Overdrive AUV (Autonomous Underwater Vehicle) hybrid course control method based on self-adaptive fuzzy controller

Abstract

The invention discloses an overdrive AUV hybrid course control method based on an adaptive fuzzy controller, and belongs to the technical field of autonomous underwater vehicles. The method comprises the following steps: acquiring an expected course and an actual course of the AUV, and calculating a course error of the AUV; inputting the course error into a differentiator to obtain course error differential; the course error and course error differential are input into an adaptive fuzzy controller to obtain an accurate rudder angle control signal and an accurate side thrust control signal, the accurate rudder angle control signal and the accurate side thrust control signal are input into an adaptive switching factor module, the proportion of the rudder angle and the side thrust in the total control force is adjusted in an adaptive mode, and the total control force is obtained. And obtaining a rudder angle signal and a side thrust signal, and hybrid-driving the AUV to operate based on the rudder angle signal and the side thrust signal. According to the method, different control forces of the AUV can be adaptively adjusted at different navigational speeds, the flutter phenomenon of the AUV during normal navigation and working condition switching is relieved, and the stability of the AUV during navigation is improved.

Description

Technical Field

[0001] The present application belongs to the technical field of autonomous underwater vehicles, and in particular to a hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller. Background Art

[0002] As a new type of underwater robot, the overdriven AUV (Autonomous Underwater Vehicle) possesses hovering capabilities and can perform complex tasks at zero or low speeds. Overdriven AUVs utilize additional auxiliary thrusters, which provide additional control force and enable precise maneuvers at low speeds. However, as AUVs become increasingly complex, frequent switching of drive modes is required, which can easily lead to navigation flutter. Therefore, optimizing the navigation control strategy of overdriven AUVs and mitigating stability issues caused by switching drive modes has become a core research topic.

[0003] Overdriven AUVs need to adopt different heading control strategies in different situations. Usually, rudder blades are suitable for use in high-speed travel because they are both energy-saving and effective in this speed range. However, when hovering at low speeds, the rudder control surface loses its function due to the reduced efficiency of the rudder blades. In addition, when dealing with large heading errors, the rudder blades alone cannot make the vehicle turn quickly. In order to quickly adjust the AUV heading, horizontal thrusters are required to provide additional force. Existing overdriven AUVs mainly adopt the design of rudder-propeller combined control, but there are still some defects in its stability and transition control at different speeds, especially when transitioning from high speed to low speed, it is easy to cause navigation flutter. Overdriven AUVs have poor stability when switching drive modes, which easily causes navigation flutter. Summary of the Invention

[0004] This application aims to solve at least one of the technical problems existing in the prior art. To this end, this application proposes a hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller. The method can adaptively adjust the magnitude of different control forces at different speeds, thereby alleviating the flutter phenomenon during the AUV's navigation and improving the AUV's stability during navigation.

[0005] In a first aspect, the present application provides a hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller, the method comprising:

[0006] Obtaining a desired heading and an actual heading of the AUV, and calculating a heading error of the AUV based on the desired heading and the actual heading;

[0007] Inputting the heading error into a differentiator to obtain a heading error differential;

[0008] Inputting the heading error and the heading error differential into an adaptive fuzzy controller to obtain an accurate rudder angle control signal and an accurate thrust control signal, the adaptive fuzzy controller comprising a telescoping factor module, a rudder angle fuzzification module, a thrust fuzzification module, a rudder angle clarity module, and a thrust clarity module, the telescoping factor module comprising a rudder angle telescoping factor and a thrust telescoping factor, the rudder angle fuzzification module comprising a rudder angle rule base module and a rudder angle inference engine module, and the thrust fuzzification module comprising a thrust rule base module and a thrust inference engine module;

[0009] Inputting the precise rudder angle control signal and the precise thrust control signal into an adaptive switching factor module, adaptively adjusting the ratio of the rudder angle and the thrust in the total control force, and obtaining a rudder angle signal and a thrust signal, wherein the adaptive switching factor module includes a rudder angle switching factor function and a thrust switching factor function, and the rudder angle switching factor function and the thrust switching factor function are mutually correlated;

[0010] Based on the rudder angle signal and the lateral thrust signal, the hybrid drive AUV operates.

[0011] According to one embodiment of the present application, inputting the heading error and the heading error differential into an adaptive fuzzy controller to obtain a precise rudder angle control signal and a precise side thrust control signal includes:

[0012] Inputting the heading error and the heading error differential into a scaling factor module to obtain a refined error set, wherein the refined error set includes a first error and a second error;

[0013] Inputting the first error and the second error into a rudder angle fuzzification module and a thrust fuzzification module respectively to obtain a fuzzy rudder angle control signal and a fuzzy thrust control signal;

[0014] The fuzzy rudder angle control signal and the fuzzy side thrust control signal are respectively input into the rudder angle clarification module and the side thrust clarification module to obtain a precise rudder angle control signal and a precise side thrust control signal.

