CN101256409A - Control method for changing structure of underwater hiding-machine space based on recursion fuzzy neural network - Google Patents
Control method for changing structure of underwater hiding-machine space based on recursion fuzzy neural network Download PDFInfo
- Publication number
- CN101256409A CN101256409A CNA2008100642563A CN200810064256A CN101256409A CN 101256409 A CN101256409 A CN 101256409A CN A2008100642563 A CNA2008100642563 A CN A2008100642563A CN 200810064256 A CN200810064256 A CN 200810064256A CN 101256409 A CN101256409 A CN 101256409A
- Authority
- CN
- China
- Prior art keywords
- centerdot
- prime
- control system
- rho
- rfnn
- 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
Links
Images
Landscapes
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
- Feedback Control In General (AREA)
Abstract
The invention provides an underwater vehicle space variable structure control method based on a recurrent fuzzy neural network. A RFNN-based rudder control system, a RFNN-based envelope rudder control system and a RFNN-based tail elevating rudder control system are designed, and combined together to form a united control system for underwater vehicle space motion. In this invention, the RFNN-based rudder control system, the RFNN-based envelope rudder control system and the RFNN-based tail elevating rudder control system are designed, and further combined to compose a united control system for underwater vehicle space motion, since the RFNN can make real-time adjustment of a controller gain epsilon, according to uncertain items of the system, the system not only has good dynamic property, but also effectively lowers buffeting and improves the robustness of an underwater vehicle automatic rudder control system.
Description
(1) technical field
What the present invention relates to is a kind of control method, particularly a kind of control method of underwater hiding-machine auto-pilot control system.
(2) background technology
Underwater hiding-machine auto-pilot control technology is the important directions of underwater hiding-machine movement control technology development.Tradition underwater hiding-machine automatic pilot system normally is made up of surface level yaw rudder system and vertical plane elevator system, is called combined control system (or centralized control system).The core of this design philosophy is outstanding kinematic behavior of dividing plane motion, and controlling Design is simplified, and realizes easily, and adapt with the dirigibility of reality behaviour ship that therefore dividing graphic design method is the main mode of research underwater hiding-machine combined control system.The part but this design also comes with some shortcomings, major defect is: owing to do not consider the coupling effect of motion in controlling Design, last combined control system robustness is weakened.General compensation method is to utilize various corrections, compensation system to improve the anti-interference of system, and this makes system become complicated, and definite optimization work of controlled variable is cumbersome.
When in fact underwater hiding-machine is done spatial movement under water, the accurate movement equation is difficult to obtain usually, coupling influence between the non-linear and equation in the equation of motion, make the maneuvering motion of underwater hiding-machine become one and have stronger probabilistic system, the method that some are controlled based on mathematical models is difficult to the designing requirement that reaches satisfied as PID, decoupling zero, the most excellent control algolithm.Become the integrated approach of structure control as a kind of control, its major advantage is to adopt coarse mathematical model to carry out controlling Design, can estimate uncertain interference effect, stronger robustness is arranged, relatively be suitable for the design of underwater hiding-machine kinetic control system.Up to now, (Recurrent Fuzzy Neural Network, adaptive sliding moding structure control method RFNN) is not applied in the submersible space motion combined control system under water as yet based on the recurrence fuzzy neural network.
(3) summary of the invention
The object of the present invention is to provide and a kind ofly can estimate uncertain interference effect, have the underwater hiding-machine space variable structure control method based on the recurrence fuzzy neural network of stronger robustness.
The object of the present invention is achieved like this:
Design yaw rudder control system, casing rudder control system and tail elevating rudder control system respectively based on RFNN, yaw rudder control system, tail elevating rudder control system, casing rudder control system group be in the same place, constitute the combined control system of underwater submersible space motion.At first by system measurements device input course angle, trim angle, the degree of depth and conversion depth information, wherein, course angle inputs to the yaw rudder control system based on RFNN, adopt network shown in Figure 3 to adjust gain parameter, output actual direction rudder angle, this parameter and speed of a ship or plane information input to rectification building-out system, output information is input to respectively that tail based on RFNN rises the rudder control system and based on the casing rudder control system (in conjunction with trim angle and depth information input) of RFNN, adopt network shown in Figure 3 to adjust gain parameter, export actual tail vane rudder angle and first rudder rudder angle.
