CN106444359A - Human-simulated intelligent control method for autonomous region keeping of water-jet propulsion unmanned ship - Google Patents
Human-simulated intelligent control method for autonomous region keeping of water-jet propulsion unmanned ship Download PDFInfo
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Abstract
The invention provides a human-simulated intelligent control method for autonomous region keeping of a water-jet propulsion unmanned ship, which is characterized in that analysis and calculation for a key parameter are performed on parameters measured by a position and attitude sensor used for controlling the boundary, a region keeping judgment system judges whether region keeping is required to be performed or not according to a calculated value and an actual value of the key parameter, a deviation equation of an under-actuated water-jet propulsion unmanned ship motion equation and a region keeping stop position trajectory equation is solved if region keeping is required to be performed, data information is transferred to a human-simulated intelligent controller, and the human-simulated intelligent controller determines a region keeping control strategy according to a regulated variable, the deviation and the variation trend of the deviation and implementing the region keeping control strategy through an execution mechanism. The human-simulated intelligent control method is applicable to the fields of region marine search and rescue and exploitation technologies and the like, and can ensure the unmanned ship not to be away from the specified region no matter how the unmanned ship moves.
Description
Technical field
The present invention relates to a kind of unmanned boat control method, it is imitative that specifically a kind of unmanned boat autonomous zone keeps
People's intelligent control method.
Background technology
Hydraulic jet propulsion unmanned surface vehicle (USV) be one kind can under actual marine environment safe autonomous navigation, and complete
The marine smart motion platform of various tasks, can carry sensor, communication device, in conjunction with hydraulic propeller advantage its have hidden
Body is good, manoeuvrable, automatic Pilot the features such as, be suitable under various adverse circumstances, execution detection study, shallow water mapping, sea
Ocean is searched and rescued and the tasks such as oceanographic research, the danger that no one was injured.Unmanned boat system be drive lacking, large disturbances, fast become
, the System with Nonlinear Coupling of multiple-input and multiple-output.For under-actuated systems due to lacking laterally driven power, it does not enable fixed
Point location function is it is also difficult to realize dynamic positioning function, but the actual task of unmanned boat needs in requiring to be related to region holding work(
Can, such as the region ocean of unmanned boat is searched and rescued and exploration, area sampling and monitoring, harbor patrol etc..Therefore, carry out unmanned boat autonomous
Region keeps the research of control technology highly significant.And autonomous zone keeping method is all to realize on the basis of dynamic positioning
, main application is the large ship with multiple propulsion plants, has not been used to the miniature self-service of single propulsion plant
Autonomous zone keeping method on ship.In open source literature therefore at home and abroad, there are no unmanned boat autonomous zone and keep controlling
The relevant report of method.
Content of the invention
Can guarantee that no matter how unmanned boat moves all without sailing out of predetermined region it is an object of the invention to provide a kind of
The apery intelligent control method that hydraulic jet propulsion unmanned boat autonomous zone keeps.
The object of the present invention is achieved like this：The parameter that the Position and attitude sensor controlling border is recorded carries out key parameter
Analysis and calculating, and by data information transfer to region keep judgement system according to the value of calculation of key parameter and actual value
Whether multilevel iudge carries out region holding, carries out region if necessary and keeps then to the drive lacking hydraulic jet propulsion unmanned boat equation of motion
Solved with the deviation equation of region stop-keeping position equation of locus, and by data information transfer to Human Simulating Intelligent Control
Device, according to the variation tendency of regulated variable, deviation and deviation, human simulated intelligent controller determines that region keeps control strategy and passes through
Actuator is implemented.
The present invention can also include：
1st, the analysis of described key parameter and calculating specifically include：
(1) whether flight path in the region that region keeps, i.e. the maximum of the distance to unmanned boat flight path for regional center O
rmax, computing formula is：
Wherein, (XO,YO) for regional center O coordinate, (X, Y) be unmanned boat motion flight path coordinate,
(2) extreme sport takes the limit range r ' of control measure apart from k, i.e. unmanned boatmax, computing formula is：
Wherein, R is zone radius, the deflection that δ acts on for perturbed force,
(3) propulsion plant reset angle θF, that is, when bow is equal to reset angle to angle ψ, propulsion plant resets, and computing formula is：
R ' is inner circle radius,
(4) propulsion plant stop position, if using O as stop position when sea situation is unknown, if known to sea situation and be four
Level sea situation and following when then using O ' as stop position,
Wherein O ' be interference force direction cross the center of circle and with inner circle intersection point.
