CN113139301B - Ship berthing-leaning backward-pushing controller design method based on generalized noise - Google Patents
Ship berthing-leaning backward-pushing controller design method based on generalized noise Download PDFInfo
- Publication number
- CN113139301B CN113139301B CN202110548231.6A CN202110548231A CN113139301B CN 113139301 B CN113139301 B CN 113139301B CN 202110548231 A CN202110548231 A CN 202110548231A CN 113139301 B CN113139301 B CN 113139301B
- Authority
- CN
- China
- Prior art keywords
- noise
- ship
- berthing
- function
- following
- 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.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 64
- 238000013461 design Methods 0.000 title claims abstract description 17
- 230000008569 process Effects 0.000 claims abstract description 24
- 238000001228 spectrum Methods 0.000 claims abstract description 24
- 230000033001 locomotion Effects 0.000 claims abstract description 20
- 238000013178 mathematical model Methods 0.000 claims abstract description 7
- 230000000750 progressive effect Effects 0.000 claims abstract description 6
- 239000011159 matrix material Substances 0.000 claims description 9
- 238000013016 damping Methods 0.000 claims description 4
- 241000219000 Populus Species 0.000 claims description 3
- 230000006978 adaptation Effects 0.000 claims description 3
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 230000002441 reversible effect Effects 0.000 claims description 3
- 230000011218 segmentation Effects 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 230000003595 spectral effect Effects 0.000 description 9
- 230000000694 effects Effects 0.000 description 5
- 238000011160 research Methods 0.000 description 3
- 238000009826 distribution Methods 0.000 description 2
- 230000001788 irregular Effects 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000005284 excitation Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003534 oscillatory effect Effects 0.000 description 1
- 230000001902 propagating effect Effects 0.000 description 1
- 238000005096 rolling process Methods 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B63—SHIPS OR OTHER WATERBORNE VESSELS; RELATED EQUIPMENT
- B63B—SHIPS OR OTHER WATERBORNE VESSELS; EQUIPMENT FOR SHIPPING
- B63B71/00—Designing vessels; Predicting their performance
- B63B71/10—Designing vessels; Predicting their performance using computer simulation, e.g. finite element method [FEM] or computational fluid dynamics [CFD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/10—Noise analysis or noise optimisation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
Abstract
The invention provides a ship berthing backward pushing controller design method based on generalized noise, which comprises the following steps: introducing generalized noise and constructing a mathematical model of the ship berthing-off system; considering the influence of complex waves on ship berthing motion in berthing process, constructing colored noise which accords with real sea wave conditions, and simulating the fitting condition of the colored noise and white noise on P-M wave spectrums; the assumption and the quotation in the random differential equation frame are quoted to prove whether the ship is stable by the berthing system or not; and a controller of the ship berthing-off control system is pushed out by adopting a backward pushing method, so as to control the ship berthing-off system. In the invention, the uncertainty of the ship leaning and leaving is characterized by adopting generalized noise in the ship leaning and leaving motion, and the influence of the generalized noise on the ship motion control in simulating the real sea wave condition is proved to be stronger than white noise; the mathematical model of the ship berthing-off system is described based on a random differential equation, and the fact that the controller system is stable from noise to state is proved, and the berthing-off model has probability progressive gain.
Description
Technical Field
The invention relates to the technical field of ship automatic control, in particular to a design method of a ship berthing-off push-back controller based on generalized noise.
Background
The berthing of ships is a high-risk and high-precision production activity. When a ship is sailing at sea, it is disturbed by complex sea environments (wind, waves and currents). The environmental conditions are quite complex: one is a largely oscillatory motion and the other is a random feature of wave forces. The complex marine environment is mainly affected by waves. As an irregular wave, a wave at sea is extremely complex, propagating not only in one direction, but also in other directions due to the random nature and variability of the wave. Therefore, it is very necessary to consider the marine environment when studying the movement of the ship against the berthing. To reduce the wave effect on the berthing motion, many scholars have adopted more accurate control algorithms. In these studies, the norm-bounded term and uncertainty term of the disturbance are mostly considered, without regard to the randomness of the wave disturbance. However, the state of the marine environment is constantly changing in the actual process. The vessel motion must have serious uncertainty. The wave-induced disturbances have random characteristics. Research on vessel motions without random disturbances is inaccurate.