The control law of described course control is:
Ride gain in the formula
Adjusted by a RFNN network real-time, sat () is a saturation function, and μ is a boundary layer thickness, is a little arithmetic number.
The control law of described degree of depth control is:
The control law of described degree of depth control is:
The present invention utilizes the design philosophy on branch plane, yaw rudder control system, casing rudder control system and tail elevating rudder control system have been designed respectively based on RFNN, and yaw rudder control system, tail elevating rudder control system, casing rudder control system pressed the certain way group and be in the same place, constitute the combined control system of underwater submersible space motion.In the design of controller, other state variable relevant with controlled variable done to disturb processing, realized full decoupled control.
Underwater submersible space motion combined control system structured flowchart as shown in Figure 1, the major function of measurement system is the required state variable of Measurement and Control System among the figure.ψ
d, θ
d, ζ
d, H
dBe respectively that the instruction course angle is set, trim angle is set, and the degree of depth is set and the conversion degree of depth is set.Rolling corrector and side wash compensator all are housed, with the influence of compensating motion coupling in common underwater hiding-machine PID auto navigator.The underwater hiding-machine actual measurement
With
Deng signal is angular velocity under the inertial coordinates system, if bigger rolling motion appears in ship, under the inertial coordinates system
With
Not exclusively corresponding with the angular velocity q and the r of hull coordinate system, these signals will be changed before feeding back to control system, and this work is finished by the rolling corrector usually.In variable structure control system, this correction not necessarily because the strong robustness of variable structure control system, can be with uncorrected
With
Feed back in the control system,
With
With the deviation of q and r, handle by the interference of control system.When the underwater hiding-machine underwater turning, owing to the normal navigation that change in depth influences underwater hiding-machine can appear in the influence of surveying wash.
Therefore in the steering rudder, must be aided with suitable elevating rudder and change the depthkeeping cycle.Because becoming the design philosophy of structure controller is that coupling influence is counted in the interference, thereby can reach the coupling effect of control action.Therefore in variable structure control system, rectification building-out control can be cancelled, and has simplified the complicacy of system and device.The present invention rises the rudder control system by yaw rudder control system, casing rudder control system, the tail that designs based on RFNN, and then formation underwater submersible space motion combined control system, because RFNN can adjust controller gain in real time according to uncertain item size in the system
The system that makes not only has good dynamic perfromance, can also reduce effectively to buffet, and improves the robustness of underwater hiding-machine auto-pilot control system.
(4) description of drawings
Fig. 1 is a underwater submersible space motion combined control system structured flowchart;
Fig. 2 is underwater submersible space motion combined control system implementing procedure figure;
Fig. 3 is the System with Sliding Mode Controller block diagram with the RFNN estimated gain;
Fig. 4-a to Fig. 4-d is underwater hiding-machine depthkeeping cycle simulation result figure, wherein speed of a ship or plane u=10kn, yaw rudder δ
r=10 °,----the motion simulation result when----expression vertical plane control system does not participate in controlling; Wherein: Fig. 4-a is the space motion path of underwater hiding-machine; Fig. 4-b, Fig. 4-c are the curves of output of trim angle and course angle; Fig. 4-d is the curve of output of yaw rudder and elevating rudder.
Fig. 5-a to Fig. 5-d is underwater hiding-machine space maneuver simulation result figure, and wherein extremely 10m, trim angle are set at θ under water from 50m floats under water for speed of a ship or plane u=12kn, underwater hiding-machine
d=5 °, the conversion degree of depth are 5m, require course angle ψ to change to 120 ° and the motion simulation curves that keep from 0 ° simultaneously; Wherein Fig. 5-a is the space motion path of underwater hiding-machine; Fig. 5-b, Fig. 5-c are the curves of output of trim angle and course angle; Fig. 5-d is the curve of output of yaw rudder and elevating rudder.