2nd, the described deviation to the drive lacking hydraulic jet propulsion unmanned boat equation of motion and region stop-keeping position equation of locus
Equation carries out solution and specifically includes：
The equation of motion of unmanned boat horizontal plane 3DOF is：
Wherein, η=[x, y, ψ]T、υT=[u, v, r], τ=[τ1,0,τ3]TIt is respectively position, speed and propulsive force, τ1With
τ3It is respectively being longitudinally propelling power and turning bow moment, m of unmanned surface vehicle11,m22,m33For comprising the system inertia square of additional mass
Battle array parameter, du,dv,drFor environmental disturbances, remaining is hydrodynamic force coefficient；
Reference locus (the x of region stop-keeping positiond,yd,ψd,ud,vd,rd) and with reference to control input (τ1d,τ3d) meet
Differomorphism conversion is carried out to the equation of motion of unmanned boat horizontal plane 3DOF, order
z1=xcos ψ-ysin ψ
z3=ψ
z5=v
z6=r
With control input conversion
After arrangement, new state equation is
Try to achieve region in the same manner to keep controlling the differomorphism transformation equation of boundary reference track
Define deviation
E=[e1,e2,e3,e4,e5,e6]T=[z1-z1d,z2-z2d,z3-z3d,z4-z4d,z5-z5d,z6-z6d]T
Then
Z is eliminated by following formula1,z2,z3,z4,z5,z6,
z4z6-z4dz6d
=z4z6-z4z6d+z4z6d-z4dz6d
=z4e6-z4de6+z4de6+z6de4
=e4e6+z4de6+z6de4
Obtain deviation equation
Wherein,
3rd, described judge whether to need to carry out region to keep specifically including：As r≤rmaxWhen it is not necessary to starting region keep；
Work as rmax＜ r≤r 'maxWhen zero, starting region keeps；As r ＞ r 'maxWhen, region keeps unsuccessfully.
4th, described determination region keeps control strategy to specifically include：
Simulating Human Intelligent Integral algorithm is as follows：
Wherein, u is controlled quentity controlled variable, and e is deviation,For deviation derivative, KpFor proportional gain, KiFor storage gain, KdFor differential
Gain；
(1), run controlled stage
Perfect error target trajectory isFor the threshold value of deviation and deviation variation rate, unmanned boat
The feature primitive collection running controlled stage is combined into：Q1={ q1,q2,q3,q4,q5,q6,q7,
Wherein：
The model that unmanned boat runs controlled stage is Φ1={ φ11,φ12,φ13,φ14,φ15,φ16,φ17,φ18,φ19,
φ110}
Wherein：
Unmanned boat runs control mode level Ψ of controlled stage1={ ψ11, ψ12, ψ13, ψ14, ψ15, ψ16}
Wherein：
Symbol u in formulan,un-1The n-th of controller, n-1 output；UmaxThe maximum of controller output；en,Control system
The deviation of system n-th, deviation variation rate；emiThe i ＆ lt extreme value of control system deviation；Kp,Kd,Ki,Sp, the ratio system of k controller
Number, differential coefficient, integral coefficient, the symbol of proportionality coefficient, gain inhibitive factor；
Unmanned boat runs set of inference rules Ω of controlled stage1={ ω11,ω12,ω13,ω14,ω15,ω16}
Wherein：
(2), parameter-adjusting level
The feature primitive set Q of unmanned boat parameter-adjusting level2={ q1,q2,q3,q4,q5,q6,q7,q8,q9}
Wherein：
The characteristic model Φ of unmanned boat parameter-adjusting level2={ Φ21, Φ22,
Wherein Φ21={ φ212, φ2141, φ215, φ2171, φ2172, φ218Be 2,4 quadrants characteristic model,
Φ22={ φ22101, φ22102, φ22103, φ22104Be 1,3 quadrants characteristic model, in formula：
Decision-making mode level Ψ of unmanned boat parameter-adjusting level2={ Ψ21, Ψ22, wherein：Ψ21={ ψ21i, i=2,41,
5,71,72,8Ψ22={ ψ22i, in i=101,102,103,104 formula：
ψ212={ Kd=Kd+kd1} ψ2141={ Kp=Kp+kp1}
ψ215={ Kp=Kp-kp1} ψ2171={ Kd=Kd+kd1,Sp=-1 }
ψ2172={ Kd=Kd+kd1,Kp=Kp-kp1} ψ218={ Kd=Kd+kd1}
ψ22101={ Kd=Kd+kd2,Kp=Kp-kp2} ψ22102={ Kp=Kp+kp2}
ψ22103={ Kd=Kd+kd2,Kp=Kp+kp2} ψ22104={ Kd=Kd+kd2,Kp=Kp-kp2}
Symbolic significance in formula is as follows：kp1,kd1,kp2,kd2：2nd, the ratio of 4 quadrants or differential increased or decrease coefficient,
L, 3 quadrants or differential increased or decrease coefficient,