On the other hand, irregular changes in sea waves lead to very difficult accurate grasping of the sea wave model. The actual sea wave has a limited spectral width and a given spectral density function, called colored noise. The wave external load calendar is a colored noise sequence meeting a certain wave spectrum, and the colored noise sequence is generated, and the wave external load calendar can reflect the wave spectrum characteristics of the actual wave although a certain difference exists in a low-frequency part. Many documents study the effect on the motion of a ship when white noise is used as external excitation. White noise can actually be considered to represent a spectrum of waves, but is an ideal spectrum of waves, which is not present in reality. This is mainly due to the fact that the actual sea wave is a colored noise sequence satisfying a certain spectral distribution instead of a white noise sequence. Not all forms of spectrum may be represented as white noise output after passing through a shape filter. The probability distribution results of white noise and colored noise are obviously different under the condition that the spectral energy is close. According to the white noise calculation result, the probability peak value is far lower than the colored noise, and according to the white noise result, even when the rolling amplitude reaches 1rad, the probability is still high, and the probability is greatly deviated from the actual test result, so that the research of waves by using colored noise to describe waves compared with white noise to describe waves has important significance on ship motion control.
Disclosure of Invention
According to the technical problem that noise interference generated by the marine environment is colored noise instead of white noise, the design method of the ship berthing backward pushing controller based on generalized noise is provided. The invention mainly researches the influence of generalized noise disturbance on ship motion control in complex sea wave environment.
The invention adopts the following technical means:
a design method of a ship berthing-off backward-pushing controller based on generalized noise comprises the following steps:
s1, introducing generalized noise, and constructing a mathematical model of a ship berthing system;
s2, considering the influence of complex waves on ship berthing motion in berthing process, constructing colored noise which accords with real sea wave conditions, and simulating the fitting condition of the colored noise and white noise on P-M wave spectrums;
s3, referring to assumptions and theories in a random differential equation frame to prove whether the ship is stable by the berthing system;
and S4, pushing out a controller of the ship berthing-off control system by adopting a back pushing method, and controlling the ship berthing-off system.
Further, the specific implementation process of the step S1 is as follows:
s11, establishing a ship berthing model without noise, wherein the ship berthing model without noise is as follows:
wherein,representing the position of the ship, consisting of the ship's spatial position X, Y and heading angle->Composition; v= [ u, v, r] T Representing the longitudinal directionThree degrees of freedom of motion speed of swinging, swaying and bow swaying,>representing a conversion matrix, M representing an inertial dynamics parameter matrix, consisting of hydrodynamic additional inertia and ship weight inertia, D representing a damping matrix, and τ representing design control force;
s12, adding noise disturbance based on the built ship berthing-off model to obtain:
where ζ represents a random process.
Further, the specific implementation process of the step S2 is as follows:
s21, assuming complex waves are a random process, according to wave theory, long peak waves are overlapped with cosine waves with different amplitudes and cosine waves with different wavelengths, and the long peak waves are expressed by the following formula:
wherein a is i 、k i 、w i And theta i Respectively representing the amplitude, the number of waves, the angular frequency and the initial phase of the ith wave;
s22, adopting a P-M spectrum, and expressing a spectrum density function of the wave as follows:
wherein a=8.1×10 -3 g 2 ,Representing significant wave heights corresponding to different wave conditions; w represents the angular frequency of the wave;
s23, fitting the simulated colored noise spectrum density with a standard P-M spectrum, wherein the colored noise spectrum density is as follows:
further, the specific implementation process of the step S3 is as follows:
s31, adding the formulaAnd (3) deforming to obtain the following components:
the marine berthing system is adjusted to the following form:
wherein,
s32, definitionThen the formulaThe method is characterized by comprising the following steps of:
s33, analyzing the disturbance intensity generated by wind, waves and flow, and making the following assumption:
a1 procedure ζ (t) is f t Adaptation and segmentation are continuous, so there is a constant K>0，
A2 functionAnd->Is indirectly continuous at t, at +.>Meets the Lipuschia condition at willThere is a constant l that depends on q q And k 0 > 0 satisfies the following equation:
||G 1 (0,t)||+||G 2 (0,t)||＜k 0
s34, according to the assumption A2, proving the function G 1 ，G 2 Meets the condition of Lipuschin:
the same proves that:
the two functions are bounded and meet the lipzetz condition;
s35, under the assumption of A1 and A2, a parameter d > 0 and a function V epsilon C exist 1 And a K-infinity functionα，And a class K function α satisfies the following inequality:
the system has a unique global solution ifIs a convex function, the system stabilizes NSS-P on a probabilistic noise-to-state basis, and the state of the system is a probabilistic progressive gain.
