Underwater glider trajectory tracking control method based on flow field reconstruction and electronic device

Abstract

The application provides an underwater glider trajectory tracking control method based on flow field reconstruction and an electronic device, and can be applied to the technical field of underwater glider control. The method comprises the following steps: based on the historical ejection point position of the underwater glider on a historical gliding profile, reconstructing the historical observation data of the underwater glider on the historical gliding profile by using a linear distribution method to obtain a historical horizontal position reconstruction sequence; the historical horizontal position reconstruction sequence is used as prior knowledge for disturbance prediction to obtain a disturbance estimation sequence of the underwater glider in a to-be-gliding profile, wherein the to-be-gliding profile is adjacent to the historical gliding profile, and the to-be-gliding profile is after the historical gliding profile; based on the disturbance estimation sequence, a target trajectory of the underwater glider in the to-be-gliding profile is determined; and the underwater glider is controlled to glide according to the target trajectory.

Description

Technical Field

[0001] This application relates to the field of underwater glider control technology, and more specifically, to an underwater glider trajectory tracking control method and electronic device based on flow field reconstruction. Background Technology

[0002] Underwater gliders glide in the ocean using a zigzag trajectory. Each zigzag motion (i.e., a dive and a surfacing motion) can be considered a profile. Through this zigzag motion, the marine environment can be observed and explored. However, current underwater trajectory tracking and control methods cannot simultaneously address both gliding energy consumption and trajectory control accuracy. Summary of the Invention

[0003] In view of this, embodiments of this application provide an underwater glider trajectory tracking control method and electronic device based on flow field reconstruction.

[0004] One aspect of this application provides a trajectory tracking control method for an underwater glider based on flow field reconstruction, comprising: reconstructing historical observation data of the underwater glider in a historical gliding profile using a linear assignment method based on the historical water exit point position of the underwater glider in a historical gliding profile, to obtain a historical horizontal position reconstruction sequence; using the historical horizontal position reconstruction sequence as prior knowledge to perform disturbance prediction, to obtain a disturbance estimation sequence of the underwater glider in a gliding profile to be glided, wherein the gliding profile to be glided is adjacent to the historical gliding profile and is after the historical gliding profile; determining the target trajectory of the underwater glider in the gliding profile to be glided based on the disturbance estimation sequence; and controlling the underwater glider to glide according to the target trajectory.

[0005] Another aspect of this application provides an electronic device, including: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method described above.

[0006] According to an embodiment of this application, based on the historical water exit point position of the underwater glider in a historical gliding profile, a historical horizontal position reconstruction sequence is obtained by reconstructing historical observation data using the linear assignment method. This historical horizontal position reconstruction sequence is then used as prior knowledge for perturbation prediction to obtain the perturbation estimation sequence of the underwater glider in the next gliding profile. This allows the determination of the underwater glider's target trajectory, and the underwater glider can be controlled to glide based on this target trajectory. This method fully utilizes historical data from the underwater glider in historical gliding profiles to construct the historical horizontal position reconstruction sequence. It eliminates the need for the underwater glider to obtain real-time underwater current velocity through high-power sensors. Furthermore, the marine environment exhibits spatiotemporally gradual changes, so changes in current velocity have little impact on the accuracy of the reconstructed historical horizontal position. By further using the historical horizontal position reconstruction sequence as prior knowledge for perturbation prediction, the target trajectory of the underwater glider in the gliding profile can be obtained. Since the target trajectory takes into account perturbation factors, its accuracy is also improved, and the gliding cost within the target trajectory can be accurately determined. Controlling the underwater glider's gliding trajectory based on the target trajectory can also make the gliding trajectory and gliding cost of the underwater glider controllable. Attached Figure Description

[0007] The above and other objects, features and advantages of this application will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0008] Figure 1 An exemplary system architecture is shown that can be applied to the underwater glider trajectory tracking control method and electronic device based on flow field reconstruction according to embodiments of this application.

[0009] Figure 2 A flowchart of an underwater glider trajectory tracking control method based on flow field reconstruction according to an embodiment of this application is shown.

[0010] Figure 3 A block diagram of an underwater glider trajectory tracking control device based on flow field reconstruction according to an embodiment of this application is shown.

[0011] Figure 4 A block diagram of an electronic device suitable for implementing the methods described above, according to an embodiment of this application, is shown. Detailed Implementation

[0012] The embodiments of this application will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of this application. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of this application for ease of explanation. However, it will be apparent that one or more embodiments may be implemented without these specific details. Furthermore, descriptions of well-known structures and technologies are omitted in the following description to avoid unnecessarily obscuring the concepts of this application.

[0013] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of this application. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0014] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0015] When using expressions such as "at least one of A, B and C", they should generally be interpreted in accordance with the meaning that is commonly understood by those skilled in the art (e.g., "a system having at least one of A, B and C" should include, but is not limited to, a system having A alone, a system having B alone, a system having C alone, a system having A and B, a system having A and C, a system having B and C, and / or a system having A, B and C, etc.).

[0016] In the embodiments of this application, the collection, updating, analysis, processing, use, transmission, provision, disclosure, and storage of data (e.g., including but not limited to user personal information) comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures have been taken to prevent unauthorized access to user personal information data and to safeguard user personal information security and network security.