(5) embodiment
For example the present invention is done description in more detail below in conjunction with accompanying drawing:
1) RFNN of yaw rudder course control becomes the structure controller design
The horizontal plane motion of underwater hiding-machine comprises axially-movable, transverse movement and rolling motion, and its equation of motion is defined as follows respectively:
Axial equation:
(1)
Horizontal equation:
(2)
The driftage equation:
U, v, w represent three linear velocity components on X, Y, Z axle of hull coordinate system, i.e. longitudinal velocity, transverse velocity and vertical velocity in the formula; P, q, r are angular velocity in roll, angular velocity in pitch and course angle speed;
θ, ψ are heeling angle, trim angle and the course angle of underwater hiding-machine; M, L, h are respectively quality, length and the heights of C.G. of hull; ρ, g are density of sea water and acceleration of gravity; ξ, η, ζ are the geographic coordinate position of hull initial point; I
x, I
y, I
zBe the moment of inertia of underwater hiding-machine around X, Y, Z axle; x
G, y
G, z
GBarycentric coordinates position for underwater hiding-machine; δ
r, δ
b, δ
sBe the yaw rudder rudder angle of underwater hiding-machine, first rudder (casing rudder) rudder angle, tail vane rudder angle; a
T, b
T, c
TThe zero dimension propulsive coefficient; u
cThe speed of benchmark navigation attitude; X '
Qq, Y '
Pq, Z '
Pp, K '
Qr, M '
Pp, N '
PqBe respectively the zero dimension hydrodynamic force coefficient of underwater hiding-machine.
Consider following relation:
Under the speed control good premise, can think that the speed u of turning motion remains unchanged; If speed is not controlled, under the situation that keeps the main propulsion motor invariablenes turning speed, by the actual change of axial equation decision speed.General surface level course controlling Design only uses equation (3) and (4) to design, and measures because transverse velocity v is difficult, therefore often ignores the coupling influence of equation (2) to course angle speed r, and this influence is finally born by the robustness of system, can obtain:
Equation (6) is changed into following form:
Wherein
Following formula shows that we move other degree of freedom to the coupling influence of yawing rotation, the nonlinear characteristic of yawing rotation itself, and the model mismatch of horizontal plane motion model (designing a model of being adopted itself is exactly the motion model of simplifying) all disturbs d by surveying
1(t) handle.Choose:
e
1(t)=ψ
d(t)-ψ(t)
In the formula, ψ
d(t) be given course angle,
Be respectively single order, second derivative; e
1(t) be the deviation of course angle.
The selection switching function is:
Can in the hope of:
Use and become the control law that structure control can get course control:
Ride gain in the formula
Adjust by a RFNN network real-time.Sat () is a saturation function, and μ is a boundary layer thickness, is a little arithmetic number.
2) RFNN of casing rudder degree of depth control becomes the structure controller design
The vertical plane motion of underwater hiding-machine comprises catenary motion and pitching, and its equation of motion is defined as follows respectively:
Vertical equation:
The trim equation:
Consider relational expression:
The manipulation of physical of underwater hiding-machine shows, deepen motor-driven on, generally requiring trim is 3 °~5 °, deepening rapidly and requiring trim is 5 °~7 °, and underwater hiding-machine is limited by the speed of a ship or plane and the sea area degree of depth, and from safety perspective, the trim angle maximum is in 7 °~10 °.Therefore, trim angle changes less generally speaking, and formula (13) can be reduced to
(15) formula is updated to (11) formula, and the form that changes the Linear Control equation into can get:
In the formula
As can be seen, we are distracter d to the influence of the influence of trim angle and manipulation tail vane from formula (17)
2(t) handled, embodied the automatic synchronization of change structure controller the head and the tail rudder.Choose
e
2(t)=ζ
d(t)-ζ(t)
ζ in the formula
d(t) be the instruction degree of depth, e
2(t) be the dark deviation of diving.
