CN108255062A - The energy saving thrust distribution method of dynamic positioning based on improved differential evolution mechanism - Google Patents
The energy saving thrust distribution method of dynamic positioning based on improved differential evolution mechanism Download PDFInfo
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Abstract
The present invention provides a kind of energy saving thrust distribution method of dynamic positioning based on improved differential evolution mechanism, includes the following steps：Step S1：Determine dynamic positioning power demand；Step S2：Establish dynamic positioning power distribution mathematical model；Step S3：Initially dissolve for the power distribution problems in dynamic positioning；Step S4：Mutational formats are selected according to mutation constant λ；Step S5：Carry out mutation operation；Step S6：Carry out crossover operation；Step S7：The adaptive value of all solutions is evaluated, and records optimal solution；Step S8：Judge whether to meet end condition, be, perform step S9, otherwise return to step S4；Step S9：Stop cycle, export optimal solution, power distribution is carried out according to optimal solution.By the present invention, thrust needed for dynamic positioning ship is reasonably allocated to each propeller, on the basis of safety of ship is ensured, ship energy consumption is reduced, lowers shipping transport cost, reduce Pollution From Ships.
Description
Technical field
The present invention relates to shipboard automation field more particularly to a kind of dynamic positioning sections based on improved differential evolution mechanism
It can thrust distribution method.
Background technology
The major function of Ship Dynamic Positioning Systems Based (DPS) is to maintain ship in desired position or driving ship along finger
Fixed track navigation.It mainly does according to the departure between the current location status and desired value of ship and external environment
It disturbs, calculates ship required total thrust and torque in real time, then calculate ship further according to thrust distribution logical method
The thrust and its angle of the required generation of each propeller of equipment, and control instruction is transmitted to propeller, propeller according to
The thrust that the instruction generates requirement completes ship's fix.Therefore, thrust distribution be a ring important in DPS, it by controller with
Push system connects to form an entirety.Propeller is no less than 5 under normal conditions, but is not The more the better, also
The factors such as the interaction between two propellers between propeller and hull are must take into account, while also to take into account ship institute
Required maneuverability.Just there are many kinds of disclosure satisfy that the thrust size of positioning requirements and the group in direction to entire propulsion system at this time
It closes, and the major function of thrust distribution logic is exactly to find out a classic combination, and it is real-time to be translated into control instruction
Distribute to each propeller.
Thrust allocation optimization problems are a multi-constraints optimization problems, it requires propeller real-time high-efficiency reasonably to generate ship
The required thrust of oceangoing ship, and meet the requirement for making energy consumption minimum as possible while a degree of maneuverability is kept.Outstanding
Distribution method can not only improve ship's fix precision, but also possess reduction energy expenditure, reduce mechanical wear and noise etc.
Function.
What dynamic positioning ship was generally equipped is full circle swinging thruster, and such propeller and its propulsion system, which are generally gathered around, to be had
Following restrictive condition：
(1) acc power limitation driven, maximum value that there are one the thrusts that each propeller generates, propeller can not generate
Than the thrust of maximum value bigger.
(2) propeller thrust and its rate of change of angle are restricted, can not change the short time very greatly.
(3) all-direction propeller can be deposited around the rotation of 360 ° of its main shaft, but because closing on the interaction between propeller
In thrust forbidden zone, it is therefore desirable to set a variation range to the rotational angle of each propeller.
In addition, the it is also contemplated that appearance of singular structure.For dynamic positioning ship, when its equipment all propellers all
When possessing the same propulsion azimuth, singular structure will occur.It is even lost at this point, Ship Maneuverability will be greatly reduced
Go, and due to the limitation of propeller rotary speed, whole system will longer time restore, this would be possible to relevant
It is produced in engineer operation into serious consequence.Therefore, it in the research and application of dynamic positioning of vessels thrust distribution, should avoid strange
The generation of diverse structure.Therefore in order to keep the balance between energy consumption and operability, a kind of scheme of compromise is proposed, i.e., according to reality
Demand setting adjustment factor, come balance ship to operability and energy consumption demand.
