An unmanned ship self-adaptive control method based on parameter identification

Abstract

The application provides an adaptive unmanned ship track control method, which measures the surge speed signal, the lateral position signal and the heading angle signal of the unmanned ship through an inertial navigation device, and obtains the filtered differential signal through a second-order oscillation differential filter according to the surge speed error signal, the lateral position error signal and the heading angle error signal, and superimposes the corresponding error integral signal to form the velocity error sliding mode signal and the heading angle error sliding mode signal; then the adaptive compensation is performed on the unmanned ship turning moment signal of the surge propulsion force and the track control through the adaptive law design, and the final surge propulsion force and turning moment are obtained through the superposition of the corresponding sliding mode nonlinear signal and the adaptive control signal of the constant surge propulsion force signal, so that the tracking control of the given speed and the expected track is realized.

Description

Technical Field

[0001] This invention relates to the field of longitudinal propulsion and speed control of unmanned surface vessels (USVs), and more specifically, to an adaptive control method for USVs based on parameter identification. Background Technology

[0002] Traditionally, longitudinal propulsion and speed control of unmanned surface vessels (USVs) generally employ error feedback and equivalent control structure compensation. Therefore, engineering design requires precise information such as the USV's structural dimensions and mass distribution information like moment of inertia before structural compensation can be performed. However, due to the numerous nonlinearities and coupling effects inherent in USV models, accurately obtaining the aforementioned model structural parameters is challenging. Furthermore, the USV's operation on the water is affected by wind and waves, resulting in inherent uncertainties in the model parameters. Therefore, relying on prior knowledge of structural information for precise compensation is difficult to fully implement in practical engineering. Some uncertainties prevent complete compensation of certain structural information, leading to deficiencies in speed control stability, anti-interference capability, and accuracy. Based on these background reasons, this invention, along with the concept of parameter identification, employs two adaptive methods for adaptive identification and compensation of the USV's structural interference information. Combining this with structural feedback control, an adaptive control method is proposed, achieving precise feedback anti-interference control of the USV's longitudinal propulsion speed. This invention also possesses high engineering application and promotion value.

[0003] It should be noted that the information in the background section above is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide an adaptive control method for unmanned surface vessels (USVs) based on parameter identification, thereby overcoming the problems of insufficient speed control stability and dynamic performance of USVs caused by uncertainties in USV structure and interference information.

[0005] According to one aspect of the present invention, an adaptive control method for unmanned surface vessels based on parameter identification is provided, comprising the following four steps:

[0006] Step S10: Install inertial navigation equipment on the unmanned surface vessel (USV) to measure its sway velocity and yaw rate signals. Based on the USV's mission, set the desired sway velocity signal and compare them to obtain the sway velocity error signal. Then, perform a combined nonlinear transformation on the sway velocity error signal to obtain a nonlinear sway velocity error signal. Next, pass the nonlinear sway velocity error signal through an inertial delay circuit to obtain a constant velocity disturbance inertial adaptive estimation signal. Based on the nonlinear sway velocity error signal and the sway velocity error signal, design a constant velocity disturbance iterative adaptive rate signal. Then, perform integral iteration to obtain a constant velocity disturbance iterative adaptive estimation signal. Finally, superimpose the constant velocity disturbance inertial adaptive estimation signal to obtain the total adaptive identification signal for the constant velocity disturbance parameters.

[0007] Step S20: Based on the aforementioned nonlinear signal of sway velocity error, the sway velocity signal and the yaw velocity signal of the unmanned surface vessel, an inertial delay element is used to obtain an adaptive inertial estimation signal for translational-rotational coupling interference; then, based on the aforementioned nonlinear combination of the sway velocity error signal, the sway velocity error nonlinear signal, the yaw velocity signal and the yaw velocity signal of the unmanned surface vessel, an iterative adaptive rate signal for translational-rotational coupling interference is obtained, and then integral iteration is performed to obtain an iterative adaptive estimation signal for translational-rotational coupling interference; finally, the adaptive inertial estimation signal for translational-rotational coupling interference is superimposed to obtain the total adaptive identification signal for translational-rotational coupling interference parameters.