Set of inference rules Ω of unmanned boat parameter-adjusting level2={ Ω21,Ω22, wherein：Ω21={ ω21i, i=2,41,
5,71,72,8, Ω22={ ω22i, i=101,102,103,104,
In formula：
(3), task adapts to level
Unmanned boat task adapts to the characteristic model Φ of level3={ φ31,φ32, wherein：φ31For inputting normalized control
Characteristic model, φ32For exporting the controlling feature model of renormalization；
Unmanned boat task adapts to the control mode collection Ψ of level3={ ψ31,ψ32, wherein：
ψ32={ un=Umax·un,0,if|un,0| ＞ 1thenun,0=
sgn(un,0), the symbolic significance in formula is as follows:
en,0,Deviation and the normalized input of deviation variation rate；en,The deviation of control system and deviation variation rate；
Dmax,Vmax：The maximum hauling distance of controlled variable, the maximum hauling speed of controlled variable；un,un,0,Umax：Actual controller
Output, normalized controller output, control the maximum input of actuator；
Unmanned boat task adapts to set of inference rules Ω of level3={ ω31,ω32, wherein：
The invention provides the apery intelligent control method that a kind of USV autonomous zone keeps, mainly kept by region
The calculating data of key parameter, judges whether to region and keeps, and carries out region if necessary and keeps then solving unmanned boat motion
Equation and the deviation equation of region stop-keeping position equation of locus, then by data information transfer to human simulated intelligent controller, enter
And using Human Simulating Intelligent Control Algorithm, the propulsion plant of unmanned boat is controlled it is ensured that no matter how unmanned boat moves, not
Predetermined region can be sailed out of.
Depending on area size is needed by task, in region, one scope of regulation (claiming to control border), within the range, push away
Enter device not output, bow, to also not keeping, only reaches or just works close to propeller when controlling border.Therefore affect unmanned
Ship autonomous zone keep effect principal element be：Unmanned boat flight path positional information x, y, ψ are respectively longitudinal coordinate, lateral coordinates
With bow to angle；The maximum r of the distance to unmanned boat flight path for key parameter such as regional center Omax, extreme sport is apart from k, the limit
Scope r 'max, reset angle θF, propulsion plant stop position etc..
The present invention includes following beneficial effect：
1st, the present invention can accomplish taking into account of stability, rapidity and accuracy, online feature identification and feature memory energy
Enough characteristic intervals being presently according to system at any time, accordingly adopt different control mode, and this Multi-mode control both considered
Stability, has taken into account rapidity and the requirement of accuracy again；
2nd, the present invention has stronger robustness, and human simulated intelligent controller design is considerable degree of to plant characteristic to be changed not
Sensitivity, can well adapt to the change of controlled system model parameter, for external interference such as stormy waves streams, by carrying out to error
Selectively integrate, reduce external interference to greatest extent；
3rd, the present invention can do with the object of difficult control, be such as difficult to fixation, approximate mathematical model come described in strong non-thread
Property and uncertain system etc., controlled device difficulty is bigger, more can embody the superiority of Human Simulating Intelligent Control.
Brief description
Fig. 1 is USV region holding structure block diagram；
Fig. 2 keeps key parameter schematic diagram for USV region；
Fig. 3 keeps calculating flow chart for USV region；
Fig. 4 produces formula system structure for Human Simulating Intelligent Control second order；
Fig. 5 is the intellect controlling system imitating human structure；
Fig. 6 is the characteristic model running controlled stage；
Fig. 7 is the characteristic model of parameter-adjusting level.