Further, in the proving process in the step S3, two quotients are further included:
lemma 1: let λ.gtoreq.0 be a constant, r (t) be a non-negative piecewise continuous function of t, if the function s (t) satisfies the inequality:then satisfy->
And (4) lemma 2: allow function s (t) for t.gtoreq.t 0 Is absolutely continuous and allows its derivative content to be inequality:
for all t.gtoreq.t 0 Wherein r (t) and c (t) are functions that are continuously integrable everywhere over each finite interval, at t.gtoreq.t 0 At the time, there are
Further, before the step S35, the method further includes defining noise to state stability and mean square asymptotic gain as follows:
definition 1 if for any ε > 0, there is a K-class function γ (-), for anyThe method meets the following conditions:
the state of the system is a probabilistic progressive gain AG-P;
definition 2: if there is one KL class function β (·,) and one K class function γ (·) for any ε > 0, then for all t ε [ t ] 0 Infinity) and a K-class function gamma (,), then for all t ε [ t ] 0 Infinity), andthe following inequality is satisfied:
further, the implementation process of the step S4 is as follows:
s41, designing a constant value required by the convergence of a controller according to the theorem 1, M and D which are positive and reversible, and defining error variables as follows:
z 1 ＝η-η d
wherein eta d Represents the reference signal, eta d ＝[X d ,Y d ,Z d ],α 1 Representing a designed stable control function;
s42, selecting a Lyapunov function as follows:
wherein alpha is 1 Selected as:
s43, selecting a second Lyapunov function as:
according to the poplar inequality transformation, the following steps are obtained:
s44, the formulaCarry formula->The method comprises the following steps:
s45, making the control rate tau be:
s46, bringing the formula of the control rate tau into the formula obtained in the step S44, wherein the formula is as follows:
further obtainWhere c=2 min { c 1 ,c 2 }，/>The tracking error satisfies the following inequality:
compared with the prior art, the invention has the following advantages:
1. in a practical marine environment, the ship is mainly affected by complex clutter, and the interference can be described by generalized noise. In marine motion control, it was first proposed that the color noise may contain complex clutter, and that the mixed description of color noise and white noise is more reasonable than describing only white noise or standard bounded and uncertainty terms.
2. Under the wider constraint condition, a random nonlinear back-push controller with colored noise in complex clutter is designed. Noise-to-state stability is analyzed, and asymptotic gain of probability of the mathematical model of the berthing motion is analyzed.
Based on the reasons, the invention can be widely popularized in the fields of ship automatic control and the like.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to the drawings without inventive effort to a person skilled in the art.
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a block diagram of a push-back controller according to the present invention.
FIG. 3 is a graph showing the P-M spectral density function provided by an embodiment of the present invention.
Fig. 4 is a graph showing the spectral density function of colored noise provided by an embodiment of the present invention.
Fig. 5 is a graph showing a white noise spectral density function provided by an embodiment of the present invention.
Fig. 6 shows the position of the ship in the X direction according to the embodiment of the present invention.
Fig. 7 shows a ship Y-direction position according to an embodiment of the present invention.
