A regional control-based offshore unmanned surface vehicle dynamic positioning method

Abstract

The application provides a marine unmanned surface vehicle power positioning method based on regional control, which comprises the following steps: flow direction estimation of an inner ring region, closing a propulsion system, making the unmanned surface vehicle in a natural drifting state under the joint action of sea waves and sea currents, obtaining the drifting speed of the unmanned surface vehicle through a GNSS system, and separating high-frequency sea wave disturbance and low-frequency sea current speed components based on a Kalman filter algorithm, so that the real-time estimation of the sea current direction is realized; current resistance control of a transition region, calculating the heading error and longitudinal displacement error, setting the heading error tolerance threshold and the position inner and outer threshold, and dynamically adjusting the propeller output through a top current control algorithm; and track control of an outer ring region, wherein the system corrects the propulsion direction through feedforward compensation according to the flow direction estimation result, so that the compensation of the water flow disturbance is realized. The application significantly improves the positioning accuracy and operation stability of the unmanned surface vehicle in complex sea conditions.

Description

Technical Field

[0001] This invention relates to the field of ship control technology, and specifically to a dynamic positioning method for unmanned surface vessels (USVs) based on area control. Background Technology

[0002] In recent years, with the rapid growth in demand for marine development and intelligent surface operations, unmanned surface vessels (USVs), as efficient autonomous operating platforms, have been widely used in various fields such as marine environmental monitoring, resource surveys, and maritime safety patrols. The complex and ever-changing marine environment, with its multiple disturbances including wind, waves, tides, and swells, poses significant challenges to the motion control of USVs. Especially in strong currents or variable flow fields, traditional anchoring positioning methods are insufficient to guarantee the stability and operational efficiency of USVs, severely hindering their widespread application.

[0003] Dynamic positioning technology, as the core technology for unmanned surface vessels (USVs) to achieve autonomous positioning without anchoring assistance, relies on real-time perception of environmental disturbances and hull status. Through dynamic adjustments to the propulsion system and servo motors, it ensures that the USV can continuously maintain or return to its target position. Most existing dynamic positioning technologies employ a global target-point-centric control strategy, failing to distinguish between the spatial differences between the hull's location and flow field disturbances, always using the target point as the control reference. This control method has significant shortcomings in real-world marine environments: firstly, the system fails to flexibly adjust the control strategy according to the intensity and direction of water flow in space, continuously outputting control commands even when the vessel is downstream or in an area with minimal disturbance, resulting in unnecessary energy consumption; secondly, to enhance current resistance, the system often relies on additional directional thrusters (commonly known as "head-up thrusters") at the bow, increasing system cost, structural complexity, and energy consumption, and negatively impacting the hull's appearance design, hindering the lightweight and integrated development requirements of USVs. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a dynamic positioning method for marine unmanned surface vessels (USVs) based on area control. This method divides the operational sea area into regions based on the relative distance between the USV and the target point, and combines this with current direction estimation results to employ targeted control strategies within different control regions. This allows the USV to adapt to environmental disturbances while achieving a balance between control accuracy and energy consumption, thereby improving the system's positioning robustness and overall energy efficiency.

[0005] To achieve the above objectives, this invention discloses a dynamic positioning method for unmanned surface vessels (USVs) based on area control, comprising the following steps:

[0006] Step S1, Estimation of the flow direction in the inner circle region, includes: turning off the propulsion system and allowing the unmanned surface vessel to drift naturally under the influence of waves and currents; collecting the velocity information of the unmanned surface vessel through GNSS; and using an unscented Kalman filter algorithm to separate the high-frequency disturbances caused by waves from the low-frequency velocity components corresponding to the currents, thereby obtaining an estimate of the current direction.

[0007] Step S2, flow control in the transition area, includes: calculating the heading error and longitudinal displacement error, and setting the heading error tolerance threshold, as well as the position threshold and the external threshold. Propulsion compensation is initiated only when at least one of the heading error and / or longitudinal displacement error exceeds the set range, and the adjustment stops after the unmanned surface vessel returns to the target range.

[0008] Step S3, track control in the outer ring area, includes: feedforward compensation of the propulsion direction based on the ocean current direction estimation results, introducing a rudder dead zone mechanism and rudder angle change limit in the heading control, and achieving track control through adaptive throttle adjustment combined with feedforward-feedback coupling.