[0015] According to one embodiment of the present application, the calculation formula of the first error is as follows:

[0016] τ1=α1ψ e

[0017] Among them, τ1 is the first error, α1 is the rudder angle expansion factor, ψ e is the heading error;

[0018] The calculation formula of the second error is as follows:

[0019]

[0020] Among them, τ2 is the second error, α2 is the side thrust expansion factor, is the heading error differential.

[0021] According to one embodiment of the present application, inputting the first error and the second error into a rudder angle fuzzification module and a thrust fuzzification module respectively to obtain a fuzzy rudder angle control signal and a fuzzy thrust control signal includes:

[0022] The first error is input into the rudder angle fuzzification module, and after the rudder angle rule base module and the rudder angle inference engine module make inference decisions, a fuzzy rudder angle control signal is obtained;

[0023] The second error is input into the thrust fuzzification module, and after the thrust rule base module and the thrust inference engine module make inference decisions, a fuzzy thrust control signal is obtained.

[0024] According to one embodiment of the present application, the first error is input into the rudder angle fuzzification module, and after the rudder angle rule base module and the rudder angle inference engine module perform reasoning and decision making, a fuzzy rudder angle control signal is obtained, including:

[0025] Inputting the first error into a triangular fuzzifier, mapping it to a membership value of a fuzzy set through a triangular membership function, and obtaining a first fuzzy set membership;

[0026] The first fuzzy set membership is input into the rudder angle rule base module and the rudder angle inference engine module. After using the first rule base for rule matching and reasoning decision-making, a fuzzy rudder angle control signal is obtained. The first rule base includes multiple IF-THEN statements.

[0027] According to one embodiment of the present application, the step of inputting the second error into the thrust fuzzification module, and obtaining the fuzzy thrust control signal after the thrust rule base module and the thrust inference engine module make inference decisions includes:

[0028] Inputting the second error into the triangular fuzzifier, mapping it to the membership value of the fuzzy set through the triangular membership function, and obtaining the second fuzzy set membership;

[0029] The second fuzzy set membership is input into the thrust rule base module and the thrust inference engine module, and the fuzzy thrust control signal is obtained after rule matching and reasoning decision-making using the second rule base. The second rule base includes multiple IF-THEN statements.

[0030] According to one embodiment of the present application, the calculation formula of the heading error is as follows:

[0031] ψ e =ψ d -ψ t

[0032] Among them, ψ d is the desired heading, ψ t is the actual heading, ψ e is the heading error.

[0033] In a second aspect, the present application provides an overdriven AUV hybrid heading control device based on an adaptive fuzzy controller, the device comprising:

[0034] An acquisition module is used to obtain a desired heading and an actual heading of the AUV, and calculate a heading error of the AUV based on the desired heading and the actual heading;

[0035] A first processing module, configured to input the heading error into a differentiator to obtain a heading error differential;

[0036] a second processing module, configured to input the heading error and the heading error differential into an adaptive fuzzy controller to obtain a precise rudder angle control signal and a precise thrust control signal, the adaptive fuzzy controller comprising a telescoping factor module, a rudder angle fuzzification module, a thrust fuzzification module, a rudder angle clarity module, and a thrust clarity module; the telescoping factor module comprising a rudder angle telescoping factor and a thrust telescoping factor; the rudder angle fuzzification module comprising a rudder angle rule base module and a rudder angle inference engine module; and the thrust fuzzification module comprising a thrust rule base module and a thrust inference engine module;

[0037] a third processing module, configured to input the precise rudder angle control signal and the precise thrust control signal into an adaptive switching factor module, adaptively adjust the ratio of the rudder angle and the thrust in the total control force, and obtain a rudder angle signal and a thrust signal, wherein the adaptive switching factor module includes a rudder angle switching factor function and a thrust switching factor function, and the rudder angle switching factor function and the thrust switching factor function are mutually correlated;

[0038] The driving module is used for hybrid driving the AUV based on the rudder angle signal and the lateral thrust signal.

[0039] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the overdriven AUV hybrid heading control method based on the adaptive fuzzy controller as described in the first aspect above is implemented.

[0040] In a fourth aspect, the present application provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller as described in the first aspect above.

[0041] In a fifth aspect, the present application provides a chip, which includes a processor and a communication interface, wherein the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the overdriven AUV hybrid heading control method based on the adaptive fuzzy controller as described in the first aspect.

[0042] In a sixth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements the hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller as described in the first aspect above.

[0043] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become obvious from the description below, or will be learned through practice of the present application.