Choosing switching function is
Can get this switching function differentiate
(19)
Use and become the control law that structure control can get degree of depth control:
3) RFNN of tail elevating rudder trim control becomes the structure controller design
Wushu (14) substitution formula (12), and the form that changes into the Linear Control equation can get:
In the formula
Equally, in the trim controller, the influence of the influence of vertical velocity w and casing rudder is all contributed to distracter d
3(t) in.Because trim angle is all smaller usually, thus sin θ ≈ θ, substitution formula (21)
Choose
e
3=θ
d-θ
In the formula, θ
dBe instruction trim angle, e
3Deviation for instruction trim angle and actual trim angle.
Get switching function:
This switching function differentiate is got:
(24)
Use and become the control law that structure control can get degree of depth control:
(25)
Can mediate to yaw rudder control system, casing rudder control system and tail elevating rudder control system by adaptive sliding mode controller as shown in Figure 3, realize jointly controlling of underwater hiding-machine based on RFNN.Below by emulation mode the main forms of motion of underwater hiding-machine space maneuver is verified.Considered the motor-driven of rudder in the emulation, the yaw rudder speed setting is | δ
r|
Max=3 °/s, the elevating rudder rotating speed is made as | δ
B, s|
Max=5 °/s.In direction controller, RFNN (1) is 2 input nodes, 12 regular nodes, 1 output node; RFNN (2) is 3 input nodes, 18 regular nodes, and 1 output node, 3 inputs are respectively: underwater hiding-machine speed of a ship or plane u, yaw rudder rudder angle δ
rWith course angle ψ.In depth controller and trim angle controller, RFNN (1) is 2 input nodes, 12 regular nodes, 1 output node; RFNN (2) is 5 input nodes, 33 regular nodes, and 1 output node, 5 inputs are respectively: underwater hiding-machine speed of a ship or plane u, yaw rudder rudder angle δ
r, head and the tail elevating rudder rudder angle δ
bAnd δ
s, and system's output feedback, for first rudder control system degree of depth ξ, be trim angle θ for the tail vane control system.
Fig. 4 provides depthkeeping turning motion simulation result, as can be seen, if the vertical plane control system does not participate in control, when circling round, underwater hiding-machine will do to change the spatially spiral motion of the degree of depth, and under the control of combined control system, can guarantee depthkeeping break-in campaign, the steady-state error of the degree of depth is less than 0.2m, and this explanation control system offside wash has good inhibitory effect.Fig. 5 provides the space maneuver simulation result.Since RFNN can be online the adjustment controller gain, make control system that good dynamic perfromance not only be arranged, also have higher steady precision.To the control requirement of the degree of depth, course and trim etc., dynamic quality was good when designed combined control system can be finished underwater submersible space motion preferably, and control accuracy is higher, has stronger robustness.
Claims (4)
1, a kind of underwater hiding-machine space variable structure control method based on the recurrence fuzzy neural network, it is characterized in that: design yaw rudder control system, casing rudder control system and tail elevating rudder control system respectively based on RFNN, yaw rudder control system, tail elevating rudder control system, casing rudder control system group be in the same place, constitute the combined control system of underwater submersible space motion; At first by system measurements device input course angle, trim angle, the degree of depth and conversion depth information, wherein, course angle inputs to the yaw rudder control system based on RFNN, adjust gain parameter, output actual direction rudder angle, this parameter and speed of a ship or plane information input to rectification building-out system, and output information is input to respectively that tail based on RFNN rises the rudder control system and based on the casing rudder control system of RFNN, adjust gain parameter, export actual tail vane rudder angle and first rudder rudder angle.