In the prior art, mainly using following several technical solutions：
Patent《Using the thrust force distribution method of power location system of ship of genetic algorithm》, application number
201110253236.2 the assigning process of thrust is carried out using genetic algorithm approach.
Patent《The thrust distribution method of dynamic positioning system》, application number 201310003584.3, using low-pass filtering and
Two kinds of optimization algorithm Distributed Calculation thruster azimuths of Sequential Quadratic Programming method and thrust size.
Patent《Using the dynamic positioning thrust distributor and its distribution method for dynamically forbidding angle》, application number
201210356674.6 the assigning process of thrust is carried out using Novel Algorithm.
The main method of dynamic positioning of vessels thrust distribution at present is to ignore the energy consumption characteristics of thrust distribution, it is difficult to find and push away
The optimal solution of power distribution.
Invention content
The purpose of the present invention is distributing mathematical model according to constructed dynamic positioning thrust, pass through improved differential evolution
Mechanism efficiently finds the optimal solution for distributing each propeller thrust and direction instruction, is ensureing that propeller resultant force satisfaction control will
On the basis of asking, marine propeller energy consumption is reduced.
To achieve the above object, the present invention uses following technical scheme：A kind of power based on improved differential evolution mechanism
Positioning energy-saving thrust distribution method, includes the following steps：Step S1：Determine dynamic positioning power demand；Step S2：It establishes dynamic
Power Positioning power distributes mathematical model；Step S3：Initially dissolve for the power distribution problems in dynamic positioning；Step S4：Root
Mutational formats are selected according to mutation constant λ；Step S5：Carry out mutation operation；Step S6：Carry out crossover operation；Step S7：Evaluation
The adaptive value of all solutions, and record optimal solution；Step S8：Judge whether to meet end condition, be, perform step S9, otherwise return
Return step S4；Step S9：Stop cycle, export optimal solution, power distribution is carried out according to optimal solution.
In an embodiment of the present invention, step S2 includes step in detail below：Step S21：About thrust assignment problem
Nonlinear optimization mathematical model is as follows：
Constraint adjusts as follows：
S=τ-B (α) F
Fmin≤F≤Fmax
△Fmin≤F-F0≤△Fmax
αmin≤α≤αmax
△αmin≤α-α0≤△αmax
Wherein, W is total energy consumption in first item, and P is weight coefficient, FiFor the thrust of i-th of propeller, kiFor calculating parameter；
Section 2 sTQs is penalty term, and s is broad sense thrust error vector；Weight matrix Q is diagonal positive definite matrix, should be taken large values, and is used
To ensure that error s levels off to zero；Section 3 (α-α0)TΩ(α-α0) it is the pace of change that angle is promoted for constraining, wherein α is
The azimuth of the propeller at this moment, α0The azimuth of propeller for previous moment, weight matrix Ω>0 is used for adjusting optimization
Target；Section 4Be for avoiding singular structure, wherein
lxnAnd lynIt is the X-direction coordinate and Y-direction coordinate of n-th of propeller respectively；X-direction is to bow, Y from ship
Direction is to ship starboard from ship；If propulsion system is unusual or levels off to unusual, i.e. det (B (α) B ' (α)) is equal to zero or near
Zero is similar to, then the value of Section 4 can be very big, is equivalent to penalty；ε in formula>0, δ be more than zero, δ be adjustment factor, for balancing
The energy consumption and maneuverability of ship, the bigger maneuverability of δ values is better, and corresponding energy consumption can also increased, and δ values are smaller, then feelings
Condition is exactly the opposite；Step S22：In constraints, τ=(τx,τy,τM)TIt is desired power and torque, F is propulsion system
Thrust matrix, B (α) F is then the practical conjunction thrust and resultant moment generated of propulsion system, and reality is calculated by B (α) calculation formula
Broad sense thrust error vector between expectation；FmaxAnd FminThe maximum value and minimum value of propeller thrust, limitation are represented respectively
The thrust range of propeller；△FmaxWith △ FminThe bound that propeller thrust changes within the unit interval, B are represented respectively
(α) calculation formula defines the range of thrust variation rate；Correspondingly, αmaxAnd αminFor the range of propeller rotation angle, △ αmax
With △ αminIt is the bound of propeller angle change amplitude between two moment.