[0044] The hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller provided by the present invention has the following beneficial effects compared with the prior art:

[0045] (1) The present invention calculates the heading error and its differential and inputs them into an adaptive fuzzy controller for processing. Combining the heading error, error differential and its control rules, the present invention outputs accurate rudder angle and side thrust control signals, which can act on different actuators, thereby achieving stable operation of the AUV at different speeds. Through the control force distribution strategy based on the switching factor, the size of different control forces can be adaptively adjusted at different speeds, thereby alleviating the AUV navigation flutter phenomenon caused by changes in the driving mode and improving the heading control accuracy.

[0046] (2) The present invention changes the heading error and the heading error differential by a scaling factor respectively to obtain a first error and a second error, and converts them into fuzzy signals. An inference module is used to make inference decisions on the fuzzy rudder angle control signal and the fuzzy side thrust control signal to generate a fuzzy rudder angle control signal set and a fuzzy side thrust control signal set. Finally, accurate control signals are obtained through clarification processing, which effectively enhances the control accuracy of the rudder angle and side thrust, reduces the deviation caused by the heading error, enables the AUV to adaptively adjust the size of different control forces at different speeds, alleviates the AUV navigation flutter phenomenon caused by the change of the driving mode, and reduces the potential navigation risk.

[0047] (3) The present invention introduces the rudder angle expansion factor and the side thrust expansion factor to perform weighted calculation on the heading error and the heading error differential, thereby obtaining the first error and the second error. This can better adapt to the needs of different heading changes of the AUV, reduce the accumulation of heading errors, and improve the accuracy and stability of the AUV heading control. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0049] Figure 1 This is one of the flow charts of the hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller provided in an embodiment of the present application;

[0050] Figure 2 is a schematic structural diagram of a side view of an autonomous underwater vehicle provided in an embodiment of the present application;

[0051] Figure 3 This is the second flow chart of the hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller provided in an embodiment of the present application;

[0052] Figure 4 Schematic diagram of the structure of an overdriven AUV hybrid heading control device based on an adaptive fuzzy controller provided in an embodiment of the present application;

[0053] Figure 5 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0054] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0055] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0056] The following, in conjunction with the accompanying drawings, describes in detail the hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller, the hybrid heading control device for an overdriven AUV based on an adaptive fuzzy controller, the electronic device, and the readable storage medium provided in the embodiments of the present application through specific embodiments and their application scenarios.

[0057] Among them, the overdriven AUV hybrid heading control method based on the adaptive fuzzy controller can be applied to the terminal, and can be specifically executed by hardware or software in the terminal.

[0058] The terminal includes, but is not limited to, a portable communication device such as a mobile phone or tablet computer having a touch-sensitive surface (e.g., a touch screen display and / or a touch pad). It should also be understood that, in some embodiments, the terminal may not be a portable communication device, but a desktop computer having a touch-sensitive surface (e.g., a touch screen display and / or a touch pad).

[0059] In the following embodiments, a terminal including a display and a touch-sensitive surface is described. However, it should be understood that the terminal may include one or more other physical user interface devices such as a physical keyboard, a mouse, and a joystick.

[0060] The embodiment of the present application provides an over-driven AUV hybrid heading control method based on an adaptive fuzzy controller. The execution subject of the over-driven AUV hybrid heading control method based on an adaptive fuzzy controller can be an electronic device or a functional module or functional entity in the electronic device that can implement the over-driven AUV hybrid heading control method based on an adaptive fuzzy controller. The electronic devices mentioned in the embodiment of the present application include but are not limited to mobile phones, tablet computers, computers, cameras and wearable devices. The following describes the over-driven AUV hybrid heading control method based on an adaptive fuzzy controller provided in the embodiment of the present application using an electronic device as an example of the execution subject.

[0061] Figure 1 This is one of the flow charts of the hybrid heading control method of an overdriven AUV based on an adaptive fuzzy controller provided in an embodiment of the present application, such as Figure 1 As shown, the hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller includes: step 110 , step 120 , step 130 , step 140 and step 150 .

[0062] Step 110: Obtain the desired heading and the actual heading of the AUV, and calculate the heading error of the AUV based on the desired heading and the actual heading;

[0063] Figure 2 is a schematic structural diagram of a side view of an autonomous underwater vehicle provided in an embodiment of the present application, such as Figure 2 As shown in the figure, the AUV has a torpedo-shaped appearance and is equipped with a tail main propeller, rear side propellers, front side propellers, and rudder blades. The tail main propeller provides navigation speed. At high speeds, the rudder blades drive the AUV to adjust its course. At low speeds, the side propellers adjust the AUV's direction.

[0064] In some embodiments, the calculation formula of the heading error is as follows:

[0065] ψ e =ψ d -ψ t

[0066] Among them, ψ d is the desired heading, ψ t is the actual heading, ψ e is the heading error.

[0067] In this embodiment, the heading error is obtained by calculating the difference between the desired heading and the actual heading, which can more accurately evaluate the heading deviation of the AUV, adjust the heading parameters in time, reduce the heading deviation, improve the accuracy and stability of the AUV heading control, and reduce potential navigation risks.

[0068] Step 120: Input the heading error into a differentiator to obtain a heading error differential;

[0069] It is easy to understand that the heading error is input into the differentiator and the heading error differential is calculated using the following formula:

[0070]

[0071] in, is the heading error differential, t is time, ψ e is the heading error.

[0072] Step 130: Input the heading error and the heading error differential into an adaptive fuzzy controller to obtain a precise rudder angle control signal and a precise thrust control signal, wherein the adaptive fuzzy controller includes a telescoping factor module, a rudder angle fuzzification module, a thrust fuzzification module, a rudder angle clarity module, and a thrust clarity module; the telescoping factor module includes a rudder angle telescoping factor and a thrust telescoping factor; the rudder angle fuzzification module includes a rudder angle rule base module and a rudder angle inference engine module; and the thrust fuzzification module includes a thrust rule base module and a thrust inference engine module.

[0073] Figure 3 This is a second flow chart of the hybrid heading control method of an overdriven AUV based on an adaptive fuzzy controller provided in an embodiment of the present application, as shown in FIG. Figure 3 As shown, the heading error and the heading error differential are input into the adaptive fuzzy controller, and the heading error and the heading error differential are input into the expansion factor module to obtain a more refined error input after the expansion factor changes. The refined error is converted into a fuzzy signal through the fuzzification module. The reasoning module and the rule base module use the rule base to make inference decisions on the fuzzy signal to obtain a fuzzy rudder angle control signal and a fuzzy side thrust control signal, which are then input into the clarification module and clarified according to certain rules to obtain a precise rudder angle control signal and a precise side thrust control signal.

[0074] Step 140: Input the precise rudder angle control signal and the precise thrust control signal into an adaptive switching factor module, adaptively adjust the ratio of the rudder angle and the thrust in the total control force, and obtain a rudder angle signal and a thrust signal. The adaptive switching factor module includes a rudder angle switching factor function and a thrust switching factor function, and the rudder angle switching factor function and the thrust switching factor function are mutually correlated.

[0075] For example, the rudder angle switching factor β1 and the thrust switching factor β2 are designed, and the calculation formula of the rudder angle switching factor is as follows:

[0076]

[0077] Where u is the speed of the AUV and λ1 is the rudder angle switching parameter.

[0078] The calculation formula of the thrust switching factor is as follows:

[0079]

[0080] Where u is the speed of the AUV and λ2 is the thrust switching parameter.

[0081] It should be noted that the expressions of the rudder angle switching factor and the thrust switching factor can be set according to the actual scenario and application, and this application does not impose any restrictions.

[0082] According to the AUV operating state, the proportion of rudder angle and side thrust in the control force is adaptively adjusted to obtain the rudder angle control force β1δ r and the thrust control force β2τ r , δ r is the precise rudder angle control signal, τ r In order to accurately control the thrust signal, the rudder angle switching parameters and the thrust switching parameters are used to adjust the switching factor weights to make the entire switching process smoother. Finally, the rudder angle control force and the thrust control force are allocated to the corresponding actuators of the AUV. The two control forces are mixed to drive the AUV to hover and move forward.

[0083] Step 150: The hybrid drive AUV operates based on the rudder angle signal and the lateral thrust signal.

[0084] According to the hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller provided in an embodiment of the present application, the heading error and its differential are calculated and input into the adaptive fuzzy controller for processing. In combination with the heading error, the error differential and its control rules, accurate rudder angle and side thrust control signals are output, which can act on different actuators, thereby achieving stable operation of the AUV at different speeds. Through a control force distribution strategy based on a switching factor, the magnitude of different control forces can be adaptively adjusted at different speeds, thereby alleviating the AUV navigation flutter phenomenon caused by changes in the drive mode and improving the heading control accuracy.

[0085] In some embodiments, inputting the heading error and the heading error differential into an adaptive fuzzy controller to obtain a precise rudder angle control signal and a precise side thrust control signal includes:

[0086] Inputting the heading error and the heading error differential into a scaling factor module to obtain a refined error set, wherein the refined error set includes a first error and a second error;

[0087] Inputting the first error and the second error into a rudder angle fuzzification module and a thrust fuzzification module respectively to obtain a fuzzy rudder angle control signal and a fuzzy thrust control signal;

[0088] The fuzzy rudder angle control signal and the fuzzy side thrust control signal are input into the rudder angle clarification module and the side thrust clarification module respectively to obtain the precise rudder angle control signal and the precise side thrust control signal.