[0009] Furthermore, step S1 involves acquiring the velocity data of the unmanned surface vessel in the NED coordinate system using GNSS, specifically as follows:

[0010] With the propulsion system shut off, the unmanned surface vessel (USV) was allowed to drift freely under the combined influence of waves and currents. Velocity observations were obtained via a GNSS system.

[0011] ;

[0012] in, and These represent the velocity components of the unmanned surface vessel along two orthogonal directions in the NED coordinate system at the current moment.

[0013] Furthermore, step S1 involves establishing a system state model that includes ocean current and wave disturbance components, and estimating the current direction using an unscented Kalman filter method, specifically as follows:

[0014] The system state vector of an unmanned surface vessel (USV) under free drifting conditions, disturbed by ocean currents and waves, is defined as... ,in, and Ocean currents in the NED coordinate system and Velocity component in the direction; and This represents the velocity component of the disturbance caused by ocean waves.

[0015] Assuming that the ocean current is approximately constant over a short period of time and the wave disturbance decays exponentially over time, the system state transition model and observation model can be expressed as follows:

[0016] ;

[0017] ；

[0018] in, The exponential decay factor representing high-frequency disturbances. For process noise, For measuring noise.

[0019] Based on the current state estimate and covariance matrix Generate a set of sigma points The Sigma points are then substituted into the state transition model and the observation model respectively for propagation to obtain the predicted state points and predicted observation points:

[0020] , ;

[0021] Therefore, the mean of the predicted state is calculated. Predicted state covariance Predicted Observation Mean Predicted observation covariance And the cross-covariance between the predicted state and the predicted observation. ,

[0022] And further, the Kalman gain is obtained:

[0023] ;

[0024] Finally, the system state and its covariance are updated to estimate the ocean current velocity component (low frequency) and the wave disturbance component (high frequency):

[0025] ;

[0026] Extract ocean current velocity components from the estimated state. and And calculate the direction of the ocean current (current angle) based on this:

[0027] ;

[0028] The value ranges from 0° to 360°, where 0° is due north. This value can be directly used for subsequent anti-flow control and attitude compensation.

[0029] Further, step S2 calculates the heading error and longitudinal displacement error, specifically as follows:

[0030] Based on the current direction of the sea area obtained in step S1 The target heading is defined as its opposite direction, that is:

[0031] ;

[0032] The current bow direction of the unmanned surface vessel is measured in real time by the inertial measurement unit and is denoted as . The heading error is defined as:

[0033] ;

[0034] Among them, the above The function is used to normalize the angle to arrive between;

[0035] Let the target location be The current location of the unmanned surface vessel is The unit direction vector of the target heading is Then the longitudinal displacement error is:

[0036] ;

[0037] in This reflects the degree of forward and backward deviation of the unmanned surface vessel in the direction of the target's bow. This indicates that the hull is located upstream of the target point. This indicates that the object was blown downstream of the target point by the water flow.

[0038] Furthermore, step S2, which initiates the propulsion compensation control strategy when the deviation exceeds the set range, specifically involves:

[0039] S21. Set the propulsion direction of the unmanned surface vessel to forward, i.e., control the thrusters to output positive thrust, so that the vessel moves upstream to the target point; at the same time, use the idle speed setting for the propulsion throttle to ensure that the rudder angle has a practical controllable effect; when the system detects a longitudinal displacement error of the unmanned surface vessel... When the outer threshold is exceeded, the condition is satisfied. When the current position is considered to have deviated from the acceptable range, the propulsion direction of the hull is set to forward, that is, the propeller is controlled to output positive thrust, so that the hull moves upstream to the target point; at the same time, the propulsion throttle is set to idle speed to ensure that the rudder angle has actual controllability.

[0040] S22. Synchronously activate the heading controller. The heading control uses a PID controller, and the control law is as follows:

[0041] ;

[0042] in This indicates the current heading error; the controller output is used to drive the rudder to stabilize the bow at the target heading.