In an embodiment of the present invention, step S4 includes the following steps：Step S41：In improved differential evolution, according to such as
Artificial bee colony algorithm is added in the mode of differential evolution algorithm as local searching strategy by lower formula；
In formula, xiFor the individual of carry out neighborhood search chosen, xkFor xiAdjacent individual, x 'iFor obtaining after neighborhood search
The particle arrived, i.e. x 'iIt is xiPass through the random individual x adjacent with itskAmendment solution after being compared to each other,It is random in [- 1,1]
The value of generation；K ∈ { 1,2,3 ..., SN } wherein SN is the quantity of population；Step S42：Population is added according to equation below to calculate
The social recognition part of method optimizes differential evolution algorithm：x′i=xr1+F(xr2-xr3)+ψ(xgbest-xr1)；Wherein ψ is range
The numerical value generated at random in [0,1], xgbestIt is globally optimal solution；xr1, xr2And xr3Be the variable that randomly selects and r1 ≠ r2 ≠
r3；F be for controlling perturbation total amount in mutation process and improving the zoom factor of convergence rate, value range be [0,
1]；New explanation x 'iBy three partially synthetic generations：The target individual x ' that first part is selectedi；Second part is by randomly choosing
Parent individuality difference generate vector；Last part is according in the target individual by being selected and current entire population
The difference of globally optimal solution carries out the solution vector of difference operation generation；Step S43：According to following steps by this step S41 and
Step S42 improved procedures are combined：If rand<λ is then utilizedOtherwise according to x 'i=xr1+F
(xr2-xr3)+ψ(xgbest-xr1) carry out mutation operation；Rand is a random function for generating random number；Wherein λ is that range exists
[0,1] control variable.
Further, according to the following formula optimizing strategy is selected to adjust λ value：
Wherein t is current cycle time, and T is selected maximum cycle.
Step S5 includes the following steps in an embodiment of the present invention：It is utilized respectively formula
ABC improvement strategies or PSO improvement strategies carry out mutation operation；Wherein ABC improvement strategies include the following steps：1. lead bee neighborhood
Search generates new explanation, and calculates its fitness value；2. according to formulaGenerate solution to be evaluated；3. it obtains
Mutant test group；PSO improvement strategies include the following steps：1. the history optimal value Pbest and the overall situation of each individual of update are most
Figure of merit Gbest；2. according to formula x 'i=xr1+F(xr2-xr3)+ψ(xgbest-xr1) generation solution to be evaluated；3. obtain mutant test group
Body.
In an embodiment of the present invention, step S6 includes the following steps：According to the intersection of equation below design dynamic increment
Parameter
CR=CRmin+(CRmax-CRmin)×(t/T)2
Wherein CRmaxAnd CRminIt is the maximum value and minimum value of cross parameter；T is current cycle time, T be it is selected most
Systemic circulation number.
Compared with prior art, artificial bee colony algorithm and particle cluster algorithm are introduced differential evolution algorithm by the method for the present invention
In, increase the diversity of differential evolution algorithm mutational formats；Mutational formats are selected, and pass through and adjust λ using constant λ is mutated
Value carry out the dynamic regulations of mutational formats, search stresses ABC improvement strategies early period, and the search later stage stresses PSO improvement strategies, with
Improve convergence speed of the algorithm and precision；Intersect the dynamic regulation of the value progress crossover operation of constant CR by adjusting, adjustment is prominent
Become the crossover probability between individual and target individual, improve algorithm the convergence speed and enhance the search precision of algorithm.Present invention side
Method according to the optimizing result of dynamic positioning ship thrust distribution model and improved differential evolution algorithm carry out thrust distribution, make its
On the basis of meeting ship thrust requirements guarantee safety of ship, make the distribution of dynamic positioning ship thrust more reasonable.