[0089] In some embodiments, the calculation formula of the first error is as follows:

[0090] τ1=α1ψ e

[0091] Among them, τ1 is the first error, α1 is the rudder angle expansion factor, ψ e is the heading error;

[0092] The calculation formula of the second error is as follows:

[0093]

[0094] Among them, τ2 is the second error, α2 is the side thrust expansion factor, is the heading error differential.

[0095] It should be noted that the calculation formula for the rudder angle expansion factor is as follows:

[0096]

[0097] Among them, ρ1 is the first scaling parameter, and E1 is the heading angle error.

[0098] The calculation formula of the side thrust expansion factor is as follows:

[0099]

[0100] Wherein, ρ2 is the second scaling parameter, and E2 is the heading angle change rate.

[0101] In some embodiments, the scaling parameter determines the degree of error refinement and is in the range of (0, 1), where E1=180 and E2=30 are the maximum values of the heading angle error and its rate of change.

[0102] In this embodiment, by introducing the rudder angle expansion factor and the side thrust expansion factor, the heading error and the heading error differential are weightedly calculated to obtain the first error and the second error, which can better adapt to the needs of different heading changes of the AUV, reduce the accumulation of heading errors, and improve the accuracy and stability of the AUV heading control.

[0103] In some embodiments, the first error and the second error are converted into a fuzzy rudder angle control signal and a fuzzy side thrust control signal through a triangular fuzzifier, and then the inference module infers and infers the fuzzy rudder angle control signal and the fuzzy side thrust control signal respectively according to the first rule base and the second rule base through the Mamdani method to generate a fuzzy rudder angle control signal set and a fuzzy side thrust control signal set. Finally, the maximum membership method is used to clarify the fuzzy rudder angle control signal set and the fuzzy side thrust control signal set to obtain an accurate rudder angle control signal and an accurate side thrust control signal.

[0104] In this embodiment, the heading error and the heading error differential are respectively changed by the scaling factor to obtain the first error and the second error, which are then converted into fuzzy signals. An inference module is used to make inference decisions on the fuzzy rudder angle control signal and the fuzzy side thrust control signal to generate a fuzzy rudder angle control signal set and a fuzzy side thrust control signal set. Finally, accurate control signals are obtained through clarification processing, which effectively enhances the control accuracy of the rudder angle and side thrust, reduces the deviation caused by the heading error, enables the AUV to adaptively adjust the size of different control forces at different speeds, alleviates the AUV navigation flutter phenomenon caused by changes in the drive mode, and reduces potential navigation risks.

[0105] In some embodiments, inputting the first error and the second error into a rudder angle fuzzification module and a thrust fuzzification module respectively to obtain a fuzzy rudder angle control signal and a fuzzy thrust control signal includes:

[0106] The first error is input into the rudder angle fuzzification module, and after the rudder angle rule base module and the rudder angle inference engine module make inference decisions, a fuzzy rudder angle control signal is obtained;

[0107] The second error is input into the thrust fuzzification module, and after the thrust rule base module and the thrust inference engine module make inference decisions, a fuzzy thrust control signal is obtained.

[0108] In this embodiment, by inputting the first error and the second error into the rudder angle fuzzification module and the thrust fuzzification module respectively, the fuzzy rudder angle control signal and the fuzzy thrust control signal are obtained according to their respective rule base modules and inference engines, thereby realizing the error fuzzification processing of the AUV, which can better adapt to the requirements of different heading changes of the AUV, reduce the accumulation of heading errors, and improve the accuracy and stability of the AUV heading control.

[0109] In some embodiments, the first error is input into the rudder angle fuzzification module, and after the rudder angle rule base module and the rudder angle inference engine module make inference decisions, a fuzzy rudder angle control signal is obtained, including:

[0110] Inputting the first error into a triangular fuzzifier, mapping it to a membership value of a fuzzy set through a triangular membership function, and obtaining a first fuzzy set membership;

[0111] The first fuzzy set membership is input into the rudder angle rule base module and the rudder angle inference engine module. After using the first rule base for rule matching and reasoning decision-making, a fuzzy rudder angle control signal is obtained. The first rule base includes multiple IF-THEN statements.

[0112] In some embodiments, for example, the first fuzzy set membership of the fuzzy rudder angle control signal is 0.8, and the rudder angle inference engine module performs rule matching and inference decision on the fuzzy rudder angle control signal through the first rule base. The first rule base is shown in Table 1, where NB represents negative large, NM represents negative medium, NS represents negative small, ZO represents zero, PS represents positive small, PM represents positive medium, PB represents positive large, and E represents positive large. ψ To fuzzy the rudder angle control signal, is the fuzzy thrust control signal, Δ r is the fuzzy rudder angle control signal set, Γ r To fuzzy the thrust control signal set, the inference module substitutes the heading angle error and the heading angle change rate into the rule antecedent (IF part) through the IF-THEN statement, matches the rules that meet the conditions through fuzzy logic operations (such as the "minimum-synthesis method"), calculates the membership degree of each rule consequence (THEN part), and finally obtains the fuzzy rudder angle control signal set that meets the rules (such as {positive: 0.8, neutral: 0.3}).