Specific embodiment
Understandable for enabling the above objects, features and advantages of the present invention to become apparent from, illustrate below in conjunction with the accompanying drawings to this
Invention is described further.
The apery intelligent control method that the USV autonomous zone of the present invention keeps mainly includes：
Step one, the analysis of key parameter and calculating, including：Propulsion plant starts position, extreme sport distance, propulsion dress
Put reset angle, propulsion plant stop position, and data information transfer is kept judgement system to region；
Under sea situation known case, unmanned boat kinestate is solved according to active force, thus keeping parameter to carry out in region
Solve；Under sea situation unknown situation, by the positional information of existing a period of time using parameter estimation the anti-power of solution of method and
Moment, solves unmanned boat kinestate finally according to active force, thus keeping parameter to solve in region；
Step 2, region keep judgement system to be compared according to the value of calculation of key parameter and actual value, judge whether needs
Carry out region holding；
Step 3, carry out region if necessary and keep then solving the unmanned boat equation of motion and region stop-keeping position track
The deviation equation of equation, then by data information transfer to human simulated intelligent controller；
Step 4, the controller based on apery intelligent algorithm determine according to the variation tendency of regulated variable, deviation and deviation
Region is kept control strategy and is effectively implemented by actuator.
The region of step one keeps analysis and the calculating of key parameter, as shown in Figure 2：
Flight path whether in the region that region keeps, i.e. the maximum r of the distance to unmanned boat flight path for regional center Omax.
Computing formula is as follows：
Wherein, (XO,YO) for regional center O coordinate, (X, Y) be unmanned boat motion flight path coordinate.
Extreme sport takes the limit range r ' of control measure apart from k, i.e. unmanned boatmax.Computing formula is as follows：
Wherein, R is zone radius, the deflection that δ acts on for perturbed force.
Propulsion plant reset angle θF, that is, when bow is equal to reset angle to angle ψ, propulsion plant resets.Computing formula is as follows：
Propulsion plant stop position, if using O as stop position when sea situation is unknown, if sea situation is known and extra large for level Four
Condition and following when using O ' as stop position.Monitoring unmanned boat position simultaneously calculates itself angle ψ and predetermined region center between, when
ψ is more than the angle ψ between predetermined stop position and regional centertWhen, unmanned boat gets final product stop motion.
Wherein, R ' be inner circle radius, O ' be interference force direction cross the center of circle and with inner circle intersection point.
The solution of the deviation equation of the unmanned boat equation of motion and region stop-keeping position equation of locus in step 3, first
The equation of motion of unmanned boat horizontal plane 3DOF is：
Wherein, η=[x, y, ψ]T, υT=[u, v, r], τ=[τ1,0,τ3]T, respectively position, speed and propulsive force, τ1With
τ3It is respectively being longitudinally propelling power and turning bow moment, m of unmanned surface vehicle11,m22,m33For comprising the system inertia square of additional mass
Battle array parameter, du,dv,drFor environmental disturbances, remaining is hydrodynamic force coefficient.
On the premise of step one region keeps key parameter, starting region keeps controlling the reference locus (x on borderd,yd,
ψd,ud,vd,rd) and with reference to control input (τ1d,τ3d) meet
Differomorphism conversion is carried out to the equation of motion of unmanned boat horizontal plane 3DOF, order
z1=xcos ψ-ysin ψ
z3=ψ
z5=v
z6=r
With control input conversion
After then arranging, new state equation is
Also region can be tried to achieve in the same manner keep controlling the differomorphism transformation equation of boundary reference track
Define deviation
E=[e1,e2,e3,e4,e5,e6]T=[z1-z1d,z2-z2d,z3-z3d,z4-z4d,z5-z5d,z6-z6d]T
Then
Z can be eliminated by following formula1,z2,z3,z4,z5,z6,
z4z6-z4dz6d
=z4z6-z4z6d+z4z6d-z4dz6d
=z4e6-z4de6+z4de6+z6de4
=e4e6+z4de6+z6de4
Obtain deviation equation
Wherein,
In step 2, region keeps judgement system to be compared according to the value of calculation of key parameter and actual value, judges that unmanned boat is
The no region that carries out keeps controlling, as r≤rmaxWhen it is not necessary to starting region keep；Work as rmax＜ r≤r 'maxWhen zero, starting region
Keep；As r ＞ r 'maxWhen, region keeps unsuccessfully.；
Human simulated intelligent controller described in step 4 keeps controlling boundary locus side according to the unmanned boat equation of motion and region
The deviation of journey makes the tactful process of region holding：As shown in Figure 4,5, wherein Fig. 4 produces for Human Simulating Intelligent Control second order
Formula system structure, Fig. 5 is the intellect controlling system imitating human structure,
Simulating Human Intelligent Integral algorithm is as follows：
Wherein, u is controlled quentity controlled variable, and e is deviation,For deviation derivative, KpFor proportional gain, KiFor storage gain, KdFor differential
Gain.