2, the underwater hiding-machine space variable structure control method based on the recurrence fuzzy neural network according to claim 1 is characterized in that: the control law of described course control is:
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN200810064256A CN100589055C (en) | 2008-04-08 | 2008-04-08 | Control method for changing structure of underwater hiding-machine space based on recursion fuzzy neural network |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN200810064256A CN100589055C (en) | 2008-04-08 | 2008-04-08 | Control method for changing structure of underwater hiding-machine space based on recursion fuzzy neural network |
Publications (2)
Publication Number | Publication Date |
---|---|
CN101256409A true CN101256409A (en) | 2008-09-03 |
CN100589055C CN100589055C (en) | 2010-02-10 |
Family
ID=39891283
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN200810064256A Expired - Fee Related CN100589055C (en) | 2008-04-08 | 2008-04-08 | Control method for changing structure of underwater hiding-machine space based on recursion fuzzy neural network |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN100589055C (en) |
Cited By (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101825903A (en) * | 2010-04-29 | 2010-09-08 | 哈尔滨工程大学 | Water surface control method for remotely controlling underwater robot |
CN102121261A (en) * | 2010-01-08 | 2011-07-13 | 上海三远机电有限公司 | Phase-locked loop synchronous switching and FNN intelligent variable frequency constant pressure water supply system |
CN102375723A (en) * | 2010-08-06 | 2012-03-14 | 腾讯科技(深圳)有限公司 | Soft keyboard skin volume optimizing method and system |
CN102591203A (en) * | 2012-02-17 | 2012-07-18 | 南京国电环保设备有限公司 | Direct nerve network control method based on differentiator for servo motor |
CN102819220A (en) * | 2012-07-24 | 2012-12-12 | 华中科技大学 | Adaptive control method of autopilot of ship |
CN104590517A (en) * | 2014-12-18 | 2015-05-06 | 西北工业大学 | Compound posture and orbit control method for underwater vehicle |
CN104794276A (en) * | 2015-04-17 | 2015-07-22 | 浙江工业大学 | Standard recurrent neural network engine idle model identification method |
CN104050329B (en) * | 2014-06-25 | 2017-07-11 | 哈尔滨工程大学 | A kind of method for detecting Collision Risk Index |
CN110703610A (en) * | 2019-11-19 | 2020-01-17 | 河海大学常州校区 | Nonsingular terminal sliding mode control method for recursive fuzzy neural network of micro gyroscope |
CN110703611A (en) * | 2019-11-19 | 2020-01-17 | 河海大学常州校区 | Micro-gyroscope sensor terminal sliding mode control system based on recursive fuzzy neural network |
US10935986B1 (en) | 2019-11-28 | 2021-03-02 | Institute Of Automation, Chinese Academy Of Sciences | Gliding depth control method, system and device for biomimetic gliding robotic dolphin |
WO2021103391A1 (en) * | 2019-11-28 | 2021-06-03 | 中国科学院自动化研究所 | Method and system for controlling gliding depth of biomimetic robotic gliding dolphin, and apparatuses |
-
2008
- 2008-04-08 CN CN200810064256A patent/CN100589055C/en not_active Expired - Fee Related
Cited By (17)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102121261A (en) * | 2010-01-08 | 2011-07-13 | 上海三远机电有限公司 | Phase-locked loop synchronous switching and FNN intelligent variable frequency constant pressure water supply system |
CN101825903B (en) * | 2010-04-29 | 2014-11-19 | 哈尔滨工程大学 | Water surface control method for remotely controlling underwater robot |
CN101825903A (en) * | 2010-04-29 | 2010-09-08 | 哈尔滨工程大学 | Water surface control method for remotely controlling underwater robot |
CN102375723A (en) * | 2010-08-06 | 2012-03-14 | 腾讯科技(深圳)有限公司 | Soft keyboard skin volume optimizing method and system |
CN102375723B (en) * | 2010-08-06 | 2016-01-20 | 腾讯科技(深圳)有限公司 | Soft keyboard skin volume optimizing method and system |
CN102591203A (en) * | 2012-02-17 | 2012-07-18 | 南京国电环保设备有限公司 | Direct nerve network control method based on differentiator for servo motor |
CN102819220A (en) * | 2012-07-24 | 2012-12-12 | 华中科技大学 | Adaptive control method of autopilot of ship |
CN102819220B (en) * | 2012-07-24 | 2014-06-04 | 华中科技大学 | Adaptive control method of autopilot of ship |
CN104050329B (en) * | 2014-06-25 | 2017-07-11 | 哈尔滨工程大学 | A kind of method for detecting Collision Risk Index |
CN104590517A (en) * | 2014-12-18 | 2015-05-06 | 西北工业大学 | Compound posture and orbit control method for underwater vehicle |
