CN109917643A - Deep water installs heave compensation feedback control system - Google Patents
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Abstract
The invention discloses deep water to install heave compensation feedback control system, including control system, detection system, fluid power system and mechanical execution system；The motor message of lash ship is detected first, acquire the heave movement signal of lifting suspension centre, the actual tension value for hanging weight practical heave velocity and hawser measured respectively by the rotary encoder being mounted on winch and the non-contact tension sensor being mounted on hawser, all detection signals are transmitted to computer control system, pass through heave compensation system model-free adaptive controller mathematical model, control system operation obtains feedback deviation amount, and by the folding and unfolding campaign of given control algolithm control winch, carry out speed and tension compensating, make to hang weight with opposing stationary speed, transfer to underwater platform, and guarantee cable tension in a certain range.The beneficial effects of the invention are as follows can be realized to hang the Active Compensation control function of weight in vertical direction.
Description
Technical field
The invention belongs to shipbuilding technical field, it is related to a kind of deep water installation heave compensation feedback control system and calculation
Method.
Background technique
It is a large inertia nonlinear system that deep water, which installs heave compensation system, there are problems that large time delay, using routine
Feedback control is difficult to obtain ideal control effect.In order to which the compensation precision for improving system and the lag for solving large inertia system are asked
Topic, the control strategy combined there is employed herein the forecast of lash ship heave movement and active control install heave compensation system to deep water
It is controlled.The forecast of lash ship lifting suspension centre heave movement has been studied in chapter 5.
Deep water install active heave compensation control system the characteristics of than more prominent, first, entire heave compensation system knot
Structure is huge, complicated, and there are the disturbing factors such as mechanical friction, cause whole system to have serious non-linear；Second, compensation
Occurs for the compensation response of system in advance at the time of hanging weight and changing the moment, due to hoisting machinery itself and hangs weight
The quality of object is all bigger, so that whole system is had very big inertia force, causes to respond serious lag.Therefore, it is generated in sea situation
When mutation or situations such as system is by environmental disturbances, the performance of control system will be challenged, the stability of control system,
Response quickly of system will grind hoisting apparatus progress real-time control and control system to the adaptability of different task and environment
Study carefully.
Summary of the invention
The purpose of the present invention is to provide deep water to install heave compensation feedback control system, and the beneficial effects of the invention are as follows energy
Enough realize hangs the Active Compensation control function of weight in vertical direction, vertical to weight is hung to weaken lash ship attitude motion
The influence of movement, and in a certain range the tension force of hawser.
The technical scheme adopted by the invention is that including control system, detection system, fluid power system and mechanical execution
System；The motor message for detecting lash ship first, acquires the heave movement signal of lifting suspension centre, is compiled by the rotation being mounted on winch
What code device and the non-contact tension sensor that is mounted on hawser measured respectively the hang practical heave velocity of weight and hawser
All detection signals are transmitted to computer control system, pass through heave compensation system model-free adaption by actual tension value
Controller mathematical model, control system operation obtain feedback deviation amount, and by the folding and unfolding fortune of given control algolithm control winch
It is dynamic, carry out speed and tension compensating, make to hang weight with opposing stationary speed, transfer to underwater platform, and guarantee hawser
Power is in a certain range.