1st, run controlled stage
Human Simulating Intelligent Control is the dynamic mistake by controlled volume deviation and deviation variation rate are monitored and judge with system
Journey, different dynamic processes takes different control algolithms.Can divide according to the size of controlled volume deviation and deviation variation rate
Error phase planeIn order to visual analyzing is carried out to dynamic control process.
In conjunction with Fig. 6, track shown in the chain-dotted line with arrow is perfect error target trajectory
For the threshold value of deviation and deviation variation rate, the feature primitive set of unmanned boat operation controlled stage：Q1={ q1,q2,q3,q4,q5,q6,
q7}
Wherein：
Control Strategy On Human Simulated Intelligence is analyzed：
1. in the starting stage controlling, when deviation is very big, corresponding region 1, take control action as big as possible, such as adopt
Pound-pound Model control, to inspire change of error speed, improves the convergence rate of control system；
2. during deviation reduction, if change of error speed is less than predetermined speed, corresponding region 4,5, take ratio
Example Model control, in order to improve change of error speed, makes deviation comparatively fast reduce；
3. during deviation reduction, if change of error speed is more than predetermined speed, corresponding region 2,7,8, than
On the basis of example mode, introduce differential mode, form the control model of proportional-plus-derivative, in order to force down change of error speed, keep away
Exempt from the appearance of overshoot；
4. when deviation and deviation variation rate are satisfied by requiring (error change speed is in predetermined velocity interval), corresponding
Region 3,6, then take holding Model control, and open loop is observed and kept, to watch how it develops quietly；
5. (overshoot occurs) during deviation increase, corresponding region 10, in order to suppress the increase of deviation, adoption rate adds
Differential and the control model of integration, make deviation turn one's head as early as possible；
6. in deviation and the equal very little of deviation variation rate (within the scope of given demand of steady state error), corresponding region 9,
Take holding Model control, can be allowed to voluntarily decays reaches balance；For the system that there is external environmental interference, pole can be taken
Value sampling keeps Model control, to reduce steady-state error or to improve capacity of resisting disturbance.
Unmanned boat runs the model Φ of controlled stage1={ φ11,φ12,φ13,φ14,φ15,φ16,φ17,φ18,φ19,
φ110}
Wherein：
Control mode level Ψ of unmanned boat motor control level1={ ψ11, ψ12, ψ13, ψ14, ψ15, ψ16}
Wherein：
Symbol u in formulan,un-1The n-th of controller, n-1 output；UmaxThe maximum of controller output；en,Control system
The deviation of system n-th, deviation variation rate；emiThe i ＆ lt extreme value of control system deviation；Kp,Kd,Ki,Sp, the ratio system of k controller
Number, differential coefficient, integral coefficient, the symbol of proportionality coefficient, gain inhibitive factor.