Description of the drawings
Fig. 1 is the main flow schematic diagram of the present invention.
Specific embodiment
Explanation is further explained to the present invention in the following with reference to the drawings and specific embodiments.
Being briefly described below for differential evolution algorithm is shown：
Mutation：Mutation is a very important link in the cyclostage, it randomly selects three parents in group
Body generates experimental subjects.In mutation operation, experimental subjects variable x 'iIt obtains as follows：
x′i=xr1+F(xr2-xr3) (1)
Wherein, xr1, xr2And xr3It is the variable that randomly selects and r1 ≠ r2 ≠ r3, F are for controlling in mutation process
The total amount that perturbs and the zoom factor for improving convergence rate, its value range are [0,1].
Intersect：Crossover operation is similar to the exchange and recombination that gene carries out two segments according to certain probability, generates filial generation
Individual.The operation is used to increase population diversity.In this operation, offspring individual is by experimental subjects and parent individuality according to following public affairs
It is generated after formula cross-mixing.
Wherein CR is by our customized intersection constants, RjIt is the real number randomly selected in range [0,1].J represents jth
The corresponding array of a component.
Selection：Selection operation is that target individual offspring individual related to it eliminates competition process.Using adaptive value as according to excellent
Win bad eliminate.To choose the minimum standard of adaptive value, selection operation can be represented with equation below：
Wherein f (x) represents the adaptive value of individual.
Being briefly described below for improved differential evolution algorithm is shown：
In improved differential evolution, we are in a manner that artificial bee colony algorithm is added in differential evolution algorithm by equation below
As local searching strategy.
In formula, x 'iIt is xkAmendment solution after being compared to each other by the random value adjacent with its,It is to be given birth at random in [- 1,1]
Into value.K ∈ { 1,2,3 ..., SN } wherein SN is the quantity of population.xiFor the individual of carry out neighborhood search chosen, xkFor xi
Adjacent individual, x 'iFor the obtained particle after neighborhood search.
In the searching process later stage, since the approximate region of optimal solution has been determined, it would be desirable to accelerate the convergence of algorithm
Property in order to optimizing faster.Therefore we add in the social recognition part of particle cluster algorithm to optimize according to equation below
Differential evolution algorithm.
x′i=xr1+F(xr2-xr3)+ψ(xgbest-xr1) (5)
Wherein ψ is the numerical value generated at random in range [0,1], xgbestIt is globally optimal solution.By formula (5) it is found that new explanation
x′iBy three partially synthetic generations：The target individual x ' that first part is selectedi；Second part is by randomly selected parent
The vector that the difference of body generates；Last part is according to global optimum in the target individual by being selected and current entire population
The difference of solution carries out the solution vector of difference operation generation.This three parts constitutes the new paragon for finding globally optimal solution.
Two improvements mode is combined according to following steps.
If(rand<λ)
Mutation operation is carried out using formula (4)；
Else
Mutation operation is carried out using formula (5)；
End
Wherein λ is control variable of the range in [0,1]；
Since the optimizing strategy that formula (4) provides has stronger ability of searching optimum, in entire optimization process
First half, refined Hook Jeeves algorighm mainly use formula (4).When algorithm enters in follow-up searching process, what formula (5) provided seeks
Dominant strategy has higher convergence rate and precision, and refined Hook Jeeves algorighm mainly carries out optimizing using formula (5).Pass through following public affairs
Formula selects optimizing strategy to adjust λ value：
Wherein t is current cycle time, and T is selected maximum cycle.
It is the Important Parameters for determining crossover probability between mutated individual and target individual to intersect constant CR.CR is larger, then tries
It tests that mutated individual accounting in individual is larger, the field search capability of algorithm can be enhanced and improves algorithm the convergence speed；CR is smaller,
It then tests mutated individual in individual and accounts for that smaller and target individual is larger in the individual accounting of experiment, the search essence of algorithm can be improved
Degree.Therefore, according to the cross parameter of equation below design dynamic increment, the search speed of algorithm early period and the search in later stage are improved
Precision.
CR=CRmin+(CRmax-CRmin)×(t/T)2 (7)
Wherein CRmaxAnd CRminIt is the maximum value and minimum value of cross parameter.
As shown in Figure 1, in a specific embodiment of the invention, a kind of dynamic positioning section based on improved differential evolution mechanism
Energy thrust distribution method, specifically includes following steps：
Step 1：Determine dynamic positioning thrust demand；
Step 2：Establish dynamic positioning power distribution mathematical model；
In an embodiment of the present invention, it is as follows about the nonlinear optimization mathematical model of thrust assignment problem：
Constraint：
S=τ-B (α) F (9)
Fmin≤F≤Fmax (10)
△Fmin≤F-F0≤△Fmax (11)
αmin≤α≤αmax (12)
△αmin≤α-α0≤△αmax (13)
In formula, W is total energy consumption in first item, and P is weight coefficient, is mainly used to adjust ratio of the energy consumption in optimization aim
Weight, the calculation of W have provided, wherein FiFor the thrust of i-th of propeller, kiFor calculating parameter, general value is 0.176.
Section 2 sTQs is penalty term, and s is broad sense thrust error vector, is mainly used to ensure the thrust and torque of propeller
It is enough to offset external interference, completes its basic location tasks.Weight matrix Q is diagonal positive definite matrix, should be taken large values, to
Ensure that error s levels off to zero.
Section 3 (α-α0)TΩ(α-α0) it is the pace of change that angle is promoted for constraining.Wherein α is the propulsion at this moment
The azimuth of device, α0The azimuth of propeller for previous moment, weight matrix Ω>0 is used for adjusting optimization aim.
Section 4Be for avoiding singular structure, wherein
lxnAnd lynBe respectively n-th of propeller X-direction coordinate (to bow from ship) and Y-direction coordinate (from ship to
Ship starboard).If propulsion system is unusual or levels off to unusual, i.e. det (B (α) B ' (α)) is equal to zero or is similar to zero, then the 4th
The value of item can be very big, be equivalent to penalty.ε in formula>0, this is that denominator is zero in order to prevent.δ is more than zero, is adjustment factor,
For balancing the energy consumption of ship and maneuverability, the bigger maneuverability of δ values is better, and corresponding energy consumption can also increased, and δ values are got over
Small, then situation is exactly the opposite.
In addition, in constraints, τ=(τx,τy,τM)TIt is desired power and torque, F is the thrust of propulsion system
Matrix, B (α) F are then the practical conjunction thrust and resultant moment generated of propulsion system, and formula (15) calculates practical between expectation
Broad sense thrust error vector.FmaxAnd FminThe maximum value and minimum value of propeller thrust are represented respectively, and formula (15) then limits
The thrust range of propeller.△FmaxWith △ FminThe bound that propeller thrust changes within the unit interval, formula are represented respectively
(15) range of thrust variation rate is defined.Correspondingly, αmaxAnd αminFor the range of propeller rotation angle, △ αmaxWith △ αmin
It is the bound of propeller angle change amplitude between two moment.
Step 3：Initially dissolve for the power distribution problems in dynamic positioning；
Step 4：Mutational formats are selected according to mutation constant λ；
Two improvements mode is combined according to following steps：
If(rand<λ)
Mutation operation is carried out using formula (4)；
Else
Mutation operation is carried out using formula (5)；
End
And λ value is adjusted by formula (6).
Step 5：Carry out mutation operation；
It is utilized respectively formula (1), ABC improvement strategies or PSO improvement strategies and carries out mutation operation.
ABC improvement strategies include the following steps：
4. bee neighborhood search is led to generate new explanation, and calculate its fitness value；
5. solution to be evaluated is generated according to formula (4)；
6. obtain mutant test group.
PSO improvement strategies include the following steps：
1. the history optimal value Pbest and global optimum Gbest of each individual of update；
2. solution to be evaluated is generated according to formula (5)；
3. obtain mutant test group.
Step 6：Carry out crossover operation；
Crossover operation is carried out according to formula (2), the wherein value of CR is determined by formula (7).
Step 7：The adaptive value of all solutions is evaluated, and records optimal solution；
Step 8：Judge whether to meet end condition, be, perform step 9, otherwise return to step 4；
End condition is greatest iteration step number.
Step 9：Stop cycle, export optimal solution, thrust distribution is carried out according to optimal solution.
The above are preferred embodiments of the present invention, all any changes made according to the technical solution of the present invention, and generated function is made
During with range without departing from technical solution of the present invention, all belong to the scope of protection of the present invention.
Claims (6)
1. a kind of energy saving thrust distribution method of dynamic positioning based on improved differential evolution mechanism, it is characterised in that：Including following
Step：
Step S1：Determine dynamic positioning power demand；
Step S2：Establish dynamic positioning power distribution mathematical model；
Step S3：Initially dissolve for the power distribution problems in dynamic positioning；
Step S4：Mutational formats are selected according to mutation constant λ；
Step S5：Carry out mutation operation；
Step S6：Carry out crossover operation；
Step S7：The adaptive value of all solutions is evaluated, and records optimal solution；
Step S8：Judge whether to meet end condition, be, perform step S9, otherwise return to step S4；
Step S9：Stop cycle, export optimal solution, power distribution is carried out according to optimal solution.
2. the energy saving thrust distribution method of the dynamic positioning according to claim 1 based on improved differential evolution mechanism, special
Sign is：Step S2 includes step in detail below：
Step S21：Nonlinear optimization mathematical model about thrust assignment problem is as follows：
Constraint adjusts as follows：
S=τ-B (α) F
Fmin≤F≤Fmax
△Fmin≤F-F0≤△Fmax
αmin≤α≤αmax
△αmin≤α-α0≤△αmax
Wherein, W is total energy consumption in first item, and P is weight coefficient, FiFor the thrust of i-th of propeller, kiFor calculating parameter；Second
Item sTQs is penalty term, and s is broad sense thrust error vector；Weight matrix Q is diagonal positive definite matrix, should be taken large values, to protect
Card error s levels off to zero；Section 3 (α-α0)TΩ(α-α0) it is the pace of change that angle is promoted for constraining, wherein α is this when
The azimuth of the propeller at quarter, α0The azimuth of propeller for previous moment, weight matrix Ω>0 is used for adjusting optimization aim；
Section 4Be for avoiding singular structure, wherein
lxnAnd lynIt is the X-direction coordinate and Y-direction coordinate of n-th of propeller respectively；X-direction is is to bow, Y-direction from ship
To ship starboard from ship；If propulsion system is unusual or levels off to unusual, i.e. det (B (α) B ' (α)) is equal to zero or is similar to zero,
Then the value of Section 4 can be very big, is equivalent to penalty；ε in formula>0, δ be more than zero, δ be adjustment factor, for balancing ship
Energy consumption and maneuverability, the bigger maneuverability of δ values is better, and corresponding energy consumption can also increased, and δ values are smaller, then situation is just
On the contrary；
Step S22：In constraints, τ=(τx,τy,τM)TIt is desired power and torque, F is the moment of thrust of propulsion system
Battle array, B (α) F is then the practical conjunction thrust and resultant moment generated of propulsion system, is calculated by B (α) calculation formula practical and expectation
Between broad sense thrust error vector；FmaxAnd FminThe maximum value and minimum value of propeller thrust are represented respectively, limit propeller
Thrust range；△FmaxWith △ FminThe bound that propeller thrust changes within the unit interval is represented respectively, and B (α) calculates public
Formula defines the range of thrust variation rate；Correspondingly, αmaxAnd αminFor the range of propeller rotation angle, △ αmaxWith △ αminIt is
The bound of propeller angle change amplitude between two moment.
3. the energy saving thrust distribution method of the dynamic positioning according to claim 1 based on improved differential evolution mechanism, special
Sign is：Step S4 includes the following steps：
Step S41：In improved differential evolution, in a manner that artificial bee colony algorithm is added in differential evolution algorithm by equation below
As local searching strategy；
In formula, xiFor the individual of carry out neighborhood search chosen, xkFor xiAdjacent individual, xi' for obtaining after neighborhood search
Particle, i.e. x 'iIt is xiPass through the random individual x adjacent with itskAmendment solution after being compared to each other,It is to be generated at random in [- 1,1]
Value；K ∈ { 1,2,3 ..., SN } wherein SN is the quantity of population；
Step S42：The social recognition part of particle cluster algorithm is added according to equation below to optimize differential evolution algorithm,
x′i=xr1+F(xr2-xr3)+ψ(xgbest-xr1)
Wherein ψ is the numerical value generated at random in range [0,1], xgbestIt is globally optimal solution；xr1, xr2And xr3It randomly selects
Variable and r1 ≠ r2 ≠ r3；F is the zoom factor for controlling perturbation total amount and raising convergence rate in mutation process,
Value range is [0,1]；New explanation x 'iBy three partially synthetic generations：The target individual x ' that first part is selectedi；Second part
It is by the vector of the difference generation of randomly selected parent individuality；Last part is according to the target individual by being selected and works as
The difference of globally optimal solution carries out the solution vector of difference operation generation in preceding entire population；
Step S43：This step S41 and step S42 improved procedures are combined according to following steps：If rand<λ is then utilizedOtherwise according to x 'i=xr1+F(xr2-xr3)+ψ(xgbest-xr1) carry out mutation operation；Rand is production
One random function of raw random number；Wherein λ is control variable of the range in [0,1].
4. the energy saving thrust distribution method of the dynamic positioning according to claim 3 based on improved differential evolution mechanism, special
Sign is：According to the following formula optimizing strategy is selected to adjust λ value：
Wherein t is current cycle time, and T is selected maximum cycle.
5. the energy saving thrust distribution method of the dynamic positioning according to claim 3 based on improved differential evolution mechanism, special
Sign is：Step S5 includes the following steps：It is utilized respectively formulaABC improvement strategies or PSO are improved
Strategy carries out mutation operation；
Wherein ABC improvement strategies include the following steps：
1. bee neighborhood search is led to generate new explanation, and calculate its fitness value；
2. according to formulaGenerate solution to be evaluated；
3. obtain mutant test group；
PSO improvement strategies include the following steps：
1. the history optimal value Pbest and global optimum Gbest of each individual of update；
2. according to formula x 'i=xr1+F(xr2-xr3)+ψ(xgbest-xr1) generation solution to be evaluated；
3. obtain mutant test group.
6. the energy saving thrust distribution method of the dynamic positioning according to claim 1 based on improved differential evolution mechanism, special
Sign is：
Step S6 includes the following steps：According to the cross parameter of equation below design dynamic increment
CR=CRmin+(CRmax-CRmin)×(t/T)2
Wherein CRmaxAnd CRminIt is the maximum value and minimum value of cross parameter；T is current cycle time, and T is that selected maximum is followed
Ring number.
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