CN113625727A - Method for controlling ship course system with complex noise based on generalized fuzzy hyperbolic model - Google Patents
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Abstract
The invention provides a method for controlling a ship course system with complex noise based on a generalized fuzzy hyperbolic model, which comprises the following steps: establishing a ship course system motion model with complex noise by combining the ship course system motion characteristic with external random interference; taking the difference value between the actual heading angle of the ship and the expected heading angle as input, and approximating a nonlinear function in the ship heading system motion model by using a generalized fuzzy hyperbolic model to obtain an intelligent fuzzy ship heading control model with complex noise; compensating the rudder angle input limit of the ship; a non-linear vessel heading controller designed to accommodate noise. The method can effectively carry out safe and accurate control on the marine course of the ship.
Description
Technical Field
The invention relates to the technical field of random interference and nonlinear ship course control, in particular to a method for controlling a ship course system with complex noise based on a generalized fuzzy hyperbolic model.
Background
The ship course system control not only plays a role in energy cost and labor intensity of sailers, but also plays an important role in navigation safety of ships. The problems of strong nonlinearity of ship motion and input rudder angle saturation are caused by the characteristics of the ship, such as the change of the loading condition and the navigational speed of the ship, the uncertainty of a ship model, the limited capability of a ship controller and the like. In addition, marine navigation is inevitably affected by the superposition of unpredictable random noises (such as wind, ocean current, tide, etc.) caused by complex sea conditions, which also causes difficulty in the course control of the ship. In a word, the development of the intelligent ship course control puts higher requirements on the accuracy of model description and the accuracy of system control. Therefore, the research of the intelligent ship course control has great difficulty.
The generalized fuzzy hyperbolic tangent model simplifies the structure identification problem of the traditional fuzzy model into the problem of determining the number of corresponding generalized fuzzy variables, so that the identification complexity is greatly reduced, and the number of identification parameters is less. Compared with other fuzzy models, the generalized fuzzy hyperbolic tangent model is more suitable for a nonlinear ship course control system, and a corresponding approximation model can be obtained as long as the ship course angle is known and the relation between the change rate of the course angle and the input rudder angle is known.
Considering that the environmental disturbances suffered by the marine navigation of the ship are various and complicated (such as wind, wave and tide), the complicated disturbances are mixed together, cannot be ignored and considered singly and cannot be predicted, and all the complicated disturbances have strong randomness. The presence of complex noise results in an inaccurate design of the heading system controller.
Disclosure of Invention
According to the technical problem, a method for controlling a ship course system with complex noise based on a generalized fuzzy hyperbolic model is provided. The invention can effectively carry out safe and accurate control on the marine course of the ship.
The technical means adopted by the invention are as follows:
a method for controlling a ship course system with complex noise based on a generalized fuzzy hyperbolic model comprises the following steps:
s1, establishing a ship course system motion model with complex noise by combining the ship course system motion characteristic with external random interference;
s2, taking the difference value between the actual heading angle and the expected heading angle of the ship as input, and approximating a nonlinear function in the ship heading system motion model by using the generalized fuzzy hyperbolic model to obtain an intelligent fuzzy ship heading control model with complex noise;
s3, compensating the rudder angle input limit of the ship;
and S4, designing a nonlinear ship heading controller for accommodating noise.
Further, the implementation process of step S1 is as follows:
s11, acquiring the electronic chart and AIS data;
s12, establishing a ship heading system motion model under the condition of considering the complex noise interference according to the acquired electronic chart and AIS data, wherein the method comprises the following steps:
wherein x is1Is the ship course, x2The speed of the change of the ship course is,
k is the turning performance index (per second) of the ship, T is the following performance index (per second) of the ship, u is the rudder angle input of the ship, and input limitation exists; y represents the system output;
representing the unknown non-linear term that satisfies the condition of lipschitz,
is that
Is approximately expressed as:
is a ship nonlinear coefficient; p (x)2) Is a function that satisfies the condition of lipplitz; xi represents random interference in the course environment and meets the following conditions
N is a constant greater than zero.