[0008] Step S30: Based on the nonlinear signal of the sway velocity error and the sway velocity signal of the unmanned surface vessel, an inertial adaptive estimation signal for translational disturbance is obtained through an inertial delay element; then, based on the nonlinear combination of the sway velocity error signal, the nonlinear signal of the sway velocity error, the sway velocity signal of the unmanned surface vessel, and the yaw rate signal, a translational disturbance iterative adaptive rate signal is obtained, and then integral iteration is performed to obtain a translational disturbance iterative adaptive estimation signal; finally, the translational disturbance inertial adaptive estimation signal is superimposed to obtain a total adaptive identification signal for translational disturbance parameters.

[0009] Step S40: Combine and integrate the sway velocity error signal and the sway velocity error nonlinear signal to obtain the velocity error combined integral signal; then solve the velocity error approximate differential signal based on the velocity constant disturbance inertial adaptive estimation signal and the sway velocity error nonlinear signal; finally, superimpose the sway velocity error signal, the velocity error combined integral signal, and the velocity error approximate differential signal based on the velocity constant disturbance parameter adaptive identification total signal, the translational rotational coupling disturbance parameter adaptive identification total signal, and the translational disturbance parameter adaptive identification total signal to obtain the final sway thrust signal, which is then sent to the unmanned surface vessel propulsion system to achieve precise tracking and control of the desired velocity of the unmanned surface vessel.

[0010] In one exemplary embodiment of the present invention, based on the unmanned surface vessel (USV) mission, a desired sway velocity signal of the USV is set, and a sway velocity error signal of the USV is obtained by comparison; then, a combined nonlinear transformation is performed on the sway velocity error signal to obtain a sway velocity error nonlinear signal; then, based on the sway velocity error nonlinear signal, an inertial delay element is passed through the sway velocity error nonlinear signal to obtain a velocity constant disturbance inertial adaptive estimation signal; and a velocity constant disturbance iterative adaptive rate signal is designed based on the sway velocity error nonlinear signal and the sway velocity error signal; then, integral iteration is performed to obtain a velocity constant disturbance iterative adaptive estimation signal; finally, the velocity constant disturbance inertial adaptive estimation signal is superimposed to obtain a velocity constant disturbance parameter adaptive identification total signal, including:

[0011] ;

[0012] ;

[0013] ;

[0014] ;

[0015] ;

[0016] ;

[0017] in The signal is the pitch speed of the unmanned surface vessel. This is the bow roll rate signal of the unmanned surface vessel; The desired oscillation speed signal for the unmanned surface vessel; This is the sway velocity error signal for the unmanned surface vessel; The differential operator for the transfer function of the inertial delay element; This is a nonlinear signal representing the oscillation velocity error. , and These are constant parameters for nonlinear transformations; The time parameter of the inertial delay element is a constant; For constant velocity disturbance inertial adaptive estimation signal; For constant velocity disturbance iterative adaptive rate signal; For constant velocity disturbance, iterative adaptive estimation signal, , This is a constant parameter signal used to adjust the speed of adaptive iteration; This is the iteration period parameter, and it is a constant. The total signal is adaptively identified for constant velocity interference parameters.

[0018] In one exemplary embodiment of the present invention, based on the aforementioned nonlinear signal of sway velocity error, the sway velocity signal of the unmanned surface vessel (USV), and the yaw rate signal, an inertial adaptive estimation signal for translational-rotational coupling interference is obtained through an inertial delay stage. Then, based on the aforementioned sway velocity error signal, the sway velocity error nonlinear signal, the sway velocity signal of the USV, and the yaw rate signal, a nonlinear combination is performed to obtain an iterative adaptive rate signal for translational-rotational coupling interference. This rate signal is then integrated and iterated to obtain an iterative adaptive estimation signal for translational-rotational coupling interference. Finally, the translational-rotational coupling interference inertial adaptive estimation signal is superimposed to obtain the total adaptive identification signal for the translational-rotational coupling interference parameters, including:

[0019] ;

[0020] ;

[0021] ;

[0022] ;

[0023] in For the adaptive estimation signal of translational-rotational coupled disturbance inertia; For translational-rotational coupling interference iterative adaptive rate signal, For iterative adaptive estimation of translational-rotational coupling interference signals; Adaptive identification of the total signal for translational-rotational coupling interference parameters; , This is a constant parameter signal used to adjust the speed of adaptive iteration.

[0024] In one exemplary embodiment of the present invention, a translational disturbance inertial adaptive estimation signal is obtained by passing the aforementioned sway velocity error nonlinear signal and the sway velocity signal of the unmanned surface vessel through an inertial delay element; then, a translational disturbance iterative adaptive rate signal is obtained by nonlinearly combining the aforementioned sway velocity error signal, the sway velocity error nonlinear signal, the sway velocity signal of the unmanned surface vessel, and the yaw rate signal; this is then integrated and iterated to obtain a translational disturbance iterative adaptive estimation signal; finally, the translational disturbance inertial adaptive estimation signal is superimposed to obtain a total translational disturbance parameter adaptive identification signal, including:

[0025] ;

[0026] ;

[0027] ;

[0028] ;

[0029] in For adaptive estimation of translational disturbance inertial signals; For translational interference iterative adaptive rate signal, Iterative adaptive estimation of the signal for translational disturbance; Adaptive identification of the total signal for translational interference parameters; , This is a constant parameter signal used to adjust the speed of adaptive iteration for translational disturbances.

[0030] In one exemplary embodiment of the present invention, the combined integral of the sway velocity error signal and the sway velocity error nonlinear signal is used to obtain a velocity error combined integral signal; then, the velocity error approximate differential signal is solved based on the velocity constant disturbance inertial adaptive estimation signal and the sway velocity error nonlinear signal; finally, the sway velocity error signal, the velocity error combined integral signal, and the velocity error approximate differential signal are superimposed on the velocity constant disturbance parameter adaptive identification total signal, the translational rotational coupling disturbance parameter adaptive identification total signal, and the translational disturbance parameter adaptive identification total signal to obtain the final sway propulsion signal, including:

[0031] ;

[0032] ;

[0033] ;

[0034] in The velocity error is a combined integral signal; It is a constant parameter; This is the approximate differential signal of the velocity error; For oscillation propulsion signal, , , These are constant control parameters.

[0035] Beneficial effects

[0036] This invention provides an adaptive control method for unmanned surface vessels (USVs) based on parameter identification, with three main innovations. First, when the USV's structure and disturbance parameters are unknown or uncertain, adaptive parameter identification is used to achieve precise and high-performance feedback closed-loop control of speed. This solves the problem of traditional methods requiring accurate information about the USV's structure and disturbances, and also enhances the speed control's anti-interference capability. Second, the method categorizes disturbance parameters into three main types: constant disturbances, translational-rotational coupled disturbances, and translational disturbances. This approach closely matches the characteristics of the USV's structural uncertainty model, offering simplicity, clear physical meaning, and a low-complexity adaptive parameter identifyer, facilitating engineering implementation and parameter adjustment. Third, the method combines inertial delay and integral iteration for combined parameter identification, effectively avoiding parameter divergence. Furthermore, the final integration with feedback control leverages its advantages, resulting in superior composite speed control performance.

[0037] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit the invention. Attached Figure Description

[0038] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention. It is obvious that the drawings described below are merely some embodiments of the invention, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0039] Figure 1 This is a flowchart of an adaptive control method for unmanned surface vessels based on parameter identification provided by the present invention.

[0040] Figure 2 This is the pitch speed signal (unit: meters per second) of the unmanned surface vessel provided by the method in the embodiments of the present invention.

[0041] Figure 3 It is the bow roll rate signal (unit: radians per second) of the unmanned surface vessel provided by the method in the embodiments of the present invention.

[0042] Figure 4 This is the sway velocity error signal (unit: meters per second) of the unmanned surface vessel provided by the method in the embodiments of the present invention.

[0043] Figure 5 It is the unitless integrated signal of the unmanned surface vessel speed error combination of the method provided in the embodiments of the present invention.

[0044] Figure 6 It is the approximate differential signal of the unmanned surface vessel speed error (unitless) provided by the method in the embodiments of the present invention.

[0045] Figure 7 It is the unmanned surface vessel oscillation thrust signal (unit: Newton) provided by the method in the embodiments of the present invention. Detailed Implementation

[0046] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make the invention more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of embodiments of the invention. However, those skilled in the art will recognize that the technical solutions of the invention may be practiced with one or more of these specific details omitted, or other methods, components, apparatus, steps, etc., may be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of the invention.

[0047] This invention provides an adaptive control method for unmanned surface vessels (USVs) based on parameter identification. The method measures the sway velocity and heading angle signals of the USV using an inertial navigation device. Based on the structure of the USV system, its interference parameters are categorized into three types: constant interference, translational-rotational coupling interference, and translational interference. Each type of interference is then combined using both inertial delay and integral iteration methods for adaptive parameter identification. The approximate differential signal of the velocity error is then solved based on the inertial delay and the nonlinear signal of the sway velocity error. Finally, the combined adaptive identification signal of the three types of interference, the sway velocity error signal, and the velocity error combined integral signal are superimposed to obtain the final sway thrust signal, achieving precise tracking control of the USV's desired velocity.

[0048] Below, we will combine the appendix Figure 1 The present invention provides a further explanation and description of an adaptive control method for unmanned surface vessels based on parameter identification. (Reference) Figure 1 As shown, this adaptive control method for unmanned surface vessels based on parameter identification includes the following steps:

[0049] Step S10 can be broken down into the following six sub-steps. The first step is to install inertial navigation equipment on the unmanned surface vessel (USV) and measure the pitch velocity and yaw rate signals of the USV.

[0050] In this invention example, the sway velocity signal of the unmanned surface vessel is as follows: Figure 2 As shown; the bow roll angular velocity signal is as follows Figure 3 As shown.

[0051] The second step is to set the desired sway velocity signal of the unmanned surface vessel (USV) based on the mission requirements, and then compare the results to obtain the sway velocity error signal of the USV as follows:

[0052] ;

[0053] in The signal is the pitch speed of the unmanned surface vessel. This is the bow roll rate signal of the unmanned surface vessel; The desired oscillation speed signal for the unmanned surface vessel; This is the sway velocity error signal for the unmanned surface vessel.

[0054] In this invention example, the following is selected Meters per second, the sway velocity error signal of the unmanned surface vessel is obtained as follows: Figure 4 As shown.

[0055] The third step involves performing a combined nonlinear transformation on the oscillation velocity error signal to obtain the following nonlinear oscillation velocity error signal:

[0056] ;

[0057] in The nonlinear signal is the oscillation velocity error signal; where , and These are constant parameters for nonlinear transformations.

[0058] In this invention example, the following is selected , and .

[0059] The fourth step involves passing the nonlinear signal of the sway velocity error through an inertial delay element to obtain the following velocity constant disturbance inertial adaptive estimation signal:

[0060] ;

[0061] in The differential operator for the transfer function of the inertial delay element; The time parameter of the inertial delay element is a constant; The signal is an adaptive estimation signal for constant velocity disturbance inertia.

[0062] In this invention example, the following is selected .

[0063] Fifth, based on the nonlinear signal of the oscillation velocity error and the oscillation velocity error signal, design the velocity constant disturbance iterative adaptive rate signal as follows:

[0064] ;

[0065] in For constant velocity disturbance iterative adaptive rate signal; , This is a constant parameter signal used to adjust the speed of adaptive iteration.

[0066] In this invention example, the following is selected , .

[0067] Step 6: Perform integral iteration to obtain the adaptive estimation signal of velocity constant disturbance; then superimpose the adaptive estimation signal of velocity constant disturbance inertia to obtain the total adaptive identification signal of velocity constant disturbance parameters as follows:

[0068] ;

[0069] ;

[0070] in For constant velocity disturbance, iterative adaptive estimation signal, This is the iteration period parameter, and it is a constant. The total signal is adaptively identified for constant velocity interference parameters. In this example, the following is selected: .

[0071] Step S20 can be broken down into the following three sub-steps. First, based on the aforementioned nonlinear signal of the sway velocity error, the sway velocity signal of the unmanned surface vessel, and the yaw rate signal, an adaptive estimation signal for the translational-rotational coupling interference is obtained through an inertial delay circuit, as follows:

[0072] ;

[0073] in This is the adaptive estimation signal for translational-rotational coupled interference inertia.

[0074] The second step involves nonlinearly combining the aforementioned sway velocity error signal, sway velocity error nonlinear signal, and the unmanned surface vessel's sway velocity signal with its yaw rate signal to obtain the translational-rotational coupling interference iterative adaptive rate signal. This is then integrated and iterated to obtain the translational-rotational coupling interference iterative adaptive estimation signal, as follows:

[0075] ;

[0076] ;

[0077] in For translational-rotational coupling interference iterative adaptive rate signal, For iterative adaptive estimation of translational-rotational coupling interference signals; , This is a constant parameter signal used to adjust the speed of adaptive iteration.

[0078] In this invention example, the following is selected , .

[0079] The third step involves superimposing the translational-rotational coupling disturbance inertial adaptive estimation signal to obtain the total adaptive identification signal for the translational-rotational coupling disturbance parameters, as follows:

[0080] ;

[0081] in The total signal is adaptively identified for translational-rotational coupling interference parameters.

[0082] Step S30 can be broken down into the following three sub-steps. First, based on the aforementioned nonlinear signal of the sway velocity error and the sway velocity signal of the unmanned surface vessel, through an inertial delay element, the translational disturbance inertial adaptive estimation signal is obtained as follows:

[0083] ;

[0084] in This is an adaptive estimation signal for translational disturbance inertia.

[0085] The second step involves nonlinearly combining the aforementioned sway velocity error signal, sway velocity error nonlinear signal, and the unmanned surface vessel's sway velocity signal and yaw rate signal to obtain the translational disturbance iterative adaptive rate signal. This is then integrated and iterated to obtain the translational disturbance iterative adaptive estimation signal, as follows:

[0086] ;

[0087] ;

[0088] in For translational interference iterative adaptive rate signal, Iterative adaptive estimation of the signal for translational disturbance. , This is a constant parameter signal used to adjust the speed of adaptive iteration for translational disturbances.

[0089] In this invention example, the following is selected , .

[0090] The third step involves superimposing the translational disturbance inertial adaptive estimation signal to obtain the total adaptive identification signal for the translational disturbance parameters, as follows:

[0091] ;

[0092] in The total signal is adaptively compensated for translational interference.

[0093] Step S40 can be broken down into the following three sub-steps. First, the oscillation velocity error signal and the nonlinear oscillation velocity error signal are combined and integrated to obtain the velocity error combined integral signal as follows:

[0094] ;

[0095] in The velocity error is a combined integral signal; This is a constant parameter.

[0096] In this invention example, the following is selected The final velocity error combined integral signal is as follows: Figure 5 As shown.

[0097] The second step involves solving for the approximate differential signal of the velocity error based on the aforementioned velocity constant disturbance inertial adaptive estimation signal and the oscillation velocity error nonlinear signal:

[0098] ;

[0099] in This is the approximate differential signal of the velocity error. In this example, the approximate differential signal of the velocity error is obtained as follows: Figure 6 As shown.

[0100] The third step involves superimposing the total adaptive identification signal of the constant velocity disturbance parameter, the total adaptive identification signal of the translational-rotational coupling disturbance parameter, and the total adaptive identification signal of the translational disturbance parameter onto the sway velocity error signal, the velocity error combined integral signal, and the velocity error approximate differential signal to obtain the final sway thrust signal. This signal is then transmitted to the unmanned surface vessel propulsion system to achieve precise tracking and control of the desired velocity of the unmanned surface vessel, as follows:

[0101] ;

[0102] in For oscillation propulsion signal, , , These are constant control parameters.

[0103] In this invention example, the following is selected , , The final obtained oscillation thrust signal is as follows Figure 7 As shown.

[0104] Depend on Figure 2It can be seen that the unmanned surface vessel's speed can eventually accelerate smoothly to 12 meters per second in about 100 seconds; while... Figure 3 It can be seen that during the start-up process of the unmanned surface vessel (USV), the bow roll rate fluctuates to some extent, but quickly stabilizes, which is a normal phenomenon. Figure 4 It can be seen that the speed error signal of the unmanned surface vessel can smoothly converge to 0, indicating high control precision. Figure 5 It can be seen that the velocity error combination integral signal of the unmanned surface vessel can converge and stabilize at around -180; from Figure 6 It can be seen that the approximate differential signal of the speed error converges to 0, and its solution is very smooth without any spikes. Therefore, it meets engineering requirements and provides a good damping effect for the entire speed control. Figure 7 It can be seen that the final pitch thrust signal of the unmanned surface vessel stabilizes at around 19,000 Newtons, which is used to maintain the speed of the unmanned surface vessel. The entire case demonstrates that the invention is entirely feasible, and its solution is easy to implement in engineering, has good robustness, and does not require precise structural interference parameters of the unmanned surface vessel, thus possessing high value for engineering application.