[0113] Table 1

[0114]

[0115] In some embodiments, the fuzzy rudder angle control set includes a positive maximum rudder angle control signal, a middle rudder angle control signal and a zero rudder angle control signal. The membership corresponding to the positive maximum rudder angle control signal is 0.8, the membership corresponding to the middle rudder angle control signal is 0.7, and the membership corresponding to the zero rudder angle control signal is 0.6. The maximum membership method is used to traverse all the rudder angle control signals in the fuzzy rudder angle control set, and the rudder angle control signal with the largest membership is used as the precise rudder angle control signal.

[0116] In this embodiment, the fuzzy rudder angle control signal is input into the rudder angle inference engine module and the fuzzy rudder angle control signal is generated by using the first rule base for rule matching and reasoning decision-making. This improves the adaptability of the AUV in complex environments, and enables the adaptive adjustment of different control forces at different speeds, thereby improving the accuracy and reliability of the AUV's heading control.

[0117] In some embodiments, the step of inputting the second error into the thrust fuzzification module, and obtaining the fuzzy thrust control signal after the thrust rule base module and the thrust inference engine module make inference decisions, includes:

[0118] Inputting the second error into the triangular fuzzifier, mapping it to the membership value of the fuzzy set through the triangular membership function, and obtaining the second fuzzy set membership;

[0119] The second fuzzy set membership is input into the thrust rule base module and the thrust inference engine module, and the fuzzy thrust control signal is obtained after rule matching and reasoning decision-making using the second rule base. The second rule base includes multiple IF-THEN statements.

[0120] In some embodiments, for example, the second fuzzy set membership of the fuzzy thrust control signal is 0.7. The thrust inference engine module performs rule matching and inference decision-making on the fuzzy thrust control signal using a second rule base. The second rule base is shown in Table 2, where NB represents negative large, NM represents negative medium, NS represents negative small, ZO represents zero, PS represents positive small, PM represents positive medium, and PB represents positive large. The thrust inference engine module substitutes the heading angle error and the heading angle change rate into the rule antecedent (IF portion) through an IF-THEN statement, matches the rules that meet the conditions through fuzzy logic operations (such as the "minimum-synthesis method"), calculates the membership of each rule consequence (THEN portion), and ultimately obtains a fuzzy thrust control signal set that meets the rules (such as {positive large: 0.7, positive medium: 0.4}).

[0121] Table 2

[0122]

[0123] In this embodiment, the fuzzy thrust control signal is input into the thrust inference engine module and the fuzzy thrust control signal is generated by using the second rule base for rule matching and reasoning decision making. This improves the adaptive ability of the AUV in complex environments, and enables the adaptive adjustment of different control forces at different speeds, thereby improving the accuracy and reliability of the AUV's heading control.

[0124] The embodiment of the present application provides an overdriven AUV hybrid heading control method based on an adaptive fuzzy controller, and the execution subject can be an overdriven AUV hybrid heading control device based on an adaptive fuzzy controller. In the embodiment of the present application, the overdriven AUV hybrid heading control method based on an adaptive fuzzy controller is executed by the overdriven AUV hybrid heading control device based on an adaptive fuzzy controller as an example to illustrate the overdriven AUV hybrid heading control method based on an adaptive fuzzy controller provided in the embodiment of the present application.

[0125] The embodiment of the present application also provides an overdriven AUV hybrid heading control device based on an adaptive fuzzy controller, such as Figure 4 As shown, the overdriven AUV hybrid heading control device based on the adaptive fuzzy controller includes: an acquisition module 410 , a first processing module 420 , a second processing module 430 , a third processing module 440 and a driving module 450 .

[0126] An acquisition module 410 is configured to acquire a desired heading and an actual heading of the AUV, and calculate a heading error of the AUV based on the desired heading and the actual heading;

[0127] A first processing module 420 is configured to input the heading error into a differentiator to obtain a heading error differential;

[0128] a second processing module 430 configured to input the heading error and the heading error differential into an adaptive fuzzy controller to obtain a precise rudder angle control signal and a precise thrust control signal, wherein the adaptive fuzzy controller includes a telescoping factor module, a rudder angle fuzzification module, a thrust fuzzification module, a rudder angle clarity module, and a thrust clarity module; the telescoping factor module includes a rudder angle telescoping factor and a thrust telescoping factor; the rudder angle fuzzification module includes a rudder angle rule base module and a rudder angle inference engine module; and the thrust fuzzification module includes a thrust rule base module and a thrust inference engine module;

[0129] a third processing module 440, configured to input the precise rudder angle control signal and the precise thrust control signal into an adaptive switching factor module, adaptively adjust the ratio of the rudder angle and the thrust in the total control force, and obtain a rudder angle signal and a thrust signal, wherein the adaptive switching factor module includes a rudder angle switching factor function and a thrust switching factor function, and the rudder angle switching factor function and the thrust switching factor function are mutually correlated;

[0130] The driving module 450 is configured to hybrid-drive the AUV based on the rudder angle signal and the lateral thrust signal.