Further, control system is by signal detection system, controller processing unit and postposition drive system three zones mould
Block composition；Signal detection system includes MRU motion reference units, tension sensor, rotary encoder and advance data processing mould
Block；Advance data processing module finally obtains satisfaction for being converted, being filtered to the voltage and current signal that sensor exports
The electric current and voltage signal of controller I/O port requirements；Signal detection system is detected and is handled to lower column signal:
1) lash ship attitude motion signal detection
The mode for acquiring ship attitude motion signal is varied, utilizes MUR motion reference units detection working mother boat
Heel, trim, heave acceleration signal, obtain speed signal by integral, logical using obtained lash ship attitude motion signal
Cross the heave movement signal that coordinate transform acquires lifting suspension centre, the interference signal as control system；
2) Compensation Feedback signal detection
Compensation Feedback signal is the lowering velocity signal and cable tension signal for hanging weight, and rotary encoder is for detecting
Hydraulic motor rotary speed is calculated by the hydraulic motor rotary speed detected and hangs the actual catenary motion speed of weight, and with give
Fixed speed signal is compared, and finally obtains the deviation signal of velocity compensation, and the instantaneous tension of hawser is examined by tension sensor
The tension variation signal for measuring, and obtaining compared with given tension value, the tension for controlling hawser compensate；
Controller processing unit includes feedback controller and forecasting controlling device；Feedback controller uses speed and tension feedback
The Compound Control Strategy that control and disturbance feedforward forecasting controlling combine carries out feedback control, forecasting controlling to speed and tension
Device effect is disturbance feedforward control, generates control action to the disturbing signal of system using the forecast of lifting suspension centre heave movement,
Weaken influence of the disturbing signal to controlled variable, according to compensation target and control system performance requirement, by predicting lifting suspension centre
Next step athletic posture, effectively generate ideal control signal, correct in time, overcome the time lag characteristic of system, improve
Control system dynamically reflect ability and control precision, to weaken influence of the lash ship attitude motion to weight catenary motion is hung,
Postposition drive system includes hydraulic system and mechanical execution system, execute the order of controller processing unit.
Further, heave compensation system model-free adaptive controller mathematical model are as follows:
Y (k+1)=f (y (k), L, y (k-ny),u(k),L,u(k-nu)) (1)
Wherein, u (k) ∈ Rm, etching system outputs and inputs when y (k) ∈ R respectively indicates k；ny,nuBe two positions just
Integer；It is unknown time-variant nonlinear function；
When each sampling of controlled device-hawser of feedback control system and the discrete models (1) for hanging weight
K is carved, system input and output are controllable, to any given uniformly bounded system desired output signal, fi(L), i=1, L, m
About (ny+ 2) each component of a variable has continuous partial derivative, and system (1) meets Generalized Lipschitz operators item
Part, i.e., to any k1≠k2, k1,k2>=0 and u (k1)≠u(k2) have
||y(k1+1)-y(k2+1)||≤b||u(k1)-u(k2)|| (2)
Wherein, y (ki+ 1)=f (y (ki),L,y(ki-ny),u(ki),L,u(ki-nu)), i=1,2, b > 0 are one normal
Number；
If system meet it is assumed above, when | | Δ u (k) | | when ≠ 0, MISO Discrete time Nonlinear Systems (2) are certain
There are pseudo- Jacobi matrix (PJM) Φ (k) of the time-varying parameter vector of a referred to as pseudo- gradient, so that
Δ y (k+1)=ΦT(k)Δu(k) (3)
Wherein, Δ y (k+1)=y (k+1)-y (k), Δ u (k)=u (k)-u (k-1), and to all moment k, Φ (k)
It is bounded,
Formula (3) is the broken line equivalent equation of non-linear MISO mathematical model (1), setting control input criterion function are as follows:
J (u (k))=| y* (k+1)-y (k+1) |2+γ|u(k)-u(k-1)|2 (4)
Wherein y* (k+1) is that system expectation tracks signal；γ is a positive weight coefficient, in order to obtain good control
Effect and performance, different nonlinear systems have different value ranges again, and general γ value is smaller, and the control system response time gets over
Fastly, but overshoot may become larger, the bad stability of system, and formula (3) are substituted into criterion function (4), and makesThe control law of adaptive heave compensation system are as follows:
Wherein, step factor ρ ∈ (0,1]；Etching system outputs and inputs when u (k) ∈ Rm, y (k) ∈ R respectively indicates k；
Y* (k+1) is that system expectation tracks signal, and γ is a positive weight coefficient；
The criterion function of parameter Estimation are as follows:
It enablesObtain the parameter Estimation equation of pseudo- partial derivative φ (k) are as follows:
Wherein, factor η ∈ (0,2] constant,It is the estimation of PJM Φ (k)
Value；
IfOrThen
Wherein,It isInitial value.