Set of inference rules Ω of unmanned boat motor control level1={ ω11,ω12,ω13,ω14,ω15,ω16}
Wherein：
2nd, parameter-adjusting level
It is exactly to adjust threshold values and parameter after human simulated intelligent controller initial model determines, find out this concrete object
Preferable phase paths are simultaneously realized.In conjunction with Fig. 7, the feature primitive set Q of unmanned boat parameter-adjusting level2={ q1,q2,q3,q4,q5,
q6,q7,q8,q9}
Wherein：
Thought according to Human Simulating Intelligent Control：Deviation variation rate than larger when should increase the differential action and weaken proportional action,
Change of error speed is little and the differential action should be weakened when deviation is larger, increase proportional action.Parameter correction for each region is adopted
Take following measure：
Region 1：Pound-pound controls does not need parameter correction；
Region 2：Exceed the restriction of deviation variation rate, parameter correction should be passed through, the differential action should be increased；
Region 3,6,9：System is operated in perfect condition it is not necessary to parameter correction, keeps pattern using parameter；
Region 41：Deviation variation rate very little, and deviation is larger, by parameter correction, increases proportional action；
Region 42：Deviation variation rate more satisfactory it is not necessary to parameter correction, pattern is kept using parameter；
Region 5：There is less deviation, but deviation variation rate enters steady state requirement, by parameter correction, weaken ratio and make
With；
Region 71：Deviation has been enter into steady state requirement, and deviation variation rate is larger, by parameter correction, increases the differential action
And introduce positive feedback, form the control model that stronger differential adds positive feedback；
Region 72：Deviation variation rate is larger, should pass through parameter correction, increases the differential action and weakens proportional action；
Region 8：Deviation has been enter into steady state requirement, but also less deviation variation rate, by parameter correction, increase differential
Effect；
Region 101：Overshoot occurs, deviation is larger and change of error speed is less, by parameter correction, somewhat increased ratio
Example effect and the reduction differential action；
Region 102：Overshoot very little, change of error speed also very little, but still it is introduced into steady state requirement, micro- increase ratio is made
With；
Region 103：Overshoot is larger, and change of error speed is also larger, by parameter correction, somewhat increases the differential action and ratio
Example effect；
Region 104：Overshoot is less, but change of error speed is still larger, by parameter correction, strengthens the differential action, slightly
Weaken proportional action.
The characteristic model Φ of unmanned boat parameter-adjusting level2={ Φ21, Φ22,
Wherein Φ21={ φ212, φ2141, φ215, φ2171, φ2172, φ218Be 2,4 quadrants characteristic model,
Φ22={ φ22101, φ22102, φ22103, φ22104Be 1,3 quadrants characteristic model.In formula：
Decision-making mode level Ψ of unmanned boat parameter-adjusting level2={ Ψ21, Ψ22, wherein：Ψ21={ ψ21i, i=2,41,
5,71,72,8Ψ22={ ψ22i, in i=101,102,103,104 formula：
ψ212={ Kd=Kd+kd1} ψ2141={ Kp=Kp+kp1}
ψ215={ Kp=Kp-kp1} ψ2171={ Kd=Kd+kd1,Sp=-1 }
ψ2172={ Kd=Kd+kd1,Kp=Kp-kp1} ψ218={ Kd=Kd+kd1}
ψ22101={ Kd=Kd+kd2,Kp=Kp-kp2} ψ22102={ Kp=Kp+kp2}
ψ22103={ Kd=Kd+kd2,Kp=Kp+kp2} ψ22104={ Kd=Kd+kd2,Kp=Kp-kp2}
Symbolic significance in formula is as follows：kp1,kd1,kp2,kd2：2nd, the ratio of 4 quadrants or differential increased or decrease coefficient,
L, 3 quadrants or differential increased or decrease coefficient.
Set of inference rules Ω of unmanned boat parameter-adjusting level2={ Ω21,Ω22, wherein：Ω21={ ω21i, i=2,41,
5,71,72,8, Ω22={ ω22i, i=101,102,103,104.
In formula：
3rd, task adapts to level
According to different control systems, different task, to all parameters running controlled stage and parameter-adjusting level and close
Value is inserted and is changed, and the input value (rate of change of deviation and deviation) to controller is normalized and to controller
Output valve carries out renormalization, and the stability of control system is monitored waiting operation.
First, according to control system parameter, the input value (rate of change of deviation and deviation) of controller is normalized；
Then, by the calculating of parameter-adjusting level and operation controlled stage, obtain normalized control and export；Finally, to normalized control
Output valve processed controls actuator to carry out renormalization, obtains actual control output valve.
Unmanned boat task adapts to the characteristic model Φ of level3={ φ31,φ32, wherein：φ31For inputting normalized control
Characteristic model, φ32For exporting the controlling feature model of renormalization.
Unmanned boat task adapts to the control mode collection Ψ of level3={ ψ31,ψ32, wherein：
ψ32={ un=Umax·un,0,if|un,0| ＞ 1thenun,0=
sgn(un,0)}.Symbolic significance in formula is as follows:
en,0,Deviation and the normalized input of deviation variation rate；en,The deviation of control system and deviation variation rate；
Dmax,Vmax：The maximum hauling distance of controlled variable, the maximum hauling speed of controlled variable；un,un,0,Umax：Actual controller
Output, normalized controller output, control the maximum input of actuator.
