CN113296499A - FPSO (Floating production storage and offloading) anchoring dynamic positioning control method for optimal heading polar region based on acceleration feedforward - Google Patents

FPSO (Floating production storage and offloading) anchoring dynamic positioning control method for optimal heading polar region based on acceleration feedforward Download PDF

Info

Publication number
CN113296499A
CN113296499A CN202110405217.0A CN202110405217A CN113296499A CN 113296499 A CN113296499 A CN 113296499A CN 202110405217 A CN202110405217 A CN 202110405217A CN 113296499 A CN113296499 A CN 113296499A
Authority
CN
China
Prior art keywords
fpso
heading
acceleration
control
mooring
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
Application number
CN202110405217.0A
Other languages
Chinese (zh)
Other versions
CN113296499B (en
Inventor
王元慧
杨伊熹
张晓云
刘向波
张潇月
蒋希赟
王海滨
刘冲
王雪莹
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Harbin Engineering University
Original Assignee
Harbin Engineering University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Harbin Engineering University filed Critical Harbin Engineering University
Priority to CN202110405217.0A priority Critical patent/CN113296499B/en
Publication of CN113296499A publication Critical patent/CN113296499A/en
Application granted granted Critical
Publication of CN113296499B publication Critical patent/CN113296499B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/0206—Control of position or course in two dimensions specially adapted to water vehicles

Abstract

The invention provides an FPSO (floating production storage and offloading) anchoring dynamic positioning control method based on acceleration feedforward for an optimal heading polar region. The invention aims to compensate disturbance by using acceleration feedforward, improve the system state estimation precision and keep the FPSO at an expected heading and position. 1. An optimal heading calculation method based on the ice coming direction according to the maximum tension and the second maximum tension of the mooring cable is designed. 2. By adding an acceleration term in the state observer, an acceleration feedforward observer of the FPSO (floating production storage and offloading) mooring dynamic positioning system is established, and the influence of fast-changing ice disturbance on state estimation can be effectively inhibited. 3. An anchoring dynamic positioning controller combining acceleration feedforward and nonlinear model predictive control is designed, the nonlinear characteristic of the original system is reserved, the constraint problem of input and output is considered, and the control of the position and the heading is realized.