CN104794276A (en) * | 2015-04-17 | 2015-07-22 | 浙江工业大学 | Standard recurrent neural network engine idle model identification method |
CN110703610A (en) * | 2019-11-19 | 2020-01-17 | 河海大学常州校区 | Nonsingular terminal sliding mode control method for recursive fuzzy neural network of micro gyroscope |
CN110703611A (en) * | 2019-11-19 | 2020-01-17 | 河海大学常州校区 | Micro-gyroscope sensor terminal sliding mode control system based on recursive fuzzy neural network |
CN110703611B (en) * | 2019-11-19 | 2022-05-10 | 河海大学常州校区 | Micro-gyroscope sensor terminal sliding mode control system based on recursive fuzzy neural network |
CN110703610B (en) * | 2019-11-19 | 2022-05-10 | 河海大学常州校区 | Nonsingular terminal sliding mode control method for recursive fuzzy neural network of micro gyroscope |
US10935986B1 (en) | 2019-11-28 | 2021-03-02 | Institute Of Automation, Chinese Academy Of Sciences | Gliding depth control method, system and device for biomimetic gliding robotic dolphin |
WO2021103391A1 (en) * | 2019-11-28 | 2021-06-03 | 中国科学院自动化研究所 | Method and system for controlling gliding depth of biomimetic robotic gliding dolphin, and apparatuses |
Also Published As
Publication number | Publication date |
---|---|
CN100589055C (en) | 2010-02-10 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN100589055C (en) | Control method for changing structure of underwater hiding-machine space based on recursion fuzzy neural network | |
Sarda et al. | Station-keeping control of an unmanned surface vehicle exposed to current and wind disturbances | |
CN106292287B (en) | A kind of UUV path following method based on adaptive sliding-mode observer | |
CN102385316B (en) | Deepening controlling method of underactuated automatic underwater vehicle based on neural network back stepping method | |
CN111666628B (en) | Adaptive fault-tolerant control method for supercavitation navigation body | |
CN102768539A (en) | AUV (autonomous underwater vehicle) three-dimension curve path tracking control method based on iteration | |
CN106774361B (en) | It is a kind of based on feedforward and feedback complex control aircraft carrier the warship stern stream suppressing method of warship | |
EP3653489B1 (en) | Methods and systems for controlling low-speed propulsion of a marine vessel | |
CN106681352B (en) | A kind of underwater robot control method of rotatable rudder propeller | |
CN115357036B (en) | Double-layer anti-interference depth tracking control method and system of under-actuated underwater vehicle | |
Fan et al. | Impact of current disturbances on AUV docking: Model-based motion prediction and countering approaches | |
CN111857165B (en) | Trajectory tracking control method of underwater vehicle | |
CN110007606A (en) | A kind of unmanned surface vehicle error constraints control method considering input saturation | |
CN103226326A (en) | Frequency domain analysis method for ship autopilot system | |
CN112987771B (en) | Mechanical sailing boat path tracking control method based on multiport output error trigger mechanism | |
Gao et al. | Nonlinear trajectory tracking control of a new autonomous underwater vehicle in complex sea conditions | |
Bibuli et al. | Line following guidance control: Application to the Charlie unmanned surface vehicle | |
CN117707162A (en) | Unmanned sailing boat dynamic event triggering control method based on improved LVS guidance | |
Zhang et al. | The application of self-tuning fuzzy PID control method to recovering AUV | |
CN112591060B (en) | Control method for X-shaped rudder of autonomous underwater vehicle | |
CN112925332B (en) | Cooperative intersection butt joint control method for unmanned ship and underwater unmanned submersible vehicle combined system | |
Juan et al. | Path following backstepping control of underactuated unmanned underwater vehicle | |
Shi et al. | Design of AUV height control based on adaptive Neuro-fuzzy inference system | |
Moe et al. | Path following of underactuated marine underwater vehicles in the presence of unknown ocean currents | |
CN113820956B (en) | High-speed AUV motion control method |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C14 | Grant of patent or utility model | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20100210 Termination date: 20180408 |
|
CF01 | Termination of patent right due to non-payment of annual fee |