[0017] In the embodiments of this application, the user's authorization or consent was obtained before obtaining or collecting the user's personal information.

[0018] The trajectory tracking of underwater gliders mainly employs either proportional-integral-derivative (PID) control based on real-time error feedback or linear quadratic regulator control (LQR) based on a small-disturbance linearized model. The former lacks a feedforward sensing mechanism for the environmental flow field, relying solely on passive, large-angle disturbance rejection based on lagging position deviations, leading to frequent actuator movements and significant energy consumption. The latter, while utilizing some dynamic information, suffers from a lack of description of the strong coupling and nonlinear characteristics of the underwater glider by the linearized model, resulting in a sharp decline in control accuracy under large disturbance conditions. Furthermore, these methods typically employ stabilization strategies that forcibly eliminate yaw errors, lacking the ability to proactively utilize ocean current fields for energy-saving planning. Additionally, the engineering challenge of continuously operating high-power Doppler current profilers to obtain real-time flow velocities makes it impossible to effectively utilize historical flow field information to achieve predictive control that balances energy efficiency and accuracy under underactuated and computationally limited constraints.

[0019] In view of this, embodiments of this application provide an underwater glider trajectory tracking and control method based on flow field reconstruction. Based on the historical water exit point position of the underwater glider in a historical gliding profile, a linear assignment method is used to reconstruct the historical observation data to obtain a historical horizontal position reconstruction sequence. This historical horizontal position reconstruction sequence is then used as prior knowledge for disturbance prediction, yielding a disturbance estimation sequence for the underwater glider in the next gliding profile. This allows the determination of the underwater glider's target trajectory, and the glider can be controlled to glide based on this target trajectory. This method fully utilizes historical data from the underwater glider in historical gliding profiles to construct the historical horizontal position reconstruction sequence. It eliminates the need for the underwater glider to acquire real-time underwater flow velocity through high-power sensors. Furthermore, the marine environment exhibits spatiotemporally gradual changes, so flow velocity variations have minimal impact on the accuracy of the reconstructed historical horizontal position. By further using the historical horizontal position reconstruction sequence as prior knowledge for disturbance prediction, the target trajectory of the underwater glider in the gliding profile can be obtained. Since the target trajectory considers disturbance factors, its accuracy is improved, and the gliding cost within the target trajectory can be accurately determined. Controlling the underwater glider's gliding trajectory based on the target trajectory can also make the gliding trajectory and gliding cost of the underwater glider controllable.

[0020] Figure 1 An exemplary system architecture is shown, according to embodiments of this application, in which an underwater glider trajectory tracking control method and electronic equipment based on flow field reconstruction can be applied. It should be noted that... Figure 1The examples shown are merely examples of system architectures that can be applied to the embodiments of this application, in order to help those skilled in the art understand the technical content of this application, but do not mean that the embodiments of this application cannot be used in other devices, systems, environments or scenarios.

[0021] like Figure 1 As shown, the system architecture 100 according to this embodiment may include an underwater glider 110 and a network 120. The underwater glider 110 may include a glider processor 111. The network 120 is used as a medium to provide a communication link between the underwater glider 110 and surface equipment. The network 120 may include various connection types, such as wired and / or wireless communication links, etc. The glider processor 111 can be used to execute an underwater glider trajectory tracking control method based on flow field reconstruction for the underwater glider 110.

[0022] It should be understood that Figure 1 The number of underwater gliders and networks shown is merely illustrative. Any number of underwater gliders and networks can be used depending on implementation needs.

[0023] Figure 2 A flowchart of an underwater glider trajectory tracking control method based on flow field reconstruction according to an embodiment of this application is shown.

[0024] like Figure 2 As shown, the method includes operations S210 to S240.

[0025] In operation S210, based on the historical water exit point position of the underwater glider in the historical gliding profile, the historical observation data of the underwater glider in the historical gliding profile is reconstructed using the linear assignment method to obtain the historical horizontal position reconstruction sequence.

[0026] In operation S220, the historical horizontal position reconstruction sequence is used as prior knowledge for perturbation prediction, resulting in the perturbation estimation sequence of the underwater glider in the gliding profile.

[0027] In operation S230, the target trajectory of the underwater glider in the gliding profile is determined based on the perturbation estimation sequence.

[0028] When operating the S240, control the underwater glider to glide according to the target trajectory.

[0029] While gliding underwater, underwater gliders cannot establish communication with surface equipment. Therefore, surface equipment cannot obtain real-time positioning signals from the underwater glider during its glide; communication is only possible after the glider emerges from the water to determine its position at the surfacing point. In a historical gliding profile, the gliding maneuvers of an underwater glider can sequentially include sinking and surfacing maneuvers. The historical surfacing point is the position of the underwater glider on the water after the surfacing maneuver within that historical gliding profile. The gliding environment of an underwater glider can be a marine environment. The historical surfacing point can be a location obtained based on the Global Positioning System (GPS).

[0030] Historical observation data can be data collected by the underwater glider using its own sensors and other components while gliding underwater. This data could include underwater current velocity, the glider's rotational speed, and depth. Depth can be calculated based on underwater pressure. Because communication with surface equipment is impossible, horizontal position data cannot be directly obtained; it can only be estimated based on the glider's movements.

[0031] The linear assignment method can be used to reconstruct the historical observation data of underwater gliders in historical gliding profiles. The linear assignment method can divide the horizontal position of the underwater glider in the historical gliding profile into an average value based on the historical observation data, and obtain the historical horizontal position reconstruction sequence. The historical horizontal position reconstruction sequence can be a predicted sequence of the historical horizontal position of the underwater glider at each point in the historical gliding profile in chronological order.

[0032] Since the historical horizontal position reconstruction sequence is based on historical observation data and the actual historical water exit points of the underwater glider, it can be used as prior knowledge for perturbation prediction to obtain the perturbation estimation sequence of the underwater glider in the gliding profile to be glided. The gliding profile to be glided is adjacent to the historical gliding profile, and it follows the historical gliding profile; that is, the gliding profile to be glided is the next gliding profile after the historical gliding profile. The perturbation estimation sequence can be a predicted sequence of interfering factors for the underwater glider's gliding in the gliding profile to be glided.

[0033] Based on this perturbation estimation sequence, the target trajectory of the underwater glider in the gliding profile can be determined recursively. The perturbation estimation sequence is a predicted sequence of interfering factors that may affect the gliding of the underwater glider in the gliding profile. The target trajectory takes into account these interfering factors, thus improving its accuracy.

[0034] According to an embodiment of this application, based on the historical water exit point position of the underwater glider in a historical gliding profile, a historical horizontal position reconstruction sequence is obtained by reconstructing historical observation data using the linear assignment method. This historical horizontal position reconstruction sequence is then used as prior knowledge for perturbation prediction to obtain the perturbation estimation sequence of the underwater glider in the next gliding profile. This allows the determination of the underwater glider's target trajectory, and the glider can be controlled to glide based on this target trajectory. This method fully utilizes historical data from the underwater glider in historical gliding profiles to construct the historical horizontal position reconstruction sequence. It eliminates the need for the underwater glider to obtain real-time underwater current velocity through high-power sensors. Furthermore, the marine environment exhibits spatiotemporally gradual changes, so changes in current velocity have little impact on the accuracy of the reconstructed historical horizontal position. By further using the historical horizontal position reconstruction sequence as prior knowledge for perturbation prediction, the target trajectory of the underwater glider in the gliding profile can be obtained. Since the target trajectory takes into account perturbation factors, its accuracy is improved, and the gliding cost under the target trajectory can be accurately determined. Controlling the underwater glider's gliding trajectory based on the target trajectory can also make the gliding trajectory and gliding cost of the underwater glider controllable.

[0035] Historical observation data for underwater gliders can be multi-source observation data, obtained by observing the state variables of the underwater glider. The state variables of the underwater glider can be defined as 13-dimensional vectors describing six degrees of freedom motion. The state variables of the underwater glider can be represented as... .in, The NED coordinate vector of the underwater glider in the North East Down (NED) coordinate system of the inertial coordinate system. These represent the northward, eastward, and vertical positions in the NED coordinate system, respectively. Let be the Euler angle vector of the underwater glider in the inertial coordinate system. These are the roll angle, pitch angle, and yaw angle of the underwater glider. Let be the linear velocity vector of the underwater glider in the carrier coordinate system. These are the forward velocity, lateral velocity, and vertical velocity of the underwater glider. Let be the angular velocity vector of the underwater glider in the carrier coordinate system. These are the roll rate, pitch rate, and yaw rate of the underwater glider, respectively. This refers to the roll rudder angle of an underwater glider.

[0036] The evolution of the state variables of an underwater glider over time can be described by a dynamic equation, which can be used to calculate the horizontal position (i.e., the north and east positions) of the underwater glider. The dynamic equation can be represented by the following formula (1).

[0037] (1);

[0038] in, For the mass and inertia matrix, The time derivative of the linear velocity. The time derivative of the angular velocity. , These are the momentum and angular momentum of the underwater glider, respectively. , These represent the resultant force and torque acting on the underwater glider during its motion. To define the control gain vector, the control quantity for the underwater glider is defined as... , The derivative of the roll rudder angle is the control quantity, which is the rate of change of the roll rudder angle. The control quantity can be input into the controller of the underwater glider so that the underwater glider can glide according to this control quantity.

[0039] Each gliding profile may include multiple sampling times, which can be represented as a sampling time series. The k-th sampling time in the gliding profile can be represented as... The entry point of the gliding profile is at the 0th sampling time, which can be represented as... The corresponding water inlet location can be represented as The point where the water exits the gliding profile is the location of the last sampling moment, which can be represented as... The corresponding outlet location can be represented as 0 ≤ k ≤ f, where k is an integer. Underwater gliders can store gliding data in real-time in their onboard memory. The raw gliding data related to historical gliding profiles stored in the onboard memory is read, and smoothing filtering and interpolation algorithms are used to clean and compensate for missing and outlier values ​​in the raw gliding data. The raw gliding data may include historical entry point locations. Historical water outlet location Historical water entry point corresponding sampling time and the corresponding sampling time of historical water outlets Historical observation data can include the attitude angle sequence and depth sequence of the underwater glider at each sampling time, for example, at the k-th sampling time. The corresponding attitude angle sequence for the underwater glider is as follows: The depth sequence is .