Detailed description of the invention
Fig. 1 is deep water installation heave compensation feedback structure schematic diagram of the present invention；
Fig. 2 is active heave compensation system control principle drawing；
Fig. 3 is to hang weight heave movement velocity variations schematic diagram after disturbance noise is added；
Fig. 4 is the catenary motion velocity variations that weight is hung before and after opening compensator；
Fig. 5 is cable tension variation before and after opening compensator；
Fig. 6 is cable tension variation before and after opening compensator using PID control.
Specific embodiment
The present invention is described in detail With reference to embodiment.
Deep water of the present invention installation heave compensation feedback control system by control system, detection system, fluid power system and
Mechanical execution system is constituted.The motor message for detecting lash ship first, acquires the heave movement signal of lifting suspension centre, is twisted by being mounted on
What the rotary encoder on vehicle measured respectively with the non-contact tension sensor being mounted on hawser hangs the practical heave of weight
All detection signals are transmitted to computer control system, pass through heave compensation system by the actual tension value of speed and hawser
Model-free adaptive controller mathematical model, control system operation obtain feedback deviation amount, and by given control algolithm control
The folding and unfolding campaign of winch carries out speed and tension compensating, make to hang weight with opposing stationary speed, transfer to underwater platform,
And guarantee cable tension in a certain range.
System structure is as shown in Figure 1, big by signal detection system 1, controller processing unit 2 and postposition drive system 3 three
Functional module composition.The practical compensation requirement of heave compensation system is installed according to deep water, the prerequisite function of control system:
(1) real-time detection lash ship attitude motion, the mainly rolling, pitching of lash ship and heave movement；(2) the hydraulic horse of real-time measure and control
Up to the size and Orientation of revolving speed；(3) tension of real-time control hawser；(4) real-time control weight lowering velocity；(5) it records in real time
The operating status of system；It (6) can entire heave compensation system hardware connection.
(1) signal detection system 1 includes MRU motion reference units 101, tension sensor 102, rotary encoder 103 etc.
Sensor and advance data processing module 104.Advance data processing module is mainly used for the voltage and current exported to sensor
Signal is converted, is filtered, finally obtain the electric current for meeting controller I/O port requirements and voltage signal (i.e. the 4 of standard~
20mA, 0~10V).Signal detection system is mainly detected and is handled to lower column signal:
1) lash ship attitude motion signal detection
The mode for acquiring ship attitude motion signal is varied, detects working mother boat using MUR motion reference units 101
Heel, trim, heave uniform acceleration signal, by integral obtain speed signal, utilize obtained lash ship attitude motion letter
The heave movement signal of lifting suspension centre, the interference signal as control system number are acquired by coordinate transform.Active compensation
One key point of control system is to improve the detection accuracy and detection real-time of lash ship attitude motion signal.
2) Compensation Feedback signal detection
Compensation Feedback signal is mainly the lowering velocity signal and cable tension signal for hanging weight.Rotary encoder 103
It, can be by the hydraulic motor that detects since hawser speed is related to hydraulic motor rotary speed for detecting hydraulic motor rotary speed
Revolving speed, which is calculated, hangs the actual catenary motion speed of weight, and is compared with given speed signal, finally obtains speed
Spend the deviation signal of compensation.The instantaneous tension of hawser is obtained by the detection of tension sensor 102, and is obtained compared with given tension value
Tension variation signal, the tension for controlling hawser compensates.
(2) control principle
Controller processing unit 2 includes feedback controller 201 and forecasting controlling device 202；Feedback controller 201 uses speed
The Compound Control Strategy combined with tension feedback control and disturbance feedforward forecasting controlling, carries out feedback control to speed and tension
System carries out bias adjustment by the deviation of the actual value and setting value of weight speed and cable tension, feedback control can realize height
Precision controlling.The major function of forecasting controlling device 202 is disturbance feedforward control, that is, utilizes the forecast pair of lifting suspension centre heave movement
The disturbing signal of system generates control action, weakens influence of the disturbing signal to controlled variable.According to compensation target and control system
System performance requirement, active heave compensation control principle G- Design is as shown in Fig. 2, pass through the fortune of the next step of prediction lifting suspension centre
Dynamic posture effectively generates ideal control signal, corrects in time, overcome the time lag characteristic of system, improves the dynamic of control system
State reflects ability and control precision, to weaken influence of the lash ship attitude motion to weight catenary motion is hung.