Description

FPSO (Floating production storage and offloading) anchoring dynamic positioning control method for optimal heading polar region based on acceleration feedforward
Technical Field
The invention relates to the field of dynamic positioning control, in particular to an FPSO (floating production storage and offloading) anchoring dynamic positioning control method based on acceleration feedforward for an optimal heading polar region.
Background
With global warming, resource development and scientific research in arctic regions are gradually developed, wherein a Floating Production Storage and Offloading (FPSO) is a mature device in many ocean resource development systems. Compared with the traditional devices such as an ocean fixed platform, the FPSO has the advantage of good flexibility, and the positioning mode can be flexibly selected according to different sea areas and different sea conditions. The anchoring dynamic positioning combines the advantages of the dynamic positioning technology and the anchoring positioning technology, reduces the complexity of anchoring arrangement and the action frequency of the propeller, thereby reducing the loss of the propeller and ensuring safer, more economic and more efficient resource exploitation.
Resource exploitation in polar regions is more complicated and difficult compared with open water areas, and the FPSO operated in the ice-covered water areas is subjected to external force which is not only wave flow, but also ice load which is rapid in change, various in shape, difficult to calculate and highly nonlinear. In order to overcome the severe environment of the polar region and enable the FPSO to be in a safe working state, the invention provides an optimal polar region FPSO anchoring dynamic positioning control method based on Acceleration feedforward (AFF), which can calculate the optimal heading according to the tension of an anchoring cable, improve the anti-interference capability of a system by using the AFF and finally control the motion state of the FPSO by a Nonlinear Model Predictive Controller (NMPC).
Disclosure of Invention
The invention aims to provide an FPSO (floating production storage and offloading) anchoring power positioning control method based on acceleration feedforward, which is used for calculating an expected heading by using anchoring cable tension, designing an AFF (active flight control) observer to reduce an estimation error of an unknown ice load on a ship state, compensating ice disturbance power by using the AFF, and controlling the heading and the position of an FPSO (floating production and offloading) by using an NMPC (non-volatile memory) to keep the FPSO in an expected state.
The purpose of the invention is realized as follows:
the FPSO anchoring power positioning control method based on acceleration feedforward for the optimal heading polar region specifically comprises the following steps:
step 1: and calculating the tension of the mooring cable by using the mooring system model according to the position of the ship, and designing an optimal heading determination method related to the maximum tension mooring cable and the secondary high tension mooring cable.
Calculating the tension of 8 mooring cables in real time to obtain the maximum tension TaAnd the next highest tension TbAnd determining the target heading. Calculating T by equation (1)aMultiplying the angular difference of (2) by the weight to calculate TaThe target heading is obtained according to the formula (3).
Figure BDA0003022039250000021
E＝α1-α2 (2)
αT＝α1+E×R (3)
Wherein R is the proportion of the maximum tension in the sum of the maximum tension and the second maximum tension, E is the angle difference between the maximum tension mooring cable and the second maximum tension mooring cable, and alphaTIs the target heading.
Step 2: and adding an acceleration term in the state observer, designing an AFF observer, estimating the position, heading and speed value of the FPSO, and directly compensating unknown ice disturbance by using the AFF in the controller.
And (3) assuming that gravity and noise of the accelerometer are ignored, and considering slow variation deviation b (t) of a mechanical device of the acceleration, an output model of the accelerometer is as follows:
Figure BDA0003022039250000022
wherein the content of the first and second substances,
Figure BDA0003022039250000023
the actual acceleration at the previous moment.
α (t) is an acceleration compensation term, and the expression is as follows:
Figure BDA0003022039250000024
wherein r isd(t) is the unknown disturbance at the last instant.
And filtering the acceleration compensation term to obtain a final acceleration compensation term as follows:
Figure BDA0003022039250000025
after finishing, the final AFF observer can be obtained as follows:
Figure BDA0003022039250000026
wherein, τ is a designed control law, and the expression is as follows:
τ＝μ(t)-τaff(t) (7)
wherein, mu (t) is a control law, tau, designed by NMPCaffIs an acceleration feedforward term, and the expression is as follows:
Figure BDA0003022039250000027
and step 3: the estimated position, heading and speed are used for NMPC design, and FPSO anchoring is obtained by combining AFF
Control law of dynamic positioning system.
The dynamic positioning system is nonlinear, and after the system is linearized by taylor expansion, when the ship motion deviates from a linearization point, the control precision of the ship can be reduced by a linear model predictive control algorithm, and a divergence phenomenon can occur in the serious case.