Unmanned boat task adapts to set of inference rules Ω of level3={ ω31,ω32, wherein：
This control method achieves invention effect, unmanned boat region ocean search and rescue and exploration travel during, by each
Module cooperation each other, makes unmanned boat independently can carry out region holding during navigation, smoothly completes preplanned mission.
Claims (5)
1. the apery intelligent control method that a kind of hydraulic jet propulsion unmanned boat autonomous zone keeps, is characterized in that：To control border
The parameter that Position and attitude sensor records carries out analysis and the calculating of key parameter, and region keeps judgement system according to the meter of key parameter
Calculation value and actual value compare, and judge whether to need to carry out region holding, carry out region if necessary and keep then drive lacking being sprayed water
The propulsion unmanned boat equation of motion is solved with the deviation equation of region stop-keeping position equation of locus, and data message is passed
Pass apery intelligent algorithm controller, human simulated intelligent controller determines area according to the variation tendency of regulated variable, deviation and deviation
Domain is kept control strategy and is implemented by actuator.
2. the apery intelligent control method that hydraulic jet propulsion unmanned boat autonomous zone according to claim 1 keeps, its feature
It is that the analysis of described key parameter is specifically included with calculating：
(1) whether flight path in the region that region keeps, i.e. the maximum r of the distance to unmanned boat flight path for regional center Omax, meter
Calculating formula is：
Wherein, (XO,YO) for regional center O coordinate, (X, Y) be unmanned boat motion flight path coordinate,
(2) extreme sport takes the limit range r ' of control measure apart from k, i.e. unmanned boatmax, computing formula is：
Wherein, R is zone radius, the deflection that δ acts on for perturbed force,
(3) propulsion plant reset angle θF, that is, when bow is equal to reset angle to angle ψ, propulsion plant resets, and computing formula is：
R ' is inner circle radius,
(4) propulsion plant stop position, if using O as stop position when sea situation is unknown, if sea situation is known and extra large for level Four
Condition and following when then using O ' as stop position,
Wherein O ' be interference force direction cross the center of circle and with inner circle intersection point.
3. the apery intelligent control method that hydraulic jet propulsion unmanned boat autonomous zone according to claim 2 keeps, its feature
It is that the described deviation equation to the drive lacking hydraulic jet propulsion unmanned boat equation of motion and region stop-keeping position equation of locus is carried out
Solution specifically includes：
The equation of motion of unmanned boat horizontal plane 3DOF is：
Wherein, η=[x, y, ψ]T、vT=[u, v, r], τ=[τ1,0,τ3]TIt is respectively position, speed and propulsive force, τ1And τ3Respectively
Being longitudinally propelling power and turning bow moment, m for unmanned surface vehicle11,m22,m33For comprising the system inertia matrix parameter of additional mass,
Remaining is hydrodynamic force coefficient；
Starting region keeps controlling the reference locus (x on borderd,yd,ψd,ud,vd,rd) and with reference to control input (τ1d,τ3d) meet
Differomorphism conversion is carried out to the equation of motion of unmanned boat horizontal plane 3DOF, order
z1=x cos ψ-y sin ψ
z3=ψ
z5=v
z6=r
With control input conversion
After arrangement, new state equation is
Try to achieve region in the same manner to keep controlling the differomorphism transformation equation of boundary reference trackFixed
Adopted deviation
E=[e1,e2,e3,e4,e5,e6]T=[z1-z1d,z2-z2d,z3-z3d,z4-z4d,z5-z5d,z6-z6d]T
Then
Z is eliminated by following formula1,z2,z3,z4,z5,z6,
z4z6-z4dz6d
=z4z6-z4z6d+z4z6d-z4dz6d
=z4e6-z4de6+z4de6+z6de4
=e4e6+z4de6+z6de4
Obtain deviation equation
Wherein,
4. the apery intelligent control method that hydraulic jet propulsion unmanned boat autonomous zone according to claim 3 keeps, its feature
It is described to judge whether to need to carry out region to keep specifically including：As r≤rmaxWhen it is not necessary to starting region keep；Work as rmax＜ r
≤r′maxWhen zero, starting region keeps；As r ＞ r 'maxWhen, region keeps unsuccessfully.