[0040] According to an embodiment of this application, based on the historical water exit point positions of an underwater glider in a historical gliding profile, the historical observation data of the underwater glider in the historical gliding profile is reconstructed using a linear allocation method to obtain a historical horizontal position reconstruction sequence. This includes: performing dead reckoning on the underwater glider based on the historical observation data of the underwater glider in the historical gliding profile to obtain a historical horizontal position prediction sequence of the underwater glider in the historical gliding profile; determining the historical cumulative gliding error of the underwater glider in the historical gliding profile based on the historical water exit point positions and the predicted water exit point positions in the historical horizontal position prediction sequence; and correcting the historical horizontal position prediction sequence using a linear allocation method based on the historical cumulative gliding error to obtain a historical horizontal position reconstruction sequence.

[0041] By combining the dynamic equation shown in formula (1), dead reckoning can be performed on the underwater glider based on historical observation data to obtain the historical horizontal position prediction sequence of the underwater glider in the historical gliding profile. The historical horizontal position prediction sequence can be the sequence of predicted horizontal positions of the underwater glider in the historical gliding profile. Based on this historical horizontal position prediction sequence, the predicted water exit point position in the historical gliding profile can be obtained.

[0042] The horizontal position of an underwater glider may have errors at each sampling time, ultimately manifesting as the error between the predicted and historical water exit points. Therefore, the error between the predicted and historical water exit points can be defined as the historical cumulative gliding error. The predicted water exit point position in the historical horizontal position prediction sequence can be represented as... Then the location of the water outlet is predicted. and the location of historical water outlets The historical cumulative gliding error between them can be expressed as .

[0043] The historical cumulative gliding error can be evenly distributed across each sampling moment of the historical horizontal position prediction sequence using the linear distribution method, thereby correcting the historical horizontal position prediction sequence and obtaining the historical horizontal position reconstruction sequence. The water exit point position of the underwater glider in the historical horizontal position reconstruction sequence is the historical water exit point position.

[0044] According to embodiments of this application, a more accurate historical horizontal position reconstruction sequence can be obtained by correcting the historical cumulative gliding error between the historical water outlet position and the predicted water outlet position.

[0045] According to an embodiment of this application, based on the historical cumulative gliding error, the historical horizontal position prediction sequence is corrected using a linear allocation method to obtain a historical horizontal position reconstruction sequence, including: obtaining the historical linear average error of the underwater glider in the historical gliding profile based on the historical cumulative gliding error and the time weight of the historical horizontal position prediction sequence; and correcting the historical horizontal position prediction sequence based on the historical linear average error to obtain a historical horizontal position reconstruction sequence of the underwater glider in the historical gliding profile.

[0046] Based on the time weight of the historical horizontal position prediction sequence at each sampling moment in the sampling time series, the historical cumulative gliding error can be allocated to obtain the historical linear average error, as shown in the following formula (2).

[0047] (2);

[0048] in, The value corresponding to the k-th sampling time in the historical horizontal position reconstruction sequence. This represents the historical cumulative gliding error.

[0049] Based on the historical linear average error, the historical horizontal position prediction sequence is corrected to obtain the historical horizontal position reconstruction sequence. This reconstruction sequence can be fused with historical observation data. The historical observation data fused with the historical horizontal position reconstruction sequence can then be represented as follows: ,in, These represent the northward and eastward positions of the underwater glider in the NED coordinate system during the historical horizontal position reconstruction sequence at the k-th sampling time. These represent the vertical position of the underwater glider in the NED coordinate system, and its roll angle, pitch angle, and yaw angle in the inertial coordinate system, respectively, in the historical observation data of the underwater glider at the k-th sampling time.

[0050] By using the historical cumulative gliding error and the time weight of the historical horizontal position prediction sequence to obtain the historical linear average error, the accuracy of the historical linear average error can be improved, thereby improving the accuracy of the historical horizontal position reconstruction sequence obtained by correcting the historical horizontal position prediction sequence based on the historical linear average error.

[0051] According to an embodiment of this application, a disturbance estimation sequence of an underwater glider in a gliding profile is obtained by using a historical horizontal position reconstruction sequence as prior knowledge for disturbance prediction. This includes: using the historical horizontal position reconstruction sequence as prior knowledge to establish a historical augmented state of the historical gliding profile, wherein the historical augmented state characterizes the state of the underwater glider under historical observation data and disturbance terms; and using the state of the underwater glider under disturbance terms in the historical augmented state to perform disturbance prediction on the disturbance terms in the gliding profile to obtain a disturbance estimation sequence of the underwater glider in the gliding profile.

[0052] Perturbation prediction is performed by leveraging the slowly varying spatiotemporal characteristics of the marine environment. Historical horizontal position reconstruction sequences can be used as prior knowledge to construct historical augmented states. It can be represented as ,in, This represents the state variables of the underwater glider. For the disturbance term, , These represent the disturbance force and the torque of the disturbance force in the x, y, and z axes of the inertial coordinate system, respectively.

[0053] The historical horizontal position reconstruction sequence can also be divided into multiple segmented features according to depth layers or time windows. For each segmented feature, a historical augmented state is constructed and perturbation prediction is performed to facilitate computation.

[0054] An augmented dynamics prediction model based on continuous time can be established, which can be expressed as the following formula (3).

[0055] (3);

[0056] in, The time derivative of the historical augmented state. To control the quantity, Let be a six-dimensional zero vector, to indicate that the time derivative of the perturbation term is approximately zero.

[0057] The perturbation prediction sequence can be obtained by using the augmented dynamics prediction model to predict the perturbation term in the gliding profile.

[0058] By establishing the historical augmented state, the disturbance term of the underwater glider in the historical gliding profile can be represented. Based on this disturbance term, the disturbance term in the gliding profile to be predicted is obtained, and the disturbance estimation sequence is obtained.

[0059] According to an embodiment of this application, perturbation prediction is performed on the perturbation terms in the gliding profile based on the perturbation terms in the historical augmented state to obtain a perturbation estimation sequence of the underwater glider in the gliding profile. This includes: using an extended Kalman filter perturbation observer, perturbation prediction is performed on the perturbation terms in the gliding profile based on the perturbation terms in the historical augmented state and historical observation data fused with the historical horizontal position reconstruction sequence to obtain a perturbation estimation sequence.

[0060] An Extended Kalman Filter (EKF) perturbation observer can be constructed. The perturbation term can be recursively updated by the Extended Kalman Filter perturbation observer. The perturbation term can be divided into multiple segments according to the sampling time. The logic of the recursive update is shown in the following formula (4).

[0061] (4);

[0062] in, For the perturbation term at the k-th sampling time, For the perturbation term at the (k-1)th sampling time, The Kalman gain at time k is... For the observation function, The augmented state prediction value at time k is obtained based on the augmented state prediction value at time k-1.

[0063] By using the above recursive filtering, the estimated value corresponding to the optimal perturbation term for each segment is calculated, and the perturbation estimation sequence that varies with depth or time in the gliding profile is obtained.

[0064] According to an embodiment of this application, the target trajectory of an underwater glider in a gliding profile is determined based on a perturbation estimation sequence, including: using historical exit points as predetermined entry points in the gliding profile; optimizing the gliding trajectory of the underwater glider based on the predetermined entry point and the perturbation estimation sequence until the objective function satisfies the optimization condition to obtain the target trajectory, wherein the objective function characterizes the correlation between the gliding energy consumption of the underwater glider and the gliding trajectory, and the optimization condition is to minimize the gliding energy consumption of the underwater glider.

[0065] Historical water exit points can be used as predetermined water entry points for the gliding profile. The gliding trajectory of the underwater glider can be optimized based on the predetermined water entry point and the disturbance estimation sequence. The objective function can be the correlation between gliding energy consumption and the gliding trajectory. The gliding energy consumption corresponding to each gliding trajectory can be calculated based on the objective function, and the gliding trajectory that minimizes the gliding energy consumption of the underwater glider can be determined as the target trajectory.

[0066] According to an embodiment of this application, the gliding trajectory of an underwater glider is optimized based on a predetermined entry point position and a disturbance estimation sequence until the objective function satisfies the optimization conditions, thereby obtaining the target trajectory. This includes: obtaining a target flight path based on the predetermined entry point position and the disturbance estimation sequence, wherein the target flight path represents the flight path of the underwater glider from the predetermined entry point position to the target heading; generating an initial control sequence based on the target flight path, wherein the initial control sequence represents the control quantity for the underwater glider; updating the initial control sequence according to the gradient of the initial control sequence based on the objective function until a target control sequence is obtained that satisfies the optimization conditions of the objective function; and determining the target trajectory based on the target control sequence.

[0067] Trajectory optimization can be performed based on the adjoint method, taking advantage of the slowly varying spatiotemporal characteristics of the marine environment. Based on the perturbation estimation sequence, the trajectory from the predetermined entry point to the target heading can be evolved. The corresponding target route, which can be represented as ,in, .

[0068] The optimization condition can be at the sampling time. The predicted water exit point location of the underwater glider in the gliding profile. Located on the target route, i.e. , This is the distance between the point where the underwater glider exits the water in the gliding profile and the target flight path.

[0069] According to an embodiment of this application, the objective function may include a terminal cost subfunction and a process cost subfunction. The terminal cost subfunction characterizes the deviation between the exit point of the underwater glider in the gliding profile and the target trajectory, while the process cost subfunction characterizes the gliding cost of the underwater glider in the gliding profile.

[0070] objective function It can be shown in the following formula (5).

[0071] (5);

[0072] in, For terminal cost subfunction, For process cost subfunction, This is the cost of the process.

[0073] The terminal cost subfunction is used to constrain the deviation between the underwater glider's exit point position in the gliding profile and the target trajectory. It can also be understood as penalizing the deviation between the underwater glider's exit point position in the gliding profile and the target trajectory.

[0074] The terminal cost subfunction can be represented by the following formula (6).

[0075] (6);

[0076] in, The penalty coefficient is... , These represent the sampling times of the underwater glider. Its northward and eastward positions.

[0077] The process cost can be represented by the following formula (7).

[0078] (7);

[0079] in, These are the servo motor energy consumption weight, fluid resistance weight, process line-following constraint weight, and anti-spinning weight, respectively. This refers to the roll rudder angle of an underwater glider. This refers to the yaw rate of the underwater glider.

[0080] Lagrange multiplier vectors can be introduced. As a costate equation, construct an augmented universal function. According to the variational principle, the costate equations, transverse conditions, and control gradients of the underwater glider's state variables can be represented by the following formulas (8) to (10).

[0081] (8);

[0082] (9);

[0083] (10);

[0084] in, Let be the co-state vector of the state variables of the underwater glider in the gliding profile. Let be the partial derivative of the process cost subfunction with respect to the state variables. Let Jacobian matrix be the state variable obtained from the dynamic equation. Let be the co-state vector of the state variables of the underwater glider at the water exit point position in the gliding profile. Let be the partial derivative of the terminal cost function with respect to the position of the underwater glider at the water exit point in the gliding profile. Let be the gradient of the objective function with respect to the control input of the underwater glider. Let be the partial derivative of the process cost subfunction with respect to the control variables of the underwater glider. Let be the Jacobian matrix of the control variables of the underwater glider obtained through the dynamic equations.

[0085] Substituting the results of formulas (8) to (10) into the augmented dynamics prediction model (i.e., formula (3)), we can obtain the gradient expression of the control quantity of the specific objective function on the underwater glider as shown in formula (11).

[0086] (11);

[0087] in, It is a subvector of the angular velocity component in the costate vector of the state variables of the underwater glider in the gliding profile.

[0088] The initial control sequence is updated using the gradient descent method. The initial control sequence can be the control quantity of the underwater glider. The control quantity is updated once at each sampling time. The update process of the control quantity can be shown in the following formula (12).

[0089] (12);

[0090] in, This is the control quantity at the (k+1)th sampling time. Let k be the control quantity at the k-th sampling time. This is the gradient descent step size. Let be the gradient of the control quantity at the k-th sampling time.

[0091] The initial control sequence can be iteratively updated based on the gradient of the objective function with respect to the initial control sequence until the obtained control sequence minimizes the gliding energy consumption of the underwater glider, thus obtaining the target control sequence with the lowest global energy consumption. And its corresponding target trajectory.

[0092] According to an embodiment of this application, controlling an underwater glider to glide according to a target trajectory includes: determining the trajectory error of the underwater glider based on the target trajectory and the actual trajectory of the underwater glider; determining an adjustment trajectory of the underwater glider within a predetermined time period based on the trajectory error; and controlling the underwater glider to glide based on the adjustment trajectory so that the underwater glider glides according to the target trajectory.

[0093] The Linear Time-Varying Model Predictive Control (LTV-MPC) method can be used to track and control underwater gliders.

[0094] The trajectory error of the underwater glider can be determined based on the target trajectory and the actual trajectory of the underwater glider. The trajectory error can include tracking error and control error; for example, the tracking error of the state variables can be defined. With control error .in, , Let these represent the state variables and control variables of the underwater glider at the current moment, respectively. and These represent the current reference working point of the underwater glider. State variables and control variables.

[0095] At the reference working point After performing Taylor expansion and linearization, the continuous-time error state equation can be represented by the following formula (13).

[0096] (13);

[0097] in, This is the time derivative of the tracking error of the state variable at the current moment. Let be the system matrix at the current moment, representing the state transition characteristics of the underwater glider. Let be the input matrix at the current moment, representing the control characteristics of the underwater glider. and Through respectively and Calculated. and The results have already been calculated in formulas (8) to (10), so the offline stored results can be directly called without having to solve them repeatedly online, thus reducing the computational load.

[0098] Set control cycle By discretizing the prediction model using the zero-order hold, we can obtain the following formula (14).

[0099] (14);

[0100] in, Let be the predicted value of the tracking error of the underwater glider's state variables at the (k+1)th sampling time. The system matrix is ​​discretized at the k-th sampling time. Let be the discretized state variables of the underwater glider at the k-th sampling time. The input matrix is ​​discretized at the k-th sampling time. The control deviation is discretized at the k-th sampling time.

[0101] Based on the trajectory error, the adjustment trajectory of the underwater glider within a predetermined time period can be determined, that is, the adjustment trajectory constructed in the control cycle, as shown in the following formula (15).

[0102] (15);

[0103] in, The objective function of model predictive control is... These are the weight matrices for the state variables, the control variables, and the terminal weights, respectively. The number of sampling times within a predetermined time period. This represents the number of sampling times for the control period corresponding to the gliding profile to be defined. The sequence of control variables to be optimized.

[0104] The underwater glider glides by adjusting its trajectory. Since the trajectory adjustment has corrected the trajectory error of the underwater glider, it can maintain the target trajectory while gliding.