The accurate feedback linearization method can obtain a new linear system from the nonlinear system through coordinate transformation, the linear system after feedback linearization keeps the nonlinear characteristic of the original motion mathematical model, and then the mooring dynamic positioning model prediction control law is designed through the linear system based on feedback linearization.
Utilizing the concept of plum derivative, relative order and differential homoembryo to linearize the accurate feedback of the FPSO system, and obtaining a state space equation as follows:
Figure BDA0003022039250000031
wherein y is the system output after accurate feedback linearization, v is the control law after accurate feedback linearization, and
v＝a(x)+b(x)u，
Figure BDA0003022039250000032
discretizing and merging equation (10) into a state space equation with an integrator:
Figure BDA0003022039250000033
wherein x isa(k)＝[Δz(k)y(k)]T，
Figure BDA0003022039250000034
Ca＝[O3×6 I3×3]
Controller design after accurate feedback linearization:
a prediction model within the optimization window can be obtained by equation (12):
Y＝Fxa(k)+ΦΔV (11)
wherein:
Figure BDA0003022039250000035
Figure BDA0003022039250000036
because the external ice environment is fast and transient with respect to the ice resistance generated by the FPSO, the rate of change of the actuator amplitude generated by the controller cannot be too great, otherwise damage to the rigid body would be unpredictable. This relaxes the position constraint, only the FPSO needs to be kept within a certain range, and the following constraints are obtained:
Umin≤U≤Umax (12)
ΔUmin≤ΔU≤ΔUmax (13)
Ymin≤Y≤Ymax (14)
wherein, UminAnd UmaxRespectively minimum and maximum actuator amplitude, DeltaUminAnd Δ UmaxRespectively minimum and maximum values of the rate of change of the amplitude of the actuator, YminAnd YmaxAre the minimum and maximum values of the output position and heading.
Finding the relation between the delta V and the delta U and U:
U＝f(ΔV) (15)
and finally, obtaining a control optimization problem about parameter delta V constraint based on nonlinear model control, wherein the control optimization problem is as follows:
minJ＝(Rs-Fxa(k))T(Rs-Fxa(k))-2ΔVTΦT(Rs-Fxa(k))+ΔVT(ΦTΦ+R')ΔV
st.LΔV≤N (16)
wherein, L and N are constant matrixes respectively.
Thus, we can obtain the optimal control input u (k) at the time k, namely the nominal control law mu (t), by solving the nonlinear constraint problem, and perform mooring dynamic positioning control on the FPSO.
The invention has the following beneficial effects:
1. the invention designs a calculation method of the expected heading, reduces the influence of ice load on an FPSO platform, and increases the safety of operation in polar regions with unstable environmental conditions.
2. Due to the influence of external ice load, the FPSO state estimation generates larger deviation, the designed AFF observer effectively reduces the influence of unknown and rapidly-changed ice load on the system state estimation, and the system state estimation precision is improved.
3. The method has the advantages that an AFF control law capable of directly compensating external ice load disturbance is designed, feedforward control is carried out on the ice load disturbance, the influence of the ice disturbance on a system can be predicted, measures are taken in advance, compared with feedback control, the method is good in real-time performance and free from influence of system lag, and therefore performance of the FPSO mooring dynamic positioning system in the polar environment can be effectively improved.
NMPC is different from a linear model prediction control method, all nonlinear terms of the system are considered, the nonlinear system is accurately linearized through differential homomorphic transformation, and the system error in the linearization process is eliminated; compared with other controllers, the NMPC is more convenient and effective in processing the input amplitude and the change rate of the input amplitude of the execution mechanism and the constraint of the motion state of the ship.
Drawings
FIG. 1 is a block diagram of FPSO mooring dynamic positioning control;
FIG. 2 is a schematic view of a mooring line distribution;
FIG. 3 is a schematic diagram of a target heading calculation method.
Detailed Description
The invention is further described below with reference to the accompanying drawings.
To make the aforementioned objects, features and advantages of the present invention clearer, the present invention will be described in further detail with reference to fig. 1 to 3 and the following detailed description, wherein fig. 1 is a block diagram of FPSO mooring dynamic positioning control; FIG. 2 is a schematic view of a mooring line distribution; FIG. 3 is a schematic diagram of a target heading calculation method.
The purpose of the invention is realized by the following steps:
as shown in fig. 1, the FPSO mooring dynamic positioning control process includes: the method comprises the steps of using a sensor (measuring system) to measure the position, the heading and the measured acceleration (ignoring gravity and noise) of the FPSO to an AFF observer, obtaining estimated values of the position, the heading and the speed of the FPSO to be used for designing an NMPC (non-volatile memory controller), obtaining an NMPC control law, and further combining the AFF control law for compensating ice load to obtain a final control law to realize the dynamic positioning control of the FPSO.
1. Building mathematical model of FPSO and anchoring system
(1) Ship motion mathematical model
Figure BDA0003022039250000051
Wherein, eta ═ xy ψ]T，υ＝[uvr]T，τmThe mooring cable acts on the tension of the ship; tau isenvIs the disturbing force acting on the FPSO.