FIG. 8 is a view of a ship heading angle provided by an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
As shown in fig. 1, the invention provides a design method of a ship berthing backward pushing controller based on generalized noise, which comprises the following steps:
s1, introducing generalized noise, and constructing a mathematical model of a ship berthing system;
in specific implementation, as a preferred embodiment of the present invention, the specific implementation procedure of the step S1 is as follows:
s11, establishing a ship berthing model without noise, wherein the ship berthing model without noise is as follows:
wherein,representing the position of the ship, consisting of the ship's spatial position X, Y and heading angle->Composition; v= [ u, v, r] T Representing the three degrees of freedom of motion speed of heave, heave and yaw, < ->Representing a conversion matrix, M representing an inertial dynamics parameter matrix, consisting of hydrodynamic additional inertia and ship weight inertia, D representing a damping matrix, and τ representing design control force;
s12, adding noise disturbance based on the built ship berthing-off model to obtain:
where ζ represents a random process.
S2, considering the influence of complex waves on ship berthing motion in berthing process, constructing colored noise which accords with real sea wave conditions, and simulating the fitting condition of the colored noise and white noise on P-M wave spectrums;
in specific implementation, as a preferred embodiment of the present invention, the specific implementation procedure of the step S2 is as follows:
s21, assuming complex waves are a random process, according to wave theory, long peak waves are overlapped with cosine waves with different amplitudes and cosine waves with different wavelengths, and the long peak waves are expressed by the following formula:
wherein a is i 、k i 、w i And theta i Respectively representing the amplitude, the number of waves, the angular frequency and the initial phase of the ith wave;
s22, adopting a P-M spectrum, and expressing a spectrum density function of the wave as follows:
wherein a=8.1×10 -3 g 2 ,Representing significant wave heights corresponding to different wave conditions; w represents the angular frequency of the wave;
s23, fitting the simulated colored noise spectrum density with a standard P-M spectrum, wherein the colored noise spectrum density is as follows:
the colored noise, white noise, and P-M spectral density functions are shown in fig. 3-5.
S3, referring to assumptions and theories in a random differential equation frame to prove whether the ship is stable by the berthing system;
in specific implementation, as a preferred embodiment of the present invention, the specific implementation procedure of the step S3 is as follows:
s31, adding the formulaAnd (3) deforming to obtain the following components:
the marine berthing system is adjusted to the following form:
wherein,
s32, definitionThen the formulaThe method is characterized by comprising the following steps of:
s33, analyzing the disturbance intensity generated by wind, waves and flow, and making the following assumption:
a1 procedure ζ (t) is f t Adaptation and segmentation are continuous, so there is a constant K>0，
A2 functionAnd->Is indirectly continuous at t, at +.>Meets the Lipuschia condition at willThere is a constant l that depends on q q And k 0 > 0 satisfies the following equation:
||G 1 (0,t)||+||G 2 (0,t)||＜k 0
s34, according to the assumption A2, proving the function G 1 ，G 2 Meets the condition of Lipuschin:
the same proves that:
the two functions are bounded and meet the lipzetz condition;
s35, under the assumption of A1 and A2, a parameter d > 0 and a function V epsilon C exist 1 And a K-infinity functionα，And a class K function α satisfies the following inequality:
the system has a unique global solution ifIs a convex function, the system stabilizes NSS-P on a probabilistic noise-to-state basis, and the state of the system is a probabilistic progressive gain.
In specific implementation, as a preferred embodiment of the present invention, in the proving process in step S3, two quotients are further included:
lemma 1: let λ.gtoreq.0 be a constant, r (t) be a non-negative piecewise continuous function of t, if the function s (t) satisfies the inequality:then satisfy->
And (4) lemma 2: allow function s (t) for t.gtoreq.t 0 Is absolutely continuous and allows its derivative content to be inequality:
for all t.gtoreq.t 0 Wherein r (t) and c (t) are functions that are continuously integrable everywhere over each finite interval, at t.gtoreq.t 0 At the time, there are
In specific implementation, as a preferred embodiment of the present invention, before the step S35, the method further includes defining the noise to state stability and the mean square asymptotic gain as follows:
definition 1 if for any ε > 0, there is a K-class function γ (-), for anyThe method meets the following conditions:
the state of the system is a probabilistic progressive gain AG-P;
definition 2: if there is one KL class function β (·,) and one K class function γ (·) for any ε > 0, then for all t ε [ t ] 0 Infinity) and a K-class function gamma (,), then for all t ε [ t ] 0 Infinity), andsatisfy the following requirementsThe following inequality:
and S4, pushing out a controller of the ship berthing-off control system by adopting a back pushing method, and controlling the ship berthing-off system.