[0105] LTV-MPC tracking control uses the evolved optimal state sequence as the adjustment trajectory and employs the LTV-MPC algorithm for real-time closed-loop tracking. This achieves high-precision, low-energy tracking of the target trajectory while suppressing real-time disturbances. Furthermore, it transforms passive correction into active planning, avoiding large rudder angle movements caused by the underwater glider's resistance to the flow field. This effectively solves the problem of severe energy consumption due to frequent maneuvers in underwater gliders, achieving the goal of minimum energy consumption in long-term underwater glider observation missions.

[0106] Figure 3 A block diagram of an underwater glider trajectory tracking control device based on flow field reconstruction according to an embodiment of this application is shown.

[0107] like Figure 3 As shown, the underwater glider trajectory tracking control device 300 based on flow field reconstruction includes a first acquisition module 310, a second acquisition module 320, a determination module 330, and a control module 340.

[0108] The first module 310 is used to reconstruct the historical observation data of the underwater glider in the historical gliding profile based on the historical water exit point position of the underwater glider in the historical gliding profile using the linear assignment method, so as to obtain the historical horizontal position reconstruction sequence.

[0109] The second module 320 is used to use the historical horizontal position reconstruction sequence as prior knowledge to predict perturbations and obtain the perturbation estimation sequence of the underwater glider in the gliding profile to be glided, wherein the gliding profile to be glided is adjacent to the historical gliding profile and the gliding profile to be glided is after the historical gliding profile.

[0110] The determination module 330 is used to determine the target trajectory of the underwater glider in the gliding profile based on the perturbation estimation sequence.

[0111] The control module 340 is used to control the underwater glider to glide according to the target trajectory.

[0112] Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be at least partially implemented as hardware circuits, such as field-programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems-on-a-chip, systems-on-a-substrate, systems-on-package, application-specific integrated circuits (ASICs), or implemented by hardware or firmware in any other reasonable manner by integrating or packaging circuits, or implemented in any one of software, hardware, and firmware, or in a suitable combination of any of these. Alternatively, one or more of the modules, submodules, units, and subunits according to the embodiments of this application can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0113] For example, any plurality of the first obtaining module 310, the second obtaining module 320, the determining module 330, and the control module 340 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this application, at least one of the first obtaining module 310, the second obtaining module 320, the determining module 330, and the control module 340 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the first obtaining module 310, the second obtaining module 320, the determining module 330, and the control module 340 may be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0114] Figure 4 A block diagram of an electronic device suitable for implementing the methods described above, according to an embodiment of this application, is shown. Figure 4 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0115] like Figure 4 As shown, an electronic device 400 according to an embodiment of this application includes a processor 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage portion 408 into a random access memory (RAM) 403. The processor 401 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 401 may also include onboard memory for caching purposes. The processor 401 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of this application.

[0116] RAM 403 stores various programs and data required for the operation of electronic device 400. Processor 401, ROM 402, and RAM 403 are interconnected via bus 404. Processor 401 executes various operations of the method flow according to embodiments of this application by executing programs in ROM 402 and / or RAM 403. It should be noted that the programs may also be stored in one or more memories other than ROM 402 and RAM 403. Processor 401 may also execute various operations of the method flow according to embodiments of this application by executing programs stored in said one or more memories.

[0117] According to embodiments of this application, the electronic device 400 may further include an input / output (I / O) interface 405, which is also connected to a bus 404. The electronic device 400 may also include one or more of the following components connected to the input / output (I / O) interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN card, modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output (I / O) interface 405 as needed. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 410 as needed so that computer programs read from it can be installed into the storage section 408 as needed.

[0118] According to embodiments of this application, the method flow according to embodiments of this application can be implemented as a computer software program. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by processor 401, it performs the functions defined in the system of embodiments of this application. According to embodiments of this application, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0119] This application also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, which, when executed, implement the method according to the embodiments of this application.

[0120] According to embodiments of this application, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, the computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0121] For example, according to embodiments of this application, a computer-readable storage medium may include ROM 402 and / or RAM 403 and / or one or more memories other than ROM 402 and RAM 403 as described above.

[0122] Embodiments of this application also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this application. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the methods provided in the embodiments of this application.

[0123] When the computer program is executed by the processor 401, it performs the functions defined in the system / apparatus of this application embodiment. According to the embodiments of this application, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0124] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via communication section 409, and / or installed from removable medium 411. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0125] According to embodiments of this application, program code for executing the computer programs provided in the embodiments of this application can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0126] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features described in the various embodiments of this application can be combined and / or combined in various ways, even if such combinations are not explicitly described in this application. In particular, the features described in the various embodiments of this application can be combined and / or combined in various ways without departing from the spirit and teachings of this application. All such combinations and / or combinations fall within the scope of this application. Embodiments of this application have been described above. However, these embodiments are merely illustrative and not intended to limit the scope of this application. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this application, and all such substitutions and modifications should fall within the scope of this application.