[0043] S23. Continue executing the combined control of steps S21 and S22 until the following two stopping conditions are met: 1) The bow has returned to the target heading, i.e., the following conditions are met. , 1) The bow error tolerance threshold; 2) The longitudinal displacement of the hull has returned to an acceptable range, satisfying the requirements. , The inner threshold is set; once the conditions are met simultaneously, the throttle output is stopped, and the vehicle enters a no-power drift state until the longitudinal error exceeds the outer threshold again, at which point the heading control is reactivated.

[0044] Furthermore, step S3 performs feedforward compensation on the propulsion direction based on the ocean current direction estimation results, specifically as follows:

[0045] Based on the ocean current velocity vector estimated in step S1 Current location of the unmanned surface vessel and target location The unit direction vector pointing to the target position is calculated as follows:

[0046] ；

[0047] Based on this, ocean current direction compensation is introduced, and the actual controlled propulsion direction vector is constructed as follows:

[0048] ;

[0049] And calculate the control reference heading based on the propulsion direction vector:

[0050] ;

[0051] This allows the unmanned surface vessel to continue navigating towards its target location even under the influence of water currents. and These represent the components of the forward propulsion direction vector in the northeast coordinate system along the north (x-axis) and east (y-axis) axes, respectively.

[0052] Furthermore, step S3 introduces a rudder dead zone mechanism and rudder angle variation limit in directional control, specifically as follows:

[0053] Calculate the current heading of the unmanned surface vessel. With the reference bow Heading deviation between When the heading deviation is less than the preset dead zone threshold, i.e. The rudder angle remains constant to suppress frequent rudder adjustments caused by small disturbances; when the heading deviation exceeds the dead zone threshold, a proportional-integral-derivative control method is used to generate a rudder angle command, the control law of which is expressed as follows:

[0054] ;

[0055] By limiting function A rate-of-change constraint is introduced for the rudder angle output, and its update method is as follows:

[0056] ;

[0057] in, This represents the maximum change in rudder angle. The rudder angle value output by the controller at the current moment. This is the actual rudder angle value at the previous moment.

[0058] Furthermore, step S3 achieves trajectory control through adaptive throttle adjustment combined with feedforward-feedback coupling, specifically as follows:

[0059] Based on the distance between the unmanned surface vessel and the target location The base throttle is set and calculated as follows:

[0060] ;

[0061] in, This is the minimum throttle setting, used to ensure the unmanned surface vessel's basic propulsion capability. This is the maximum throttle, corresponding to the maximum value that the propulsion system is allowed to output. This is the distance weighting coefficient. Based on this, a combination of feedforward and feedback is used to correct the base throttle, and its control law is:

[0062] ；

[0063] in, As a feedforward term, the throttle is dynamically compensated based on the water flow intensity to improve the anti-disturbance capability; This is a feedback item used to correct the current path deviation. (To reduce lateral deviation), thereby improving tracking stability.

[0064] On the other hand, the present invention provides a dynamic positioning method for unmanned surface vessels based on area control, comprising: at least one processor, and at least one memory communicatively connected to the processor, wherein the memory stores area control program instructions executable by the processor, and the processor can execute the above-mentioned dynamic positioning method by calling the program instructions.

[0065] On the other hand, the present invention provides a non-transitory computer-readable storage medium storing computer instructions that cause the computer to execute the above-described dynamic positioning method.

[0066] The beneficial effects of the above-described technical solution of the present invention are as follows:

[0067] This invention integrates flow direction estimation and zoned control strategies to achieve accurate flow direction estimation in the inner zone, efficient anti-current control in the transition zone, and reliable track return in the outer zone, significantly improving the positioning accuracy and operational stability of unmanned surface vessels in complex sea conditions. Attached Figure Description

[0068] Figure 1 This is a schematic diagram of the dynamic positioning method for unmanned surface vessels based on regional control according to the present invention.