Claims

1. An adaptive control method for unmanned surface vessels based on parameter identification, characterized in that, Includes the following steps: Step S10: Install inertial navigation equipment on the unmanned surface vessel (USV) to measure the sway velocity signal and yaw rate signal of the USV. Based on the USV mission, set the desired sway velocity signal of the USV and compare them to obtain the sway velocity error signal of the USV. Then, perform a combined nonlinear transformation on the sway velocity error signal to obtain the sway velocity error nonlinear signal. Finally, pass the sway velocity error nonlinear signal through an inertial delay circuit to obtain the velocity constant disturbance inertial adaptive estimation signal. Based on the nonlinear signal and the oscillation velocity error signal, an iterative adaptive rate signal for constant velocity interference is designed. Then, integration iteration is performed to obtain the iterative adaptive estimation signal for constant velocity interference. Finally, the adaptive estimation signal for constant velocity interference inertia is superimposed to obtain the overall adaptive identification signal for constant velocity interference parameters, as follows: ； ； ； ； ； ； in The signal is the pitch speed of the unmanned surface vessel. This is the bow roll rate signal of the unmanned surface vessel; The desired oscillation speed signal for the unmanned surface vessel; This is the sway velocity error signal for the unmanned surface vessel; The differential operator for the transfer function of the inertial delay element; This is a nonlinear signal representing the oscillation velocity error. , and These are constant parameters for nonlinear transformations; The time parameter of the inertial delay element is a constant; For constant velocity disturbance inertial adaptive estimation signal; For constant velocity disturbance iterative adaptive rate signal; For constant velocity disturbance, iterative adaptive estimation signal, , This is a constant parameter signal used to adjust the speed of adaptive iteration; This is the iteration period parameter, and it is a constant. Adaptive identification of the total signal for constant velocity interference parameters; Step S20: Based on the aforementioned nonlinear signal of sway velocity error, the sway velocity signal of the unmanned surface vessel (USV), and the yaw rate signal, an inertial adaptive estimation signal for translational-rotational coupling interference is obtained through an inertial delay circuit. Then, based on the aforementioned sway velocity error signal, the nonlinear signal of sway velocity error, and the yaw rate signal of the USV, a nonlinear combination is performed to obtain the iterative adaptive rate signal for translational-rotational coupling interference. This is then integrated and iterated to obtain the iterative adaptive estimation signal for translational-rotational coupling interference. Finally, the translational-rotational coupling interference inertial adaptive estimation signal is superimposed to obtain the overall adaptive identification signal for the translational-rotational coupling interference parameters, as follows: ； ； ； ； in For the adaptive estimation signal of translational-rotational coupled disturbance inertia; For translational-rotational coupling interference iterative adaptive rate signal, For iterative adaptive estimation of translational-rotational coupling interference signals; Adaptive identification of the total signal for translational-rotational coupling interference parameters; , This is a constant parameter signal used to adjust the speed of adaptive iteration; Step S30: Based on the aforementioned nonlinear signal of the sway velocity error and the sway velocity signal of the unmanned surface vessel (USV), an inertial adaptive estimation signal for translational disturbance is obtained through an inertial delay circuit. Then, the aforementioned sway velocity error signal, the nonlinear signal of the sway velocity error, the sway velocity signal of the USV, and the yaw rate signal are nonlinearly combined to obtain an iterative adaptive rate signal for translational disturbance. This rate signal is then integrated and iterated to obtain an iterative adaptive estimation signal for translational disturbance. Finally, the translational disturbance inertial adaptive estimation signals are superimposed to obtain the overall adaptive identification signal for translational disturbance parameters, as follows: ； ； ； ； in For adaptive estimation of translational disturbance inertial signals; For translational disturbance iterative adaptive rate signal, Iterative adaptive estimation of the signal for translational disturbance; Adaptive identification of the total signal for translational interference parameters; , This is a constant parameter signal used to adjust the speed of adaptive iteration for translational disturbances; Step S40: The sway velocity error signal and the sway velocity error nonlinear signal are combined and integrated to obtain the velocity error combined integral signal; then, the velocity error approximate differential signal is solved based on the velocity constant disturbance inertial adaptive estimation signal and the sway velocity error nonlinear signal; finally, the sway velocity error signal, the velocity error combined integral signal, and the velocity error approximate differential signal are superimposed on the velocity constant disturbance parameter adaptive identification total signal, the translational rotational coupling disturbance parameter adaptive identification total signal, and the translational disturbance parameter adaptive identification total signal to obtain the final sway thrust signal, which is then sent to the unmanned surface vessel propulsion system to achieve precise tracking and control of the desired velocity of the unmanned surface vessel as follows: ； ； ； in The velocity error is a combined integral signal; It is a constant parameter; This is the approximate differential signal of the velocity error; For oscillation propulsion signal, , , These are constant control parameters.

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