Claims

1. A method for trajectory tracking control of an underwater glider based on flow field reconstruction, characterized in that, include: Based on the historical water exit point position of the underwater glider in the historical gliding profile, the historical observation data of the underwater glider in the historical gliding profile are reconstructed using the linear assignment method to obtain the historical horizontal position reconstruction sequence. The historical horizontal position reconstruction sequence is used as prior knowledge for perturbation prediction to obtain the perturbation estimation sequence of the underwater glider in the gliding profile to be glided, wherein the gliding profile to be glided is adjacent to the historical gliding profile and is after the historical gliding profile. Based on the disturbance estimation sequence, the target trajectory of the underwater glider in the gliding profile is determined; The underwater glider is controlled to glide according to the target trajectory.

2. The method according to claim 1, characterized in that, Based on the historical water exit point positions of the underwater glider in historical gliding profiles, the historical observation data of the underwater glider in the historical gliding profiles are reconstructed using the linear assignment method to obtain a historical horizontal position reconstruction sequence, including: Based on historical observation data of the underwater glider in historical gliding profiles, dead reckoning is performed on the underwater glider to obtain a predicted sequence of the historical horizontal position of the underwater glider in the historical gliding profiles. Based on the historical water outlet location and the predicted water outlet location in the historical horizontal position prediction sequence, the historical cumulative gliding error of the underwater glider on the historical gliding profile is determined. Based on the historical cumulative gliding error, the historical horizontal position prediction sequence is corrected using the linear allocation method to obtain the historical horizontal position reconstruction sequence.

3. The method according to claim 2, characterized in that, The step of correcting the historical horizontal position prediction sequence based on the historical cumulative gliding error using a linear allocation method to obtain the historical horizontal position reconstruction sequence includes: Based on the historical cumulative gliding error and the time weight of the historical horizontal position prediction sequence, the historical linear average error of the underwater glider in the historical gliding profile is obtained; The historical horizontal position prediction sequence is corrected based on the historical linear average error to obtain the historical horizontal position reconstruction sequence of the underwater glider in the historical gliding profile.

4. The method according to any one of claims 1 to 3, characterized in that, The step of using the reconstructed historical horizontal position sequence as prior knowledge for perturbation prediction to obtain the perturbation estimation sequence of the underwater glider in the gliding profile includes: Using the historical horizontal position reconstruction sequence as prior knowledge, the historical augmented state of the historical gliding profile is established, wherein the historical augmented state characterizes the state of the underwater glider under the historical observation data and the disturbance term; Based on the state of the underwater glider under the disturbance term in the historical augmented state, the disturbance term in the gliding profile is predicted to obtain the disturbance estimation sequence of the underwater glider in the gliding profile.

5. The method according to claim 4, characterized in that, The step of predicting the disturbance terms in the gliding profile based on the disturbance terms in the historical augmented state to obtain the disturbance estimation sequence of the underwater glider in the gliding profile includes: By using an extended Kalman filter perturbation observer, perturbation prediction is performed on the perturbation terms in the gliding profile to be glided based on the perturbation terms in the historical augmented state and historical observation data fused with the historical horizontal position reconstruction sequence, thus obtaining the perturbation estimation sequence.

6. The method according to any one of claims 1 to 3, characterized in that, Determining the target trajectory of the underwater glider in the gliding profile based on the disturbance estimation sequence includes: The historical water exit point location is used as the predetermined water entry point location for the gliding profile to be glided. The gliding trajectory of the underwater glider is optimized based on the predetermined entry point and the disturbance estimation sequence until the objective function satisfies the optimization condition, thus obtaining the target trajectory. The objective function represents the correlation between the gliding energy consumption and the gliding trajectory of the underwater glider, and the optimization condition is to minimize the gliding energy consumption of the underwater glider.

7. The method according to claim 6, characterized in that, The optimization of the underwater glider's gliding trajectory based on the predetermined entry point location and the disturbance estimation sequence until the objective function satisfies the optimization conditions, resulting in the target trajectory, includes: Based on the predetermined water entry point location and the disturbance estimation sequence, a target route is obtained, wherein the target route represents the route taken by the underwater glider from the predetermined water entry point location to the target heading; Based on the target flight path, an initial control sequence is generated, wherein the initial control sequence represents the control quantity on the underwater glider; The initial control sequence is updated according to the gradient of the objective function on the initial control sequence until the target control sequence that satisfies the optimization conditions of the objective function is obtained. The target trajectory is determined based on the target control sequence.

8. The method according to claim 7, characterized in that, The objective function includes a terminal cost subfunction and a process cost subfunction. The terminal cost subfunction represents the deviation between the water exit point of the underwater glider in the gliding profile and the target trajectory, and the process cost subfunction represents the gliding cost of the underwater glider in the gliding profile.

9. The method according to claim 7, characterized in that, The step of controlling the underwater glider to glide according to the target trajectory includes: Based on the target trajectory and the actual trajectory of the underwater glider, determine the trajectory error of the underwater glider; Based on the trajectory error, the adjustment trajectory of the underwater glider within the predetermined time period is determined; The underwater glider is controlled to glide based on the adjusted trajectory, so that the underwater glider glides along the target trajectory.

10. An electronic device, characterized in that, include: One or more processors; Memory, used to store one or more programs. Wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the method of any one of claims 1 to 9.

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