[0069] Figure 2 This is a flowchart of the dynamic positioning method for unmanned surface vessels based on area control according to the present invention. Detailed Implementation

[0070] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0071] This invention provides a dynamic positioning method for unmanned surface vessels (USVs) based on area control, mainly including: ① current direction estimation in the inner region; ② current control in the transition region; ③ trajectory control in the outer region. Specifically, the USV's trajectory is determined by the radius of the target point. Within the radius, the main focus is on accurately estimating the direction of environmental flow, without implementing active control, to ensure accurate collection of disturbance information; when the unmanned surface vessel's position is within the radius... With radius During the transition zone, the system will dynamically adjust the thruster output through a top-current control algorithm to effectively counteract water flow disturbances and significantly extend the stable dwell time of the unmanned surface vessel in the target area; if the unmanned surface vessel's position exceeds the radius... In the target area, the system performs feedforward compensation on the propulsion direction based on the ocean current direction estimation results, and dynamically adjusts the thruster output power by combining the distance deviation feedback value between the unmanned surface vessel and the target point. The method proposed in this invention effectively integrates water flow disturbance estimation and regional control mechanisms, significantly improving the autonomous positioning and anti-disturbance performance of marine unmanned surface vessels in complex sea conditions, and meeting the requirements of high-precision and high-efficiency marine operations.

[0072] The specific steps of this invention include:

[0073] ① Estimation of flow direction in the inner circle region ( ),include:

[0074] a. Turn off the propulsion system and allow the unmanned surface vessel to drift naturally under the combined action of waves and currents, and collect the velocity information of the unmanned surface vessel in the flow field through the GNSS system;

[0075] b. Based on the unscented Kalman filter algorithm, high-frequency wave disturbances and low-frequency ocean current velocities are separated, and the direction of the ocean current is extracted.

[0076] ② Flow control in the transition zone ( ),include:

[0077] a. Calculate heading error With longitudinal displacement error And set the heading error tolerance threshold. and location threshold and outer threshold ;

[0078] b. Use a joint control strategy when the heading error exceeds the tolerance threshold (e.g.) And longitudinal displacement Exceeding the outer threshold (e.g.) Propulsion compensation is activated until the heading error decreases and the longitudinal displacement... Return to the inner threshold (e.g.) Stop, reduce frequent adjustments, and achieve energy-saving and stable position maintenance.

[0079] ③ Track control in the outer ring area ( ),include:

[0080] a. Based on the estimated ocean current direction, the propulsion direction is corrected through feedforward compensation to compensate for water flow disturbance;

[0081] b. Introduce a rudder dead zone strategy and rudder angle change limit to achieve low-frequency control output and avoid energy consumption and mechanical wear caused by high-frequency rudder behavior;

[0082] c. The propulsion power is dynamically adjusted according to the target distance, and adaptive amplitude limiting is performed in strong current environments. Combined with feedforward and feedback strategies, stable and low-power trajectory control is achieved.

[0083] The schematic diagram and flowchart of this invention are as follows: Figure 1 and Figure 2 As shown, the details of the method of the present invention will be described below.

[0084] 1. Estimation of flow direction in the inner circle

[0085] 1.1 Drift Data Sampling and State Modeling

[0086] After the dynamic positioning system is activated, the unmanned surface vessel (USV) will first enter the current estimation phase. During this phase, the USV is in a powerless state, meaning that the electronic throttle and servo systems stop outputting control commands, and the hull drifts freely only under the influence of water dynamics, wind loads, and inertia.

[0087] First, a system state vector containing ocean current (low frequency) and ocean wave (high frequency) components is constructed based on the Earth-Fixed Coordinate System (NED):

[0088] ;

[0089] in, and Ocean currents in the NED coordinate system and Velocity component in the direction; and This represents the velocity component of the disturbance caused by ocean waves.

[0090] Next, assuming that the ocean current remains approximately constant over a short period of time, while the wave disturbance decays exponentially, the nonlinear state transition function is defined as follows:

[0091] ;

[0092]

[0093] in, The exponential decay factor representing high-frequency disturbances. For process noise with zero mean and Gaussian distribution, the covariance matrix is ​​denoted as... .

[0094] Finally, the unmanned surface vessel can obtain its velocity observations in the NED coordinate system via a GNSS system, therefore the observation equations can be constructed as follows:

[0095] ;

[0096] in, The speed value is the actual speed observed by the unmanned surface vessel. For the observation function, Measurement noise with zero mean and Gaussian distribution, and covariance of . .

