology network, the CPG topology network outputs the control output u of the ith steering enginei；
And 5: required rotation angle theta of ith steering engineiAnd the control output uiThe size of (A) is linear:
θi＝Cθui+θi0
wherein, CθIs a proportionality coefficient; thetai0The angle of the ith steering engine zero position.
Step 6: the angle is input into a controller to control the rotation angle of a steering engine, so that the amplitude of the flapping wings of the simulated bat ray aircraft on two sides in the navigation process is asymmetrically changed, a yawing moment capable of correcting the course is generated, the course angle of the simulated bat ray aircraft is changed, the angle deviation between the actual course angle and the expected course angle of the simulated bat ray aircraft is 0, and the course control of the simulated bat ray aircraft based on the amplitude of the flapping wings is realized.
3. The method of claim 2, further comprising: coupling weights w in the CPG phase oscillator modelijPresence of only omega12、ω23、ω45、ω56、ω25Five forms, take the value of omega12＝ω23＝ω34＝ω45＝3、ω25＝2。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110635064.9A CN113325858A (en) | 2021-06-08 | 2021-06-08 | Simulated bat aircraft course control method based on flapping wing amplitude |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110635064.9A CN113325858A (en) | 2021-06-08 | 2021-06-08 | Simulated bat aircraft course control method based on flapping wing amplitude |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113325858A true CN113325858A (en) | 2021-08-31 |
Family
ID=77420030
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110635064.9A Withdrawn CN113325858A (en) | 2021-06-08 | 2021-06-08 | Simulated bat aircraft course control method based on flapping wing amplitude |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113325858A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115081318A (en) * | 2022-06-10 | 2022-09-20 | 西北工业大学 | Simulated bat aircraft experimental data prediction method based on antagonistic neural network |
| CN116330293A (en) * | 2023-04-13 | 2023-06-27 | 西北工业大学宁波研究院 | CPG phase oscillator model with space and time asymmetry characteristics |
| CN116974189A (en) * | 2023-05-11 | 2023-10-31 | 西北工业大学宁波研究院 | CPG trapezoidal wave phase oscillator model of simulated ray underwater vehicle |
| CN117148727A (en) * | 2023-10-31 | 2023-12-01 | 西北工业大学 | Method for controlling bottom-dwelling submergence of simulated ray craft based on tail fin and variable buoyancy system |
| CN117406757A (en) * | 2023-12-12 | 2024-01-16 | 西北工业大学宁波研究院 | Underwater autonomous navigation method based on three-dimensional global vision |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101870109A (en) * | 2009-04-22 | 2010-10-27 | 中国科学院自动化研究所 | Fish swimming imitating robot movement control device and method |
| CN104477357A (en) * | 2014-12-18 | 2015-04-01 | 北京航空航天大学 | Implementation method for rapid great pitch angle change motion of pectoral fin paddling type robotic fish |
| CN105785999A (en) * | 2016-04-27 | 2016-07-20 | 大连海事大学 | Unmanned surface vehicle course motion control method |
| CN107323638A (en) * | 2017-06-29 | 2017-11-07 | 上海海洋大学 | A kind of bionical devil ray device |
| CN109814581A (en) * | 2019-01-09 | 2019-05-28 | 哈尔滨工业大学（威海） | ROV underwater robot automatic fixing depth motion control method |
| CN109839939A (en) * | 2019-02-20 | 2019-06-04 | 博雅工道（北京）机器人科技有限公司 | A kind of bionical underwater fish swimming posture planing method based on CPG model |
| CN110937092A (en) * | 2019-12-12 | 2020-03-31 | 华南理工大学 | CPG control method of multi-mode bionic stay wire robot fish and robot fish |
| CN210455158U (en) * | 2019-08-16 | 2020-05-05 | 上海澳浔科技有限公司 | Bionic bat ray based on joint type mechanical arm |
| CN111190364A (en) * | 2019-12-06 | 2020-05-22 | 南京工程学院 | Bionic dolphin intelligent control method based on sensory feedback CPG model |
| CN111930132A (en) * | 2020-07-22 | 2020-11-13 | 西北工业大学 | Track control method for underwater autonomous vehicle |
-
2021
- 2021-06-08 CN CN202110635064.9A patent/CN113325858A/en not_active Withdrawn
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101870109A (en) * | 2009-04-22 | 2010-10-27 | 中国科学院自动化研究所 | Fish swimming imitating robot movement control device and method |
| CN104477357A (en) * | 2014-12-18 | 2015-04-01 | 北京航空航天大学 | Implementation method for rapid great pitch angle change motion of pectoral fin paddling type robotic fish |
| CN105785999A (en) * | 2016-04-27 | 2016-07-20 | 大连海事大学 | Unmanned surface vehicle course motion control method |
| CN107323638A (en) * | 2017-06-29 | 2017-11-07 | 上海海洋大学 | A kind of bionical devil ray device |
| CN109814581A (en) * | 2019-01-09 | 2019-05-28 | 哈尔滨工业大学（威海） | ROV underwater robot automatic fixing depth motion control method |
| CN109839939A (en) * | 2019-02-20 | 2019-06-04 | 博雅工道（北京）机器人科技有限公司 | A kind of bionical underwater fish swimming posture planing method based on CPG model |