[0131] According to the hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller provided in an embodiment of the present application, the heading error and its differential are calculated and input into the adaptive fuzzy controller for processing. In combination with the heading error, the error differential and its control rules, accurate rudder angle and side thrust control signals are output, which can act on different actuators, thereby achieving stable operation of the AUV at different speeds. Through a control force distribution strategy based on a switching factor, the magnitude of different control forces can be adaptively adjusted at different speeds, thereby alleviating the AUV navigation flutter phenomenon caused by changes in the drive mode and improving the heading control accuracy.

[0132] The overdriven AUV hybrid heading control device based on the adaptive fuzzy controller provided in the embodiment of the present application can achieve Figures 1 to 3 To avoid repetition, the various processes implemented in the embodiment of the overdriven AUV hybrid heading control method based on the adaptive fuzzy controller are not described here.

[0133] In some embodiments, as Figure 5 As shown, an embodiment of the present application also provides an electronic device 500, including a processor 501, a memory 502, and a computer program stored in the memory 502 and executable on the processor 501. When the program is executed by the processor 501, each process of the embodiment of the overdriven AUV hybrid heading control method based on the adaptive fuzzy controller is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0134] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0135] The embodiment of the present application also provides a non-transitory computer-readable storage medium, which stores a computer program. When the computer program is executed by the processor, the various processes of the embodiment of the overdriven AUV hybrid heading control method based on the adaptive fuzzy controller are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0136] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0137] An embodiment of the present application further provides a computer program product, including a computer program, which, when executed by a processor, implements the above-mentioned hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller.

[0138] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0139] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, which is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above-mentioned embodiment of the overdriven AUV hybrid heading control method based on an adaptive fuzzy controller, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0140] It should be understood that the chip mentioned in the embodiments of the present application can also be called a device-level chip, a device chip, a chip device, or an on-chip device chip, etc.

[0141] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0142] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, disk, CD-ROM), including a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the overdriven AUV hybrid heading control method based on an adaptive fuzzy controller in each embodiment of the present application.

[0143] In the description of this application, "first feature" and "second feature" may include one or more such features.

[0144] In the description of this application, “plurality” means two or more.

[0145] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

[0146] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0147] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and purpose of the present application, and that the scope of the present application is defined by the claims and their equivalents.

Claims

1. A hybrid heading control method for overdriven AUV based on adaptive fuzzy controller, characterized in that: The method comprises: Obtaining a desired heading and an actual heading of the AUV, and calculating a heading error of the AUV based on the desired heading and the actual heading; Inputting the heading error into a differentiator to obtain a heading error differential; Inputting the heading error and the heading error differential into an adaptive fuzzy controller to obtain an accurate rudder angle control signal and an accurate thrust control signal, the adaptive fuzzy controller comprising a telescoping factor module, a rudder angle fuzzification module, a thrust fuzzification module, a rudder angle clarity module, and a thrust clarity module, the telescoping factor module comprising a rudder angle telescoping factor and a thrust telescoping factor, the rudder angle fuzzification module comprising a rudder angle rule base module and a rudder angle inference engine module, and the thrust fuzzification module comprising a thrust rule base module and a thrust inference engine module; Inputting the precise rudder angle control signal and the precise thrust control signal into an adaptive switching factor module, adaptively adjusting the ratio of the rudder angle and the thrust in the total control force, and obtaining a rudder angle signal and a thrust signal, wherein the adaptive switching factor module includes a rudder angle switching factor function and a thrust switching factor function, and the rudder angle switching factor function and the thrust switching factor function are mutually correlated; Based on the rudder angle signal and the lateral thrust signal, the hybrid drive AUV operates.

2. The hybrid heading control method for overdriven AUV based on adaptive fuzzy controller according to claim 1 is characterized in that: The step of inputting the heading error and the heading error differential into an adaptive fuzzy controller to obtain an accurate rudder angle control signal and an accurate side thrust control signal comprises: Inputting the heading error and the heading error differential into a scaling factor module to obtain a refined error set, wherein the refined error set includes a first error and a second error; Inputting the first error and the second error into a rudder angle fuzzification module and a thrust fuzzification module respectively to obtain a fuzzy rudder angle control signal and a fuzzy thrust control signal; The fuzzy rudder angle control signal and the fuzzy side thrust control signal are respectively input into the rudder angle clarification module and the side thrust clarification module to obtain a precise rudder angle control signal and a precise side thrust control signal.