[0097] 1.2 Estimation of ocean current and wave components based on unscented Kalman filtering:

[0098] Based on the unmanned surface vessel velocity observations and corresponding observation equations obtained in step 1.1, the system state is estimated using an unscented Kalman filter (UKF). The main steps are as follows:

[0099] First, based on the average state at the current moment. Covariance ,generate sigma points:

[0100] ;

[0101] ;

[0102] ;

[0103] in ， For the first matrix List, Let be the state dimension. For UKF filter coefficients, and This is the adjustment coefficient for the UKF filter, used to control the distribution range of sigma points.

[0104] Next, for each sigma point Input the state transition function respectively The predicted state sigma point is obtained. Then input the predicted state sigma point into the observation function. The predicted observation sigma points in the observation space are obtained. Meanwhile, the predicted state mean and covariance are calculated as follows:

[0105] ;

[0106] ;

[0107] The predicted mean and covariance of the observed states are:

[0108] ;

[0109] ;

[0110] in, For a weighting system used to estimate the mean, These are the weighting coefficients used to estimate the covariance. Furthermore, the cross-covariance matrix between the predicted state and the predicted observations is:

[0111] ;

[0112] Finally, the Kalman gain is calculated based on the predicted covariance and cross-covariance matrices:

[0113] ;

[0114] Using actual observations Update the calculation of Kalman gain, state equation, and covariance matrix:

[0115] ;

[0116] ;

[0117] 1.3 Output ocean current direction

[0118] Extract ocean current velocity components from the estimated state. and Therefore, the direction of the ocean current (current angle) can be calculated as follows:

[0119] ;

[0120] The value ranges from 0° to 360°, where 0° is due north. This value can be directly used for subsequent anti-flow control and attitude compensation.

[0121] 2. Flow control in the transition zone

[0122] 2.1 Definitions of heading error, longitudinal displacement error, and control threshold

[0123] When the unmanned surface vessel is in the transition zone between the "inner circle" and the "outer circle" ( When the bow is aligned with the opposite direction of the water flow, the primary objective is to maintain the position within a certain tolerance range. Considering the dynamic characteristics of the ship's propulsion system, namely that the generation of steering torque strictly depends on the power output provided by the propulsion system, the system needs to adopt a coordinated control strategy to achieve synchronous optimization of bow adjustment and position compensation.

[0124] Based on the current direction of the sea area obtained in step 1.3 The target heading is defined as its opposite direction, that is:

[0125] ;

[0126] The current bow direction of the unmanned surface vessel is measured in real time by the IMU (Inertial Measurement Unit), denoted as . Therefore, heading error can be defined as:

[0127] ;

[0128] in, The function is used to normalize the angle to arrive Ensure continuity in angle processing between them.

[0129] Let the target location be The current location of the unmanned surface vessel is The unit direction vector of the target heading is Therefore, the longitudinal position error (the offset along the bow direction of the target) is:

[0130] ;

[0131] This value reflects the degree of forward and backward deviation of the unmanned surface vessel in the direction of the target's bow. This indicates that the hull is located "upstream" of the target point. This indicates that the object was "blown" downstream of the target point by the water flow.

[0132] 2.2 Key Threshold Settings

[0133] To enhance system robustness and energy efficiency, this strategy designs three key thresholds: the heading error tolerance threshold. Typical value set to 30°; Position control with dual thresholds: inner threshold External threshold This value satisfies ,For example: , .

[0134] 2.3 Joint Control Strategy Design

[0135] When the system detects that the unmanned surface vessel has been blown downstream of the target point by the water flow, i.e., longitudinal displacement error Exceeding the outer threshold ( When the current position is deemed to have deviated from an acceptable range, the system will enter a joint heading and position adjustment state to achieve the return of the ship's position and synchronous correction of the heading. In this state, the controller performs the following operations:

[0136] First, set the propulsion direction to forward, that is, control the thrusters to output positive thrust, so that the hull moves slowly upstream to the target point. At the same time, use the idle speed setting for the propulsion throttle to ensure that the rudder angle has a real controllable effect.

[0137] Next, the system synchronously activates the azimuth controller to ensure the bow remains stably against the current. The azimuth control uses a PID controller, with the following control law:

[0138] ;

[0139] in This indicates the current heading error. The controller output is used to drive the rudder to stabilize the bow at the target heading.

[0140] The system continues to execute the above joint control until the following two stopping conditions are met: 1) The bow has returned to the target heading, i.e., the following conditions are met. ;2) The longitudinal displacement of the hull has returned to an acceptable range, satisfying the requirements. Once the above conditions are met simultaneously, the system will stop throttle output and enter a powerless drift state until the longitudinal error exceeds the outer threshold again, at which point the heading control will be reactivated.

[0141] Furthermore, to prevent the system from frequently entering and exiting the control zone at the boundary, resulting in frequent start-ups and shutdowns of the propulsion system, the control logic incorporates a hysteresis mechanism and a state-maintaining strategy. The control process is only reactivated when the deviation continues to exceed the limit for a certain period of time, thereby improving energy efficiency and control stability.

[0142] 3. Track control in the outer ring area

[0143] 3.1 Feedforward propulsion direction compensation based on ocean current information

[0144] The ocean current velocity vector for the current sea area can be obtained from step 1. Based on this, let the current position of the unmanned surface vessel be... The target location is Therefore, the unit vector of the target's propulsion direction can be obtained as:

[0145] ；

[0146] To overcome water flow disturbance, the system calculates the anti-current yaw angle based on the current current velocity vector and the desired direction, ensuring that the propulsion direction remains aligned with the target point despite water flow disturbance. First, the actual controlled propulsion direction vector is calculated:

[0147] ;

[0148] Next, calculate the anti-current yaw angle:

[0149] ;

[0150] in, For the controller reference heading, and These represent the components of the propulsion direction vector in the north (x-axis) and east (y-axis) directions, respectively, in the northeast coordinate system. Essentially, this method improves track stability by introducing an ocean current compensation model into the control pre-processing stage, reducing the range of angular errors that need to be corrected in the subsequent feedback system.

[0151] 3.2 Introducing a rudder dead zone control mechanism and limiting rudder angle changes

[0152] The core idea of ​​rudder dead zone control is to maintain a constant rudder angle within a small heading error, avoiding frequent rudder angle adjustments caused by minor disturbances. Let the current heading be... Feedforward reference heading is The heading error is ,when When the dead zone threshold is reached, the rudder angle remains constant. This mechanism can effectively shield against high-frequency small disturbances and improve the steady-state performance of the system.

[0153] When the error exceeds the dead zone, PID control is activated, and the specific control law is as follows:

[0154] ;

[0155] To prevent rudder angle jumps, the system further introduces a rate-of-change limiter:

[0156] ;

[0157] in, This represents the maximum change in rudder angle. The rudder angle value output by the controller at the current moment. This is the actual rudder angle value at the previous moment.

[0158] With the above strategy, the system only performs rudder control when the heading deviates significantly from the desired direction, and outputs rudder angle commands in a slowly changing manner, reducing the load on the servo motor and improving rudder control efficiency.

[0159] 3.2 Achieving adaptive throttle adjustment and feedforward-feedback coupled control

[0160] Based on the distance between the unmanned surface vessel (USV) and the target point, as well as the current water flow conditions, the throttle of the USV is adaptively adjusted to achieve energy-saving navigation and stable control.

[0161] First, the system determines the current location of the unmanned surface vessel. With the target point Distance between Set the base throttle:

[0162] ；

[0163] in, This is the minimum throttle setting, used to ensure the unmanned surface vessel's basic propulsion capability. This is the maximum throttle, corresponding to the maximum value that the propulsion system is allowed to output. This is the distance weighting coefficient. The function exhibits exponential growth characteristics, reflecting the energy-saving control logic of increasing throttle at long distances and gradually decreasing throttle at close distances. This ensures rapid return to the target while suppressing overshoot and fuel waste when approaching the target.

[0164] Next, in strong current conditions, throttle limiting and control frequency adjustment are implemented. Specifically, if the current ocean current speed is detected... Exceeding the set threshold If this condition is met, the system is determined to be in a high-current state. To prevent the thruster from operating at full load for extended periods, which could lead to a surge in energy consumption or equipment damage, the throttle output will be limited to:

[0165] ,when ;

[0166] in, This represents the upper limit of the safe throttle for the propulsion system under strong current conditions. Simultaneously, to improve propulsion efficiency, the system no longer simply points the propulsion direction towards the target point, but instead reconfigures the propulsion direction, causing it to deflect at a certain angle relative to the current current direction (oblique convection propulsion):

[0167] ;

[0168] in This is the disturbance compensation ratio. In this way, the unmanned surface vessel (USV) can obtain an effective reverse propulsion component at lower throttle output, thereby improving control performance and reducing energy consumption.

[0169] Finally, to further enhance the system's response to external disturbances and path tracking accuracy, the control system introduces a feedforward-feedback coupling mechanism to adjust the base throttle. Make corrections:

[0170] ；

[0171] in, As a feedforward term, the throttle is dynamically compensated based on the water flow intensity to improve the anti-disturbance capability; This is a feedback item used to correct the current path deviation. (To reduce lateral deviation), thereby improving tracking stability.

[0172] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A regional control based method for dynamic positioning of an offshore unmanned surface vehicle, characterized in that, Includes the following steps: Step S1, Estimation of the flow direction in the inner circle region, includes: turning off the propulsion system and allowing the unmanned surface vessel to drift naturally under the influence of waves and currents; collecting the velocity data of the unmanned surface vessel in the NED coordinate system through GNSS; establishing a system state model that includes the components of ocean currents and wave disturbances; and estimating the ocean current direction using the unscented Kalman filter method. Step S2, flow control in the transition area, includes: calculating the heading error and longitudinal displacement error, and setting the heading error tolerance threshold, as well as the position threshold and the external threshold. Propulsion compensation is initiated only when at least one of the heading error and / or longitudinal displacement error exceeds the set range, and the adjustment stops after the unmanned surface vessel returns to the target range. Step S3, track control in the outer ring region, includes: feedforward compensation of the propulsion direction based on ocean current direction estimation results; introducing a rudder dead zone mechanism and rudder angle variation limit in heading control; and achieving track control through adaptive throttle adjustment combined with feedforward-feedback coupling. Specifically, achieving track control through adaptive throttle adjustment combined with feedforward-feedback coupling involves: According to the distance between the unmanned ship and the target position Setting base throttle The calculation method is: ； wherein, is the minimum throttle, used to ensure the basic propulsion ability of the unmanned ship, is the maximum throttle, corresponding to the maximum value allowed by the propulsion system output, is the distance weight coefficient, on this basis, the basic throttle is corrected in a combination of feedforward and feedback, and the control law is: ； wherein, is a feed-forward term, dynamically compensating the throttle according to the water flow intensity, improving the anti-disturbance ability; is a feedback term, used to correct the current path deviation, wherein is a lateral deviation, improving the tracking stability.

2. The regional control based dynamic positioning method for offshore unmanned surface vehicle according to claim 1, characterized in that, Step S1 involves acquiring velocity data of the unmanned surface vessel in the NED coordinate system using GNSS, specifically as follows: The propulsion system is shut down, allowing the unmanned surface vessel (USV) to drift freely under the combined influence of waves and currents. Velocity observations are obtained via a GNSS system, and these velocity observations are expressed as follows: ； wherein, with are the velocity components of the USV along the two orthogonal directions of the NED coordinate system at the current time instant.

3. The regional control based dynamic positioning method for offshore unmanned surface vehicle according to claim 2, characterized in that, Step S1 establishes a system state model including ocean current and wave disturbance components, and uses the unscented Kalman filter method to estimate the ocean current direction, specifically: The system state vector of the unmanned surface vehicle under the disturbance of the sea current and the sea wave in the free drifting state is defined as wherein, and are the velocity components of the sea current in the directions of and respectively in the NED coordinate system; and are the disturbance velocity components caused by the sea wave; Assuming that the ocean current is approximately constant over a short period of time and the wave disturbance decays exponentially over time, the system state transition model and observation model are expressed as follows: ； ； in, The exponential decay factor representing high-frequency disturbances. For process noise, For measuring noise; Based on the current state estimate and covariance matrix Generate a set of sigma points The sigma points are then substituted into the state transition model and the observation model for propagation to obtain the predicted state points and predicted observation points: , ； Therefore, the mean of the predicted state is calculated. Predicted state covariance Predicted Observation Mean Predicted observation covariance And the cross-covariance between the predicted state and the predicted observation. , And further, the Kalman gain is obtained: ； Finally, the system state and its covariance are updated to estimate the ocean current velocity components and wave disturbance components. ； Extract ocean current velocity components from the estimated state. and And calculate the direction of the ocean current based on this: ； The value ranges from 0° to 360°, where 0° is due north. This value can be directly used for subsequent anti-flow control and attitude compensation.