In specific implementation, as a preferred embodiment of the present invention, the implementation procedure of the step S4 is as follows:
s41, designing a constant value required by the convergence of a controller according to the theorem 1, M and D which are positive and reversible, and defining error variables as follows:
z 1 ＝η-η d
wherein eta d Represents the reference signal, eta d ＝[X d ,Y d ,Z d ],α 1 Representing a designed stable control function;
s42, selecting a Lyapunov function as follows:
wherein alpha is 1 Selected as:
s43, selecting a second Lyapunov function as:
according to the poplar inequality transformation, the following steps are obtained:
s44, the formulaCarry formula->The method comprises the following steps:
s45, making the control rate tau be:
s46, bringing the formula of the control rate tau into the formula obtained in the step S44, wherein the formula is as follows:
further obtainWhere c=2 min { c 1 ,c 2 }，/>The tracking error satisfies the following inequality:
examples
The following further describes the scheme and effects of the present invention through specific application examples.
It is known that: mathematical model parameter of ship motion control nonlinear systemThe initial position of the ship is eta= [0m 0 mg 0deg ]] T The reference signal is eta d ＝[15m 10m 5deg] T The sampling time was 100s.
The reference signal model is selected according to the actual situation:
η r is a vector of the berthing position of the vessel. The natural frequency ρ is designated as 0.05 and the damping ratio σ is designated as 0.9.
Colored noise sequence:
where N (t) is a white noise sequence with a power spectral density of 1, the parameter values α=0.4, β= 0.4474, γ= 0.1964, and example simulation results are shown in fig. 5-8. It can be seen that the controller designed based on the push-back method has good control effect.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (7)
1. The design method of the ship berthing back-pushing controller based on generalized noise is characterized by comprising the following steps of:
s1, introducing generalized noise, and constructing a mathematical model of a ship berthing system;
s2, considering the influence of complex waves on ship berthing motion in berthing process, constructing colored noise which accords with real sea wave conditions, and simulating the fitting condition of the colored noise and white noise on P-M wave spectrums;
s3, referring to assumptions and theories in a random differential equation frame to prove whether the ship is stable by the berthing system;
and S4, pushing out a controller of the ship berthing-off control system by adopting a back pushing method, and controlling the ship berthing-off system.
2. The design method of the ship berthing backward pushing controller based on generalized noise according to claim 1, wherein the specific implementation process of the step S1 is as follows:
s11, establishing a ship berthing model without noise, wherein the ship berthing model without noise is as follows:
wherein,representing the position of the ship, consisting of the ship's spatial position X, Y and heading angle->Composition; v= [ u, v, r] T Representing the three degrees of freedom of motion speed of heave, heave and yaw, < ->Representing a conversion matrix, M representing an inertial dynamics parameter matrix, consisting of hydrodynamic additional inertia and ship weight inertia, D representing a damping matrix, and τ representing design control force;
s12, adding noise disturbance based on the built ship berthing-off model to obtain:
where ζ represents a random process.