5. the apery intelligent control method that hydraulic jet propulsion unmanned boat autonomous zone according to claim 4 keeps, its feature
It is that described determination region keeps control strategy to specifically include：
Simulating Human Intelligent Integral algorithm is as follows：
Wherein, u is controlled quentity controlled variable, and e is deviation,For deviation derivative, KpFor proportional gain, KiFor storage gain, KdFor the differential gain；
(1), run controlled stage
Perfect error target trajectory isFor the threshold value of deviation and deviation variation rate, people's ship runs control
The feature primitive collection of level processed is combined into：Q1={ q1,q2,q3,q4,q5,q6,q7,
Wherein：q2:|en|≥e1,q3:|en|≥e2,q4:|en|≥e3,
The model that unmanned boat runs controlled stage is Φ1={ φ11,φ12,φ13,φ14,φ15,φ16,φ17,φ18,φ19,φ110}
Wherein：
Unmanned boat runs control mode level Ψ of controlled stage1={ ψ11, ψ12, ψ13, ψ14, ψ15, ψ16}
Wherein：
Symbol u in formulan,un-1The n-th of controller, n-1 output；UmaxThe maximum of controller output；Control system n-th
Secondary deviation, deviation variation rate；emiThe i ＆ lt extreme value of control system deviation；Kp,Kd,Ki,Sp, the proportionality coefficient of k controller, micro-
Divide coefficient, integral coefficient, the symbol of proportionality coefficient, gain inhibitive factor；
Unmanned boat runs set of inference rules Ω of controlled stage1={ ω11,ω12,ω13,ω14,ω15,ω16}
Wherein：
(2), parameter-adjusting level
The feature primitive set Q of unmanned boat parameter-adjusting level2={ q1,q2,q3,q4,q5,q6,q7,q8,q9}
Wherein：
The characteristic model Φ of unmanned boat parameter-adjusting level2={ Φ21, Φ22,
Wherein Φ21={ φ212, φ2141, φ215, φ2171, φ2172, φ218Be 2,4 quadrants characteristic model,
Φ22={ φ22101, φ22102, φ22103, φ22104Be 1,3 quadrants characteristic model, in formula：
Decision-making mode level Ψ of unmanned boat parameter-adjusting level2={ Ψ21, Ψ22, wherein：Ψ21={ ψ21i, i=2,41,5,71,
72,8Ψ22={ ψ22i, in i=101,102,103,104 formula：
ψ212={ Kd=Kd+kd1}ψ2141={ Kp=Kp+kp1}
ψ215={ Kp=Kp-kp1}ψ2171={ Kd=Kd+kd1,Sp=-1 }
ψ2172={ Kd=Kd+kd1,Kp=Kp-kp1}ψ218={ Kd=Kd+kd1}
ψ22101={ Kd=Kd+kd2,Kp=Kp-kp2}ψ22102={ Kp=Kp+kp2}
ψ22103={ Kd=Kd+kd2,Kp=Kp+kp2}ψ22104={ Kd=Kd+kd2,Kp=Kp-kp2}
Symbolic significance in formula is as follows：kp1,kd1,kp2,kd2：2nd, the ratio of 4 quadrants or differential increased or decrease coefficient, l, 3 as
Limit or differential increased or decrease coefficient,
Set of inference rules Ω of unmanned boat parameter-adjusting level2={ Ω21,Ω22, wherein：Ω21={ ω21i, i=2,41,5,71,
72,8, Ω22={ ω22i, i=101,102,103,104,
In formula：
(3), task adapts to level
Unmanned boat task adapts to the characteristic model Φ of level3={ φ31,φ32, wherein：φ31For inputting normalized controlling feature mould
Type, φ32For exporting the controlling feature model of renormalization；
Unmanned boat task adapts to the control mode collection Ψ of level3={ ψ31,ψ32, wherein：
ψ32={ un=Umax·un,0,if|un,0| ＞ 1thenun,0=sgn
(un,0), the symbolic significance in formula is as follows:
Deviation and the normalized input of deviation variation rate；The deviation of control system and deviation variation rate；Dmax,
Vmax：The maximum hauling distance of controlled variable, the maximum hauling speed of controlled variable；un,un,0,Umax：Actual controller defeated
Go out, normalized controller output, control the maximum input of actuator；
Unmanned boat task adapts to set of inference rules Ω of level3={ ω31,ω32, wherein：
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