4. The dynamic positioning method for unmanned surface vessels based on area control according to claim 3, characterized in that, Step S2 calculates the heading error and longitudinal displacement error, specifically as follows: Based on the current direction of the sea area obtained in step S1 The target heading is defined as its opposite direction, that is: ； The current bow direction of the unmanned surface vessel is measured in real time by the inertial measurement unit and denoted as . The heading error is defined as: ； Among them, the above The function is used to normalize the angle to arrive between; Let the target location be The current location of the unmanned surface vessel is The unit direction vector of the target heading is Then the longitudinal displacement error is: ； in This reflects the degree of forward and backward deviation of the unmanned surface vessel in the direction of the target's bow. This indicates that the hull is located upstream of the target point. This indicates that the object was blown downstream of the target point by the water flow.

5. The dynamic positioning method for unmanned surface vessels based on area control according to claim 4, characterized in that, Step S2, which initiates the propulsion compensation control strategy when the deviation exceeds the set range, specifically involves: S21. When the system detects longitudinal displacement error of the unmanned surface vessel When the outer threshold is exceeded, the condition is satisfied. When the current position is considered to have deviated from the acceptable range, the propulsion direction of the hull is set to forward, that is, the propeller is controlled to output positive thrust, so that the hull moves upstream to the target point; at the same time, the propulsion throttle is set to idle speed to ensure that the rudder angle has actual controllability. S22. Synchronously activate the heading controller. The heading control uses a PID controller, and the control law is as follows: ； in This indicates the current heading error; the controller output is used to drive the rudder to stabilize the bow at the target heading. S23. Continue executing the combined control of steps S21 and S22 until the following two stopping conditions are met: 1) The bow has returned to the target heading, i.e., the following conditions are met. , 1) The bow error tolerance threshold; 2) The longitudinal displacement of the hull has returned to an acceptable range, satisfying the requirements. , The inner threshold is set; once the conditions are met simultaneously, the throttle output is stopped, and the vehicle enters a no-power drift state until the longitudinal error exceeds the outer threshold again, at which point the heading control is reactivated.

6. The dynamic positioning method for unmanned surface vessels based on area control according to claim 1, characterized in that, Step S3 involves feedforward compensation of the propulsion direction based on the ocean current direction estimation results, specifically as follows: Based on the ocean current velocity component estimated in step S1 Current location of the unmanned surface vessel and target location The unit direction vector pointing to the target position is calculated as follows: ； Based on this, ocean current direction compensation is introduced, and the actual controlled propulsion direction vector is constructed as follows: ； The control reference heading is calculated based on the propulsion direction vector. ； This enables the unmanned surface vessel to continue navigating toward its target location even under the influence of water currents, among which... and These represent the northward and eastward components of the propagation direction vector in the northeast coordinate system.

7. The dynamic positioning method for unmanned surface vessels based on area control according to claim 6, characterized in that, Step S3 introduces a rudder dead zone mechanism and rudder angle variation limit in directional control, specifically as follows: Calculate the current heading of the unmanned surface vessel. With the reference bow Heading deviation between When the heading deviation is less than the preset dead zone threshold, i.e. The rudder angle remains constant; when the heading deviation exceeds the dead zone threshold, a proportional-integral-derivative control method is used to generate a rudder angle command, the control law of which is expressed as: ； And through the limiting function The rate of change of the rudder angle output is limited, and its update method is as follows: ； in, This represents the maximum change in rudder angle. The rudder angle value output by the controller at the current moment. This is the actual rudder angle value at the previous moment.

8. A dynamic positioning method for unmanned surface vessels (USVs) based on area control, comprising: At least one processor, and at least one memory communicatively connected to the processor, wherein the memory stores region control program instructions executable by the processor, and the processor invokes the program instructions to execute the dynamic positioning method according to any one of claims 1 to 7.

9. A non-transitory computer-readable storage medium storing computer instructions that cause the computer to perform the dynamic positioning method according to any one of claims 1 to 7.

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