Postposition drive system 3 includes hydraulic system and mechanical execution system.To carry out executing controller processing unit 2
Order.
Heave compensation system model-free adaptive controller mathematical model:
The input signal that deep water installs heave compensation control system is the heave movement speed of controlled device and of hawser
Power, output signal are therefore winch folding and unfolding movement velocity and direction can use following discrete time Nonlinear M ISO (Multiple
Input and Single Output) mathematical model expression are as follows:
Y (k+1)=f (y (k), L, y (k-ny),u(k),L,u(k-nu)) (1)
Wherein, etching system outputs and inputs when u (k) ∈ Rm, y (k) ∈ R respectively indicate k；ny,nuBe two positions just
Integer；It is unknown time-variant nonlinear function.
When each sampling of controlled device-hawser of feedback control system and the discrete models (1) for hanging weight
K is carved, system input and output are controllable, to any given uniformly bounded system desired output signal, fi(L), i=1, L, m
About (ny+ 2) each component of a variable has continuous partial derivative.And system (1) meets Generalized Lipschitz operators item
Part, i.e., to any k1≠k2, k1,k2>=0 and u (k1)≠u(k2) have
||y(k1+1)-y(k2+1)||≤b||u(k1)-u(k2)|| (2)
Wherein, y (ki+ 1)=f (y (ki),L,y(ki-ny),u(ki),L,u(ki-nu)), i=1,2, b > 0 are one normal
Number.
If system meet it is assumed above, when | | Δ u (k) | | when ≠ 0, MISO Discrete time Nonlinear Systems (2) are certain
There are one be referred to as " pseudo- gradient (Pseudo-gradient, PG) " time-varying parameter vector pseudo- Jacobi matrix (PJM) Φ
(k), so that
Δ y (k+1)=ΦT(k)Δu(k) (3)
Wherein, Δ y (k+1)=y (k+1)-y (k), Δ u (k)=u (k)-u (k-1), and to all moment k, Φ (k)
It is bounded,
Formula (3) is the broken line equivalent equation of non-linear MISO mathematical model (1), in equivalent process, it is desirable that sampling week
The value of phase dt and input signal winch folding and unfolding velocity variations Δ u (k) want sufficiently small, and pseudo- partial derivative can be regarded as one slowly
Time-varying parameter.Therefore, pseudo- partial derivative and the relationship of control input signal u (k) can be ignored when designing adaptive controller.
Setting control input criterion function are as follows:
J (u (k))=| y* (k+1)-y (k+1) |2+γ|u(k)-u(k-1)|2 (4)
Wherein y* (k+1) is that system expectation tracks signal；γ is a positive weight coefficient, in order to obtain good control
Effect and performance, different nonlinear systems have different value ranges again, and general γ value is smaller, and the control system response time gets over
Fastly, but overshoot may become larger, the bad stability of system.
Formula (3) are substituted into criterion function (4), and are madeIt is available from the control for adapting to heave compensation system
Rule are as follows:
Wherein, step factor ρ ∈ (0,1].
The criterion function of parameter Estimation can be obtained by model (3) are as follows:
Similarly, it enablesObtain the parameter Estimation equation of pseudo- partial derivative φ (k) are as follows:
Wherein, factor η ∈ (0,2] constant,It is estimating for PJM Φ (k)
Evaluation.
IfOrThen
Wherein,It isInitial value.
Non-parameter model adaptive control algorithm is constituted by control law (5) and parameter Estimation equation (7), (8).
Heave compensation system model-free adaptive controller mathematical model stability analysis:
The puppet ladder of the non-parameter model adaptive control of heave compensation control system is made of equation (6-15) and (6-16)
Spend Φ (k) algorithm for estimating, estimated valueIt must bounded.