Figure BDA0003022039250000052
Is a coordinate transformation matrix, M is a system inertia matrix, D is a damping coefficient matrix, and the expression is as follows:
Figure BDA0003022039250000053
Figure BDA0003022039250000054
Figure BDA0003022039250000055
(2) buoy mooring system model
The mooring system is assumed to be composed of 8 symmetrically distributed mooring cables, the inner tower of the FPSO is fixed to the seabed through an anchor, and the horizontal tension expression of the ith (i ═ 1, …,8) cable is analyzed by statics of catenary theory as shown in fig. 2:
Figure BDA0003022039250000056
wherein L isiRepresents the length of the ith cable, ThiRepresents the horizontal tension of the ith cable, and the expressions of a, b, c and d are shown in formulas (4) to (7), XiIs LiThe projection in the horizontal direction and can be calculated by:
Figure BDA0003022039250000061
wherein (x)i,yi) Represents the i-th cable anchor position and (x, y) represents the coordinates of the turret center in the northeast coordinate system.
Figure BDA0003022039250000062
Figure BDA0003022039250000063
Figure BDA0003022039250000064
Figure BDA0003022039250000065
Wherein the content of the first and second substances,
Figure BDA0003022039250000066
representing the angle between the lower end of the j-th section of the mooring line and the horizontal plane,
Figure BDA0003022039250000067
represents the angle, omega, between the upper end of the j-th section of the mooring line and the horizontal planejIs the weight per unit length, T, of the j-th section of the mooring linehIs the tension of the mooring line in the horizontal direction.
The horizontal resultant tension of all cables of the whole anchoring system in the northeast coordinate system can be obtained according to the formula (5):
Figure BDA0003022039250000068
wherein, thetai＝arctan[(yi-y)/(xi-x)]。
Finally, by converting the matrix JR(psi) converting the resultant tension and moment in the northeast coordinate system into the hull coordinate system to obtain tau in the FPSO motion mathematical modelm：
Figure BDA0003022039250000069
Wherein, Xm、YmAnd NmThe resultant force and moment of anchoring cable of anchoring system respectively representing longitudinal direction, transverse direction and heading direction under ship body coordinate system, Xall、YallAnd NallRepresenting longitudinal, transverse and heading mooring system mooring cable resultant forces and moments, respectively, in the northeast coordinate system.
2. Calculating an expected heading
Calculating the tension of 8 mooring cables in real time to obtain the maximum tension mooring cable TaAnd second-order large tension mooring cable TbCalculating T by equation (13)aMultiplying the weight of the sum of the maximum and the second maximum tensions by the angular difference of (14) to calculate TaThe target heading is obtained according to equation (15). The target heading is schematically shown in fig. 3.
Figure BDA0003022039250000071
E＝α1-α2 (30)
αT＝α1+E×R (31)
Wherein R is the proportion of the maximum tension in the sum of the maximum tension and the second maximum tension, E is the angle difference between the maximum tension mooring cable and the second maximum tension mooring cable, and alphaTIs the target heading.
3. Design acceleration feedforward observer
From the mathematical model of the ship motion of equation (1), considering the measurement deviation b (t) of the accelerometer itself, and regarding it as the wiener process, the following model can be obtained:
Figure BDA0003022039250000072
wherein r is unknown environmental force and system unmodeled term, and w is zero-mean Gaussian driving noise.
And (3) assuming that gravity and noise of the accelerometer are ignored, and considering slow variation deviation b (t) of a mechanical device of the acceleration, an output model of the accelerometer is as follows:
Figure BDA0003022039250000073
wherein the content of the first and second substances,
Figure BDA0003022039250000074
the actual acceleration at the previous moment.
The observer is modeled by equation (16) as:
Figure BDA0003022039250000075
wherein, C1、C2And C3Is a matrix to be designed, alpha (t) is an acceleration compensation term, and the expression is as follows:
Figure BDA0003022039250000076
Figure BDA0003022039250000088
wherein r isd(t) is the unknown disturbance at the last instant.
Bringing formula (19) into formula (18) can be:
Figure BDA0003022039250000081
equation (16) is subtracted from equation (20), and the closed loop dynamic error is expressed as:
Figure BDA0003022039250000082
wherein the content of the first and second substances,
Figure BDA0003022039250000083
as can be seen from the closed-loop error dynamic expression, by adding an acceleration feedforward term, the error dynamic quick-acting disturbance r (t) of the observer of the nominal system is effectively inhibited, so that the state estimation precision is improved.
And filtering the acceleration compensation term to obtain a final acceleration compensation term as follows:
Figure BDA0003022039250000084
after finishing, the final AFF observer can be obtained as follows:
Figure BDA0003022039250000085
wherein, τ is a designed control law, and the expression is as follows:
τ＝μ(t)-τaff(t) (40)
wherein μ (t) is a control law designed by NMPC, and the specific design is shown in the next section. Tau isaffIs an acceleration feedforward term, and the expression is as follows:
Figure BDA0003022039250000086
4. controlling ship position and heading using NMPC
And (3) utilizing the concepts of plum derivative, relative order and differential homoembryo to accurately feed back and linearize the ship model.