Further, the specific implementation process of step S2 is as follows:
s21, performing linear transformation on the input variables by using the generalized fuzzy hyperbolic model to obtain generalized input variables, wherein the generalized input variables are as follows:
x＝[ 1x(t), 2x(t),..., nx(t)]T
wherein the content of the first and second substances, ix＝xz-dzj， ixis given by
wiTo be xzNumber of linear transformations, dzjIs xzA linear transformation point;
s22, approximating the nonlinear term in the ship course control model by using the generalized fuzzy hyperbolic model to obtain the following description:
wherein the content of the first and second substances,
is the approximation error of the generalized fuzzy hyperbolic model,
in order to optimize the parameter vector,
Giobtaining an approximation term according to a generalized fuzzy hyperbolic tangent model;
s23, obtaining an intelligent fuzzy ship course control model based on the generalized fuzzy hyperbolic model and with complex noise, and comprising the following steps:
further, the specific implementation process of step S3 is as follows:
s31, inputting the limited rudder angle u-u of the shipm≤u≤uMWherein, -umAnd uMRespectively representing the minimum value and the maximum value of the known input rudder angle u according to the marine navigation of the ship;
s32, carrying out saturation limitation on the ship rudder angle u with limited input to obtain an input value as follows:
where v represents the control input for which the overall system is designed.
Further, the specific implementation process of step S4 is as follows:
s41, based on the intelligent fuzzy ship course control model, considering a ship rudder angle subjected to saturation limitation, designing a fuzzy self-adaptive update rate as follows:
wherein Z is2Representing an error variable, Z2＝x2-α2，α2For the designed virtual control rate, gamma, rho are design parameters greater than zero;
s42, designing a non-linear ship heading controller for accommodating noise by combining the designed fuzzy self-adaptive update rate, and the following steps:
wherein Z is1，Z2Is an error variable, e is a compensation variable introduced by an auxiliary design system, theta is a fuzzy adaptive update rate,
approximating the resulting state-dependent tangent function matrix according to a generalized fuzzy hyperbolic tangent model, C2For p is an interference function caused by external environment changes,
as derivative of the virtual control rate, K2， C2Are relevant design parameters.
The invention also provides a storage medium which comprises a stored program, wherein when the program runs, the method for controlling the ship heading system with the complex noise based on the generalized fuzzy hyperbolic model is executed.
The invention also provides an electronic device which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor runs and executes the method for controlling the ship course system with the existence of the complex noise based on the generalized fuzzy hyperbolic model through the computer program.
Compared with the prior art, the invention has the following advantages:
1. the invention provides a method for controlling a ship course system with complex noise based on a generalized fuzzy hyperbolic model, which is characterized in that a ship course system motion model with complex noise is established by combining the motion characteristic of the ship course system and external random interference, a nonlinear function in the ship course system motion model is approximated by the generalized fuzzy hyperbolic model, and an intelligent fuzzy ship course control model with complex noise is designed; and compensating the input limit of the rudder angle of the ship, and designing a nonlinear ship course controller for accommodating noise.
2. According to the method for controlling the ship course system with the complex noise based on the generalized fuzzy hyperbolic model, the generalized fuzzy hyperbolic model has fewer identification parameters, so that the complexity of the traditional ship fuzzy model can be simplified. The generalized fuzzy hyperbolic model GFHM is more suitable for processing a ship which is a multivariable nonlinear system with known variables which are difficult to measure and are limited.
Based on the reason, the method can be widely popularized in the fields of random interference, non-linear ship course 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 needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a schematic diagram of an intelligent fuzzy ship course control model with complex noise according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a non-linear ship heading controller according to an embodiment of the invention.
Fig. 4 is a ship course duration curve provided by the embodiment of the present invention.
Fig. 5 is a ship course tracking error duration curve provided by the embodiment of the present invention.
Fig. 6 is a time-course curve of the rudder angle of the ship provided by the embodiment of the invention.
Fig. 7 is a ship turning angle speed duration curve provided by the embodiment of the invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or 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 method for controlling a ship course system with complex noise based on a generalized fuzzy hyperbolic model, which comprises the following steps:
s1, establishing a ship course system motion model with complex noise by combining the ship course system motion characteristic with external random interference;
s2, taking the difference value between the actual heading angle and the expected heading angle of the ship as input, and approximating a nonlinear function in the ship heading system motion model by using the generalized fuzzy hyperbolic model to obtain an intelligent fuzzy ship heading control model with complex noise;
s3, compensating the rudder angle input limit of the ship;
and S4, designing a nonlinear ship heading controller for accommodating noise.
In specific implementation, as a preferred embodiment of the present invention, the implementation process of step S1 is as follows:
s11, acquiring the electronic chart and AIS data; in this embodiment, the electronic chart and the AIS data are acquired through the data acquisition unit, wherein the data acquisition unit includes a satellite positioning system, a shipborne GPS and a shipborne AIS.
S12, establishing a ship heading system motion model under the condition of considering the complex noise interference according to the acquired electronic chart and AIS data, wherein the method comprises the following steps:
wherein x is1Is the ship course, x2The speed of the change of the ship course is,
k is the turning performance index (per second) of the ship, T is the following performance index (per second) of the ship, u is the rudder angle input of the ship, and input limitation exists; y represents the system output;
representing the unknown non-linear term that satisfies the condition of lipschitz,
is that
Is approximately expressed as:
is a ship nonlinear coefficient; p (x)2) Is a function that satisfies the condition of lipplitz; ξ represents random interference in a heading environmentDisturbance, satisfies the following conditions
N is a constant greater than zero. In the present embodiment, considering the complex noise disturbance includes considering the complex noise disturbance existing in the actual navigation environment, such as wind, waves, current, tide, etc.
In specific implementation, as a preferred embodiment of the present invention, the specific implementation process of step S2 is as follows:
s21, performing linear transformation on the input variables by using the generalized fuzzy hyperbolic model to obtain generalized input variables, wherein the generalized input variables are as follows:
x＝[ 1x(t), 2x(t),..., nx(t)]T
wherein the content of the first and second substances, ix＝xz-dzj， ixis given by
wiTo be xzNumber of linear transformations, dzjIs xzA linear transformation point; in the embodiment, the difference between the actual heading angle and the expected heading angle of the ship in the ship compass equipment is collected as input.
S22, approximating the nonlinear term in the ship course control model by using the generalized fuzzy hyperbolic model to obtain the following description:
wherein the content of the first and second substances,
is the approximation error of the generalized fuzzy hyperbolic model,
in order to optimize the parameter vector,
Giobtaining an approximation term according to a generalized fuzzy hyperbolic tangent model;
s23, as shown in FIG. 2, obtaining an intelligent fuzzy ship course control model based on the generalized fuzzy hyperbolic model and with complex noise, as follows:
in specific implementation, as a preferred embodiment of the present invention, the specific implementation process of step S3 is as follows:
s31, inputting the limited rudder angle u-u of the shipm≤u≤uMWherein, -umAnd uMRespectively representing the minimum and maximum values of the known input rudder angle u (the maximum amplitude of the rudder angle of the ship is generally 35 °) according to the marine navigation of the ship;
s32, carrying out saturation limitation on the ship rudder angle u with limited input to obtain an input value as follows:
where v represents the control input for which the overall system is designed. In this embodiment, another embodiment is included, in which the input value obtained through saturation limitation is compared with the output of the "intermediate controller", and the compared error signal is "fed back" to the auxiliary compensation module, so as to cyclically compensate the rudder angle input limitation of the ship.
In specific implementation, as a preferred embodiment of the present invention, the specific implementation process of step S4 is as follows:
s41, based on the intelligent fuzzy ship course control model, considering a ship rudder angle subjected to saturation limitation, designing a fuzzy self-adaptive update rate as follows:
wherein Z is2Representing an error variable, Z2＝x2-α2，α2For the designed virtual control rate, gamma, rho are design parameters greater than zero;
s42, designing a non-linear ship heading controller for accommodating noise as shown in fig. 3 in combination with the designed fuzzy adaptive update rate, as follows:
wherein Z is1，Z2Is an error variable, e is a compensation variable introduced by an auxiliary design system, theta is a fuzzy adaptive update rate,
approximating the resulting state-dependent tangent function matrix according to a generalized fuzzy hyperbolic tangent model, C2For p is an interference function caused by external environment changes,
as derivative of the virtual control rate, K2， C2Are relevant design parameters.
In order to verify the effectiveness of the method, a simulation experiment is carried out, the experimental result is shown in figures 4-7, and the simulation result shows that the algorithm can effectively control the ship course.
The embodiment of the application also discloses a storage medium which comprises a stored program, wherein when the program runs, the method for controlling the ship course system with the complex noise based on the generalized fuzzy hyperbolic model is executed.
The embodiment of the application also discloses an electronic device, which comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor runs and executes the method for controlling the ship course system with the complex noise based on the generalized fuzzy hyperbolic model through the computer program.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (7)
1. A method for controlling a ship course system with complex noise based on a generalized fuzzy hyperbolic model is characterized by comprising the following steps:
s1, establishing a ship course system motion model with complex noise by combining the ship course system motion characteristic with external random interference;
s2, taking the difference value between the actual heading angle and the expected heading angle of the ship as input, and approximating a nonlinear function in the ship heading system motion model by using the generalized fuzzy hyperbolic model to obtain an intelligent fuzzy ship heading control model with complex noise;
s3, compensating the rudder angle input limit of the ship;
and S4, designing a nonlinear ship heading controller for accommodating noise.
2. The method for controlling a ship heading system with complex noise based on the generalized fuzzy hyperbolic model as claimed in claim 1, wherein the step S1 is implemented as follows:
s11, acquiring the electronic chart and AIS data;
s12, establishing a ship heading system motion model under the condition of considering the complex noise interference according to the acquired electronic chart and AIS data, wherein the method comprises the following steps:
wherein x is1Is the ship course, x2The speed of the change of the ship course is,
k is the turning performance index (per second) of the ship, T is the following performance index (per second) of the ship, u is the rudder angle input of the ship, and input limitation exists; y represents the system output;
representing the unknown non-linear term that satisfies the condition of lipschitz,
is that
Is approximately expressed as:
is a ship nonlinear coefficient; p (x)2) Is a function that satisfies the condition of lipplitz; xi represents random interference in the course environment and meets the following conditions
N is a constant greater than zero。
3. The method for controlling the ship heading system with the complex noise based on the generalized fuzzy hyperbolic model as claimed in claim 1, wherein the step S2 is implemented as follows:
s21, performing linear transformation on the input variables by using the generalized fuzzy hyperbolic model to obtain generalized input variables, wherein the generalized input variables are as follows:
x＝[ 1x(t), 2x(t),..., nx(t)]T
wherein the content of the first and second substances, ix＝xz-dzj， ixis given by
wiTo be xzNumber of linear transformations, dzjIs xzA linear transformation point;
s22, approximating the nonlinear term in the ship course control model by using the generalized fuzzy hyperbolic model to obtain the following description:
wherein the content of the first and second substances,
is the approximation error of the generalized fuzzy hyperbolic model,
in order to optimize the parameter vector,
Giobtaining an approximation term according to a generalized fuzzy hyperbolic tangent model;
s23, obtaining an intelligent fuzzy ship course control model based on the generalized fuzzy hyperbolic model and with complex noise, and comprising the following steps:
4. the method for controlling the ship heading system with the complex noise based on the generalized fuzzy hyperbolic model as claimed in claim 1, wherein the step S3 is implemented as follows:
s31, inputting the limited rudder angle u-u of the shipm≤u≤uMWherein, -umAnd uMRespectively representing the minimum value and the maximum value of the known input rudder angle u according to the marine navigation of the ship;
s32, carrying out saturation limitation on the ship rudder angle u with limited input to obtain an input value as follows:
where v represents the control input for which the overall system is designed.
5. The method for controlling the ship heading system with the complex noise based on the generalized fuzzy hyperbolic model as claimed in claim 1, wherein the step S4 is implemented as follows:
s41, based on the intelligent fuzzy ship course control model, considering a ship rudder angle subjected to saturation limitation, designing a fuzzy self-adaptive update rate as follows:
wherein Z is2Indicating errorVariable, Z2＝x2-α2，α2For the designed virtual control rate, gamma, rho are design parameters greater than zero;
s42, designing a non-linear ship heading controller for accommodating noise by combining the designed fuzzy self-adaptive update rate, and the following steps:
wherein Z is1，Z2Is an error variable, e is a compensation variable introduced by an auxiliary design system, theta is a fuzzy adaptive update rate,
a state correlation tangent function matrix obtained by approximation according to a generalized fuzzy hyperbolic tangent model, wherein p is an interference function caused by external environment change,
as derivative of the virtual control rate, K2，C2Are relevant design parameters.
6. A storage medium comprising a stored program, wherein the program when executed performs the method of any one of claims 1 to 5.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the computer program to perform the method of any one of claims 1 to 5.
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