| CN210455158U (en) * | 2019-08-16 | 2020-05-05 | 上海澳浔科技有限公司 | Bionic bat ray based on joint type mechanical arm |
| CN111190364A (en) * | 2019-12-06 | 2020-05-22 | 南京工程学院 | Bionic dolphin intelligent control method based on sensory feedback CPG model |
| CN110937092A (en) * | 2019-12-12 | 2020-03-31 | 华南理工大学 | CPG control method of multi-mode bionic stay wire robot fish and robot fish |
| CN111930132A (en) * | 2020-07-22 | 2020-11-13 | 西北工业大学 | Track control method for underwater autonomous vehicle |
Non-Patent Citations (1)
| Title |
|---|
| YONG CAO，ET AL.: "CPG-fuzzy-based control of a cownose-ray-like fish robot", 《INDUSTRIAL ROBOT》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115081318A (en) * | 2022-06-10 | 2022-09-20 | 西北工业大学 | Simulated bat aircraft experimental data prediction method based on antagonistic neural network |
| CN115081318B (en) * | 2022-06-10 | 2024-01-26 | 西北工业大学 | Artificial bata ray based on antagonistic neural network method for predicting experimental data of aircraft |
| CN116330293A (en) * | 2023-04-13 | 2023-06-27 | 西北工业大学宁波研究院 | CPG phase oscillator model with space and time asymmetry characteristics |
| CN116974189A (en) * | 2023-05-11 | 2023-10-31 | 西北工业大学宁波研究院 | CPG trapezoidal wave phase oscillator model of simulated ray underwater vehicle |
| CN116974189B (en) * | 2023-05-11 | 2024-05-10 | 西北工业大学宁波研究院 | CPG trapezoidal wave control method for simulated ray underwater vehicle |
| CN117148727A (en) * | 2023-10-31 | 2023-12-01 | 西北工业大学 | Method for controlling bottom-dwelling submergence of simulated ray craft based on tail fin and variable buoyancy system |
| CN117148727B (en) * | 2023-10-31 | 2024-01-30 | 西北工业大学 | Method for controlling bottom-dwelling submergence of simulated ray craft based on tail fin and variable buoyancy system |
| CN117406757A (en) * | 2023-12-12 | 2024-01-16 | 西北工业大学宁波研究院 | Underwater autonomous navigation method based on three-dimensional global vision |
| CN117406757B (en) * | 2023-12-12 | 2024-04-19 | 西北工业大学宁波研究院 | Underwater autonomous navigation method based on three-dimensional global vision |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113325858A (en) | Simulated bat aircraft course control method based on flapping wing amplitude | |
| Harper et al. | Modeling the dynamics of spring-driven oscillating-foil propulsion | |
| US9290268B2 (en) | Hovering and gliding multi-wing flapping micro aerial vehicle | |
| JP2023082107A (en) | Vertical takeoff and landing (vtol) air vehicle | |
| US6568634B2 (en) | Wing-drive mechanism and vehicle employing same | |
| US6206324B1 (en) | Wing-drive mechanism, vehicle employing same, and method for controlling the wing-drive mechanism and vehicle employing same | |
| CN113341693B (en) | Course control method based on asymmetric phase difference and amplitude of flapping wings | |
| Wang et al. | Design, modeling, control, and experiments for a fish-robot-based IoT platform to enable smart ocean | |
| Yu et al. | A framework for biomimetic robot fish's design and its realization | |
| CN112130566A (en) | Unmanned ship, unmanned plane hybrid formation control method and control system thereof based on fuzzy logic and sliding mode control strategy | |
| Izraelevitz et al. | A novel degree of freedom in flapping wings shows promise for a dual aerial/aquatic vehicle propulsor | |
| Zhang et al. | Design and locomotion control of a dactylopteridae-inspired biomimetic underwater vehicle with hybrid propulsion | |
| Garcia et al. | Attitude stabilization with real-time experiments of a tail-sitter aircraft in horizontal flight | |
| CN114779645B (en) | Pectoral fin flapping robot fish formation control method under directional fixed communication topology | |
| CN110703788A (en) | Stability augmentation control method of miniature flapping-wing aircraft and implementation thereof | |
| CN113342012B (en) | Course control method of sliding and flapping integrated aircraft | |
| Free et al. | Bioinspired pursuit with a swimming robot using feedback control of an internal rotor | |
| CN107315348B (en) | Position and posture control method of unmanned underwater vehicle based on punishment type wavelet network | |
| CN116482974A (en) | CPG phase oscillator model with sliding and flapping switching functions | |
| CN116225069A (en) | CPG-based formation control method for bionic ornithopter flying robot | |
| Moore | Closed-Loop Control of a Delta-Wing Unmanned Aerial-Aquatic Vehicle | |
| Siegenthaler et al. | System integration and fin trajectory design for a robotic sea-turtle | |
| CN113341973B (en) | Course control method based on asymmetric phase difference of flapping wings | |
| CN113342011A (en) | Gliding course control method of simulated bat aircraft based on rolling mechanism | |
| Hua et al. | Balanced-force-control of underactuated thrust-propelled vehicles |
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 | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20210831 |