Order to
Figure BDA0003022039250000087
According to the formula (1-4), the state quantity is an estimated value of the previous section, and is expanded into the following form:
Figure BDA0003022039250000091
wherein the content of the first and second substances,
Figure BDA0003022039250000092
Figure BDA0003022039250000093
Figure BDA0003022039250000094
writing equation (26) as a standard nonlinear state space model:
Figure BDA0003022039250000095
wherein the content of the first and second substances,
Figure BDA0003022039250000096
Figure BDA0003022039250000097
the derivative of lie is taken over the output variable h (x):
Figure BDA0003022039250000098
Figure BDA0003022039250000099
Figure BDA0003022039250000101
Figure BDA0003022039250000102
Figure BDA0003022039250000103
due to b1(x) All elements in the matrix are zero, and b (x) is a non-singular matrix, and the relative order of the non-singular matrix is equal to the order of the original system, so that accurate feedback linearization can be realized. The new state variable z after the accurate feedback linearization is therefore:
Figure BDA0003022039250000104
wherein the content of the first and second substances,
Figure BDA0003022039250000105
Figure BDA0003022039250000106
finally, the state space equation after accurate feedback linearization is:
Figure BDA0003022039250000107
wherein y is the system output after precise feedback linearization, v is the control law after precise feedback linearization, and v ═ a (x) + b (x) u,
Figure BDA0003022039250000108
controller design after accurate feedback linearization:
discretizing equation (34) into a discrete-time state-space equation:
Figure BDA0003022039250000109
wherein z (k +1) is the state at the moment k +1 after discretization, z (k) is the state at the moment k after discretization, v (k) is the control input at the moment k after discretization, y (k) is the system output at the moment k after discretization, Ad、BdAnd CdIs a system matrix.
From z (k +1) ═ z (k) + Δ z (k +1), y (k +1) ═ y (k) + Δ y (k +1), and taken into formula (35), it can be obtained:
Δz(k+1)＝AdΔz(k)+BdΔv(k) (52)
y(k+1)＝y(k)+CdAdΔz(k)+CdBdΔv(k) (53)
the above is expressed as a state space equation with an integrator:
Figure BDA0003022039250000111
wherein x isa(k)＝[Δz(k)y(k)]T，
Figure BDA0003022039250000112
Ca＝[03×6 I3×3]
Controller design after accurate feedback linearization:
1) prediction model
Within an optimization window, the future N can be predictedcN in control time domainpA system output (N)c≤Np)：
Y＝Fxa(k)+ΦΔV (55)
Wherein:
Figure BDA0003022039250000113
Figure BDA0003022039250000116
2) roll optimization
By optimizing the performance index, a control input Δ v that optimizes the objective function is obtained. The objective function is established as follows:
J＝(Rs-Y)T(Rs-Y)+ΔVTR'ΔV (56)
wherein R issIs a desired output and
Figure BDA0003022039250000114
rwis an adjustment parameter.
By bringing (39) into formula (40), we can obtain:
J＝(Rs-Fxa(k))T(Rs-Fxa(k))-2ΔVTΦT(Rs-Fxa(k))+ΔVT(ΦTΦ+R')ΔV (57)
taking the derivative of the above formula, and letting:
Figure BDA0003022039250000115
then, the optimal input sequence Δ V under the unconstrained condition of the time k can be obtained as follows:
ΔV＝(ΦTΦ+R')-1ΦT(Rs-Fxa(k)) (59)
according to the idea of rolling optimization, the first component Δ V (k) of the solution Δ V of equation (43) is substituted into the system, so that the output value y (k +1) can be obtained at the time k +1, and taken as the measured value at the next time, and then Δ V at the next time is calculated, and the expected position under the unconstrained condition can be found by repeating the steps.
3) Feedback correction
Depending on the nature of the ice load, the following constraints exist:
Umin≤U≤Umax (60)
ΔUmin≤ΔU≤ΔUmax (61)
Ymin≤Y≤Ymax (62)
expand U into:
Figure BDA0003022039250000121
the constraint controlling the input sequence U can be expressed as:
-(P1u(k-1)+P2ΔU)≤-Umin (64)
P1u(k-1)+P2ΔU≤Umax (65)
to link the constraints to Δ V, the constraints on Δ U and Y are translated into constraints on Δ V by the following steps:
by developing the equation (36), the relationship between the state z and the control Δ v after the precise feedback linearization at the time from k +1 to k + m can be obtained:
Figure BDA0003022039250000122
the above formula is collated to obtain a state expression in an optimization window:
Z＝G+HΔV (67)
wherein the content of the first and second substances,
Figure BDA0003022039250000131
Figure BDA0003022039250000132
similar to equation (47), expand V into:
Figure BDA0003022039250000133
using equation (52) and V ═ a (x) + b (x) U, a relationship between Δ V and U can be established:
U＝f(ΔV) (69)
using the output constraint of equation (46), the output versus Δ V can be found as:
Ymin≤Fxa(k)+ΦΔV≤Ymax (70)
and finally, controlling the control optimization problem about parameter delta V constraint based on the nonlinear model to:
minJ＝(Rs-Fxa(k))T(Rs-Fxa(k))-2ΔVTΦT(Rs-Fxa(k))+ΔVT(ΦTΦ+R')ΔV
Figure BDA0003022039250000134
wherein the content of the first and second substances,
Figure BDA0003022039250000135
Figure BDA0003022039250000136
thus, we can solve this nonlinear constraint problem to find the optimal control input at time k:
u(k)＝b(z(k))-1[b(z(k-1))u(k-1)+a(z(k-1))-a(z(k))+Δv(k)] (72)
here, u (k) is the nominal control law μ (t), and thus the final FPSO mooring dynamic positioning control law is:
Figure BDA0003022039250000141
and the final control law tau is utilized to realize that the FPSO anchoring dynamic positioning system in the water area of unknown ice environment keeps the optimal heading and enables the FPSO anchoring dynamic positioning system to be in a safe working area.