3. The hybrid heading control method for overdriven AUV based on adaptive fuzzy controller according to claim 2 is characterized in that: The calculation formula of the first error is as follows: τ1=α1ψ e Among them, τ1 is the first error, α1 is the rudder angle expansion factor, ψ e is the heading error; The calculation formula of the second error is as follows: Among them, τ2 is the second error, α2 is the side thrust expansion factor, is the heading error differential.

4. The hybrid heading control method for overdriven AUV based on adaptive fuzzy controller according to claim 2 is characterized in that: The step of inputting the first error and the second error into a rudder angle fuzzification module and a thrust fuzzification module respectively to obtain a fuzzy rudder angle control signal and a fuzzy thrust control signal comprises: The first error is input into the rudder angle fuzzification module, and after the rudder angle rule base module and the rudder angle inference engine module make inference decisions, a fuzzy rudder angle control signal is obtained; The second error is input into the thrust fuzzification module, and after the thrust rule base module and the thrust inference engine module make inference decisions, a fuzzy thrust control signal is obtained.

5. The hybrid heading control method for overdriven AUV based on adaptive fuzzy controller according to claim 4 is characterized in that: The first error is input into the rudder angle fuzzification module, and after the rudder angle rule base module and the rudder angle inference engine module make inference decisions, a fuzzy rudder angle control signal is obtained, including: Inputting the first error into a triangular fuzzifier, mapping it to a membership value of a fuzzy set through a triangular membership function, and obtaining a first fuzzy set membership; The first fuzzy set membership is input into the rudder angle rule base module and the rudder angle inference engine module. After using the first rule base for rule matching and reasoning decision-making, a fuzzy rudder angle control signal is obtained. The first rule base includes multiple IF-THEN statements.

6. The hybrid heading control method for overdriven AUV based on adaptive fuzzy controller according to claim 4 is characterized in that: The second error is input into the thrust fuzzification module, and after the thrust rule base module and the thrust inference engine module make inference decisions, a fuzzy thrust control signal is obtained, including: Inputting the second error into the triangular fuzzifier, mapping it to the membership value of the fuzzy set through the triangular membership function, and obtaining the second fuzzy set membership; The second fuzzy set membership is input into the thrust rule base module and the thrust inference engine module, and the fuzzy thrust control signal is obtained after rule matching and reasoning decision-making using the second rule base. The second rule base includes multiple IF-THEN statements.

7. The hybrid heading control method for overdriven AUV based on adaptive fuzzy controller according to claim 1, characterized in that: The calculation formula of the heading error is as follows: ψ e =ψ d -ψ t Among them, ψ d is the desired heading, ψ t is the actual heading, ψ e is the heading error.

8. An overdriven AUV hybrid heading control device based on an adaptive fuzzy controller, implemented by the overdriven AUV hybrid heading control method based on an adaptive fuzzy controller according to any one of claims 1 to 7, characterized in that: The device comprises: An acquisition module is used to obtain a desired heading and an actual heading of the AUV, and calculate a heading error of the AUV based on the desired heading and the actual heading; A first processing module, configured to input the heading error into a differentiator to obtain a heading error differential; a second processing module, configured to input the heading error and the heading error differential into an adaptive fuzzy controller to obtain a precise rudder angle control signal and a precise thrust control signal, the adaptive fuzzy controller comprising a telescoping factor module, a rudder angle fuzzification module, a thrust fuzzification module, a rudder angle clarity module, and a thrust clarity module; the telescoping factor module comprising a rudder angle telescoping factor and a thrust telescoping factor; the rudder angle fuzzification module comprising a rudder angle rule base module and a rudder angle inference engine module; and the thrust fuzzification module comprising a thrust rule base module and a thrust inference engine module; a third processing module, configured to input the precise rudder angle control signal and the precise thrust control signal into an adaptive switching factor module, adaptively adjust the ratio of the rudder angle and the thrust in the total control force, and obtain a rudder angle signal and a thrust signal, wherein the adaptive switching factor module includes a rudder angle switching factor function and a thrust switching factor function, and the rudder angle switching factor function and the thrust switching factor function are mutually correlated; The driving module is used for hybrid driving the AUV based on the rudder angle signal and the lateral thrust signal.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the overdriven AUV hybrid heading control method based on the adaptive fuzzy controller is implemented as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the hybrid heading control method for an overdriven AUV based on an adaptive fuzzy controller is implemented as claimed in any one of claims 1 to 7.

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