3. The design method of the ship berthing backward pushing controller based on generalized noise according to claim 1, wherein the specific implementation process of the step S2 is as follows:
s21, assuming complex waves are a random process, according to wave theory, long peak waves are overlapped with cosine waves with different amplitudes and cosine waves with different wavelengths, and the long peak waves are expressed by the following formula:
wherein a is i 、k i 、w i And theta i Respectively representing the amplitude, the number of waves, the angular frequency and the initial phase of the ith wave;
s22, adopting a P-M spectrum, and expressing a spectrum density function of the wave as follows:
wherein a=8.1×10 -3 g 2 , Representing significant wave heights corresponding to different wave conditions; w represents the angular frequency of the wave;
s23, fitting the simulated colored noise spectrum density with a standard P-M spectrum, wherein the colored noise spectrum density is as follows:
4. the design method of the ship berthing backward pushing controller based on generalized noise according to claim 1, wherein the specific implementation process of the step S3 is as follows:
s31, adding the formulaAnd (3) deforming to obtain the following components:
the marine berthing system is adjusted to the following form:
wherein,
s32, definitionThen the formulaThe method is characterized by comprising the following steps of:
s33, analyzing the disturbance intensity generated by wind, waves and flow, and making the following assumption:
a1 procedure ζ (t) is f t Adaptation and segmentation are continuous, so there is a constant K>0，
A2 functionAnd->Is indirectly continuous at t, at +.>Meets the Lipuschia condition at willThere is a constant l that depends on q q And k 0 > 0 satisfies the following equation:
||G 1 (0,t)||+||G 2 (0,t)||＜k 0
s34, according to the assumption A2, proving the function G 1 ，G 2 Meets the condition of Lipuschin:
the same proves that:
the two functions are bounded and meet the lipzetz condition;
s35, under the assumption of A1 and A2, a parameter d > 0 and a function V epsilon C exist 1 And a K-infinity functionα，And a class K function α satisfies the following inequality:
the system has a unique global solution ifIs a convex function, the system stabilizes NSS-P based on probability noise to state, and the state of the system is a gradual probabilityGain is entered.
5. The design method of the generalized noise-based marine berthing backward thrust controller according to claim 4, wherein the proving process in the step S3 further comprises two quotients:
lemma 1: let λ.gtoreq.0 be a constant, r (t) be a non-negative piecewise continuous function of t, if the function s (t) satisfies the inequality:
then satisfy->
And (4) lemma 2: allow function s (t) for t.gtoreq.t 0 Is absolutely continuous and allows its derivative content to be inequality:
for all t.gtoreq.t 0 Wherein r (t) and c (t) are functions that are continuously integrable everywhere over each finite interval, at t.gtoreq.t 0 At the time, there are
6. The generalized noise based marine berthing back-push controller design method of claim 4, further comprising, prior to said step S35, giving a definition of noise-to-state stability and mean square asymptotic gain, as follows:
definition 1 if for any ε > 0, there is a K-class function γ (-), for anyThe method meets the following conditions:
the state of the system is a probabilistic progressive gain AG-P;
definition 2: if there is one KL class function β (·,) and one K class function γ (·) for any ε > 0, then for all t ε [ t ] 0 Infinity) and a K-class function gamma (,), then for all t ε [ t ] 0 Infinity), andthe following inequality is satisfied:
7. the design method of the ship berthing backward pushing controller based on generalized noise according to claim 1, wherein the implementation process of the step S4 is as follows:
s41, designing a constant value required by the convergence of a controller according to the theorem 1, M and D which are positive and reversible, and defining error variables as follows:
z 1 ＝η-η d
wherein eta d Represents the reference signal, eta d ＝[X d ,Y d ,Z d ],α 1 Representing a designed stable control function;
s42, selecting a Lyapunov function as follows:
wherein alpha is 1 Selected as:
s43, selecting a second Lyapunov function as:
according to the poplar inequality transformation, the following steps are obtained:
s44, the formulaCarry formula->The method comprises the following steps:
s45, making the control rate tau be:
s46, bringing the formula of the control rate tau into the formula obtained in the step S44, wherein the formula is as follows:
further obtainWhere c=2 min { c 1 ,c 2 }，/>The tracking error satisfies the following inequality:
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110548231.6A CN113139301B (en) | 2021-05-19 | 2021-05-19 | Ship berthing-leaning backward-pushing controller design method based on generalized noise |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110548231.6A CN113139301B (en) | 2021-05-19 | 2021-05-19 | Ship berthing-leaning backward-pushing controller design method based on generalized noise |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113139301A CN113139301A (en) | 2021-07-20 |
| CN113139301B true CN113139301B (en) | 2024-03-15 |
Family
ID=76818061
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110548231.6A Active CN113139301B (en) | 2021-05-19 | 2021-05-19 | Ship berthing-leaning backward-pushing controller design method based on generalized noise |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113139301B (en) |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109739238A (en) * | 2019-01-16 | 2019-05-10 | 大连海事大学 | A kind of ship automatic berthing system and its working method |
| CN111199095A (en) * | 2019-12-24 | 2020-05-26 | 青岛科技大学 | Intelligent ship berthing-alongside algorithm test environment construction method based on three-dimensional simulation |
| CN111469983A (en) * | 2020-04-20 | 2020-07-31 | 上海船舶研究设计院（中国船舶工业集团公司第六0四研究院） | Intelligent ship berthing and departing method, device and system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ES2408155T3 (en) * | 2003-12-01 | 2013-06-18 | Rolls-Royce Naval Marine, Inc. | Control of a water-propelled ship |
-
2021
- 2021-05-19 CN CN202110548231.6A patent/CN113139301B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109739238A (en) * | 2019-01-16 | 2019-05-10 | 大连海事大学 | A kind of ship automatic berthing system and its working method |
| CN111199095A (en) * | 2019-12-24 | 2020-05-26 | 青岛科技大学 | Intelligent ship berthing-alongside algorithm test environment construction method based on three-dimensional simulation |
| CN111469983A (en) * | 2020-04-20 | 2020-07-31 | 上海船舶研究设计院（中国船舶工业集团公司第六0四研究院） | Intelligent ship berthing and departing method, device and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113139301A (en) | 2021-07-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Qian et al. | Adaptive repetitive learning control for an offshore boom crane | |
| Zhang et al. | Ship motion attitude prediction based on an adaptive dynamic particle swarm optimization algorithm and bidirectional LSTM neural network | |
| CN109917657B (en) | Anti-interference control method and device for dynamic positioning ship and electronic equipment | |
| CN107065569B (en) | Ship dynamic positioning sliding mode control system and method based on RBF neural network compensation | |
| Wang et al. | Dynamic tanker steering control using generalized ellipsoidal-basis-function-based fuzzy neural networks | |
| Fortuna et al. | A roll stabilization system for a monohull ship: modeling, identification, and adaptive control | |
| Liao et al. | Linear non-causal optimal control of an attenuator type wave energy converter m4 | |
| Jahromi et al. | Long term prediction of tidal currents | |
| CN109460874A (en) | A kind of ariyoshi wave height prediction technique based on deep learning | |
| CN113687597B (en) | Unmanned ship path tracking method based on second-order wave drift force | |
| CN113139301B (en) | Ship berthing-leaning backward-pushing controller design method based on generalized noise | |
| Zhong et al. | USV path following controller based on DDPG with composite state-space and dynamic reward function | |
| Wang et al. | Output-feedback control for cooperative diving of saucer-type underwater gliders based on a fuzzy observer and event-triggered communication | |
| Kim et al. | Fully Coupled Response Simulations of Theme Offshore Structures. in Water Depths of Up to 10,000 Feet | |
| Zhang et al. | Explicit stochastic model predictive control for anti-pitching a high-speed multihull | |
| Lin et al. | An improved autoregressive method with kalman filtering theory for vessel motion predication | |
| Ma | Machine learning in ocean applications: wave prediction for advanced controls of renewable energy and modeling nonlinear viscous hydrodynamics | |
| CN111797474A (en) | Method, device and medium for establishing and predicting ship dynamic stability performance prediction model | |
| Jordán et al. | Optimal identification of potential-radiation hydrodynamics for moored floating structures—a new general approach in state space | |
| CN114114905B (en) | Optimal tracking control method for data-driven carrier-based rocket launcher launching device | |
| Deryabin et al. | A vessel’s dead reckoning position estimation by using of neural networks | |
| Wang et al. | Nonsingular fast terminal sliding mode-based robust adaptive structural reliable position-mooring control with uncertainty estimation | |
| Fan et al. | Ship longitudinal stabilization control based on CGSA and nonlinear switch modification | |
| Fu et al. | Modeling and controlling of engineering ship based on genetic algorithm | |
| Liu et al. | Improving deterministic pitch motions estimation using bivariate sequential wave input |
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 |