Claims (1)

1. An optimal polar region FPSO (floating production storage and offloading) anchoring dynamic positioning control method based on acceleration feedforward is characterized by comprising the following steps: the method specifically comprises the following steps:
step 1: and calculating the tension of the mooring cable by using the mooring system model according to the position of the ship, and designing an optimal heading determination method related to the maximum tension mooring cable and the secondary high tension mooring cable.
Calculating the tension of 8 mooring cables in real time to obtain the maximum tension TaAnd the next highest tension TbAnd determining the target heading. Calculating T by equation (1)aMultiplying the angular difference of (2) by the weight to calculate TaThe target heading is obtained according to the formula (3).
Figure FDA0003022039240000011
E＝α1-α2 (2)
αT＝α1+E×R (3)
Wherein R is the proportion of the maximum tension in the sum of the maximum tension and the second maximum tension, E is the angle difference between the maximum tension mooring cable and the second maximum tension mooring cable, and alphaTIs the target heading.
Step 2: and adding an acceleration term in the state observer, designing an AFF observer, estimating the position, heading and speed value of the FPSO, and directly compensating unknown ice disturbance by using the AFF in the controller.
And (3) assuming that gravity and noise of the accelerometer are ignored, and considering slow variation deviation b (t) of a mechanical device of the acceleration, an output model of the accelerometer is as follows:
Figure FDA0003022039240000012
wherein the content of the first and second substances,
Figure FDA0003022039240000013
the actual acceleration at the previous moment.
α (t) is an acceleration compensation term, and the expression is as follows:
Figure FDA0003022039240000014
wherein r isd(t) is the unknown disturbance at the last instant.
And filtering the acceleration compensation term to obtain a final acceleration compensation term as follows:
Figure FDA0003022039240000015
after finishing, the final AFF observer can be obtained as follows:
Figure FDA0003022039240000021
wherein, τ is a designed control law, and the expression is as follows:
τ＝μ(t)-τaff(t) (7)
wherein, mu (t) is a control law, tau, designed by NMPCaffIs an acceleration feedforward term, and the expression is as follows:
Figure FDA0003022039240000022
and step 3: and (4) applying the estimated position, heading and speed to NMPC design, and combining AFF to obtain a control law of the FPSO mooring dynamic positioning system.
The dynamic positioning system is nonlinear, and after the system is linearized by taylor expansion, when the ship motion deviates from a linearization point, the control precision of the ship can be reduced by a linear model predictive control algorithm, and a divergence phenomenon can occur in the serious case.
The accurate feedback linearization method can obtain a new linear system from the nonlinear system through coordinate transformation, the linear system after feedback linearization keeps the nonlinear characteristic of the original motion mathematical model, and then the mooring dynamic positioning model prediction control law is designed through the linear system based on feedback linearization.
Utilizing the concept of plum derivative, relative order and differential homoembryo to linearize the accurate feedback of the FPSO system, and obtaining a state space equation as follows:
Figure FDA0003022039240000023
wherein y is the system output after precise feedback linearization, v is the control law after precise feedback linearization, and v ═ a (x) + b (x) u,
Figure FDA0003022039240000024
discretizing and merging equation (10) into a state space equation with an integrator:
Figure FDA0003022039240000025
wherein x isa(k)＝[Δz(k) y(k)]T,
Figure FDA0003022039240000026
Ca＝[O3×6I3×3]
Controller design after accurate feedback linearization:
a prediction model within the optimization window can be obtained by equation (12):
Y＝Fxa(k)+ΦΔV (11)
wherein:
Figure FDA0003022039240000031
Figure FDA0003022039240000032
because the external ice environment is fast and transient with respect to the ice resistance generated by the FPSO, the rate of change of the actuator amplitude generated by the controller cannot be too great, otherwise damage to the rigid body would be unpredictable. This relaxes the position constraint, only the FPSO needs to be kept within a certain range, and the following constraints are obtained:
Umin≤U≤Umax (12)
ΔUmin≤ΔU≤ΔUmax (13)
Ymin≤Y≤Ymax (14)
wherein, UminAnd UmaxRespectively minimum and maximum actuator amplitude, DeltaUminAnd Δ UmaxRespectively minimum and maximum values of the rate of change of the amplitude of the actuator, YminAnd YmaxAre the minimum and maximum values of the output position and heading.
Finding the relationship of Δ V to Δ U and U:
U＝f(ΔV) (15)
and finally, obtaining a control optimization problem about parameter delta V constraint based on nonlinear model control, wherein the control optimization problem is as follows:
minJ＝(Rs-Fxa(k))T(Rs-Fxa(k))-2ΔVTΦT(Rs-Fxa(k))+ΔVT(ΦTΦ+R')ΔV
st.LΔV≤N (16)
wherein, L and N are constant matrixes respectively.
Thus, we can obtain the optimal control input u (k) at the time k, namely the nominal control law mu (t), by solving the nonlinear constraint problem, and perform mooring dynamic positioning control on the FPSO.
CN202110405217.0A 2021-04-15 2021-04-15 Optimal polar region FPSO (Floating production storage and offloading) anchoring dynamic positioning control method based on acceleration feedforward Active CN113296499B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110405217.0A CN113296499B (en) 2021-04-15 2021-04-15 Optimal polar region FPSO (Floating production storage and offloading) anchoring dynamic positioning control method based on acceleration feedforward