It proves: enablingFormula (7) both ends are subtracted into Φ (k) simultaneously, are obtained:
| | Φ (k) | | have the upper bound, that is, there is a normal number b, make | | Φ (k) | |≤b, therefore | | Φ (k-1)-Φ (k) |
|≤2b, formula (9) both sides take norm, obtain:
For 0 η≤2 < and μ > 0, following formula is set up
Therefore there are 0 < d < 1, so that:
Wushu (12) is updated to (10), obtains:
ThereforeBounded, in addition, Φ (k) bounded, soBounded.As y* (k+1)=y*=const, exist
One positive number λmin> 0, so that working as λ >=λminWhen, system tracking error is convergent and BIBO is stable.
Control System Imitation
By control object-hawser of deep water installation system and the computation model of weight and MFA control algorithm
Equation group (5), (6) and (8) establishes heave compensation control system simulink emulation.When system emulation, transported with the heave of suspension centre
Dynamic speed is the interference signal of heave compensation system mathematical model, when actual value y (k) and control target value y (k+1) are with larger
When deviation, when just starting such as control system, it is necessary to be saturated limitation to control law calculated result u (k), control system is avoided to produce
Raw biggish oscillation.The parameter of heave compensation controller is set are as follows: sampling interval dt=0.5s, μ=1, λ=1, ε=0.01, η
=1.5, ρ=1,U (1)=u (2)=[0,0]T, winch speed variation targets yr(k)=0, xr=
0.5m/s, Tr=0.8 × 106N。
Start heave compensation system, random disturbances noise is added, when signal-to-noise ratio is 50,20,10db respectively, hangs weight liter
Such as (a) signal-to-noise ratio of Fig. 3 is 50db, (b) signal-to-noise ratio is 20db, (c) signal-to-noise ratio is 10db for heavy movement velocity variation.
When being turned off and on heave compensation system, weight catenary motion velocity variations and cable tension variation comparison diagram are hung
It is as shown in Figures 4 and 5 respectively.It can be seen that by simulation result, after random disturbances noise is added, system can be quickly returning to equilbrium position,
MFA control algorithm based on tight format dynamical linearization has good adaptive ability and robustness.Fig. 4 and
Fig. 5 simulation result shows that heave compensation controller can effectively weaken influence of the lash ship motion artifacts to weight heave movement is hung,
And there is good inhibiting effect to the fluctuation of cable tension, deep water installation active compensation control system can handle complexity
, control object with nonlinear characteristic, be able to satisfy the performance requirement of deep water installation, control effect is preferable.It will be appreciated from fig. 6 that
More preferable than the compensation effect obtained using pid control algorithm using MFA control algorithm, compensation precision is higher.
The above is only not to make limit in any form to the present invention to better embodiment of the invention
System, any simple modification that embodiment of above is made according to the technical essence of the invention, equivalent variations and modification,
Belong in the range of technical solution of the present invention.
Claims (3)
1. deep water installs heave compensation feedback control system, it is characterised in that: including control system, detection system, hydraulic-driven
System and mechanical execution system；The motor message for detecting lash ship first, acquires the heave movement signal of lifting suspension centre, by being mounted on
What the rotary encoder on winch measured respectively with the non-contact tension sensor being mounted on hawser hangs the practical liter of weight
All detection signals are transmitted to computer control system, pass through heave compensation system by the actual tension value of settling velocity degree and hawser
System model-free adaptive controller mathematical model, control system operation obtain feedback deviation amount, and by given control algolithm control
The folding and unfolding campaign of winch processed carries out speed and tension compensating, make to hang weight with opposing stationary speed, transfer to it is underwater flat
Platform, and guarantee cable tension in a certain range.
2. according to deep water described in claim 1 install heave compensation feedback control system, it is characterised in that: the control system by
Signal detection system, controller processing unit and postposition drive system three zones module composition；Signal detection system includes MRU
Motion reference units, tension sensor, rotary encoder and advance data processing module；Advance data processing module is used for biography
The voltage and current signal of sensor output is converted, is filtered, and the electric current and electricity for meeting controller I/O port requirements are finally obtained
Press signal；Signal detection system is detected and is handled to lower column signal:
1) lash ship attitude motion signal detection
Acquire ship attitude motion signal mode it is varied, using MUR motion reference units detection working mother boat heel,
Trim, heave acceleration signal, obtain speed signal by integral, pass through coordinate using obtained lash ship attitude motion signal
Transformation acquires the heave movement signal of lifting suspension centre, the interference signal as control system；
2) Compensation Feedback signal detection
Compensation Feedback signal is the lowering velocity signal and cable tension signal for hanging weight, and rotary encoder is hydraulic for detecting
Motor rotary speed is calculated by the hydraulic motor rotary speed detected and hangs the actual catenary motion speed of weight, and with it is given
Speed signal is compared, and finally obtains the deviation signal of velocity compensation, and the instantaneous tension of hawser is detected by tension sensor
The tension variation signal for arriving, and obtaining compared with given tension value, the tension for controlling hawser compensate；
Controller processing unit includes feedback controller and forecasting controlling device；Feedback controller is controlled using speed and tension feedback
The Compound Control Strategy combined with disturbance feedforward forecasting controlling carries out feedback control to speed and tension, and forecasting controlling device is made
With being disturbance feedforward control, control action is generated to the disturbing signal of system using the forecast of lifting suspension centre heave movement, is weakened
Influence of the disturbing signal to controlled variable, according to compensation target and control system performance requirement, by under prediction lifting suspension centre
The athletic posture of one step effectively generates ideal control signal, corrects in time, overcome the time lag characteristic of system, improve control
System dynamically reflect ability and control precision, to weaken influence of the lash ship attitude motion to weight catenary motion is hung, postposition
Drive system includes hydraulic system and mechanical execution system, execute the order of controller processing unit.
3. installing heave compensation feedback control system according to deep water described in claim 1, it is characterised in that: the heave compensation system
System model-free adaptive controller mathematical model are as follows:
Y (k+1)=f (y (k), L, y (k-ny),u(k),L,u(k-nu)) (1)
Wherein, u (k) ∈ Rm, etching system outputs and inputs when y (k) ∈ R respectively indicates k；ny,nuIt is the just whole of two positions
Number；It is unknown time-variant nonlinear function；
Each sampling instant k of controlled device-hawser of feedback control system and the discrete models (1) for hanging weight,
System input and output are controllable, to any given uniformly bounded system desired output signal, fi(L), i=1, L, m about
(ny+ 2) each component of a variable has continuous partial derivative, and system (1) meets generalized Lipschitz condition, i.e.,
To any k1≠k2, k1,k2>=0 and u (k1)≠u(k2) have
||y(k1+1)-y(k2+1)||≤b||u(k1)-u(k2)|| (2)
Wherein, y (ki+ 1)=f (y (ki),L,y(ki-ny),u(ki),L,u(ki-nu)), i=1,2, b > 0 are a constants；
If system meet it is assumed above, when | | Δ u (k) | | when ≠ 0, MISO Discrete time Nonlinear Systems (2) are certainly existed
Pseudo- Jacobi matrix (PJM) Φ (k) of the time-varying parameter vector of one referred to as pseudo- gradient, so that
Δ y (k+1)=ΦT(k)Δu(k) (3)
Wherein, Δ y (k+1)=y (k+1)-y (k), Δ u (k)=u (k)-u (k-1), and be to have to all moment k, Φ (k)
Boundary,
Formula (3) is the broken line equivalent equation of non-linear MISO mathematical model (1), setting control input criterion function are as follows:
J (u (k))=| y* (k+1)-y (k+1) |2+γ|u(k)-u(k-1)|2 (4)
Wherein y* (k+1) is that system expectation tracks signal；γ is a positive weight coefficient, in order to obtain good control effect
And performance, different nonlinear systems have different value ranges again, general γ value is smaller, and the control system response time is faster,
But overshoot may become larger, the bad stability of system, and formula (3) are substituted into criterion function (4), and makesFrom
Adapt to the control law of heave compensation system are as follows:
Wherein, step factor ρ ∈ (0,1]；u(k)∈Rm, etching system outputs and inputs when y (k) ∈ R respectively indicates k；y*(k+
It 1) is that system expectation tracks signal, γ is a positive weight coefficient；
The criterion function of parameter Estimation are as follows:
It enablesObtain the parameter Estimation equation of pseudo- partial derivative φ (k) are as follows:
Wherein, factor η ∈ (0,2] constant,It is the estimated value of PJM Φ (k)；
IfOrThen
Wherein,It isInitial value.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110376901A (en) * | 2019-08-19 | 2019-10-25 | 哈尔滨工业大学（深圳） | A kind of iterative learning control method based on dynamic controller |
| CN110426954A (en) * | 2019-07-25 | 2019-11-08 | 山东大学 | Deep-sea crane active compensation controller and control system |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100230370A1 (en) * | 2008-05-21 | 2010-09-16 | Klaus Schneider | Crane control with active heave compensation |
| CN104876145A (en) * | 2014-12-19 | 2015-09-02 | 上海交通大学 | Electric active heave compensation winch system |
| CN105227017A (en) * | 2015-10-27 | 2016-01-06 | 青岛远洋船员职业学院 | A kind of method and system for the angle of rake high-order MFAC of boats and ships gondola SSP |
-
2018
- 2018-09-20 CN CN201811097522.2A patent/CN109917643A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20100230370A1 (en) * | 2008-05-21 | 2010-09-16 | Klaus Schneider | Crane control with active heave compensation |
| CN104876145A (en) * | 2014-12-19 | 2015-09-02 | 上海交通大学 | Electric active heave compensation winch system |
| CN105227017A (en) * | 2015-10-27 | 2016-01-06 | 青岛远洋船员职业学院 | A kind of method and system for the angle of rake high-order MFAC of boats and ships gondola SSP |
Non-Patent Citations (11)
| Title |
|---|
| YONGLING FU 等: "The application of co-simulation based on AMESim and Matlab in electro-hydraulic servo system", 《PROCEEDINGS OF 2011 INTERNATIONAL CONFERENCE ON ELECTRONIC & MECHANICAL ENGINEERING AND INFORMATION TECHNOLOGY》 * |
| ZHONGSHENG HOU 等: "The Model-Free Learning Adaptive Control of a Class of Miso Nonlinear Discrete-Time Systems", 《IFAC PROCEEDINGS VOLUMES》 * |
| 何平: "主动式波浪补偿控制***研究", 《中国优秀博硕士学位论文全文数据库（硕士） 信息科技辑》 * |
| 侯忠生 等: "《无模型自适应控制 理论与应用》", 30 June 2013, 科学出版社 * |
| 刘世达: "数据驱动建模与无模型自适应控制及在复杂工业***中的应用", 《中国博士学位论文全文数据库 信息科技辑》 * |
| 叶建: "船舶吊装补给主动式升沉补偿***控制策略研究", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
| 姚文龙 等: "船舶吊舱SSP推进电机的无模型自适应矢量控制方法", 《交通运输工程学报》 * |
| 李世振 等: "主动式水下拖曳升沉补偿***的非线性控制", 《中南大学学报(自然科学版)》 * |
| 武云霞 等: "深水吊装升沉补偿液压***建模与优化", 《中国海洋大学学报》 * |
| 王君婷: "无模型自适应控制的研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 王海波 等: "水下拖曳升沉补偿***的非参数模型自适应控制", 《控制理论与应用》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110426954A (en) * | 2019-07-25 | 2019-11-08 | 山东大学 | Deep-sea crane active compensation controller and control system |
| CN110376901A (en) * | 2019-08-19 | 2019-10-25 | 哈尔滨工业大学（深圳） | A kind of iterative learning control method based on dynamic controller |
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