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110405217.0A CN113296499B (en) 2021-04-15 2021-04-15 Optimal polar region FPSO (Floating production storage and offloading) anchoring dynamic positioning control method based on acceleration feedforward

Publications (2)

Publication Number Publication Date
CN113296499A true CN113296499A (en) 2021-08-24
CN113296499B CN113296499B (en) 2022-10-28

Family

ID=77319843

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110405217.0A Active CN113296499B (en) 2021-04-15 2021-04-15 Optimal polar region FPSO (Floating production storage and offloading) anchoring dynamic positioning control method based on acceleration feedforward

Country Status (1)

Country Link
CN (1) CN113296499B (en)

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103970021A (en) * 2014-05-21 2014-08-06 哈尔滨工程大学 Relaxation power positioning control system based on model prediction control
CN105974930A (en) * 2016-04-18 2016-09-28 哈尔滨工程大学 Method for tracking movement mother ship by UUV (Unmanned Underwater Vehicle) based on nonlinear model predictive control
CN106227221A (en) * 2016-09-28 2016-12-14 哈尔滨工程大学 A kind of unmanned boat dynamic position control method
CN110687793A (en) * 2019-11-04 2020-01-14 青岛科技大学 Input increment-based nonlinear unbiased prediction control method for ship dynamic positioning system
CN110687794A (en) * 2019-11-04 2020-01-14 青岛科技大学 Nonlinear unbiased prediction control method of ship dynamic positioning system based on disturbance observer
US20200066369A1 (en) * 2018-08-21 2020-02-27 Lonza Ltd. Process for creating reference data for predicting concentrations of quality attributes
EP3639102A1 (en) * 2017-06-15 2020-04-22 ABB Schweiz AG Controlling marine vessel

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103970021A (en) * 2014-05-21 2014-08-06 哈尔滨工程大学 Relaxation power positioning control system based on model prediction control
CN105974930A (en) * 2016-04-18 2016-09-28 哈尔滨工程大学 Method for tracking movement mother ship by UUV (Unmanned Underwater Vehicle) based on nonlinear model predictive control
CN106227221A (en) * 2016-09-28 2016-12-14 哈尔滨工程大学 A kind of unmanned boat dynamic position control method
EP3639102A1 (en) * 2017-06-15 2020-04-22 ABB Schweiz AG Controlling marine vessel
US20200066369A1 (en) * 2018-08-21 2020-02-27 Lonza Ltd. Process for creating reference data for predicting concentrations of quality attributes
CN110687793A (en) * 2019-11-04 2020-01-14 青岛科技大学 Input increment-based nonlinear unbiased prediction control method for ship dynamic positioning system
CN110687794A (en) * 2019-11-04 2020-01-14 青岛科技大学 Nonlinear unbiased prediction control method of ship dynamic positioning system based on disturbance observer

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
GUOQING XIA;JU LIU;ANG ZHAO: "Neural network predictive model based NMPC for ship path following considering amplitude and rate constraints", 《THE 27TH CHINESE CONTROL AND DECISION CONFERENCE (2015 CCDC)》 *
张爱华: "动力定位船任务驱动的跟踪控制方法研究", 《中国博士学位论文全文数据库 工程科技Ⅱ辑》 *
王赟卓: "动力定位船舶低速航迹预测控制研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 *

Also Published As

Publication number Publication date
CN113296499B (en) 2022-10-28

Similar Documents

Publication Publication Date Title
Messineo et al. Offshore crane control based on adaptive external models
CN110597069B (en) Underwater robot self-adaptive regional power positioning control method based on RBF neural network
CN108445762B (en) Dynamic positioning control method based on UKF filtering and constraint model predictive control
CN103970021B (en) A kind of lax power-positioning control system based on Model Predictive Control
CN109739248B (en) Ship-borne three-degree-of-freedom parallel stable platform stability control method based on ADRC
Ren et al. Active heave compensation of floating wind turbine installation using a catamaran construction vessel
CN110032075B (en) Design method of saturation compensation control system of dynamic positioning ship
CN116627043B (en) Regional power positioning control method of combined anchoring system
Xia et al. Modeling and three-layer adaptive diving control of a cable-driven underwater parallel platform
CN114115276A (en) Ship dynamic positioning control method based on online grouping optimization model prediction
CN113296499B (en) Optimal polar region FPSO (Floating production storage and offloading) anchoring dynamic positioning control method based on acceleration feedforward
CN104142626A (en) Ship dynamic positioning control method based on inverse system and internal model control
Tomera Nonlinear observers design for multivariable ship motion control
Patil et al. A time-domain method for analyzing the ship roll stabilization based on active fin control
Wang et al. Numerical and experimental study on the influence of the set point on the operation of a thruster-assisted position mooring system
Værnø et al. An output feedback controller with improved transient response of marine vessels in dynamic positioning
CN105807767B (en) The adaptive filter method that tracking environmental power is mutated in dynamic positioning
CN113485390A (en) Autonomous underwater robot dynamic positioning method and system capable of resisting ocean current disturbance
Ye et al. Position control of crane vessel during offshore installations: Using adaptive and robust control methods
Xu et al. Review of Heave Compensation Systems: Design and Control Strategies
Hosseinnajad et al. Application of observer-based sliding mode controller in dynamic positioning systems
Cheng et al. Application of linearization via state feedback to heading control for autonomous underwater vehicle
CN112835369A (en) Unmanned ship speed change curve path tracking control method based on ESO (electronic stability evaluation) drift angle estimation
Wang et al. Nonsingular fast terminal sliding mode-based robust adaptive structural reliable position-mooring control with uncertainty estimation
Tannuri et al. Comparing two different control algorithms applied to dynamic positioning of a pipeline launching barge

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant