Steering engine fault detection method, device, equipment and medium

Abstract

The invention relates to the technical field of underwater vehicles, and discloses a steering engine fault detection method, device and equipment and a medium, and is applied to an autonomous underwater vehicle, and the method comprises the steps: obtaining the current state data and expected state data of the autonomous underwater vehicle, virtual instruction rudder angles in different directions are determined based on the current state data and the expected state data; determining an actual instruction rudder angle corresponding to the virtual instruction rudder angle; a target residual value between the virtual instruction rudder angle and the actual driving rudder angle in different directions is determined, and the fault condition of the steering engine is determined based on the target residual value and a preset residual threshold value; and under the condition that the steering engine has a fault, determining a clamping stagnation angle corresponding to the fault steering engine with the fault based on the actual instruction rudder angle and the target residual value. According to the technical scheme provided by the invention, the fault of the steering engine can be accurately detected in real time, and the detection precision and reliability are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of underwater vehicles, and particularly relates to a rudder failure detection method and device, equipment and a medium. BACKGROUND

[0002] The rudder system of an autonomous underwater vehicle (AUV) is crucial for the attitude and heading control of the vehicle, especially the X-rudder system, which complicates the failure detection while improving stability. The AUV rudder system is prone to failure in complex environments. Traditional hardware redundancy or sensor solutions are costly and have poor adaptability. Intelligent detection methods based on data-driven are not suitable for real-time monitoring of AUVs due to computational complexity and latency issues.

[0003] Therefore, how to detect rudder failure in real time and accurately, and improve detection accuracy and reliability, is a technical problem to be solved at present. SUMMARY

[0004] The present application provides a rudder failure detection method, device, equipment and medium, which achieves the technical effect of detecting rudder failure in real time and accurately, and improving detection accuracy and reliability.

[0005] In order to achieve the above purpose, the main technical scheme adopted by the present application includes: In a first aspect, the present application provides a rudder failure detection method applied to an autonomous underwater vehicle, the method comprising: obtaining current state data and expected state data of the autonomous underwater vehicle, and determining virtual command rudder angles in different directions based on the current state data and the expected state data; determining actual command rudder angles corresponding to the virtual command rudder angles; determining target residual values between the virtual command rudder angles and actual driving rudder angles in different directions, and determining a failure condition of the rudder based on the target residual values and a pre-set residual threshold value; in the case that the rudder has a failure, determining a stuck angle corresponding to a failure rudder based on the actual command rudder angles and the target residual values.

[0006] The rudder failure detection method provided by the embodiment comprises the following steps: acquiring current state data and expected state data of the vehicle, and calculating a virtual command rudder angle in different directions based on the data, which provides a preliminary command for rudder control; converting the virtual command rudder angle into an actual command rudder angle to drive the rudder to adjust more accurately; next, calculating a target residual value between the virtual command rudder angle and the actual driving rudder angle, and comparing the target residual value with a preset residual threshold value to determine whether the rudder is faulty; if the rudder is detected to be faulty, calculating a stuck angle of the faulty rudder according to the actual command rudder angle and the target residual value. The embodiment can not only effectively detect rudder failure, but also identify the specific rudder that has a stuck failure and quantify the real-time stuck angle of the faulty rudder.

[0007] In one embodiment, when the direction is the vertical direction, the current state data comprises a current vertical speed, a current pitch angular speed, a current pitch angle and a current depth, and the expected state data comprises an expected depth; and the determination of the virtual command rudder angle comprises: determining a depth difference value of the current depth and the expected depth, and integrating the depth difference value to obtain a depth integral term; and determining a vertical direction control gain matched with the current vertical speed, the current pitch angular speed, the current pitch angle, the depth difference value and the depth integral term. determining a vertical target term matched with the current vertical speed, the current pitch angular speed, the current pitch angle, the depth difference value and the depth integral term according to the vertical direction control gain; adding all the vertical target terms to obtain the virtual command rudder angle in the vertical direction.

[0008] The embodiment determines a depth difference value between the current depth and the expected depth, and integrates the depth difference value to obtain a depth integral term, which helps to eliminate steady-state error and ensure that the AUV can be stably maintained near the expected depth for a long time. Next, a control gain is determined according to the current vertical speed, pitch angular speed, pitch angle, depth difference value and depth integral term, and the gain can be adjusted according to different state variables to optimize the control effect. Then, a corresponding vertical target term is calculated for each state variable according to the obtained control gain, and the vertical target terms are used to accurately adjust the vertical direction movement. Finally, all the vertical target terms are weighted and summed to obtain the virtual command rudder angle in the vertical direction, which will be used as a control input to adjust the rudder surface of the AUV, so as to realize accurate control of the depth of the AUV.

[0009] In one embodiment, when the direction is the horizontal direction, the current state data includes a current lateral velocity, a current yaw angular velocity and a current yaw angle, the desired state data includes a desired yaw angle; and the determination of the virtual command rudder angle comprises: determining a yaw angle difference between the current yaw angle and the desired yaw angle, and integrating the yaw angle difference to obtain a yaw angle integral term; determining a horizontal direction control gain matched with the current lateral velocity, the current yaw angular velocity, the yaw angle difference and the yaw angle integral term; determining a horizontal target term matched with the current lateral velocity, the current yaw angular velocity, the yaw angle difference and the yaw angle integral term, respectively, according to the horizontal direction control gain; adding all the horizontal target terms to obtain the virtual command rudder angle in the horizontal direction.

[0010] In this embodiment, the yaw angle difference between the current yaw angle and the desired yaw angle is calculated and integrated to obtain the yaw angle integral term, which helps to eliminate the long-term steady-state error. Then, the corresponding horizontal direction control gain is determined according to the current lateral velocity, yaw angular velocity, yaw angle difference and yaw angle integral term. These gain values optimize the control input to improve the accuracy of AUV heading control. Next, according to these gain values, the horizontal target terms matched with the current lateral velocity, yaw angular velocity, yaw angle difference and yaw angle integral term are determined, respectively. These target terms play a role in adjusting and correcting in horizontal control. Finally, by adding all the horizontal target terms, the virtual command rudder angle in the horizontal direction is obtained as the control input to guide the AUV to adjust the rudder, thereby achieving accurate heading control.

[0011] In one embodiment, when the direction is the roll direction, the current state data includes a current roll angular velocity and a current roll angle, the desired state data includes a desired roll angle; and the determination of the virtual command rudder angle comprises: determining a roll angle difference between the current roll angle and the desired roll angle, and integrating the roll angle difference to obtain a roll angle integral term; determining a roll direction control gain matched with the current roll angular velocity, the roll angle difference and the roll angle integral term; determining a roll target term matched with the current roll angular velocity, the roll angle difference and the roll angle integral term, respectively, according to the roll direction control gain; adding all the roll target terms to obtain the virtual command rudder angle in the roll direction.

[0012] The embodiment determines the roll angle difference between the current roll angle and the desired roll angle, and integrates the roll angle difference to obtain a roll angle integral term, so as to accurately evaluate and correct the roll error of the AUV; then, the roll direction control gain that meets the system requirements is calculated by using the roll angular velocity, the roll angle difference and the roll angle integral term, so as to ensure that the system can quickly and effectively adjust the roll angle at any time; then, based on the control gain, the roll target term matched with each control variable is calculated, so as to further refine the control strategy; finally, the virtual command rudder angles are added to obtain the virtual command rudder angle, so as to serve as the control input of the AUV, and the rudder surface is adjusted to accurately control the roll angle.

[0013] In one embodiment, the determining the actual command rudder angle corresponding to the virtual command rudder angle comprises: combining the virtual command rudder angles in different directions into a virtual command rudder angle vector; converting the virtual command rudder angle vector into an actual command rudder angle vector by using a preset conversion matrix; wherein the actual command rudder angle vector comprises an actual command rudder angle corresponding to each rudder angle.

[0014] The embodiment combines the virtual command rudder angles in different directions into a virtual command rudder angle vector. The virtual command rudder angle vector can effectively integrate the control requirements in each direction, thereby providing a unified control basis for subsequent rudder adjustment. Then, the virtual command rudder angle vector is converted into an actual command rudder angle vector by using a preset conversion matrix. The conversion process ensures that each rudder angle can correspond to an actual control command, realizes accurate matching between the virtual command and the actual rudder angle, and optimizes the motion control of the AUV, so that the AUV is more accurate and efficient in multi-dimensional attitude control.

[0015] In one embodiment, the determining the target residual error value between the virtual command rudder angle and the actual driving rudder angle in different directions comprises: for any direction, determining an error difference value between the virtual command rudder angle and the actual driving rudder angle; subtracting a disturbance term corresponding to the any direction from the error difference value to obtain an initial residual error value; filtering the initial residual error value to obtain a filtered target residual error value.

[0016] The embodiment can accurately identify the deviation of the autonomous underwater vehicle in each direction by determining the error difference between the virtual rudder angle and the actual driving rudder angle. Then, the influence of external disturbance is removed from the error difference by subtracting the disturbance term related to each direction to obtain an initial residual value, which helps to remove the interference of noise. Finally, the filtered target residual value is obtained by filtering the initial residual value, further eliminating high-frequency noise and ensuring stability and accuracy.

[0017] In one embodiment, the determination of the jamming angle of the fault rudder corresponding to the fault rudder based on the actual command rudder angle and the target residual value comprises: The fault rudder is obtained, and the actual fault command rudder angle corresponding to the fault rudder and the target fault residual value in different directions are determined. A target weighted residual value matched with the target fault residual value is determined. An average weighted residual value corresponding to the target weighted residual value is determined. An angle difference between the actual fault command rudder angle and the average weighted residual value is determined as the jamming angle of the fault rudder.

[0018] The embodiment determines the fault rudder, and obtains the actual fault command rudder angle corresponding to the fault rudder and the target fault residual value in different directions, which provides basic information for subsequent fault compensation. Then, the target weighted residual value is obtained by weighting calculation of the target fault residual value and the corresponding element in the conversion matrix, so as to quantify the influence of the rudder fault on each direction. Further, a stable residual index is obtained by calculating the average value of the target weighted residual value, reducing the influence of the error in a single direction and ensuring the balance. Finally, the jamming angle of the fault rudder is accurately determined by comparing the angle difference between the actual fault command rudder angle and the average weighted residual value.

[0019] In a second aspect, the embodiment of the present application provides a rudder fault detection device applied to an autonomous underwater vehicle, and the device comprises: A virtual command determination unit is configured to obtain current state data and expected state data of the autonomous underwater vehicle, and determine a virtual command rudder angle in different directions based on the current state data and the expected state data. An actual command determination unit is configured to determine an actual command rudder angle corresponding to the virtual command rudder angle. A fault condition determination unit is configured to determine a target residual value between the virtual command rudder angle and an actual driving rudder angle in different directions, and determine a fault condition of a rudder based on the target residual value and a pre-set residual threshold value. ​​​A jamming angle determination unit is configured to determine a jamming angle corresponding to a faulty rudder in the case of a fault in the rudder, based on the actual command rudder angle and the target residual value.

[0020] In a third aspect, an embodiment of the present application provides a computer device, comprising: A memory and a processor, which are in communication connection with each other, and the memory stores computer instructions, and the processor executes the computer instructions to perform the rudder fault detection method.

[0021] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores computer instructions, and the computer instructions are used to make a computer execute the rudder fault detection method. BRIEF DESCRIPTION OF DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the specific embodiments or prior art of the present application, the drawings needed in the specific embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description are some embodiments of the present application, and those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0023] Figure 1 A flowchart of a rudder fault detection method provided by an embodiment of the present application; Figure 2 A flowchart of a determination method of a virtual command rudder angle corresponding to a vertical direction provided by an embodiment of the present application; Figure 3 A layout diagram of a rudder provided by an embodiment of the present application; Figure 4 A flowchart of a determination method of a virtual command rudder angle corresponding to a horizontal direction provided by an embodiment of the present application; Figure 5 A flowchart of a determination method of a virtual command rudder angle corresponding to a roll direction provided by an embodiment of the present application; Figure 6 A flowchart of step S3 provided by an embodiment of the present application; Figure 7 A frame diagram of an actual command rudder angle provided by an embodiment of the present application; Figure 8 A flowchart of step S5 provided by an embodiment of the present application; Figure 9 A flowchart of step S7 provided by an embodiment of the present application; Figure 10 A running depth, yaw angle and roll angle data information diagram provided by an embodiment of the present application; Figure 11 A rudder angle data information diagram provided for an embodiment of the present application; Figure 12 A target residual value information diagram provided for an embodiment of the present application; Figure 13 A block diagram of a rudder failure detection device provided for an embodiment of the present application; Figure 14 A structural schematic diagram of a computer device provided for an embodiment of the present application. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in a clear and complete manner with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0025] An autonomous underwater vehicle (AUV) is an important carrier for ocean resource exploration, underwater emergency rescue and strategic reconnaissance tasks, and its application value is increasingly prominent. The rudder system of the AUV is a core actuator responsible for controlling the attitude and heading of the vehicle. In particular, the X-rudder system adopts a four-surface X-shaped spatial symmetrical layout, which improves the running stability of the rudder system, but also makes the detection of rudder failure a key factor affecting the tracking accuracy of the AUV and the stability of the task.

[0026] Currently, in complex surface and underwater environments, the AUV rudder system is prone to failure such as sticking, efficiency decline, drift, etc. These failures not only affect the accuracy of the track, but also may cause the vehicle to lose control and even be damaged in severe cases. Therefore, real-time and accurate rudder failure detection technology is crucial to ensure the safe operation of the AUV. However, the traditional hardware redundancy technology or additional sensor scheme, although it can detect failures, has significant shortcomings such as high cost, poor adaptability to external environment, and complex installation and maintenance.

[0027] Compared with traditional methods, intelligent detection techniques based on data driving, such as deep learning, can provide more accurate fault diagnosis, but due to their high computational complexity, high time delay and the need for a large amount of fault data as prior knowledge, these techniques are not suitable for real-time monitoring of high-dynamic systems such as AUVs. Therefore, the fault detection method based on observer becomes a more promising solution. This method can timely and effectively complete fault detection by combining the dynamic model of AUV, the command rudder angle information and the real-time state information without increasing the cost of additional hardware.

[0028] As a typical disturbance estimation tool, the disturbance observer has the advantages of direct disturbance estimation, independence on accurate model, low-pass noise suppression and strong robustness, and is therefore very suitable for application in the detection of AUV rudder failure. Existing methods can usually only determine whether a rudder failure has occurred, and lack specific identification of the failure type, which limits the accuracy and reliability of fault detection.

[0029] Therefore, how to detect AUV rudder failure in real time and accurately to improve the accuracy and reliability of fault detection is a technical problem that needs to be solved at present.

[0030] In order to solve the above technical problems, according to the embodiments of the present application, a rudder failure detection method embodiment is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that here.

[0031] In the present embodiment, a rudder failure detection method is provided, Figure 1 The flowchart of the rudder failure detection method provided in the embodiments of the present application is shown in Figure 1 As shown, it is applied to an autonomous underwater vehicle, and the flowchart includes the following steps: Step S1, obtaining current state data and desired state data of the autonomous underwater vehicle, and determining virtual command rudder angles in different directions based on the current state data and the desired state data.

[0032] Specifically, in the control system of the autonomous underwater vehicle (AUV), the current state data and the desired state data are obtained. The current state data usually includes the actual position, speed, attitude angle (such as pitch angle, yaw angle, roll angle) and other related motion data of the AUV, which are collected in real time by sensors such as inertial measurement units, depth sensors, speed meters, etc. The desired state data is set in advance according to the task target of the AUV, for example, the desired depth, the desired yaw angle, the desired lateral speed, etc., which reflect the ideal state that the AUV should achieve when performing the task.

[0033] Based on the current state data and the desired state data, the control system determines virtual command rudder angles in different directions through a series of calculations and algorithms. These virtual command rudder angles are the key input signals for controlling the motion of the AUV, guiding the adjustment of each rudder of the AUV, so that the actual motion state of the AUV is as close as possible to the desired state. Specifically, the control system calculates the required rudder angle adjustment in each direction, i.e. the virtual command rudder angle, according to the difference between the current state and the desired state, combined with the dynamic model and control algorithm (such as PID control, LQR control, etc.). These virtual command rudder angles are then converted into actual command rudder angles and sent to the actuators (such as rudders) of the AUV, so as to realize precise control of the motion of the AUV.

[0034] Step S3, determining the actual command rudder angle corresponding to the virtual command rudder angle.

[0035] Specifically, in the control system of an autonomous underwater vehicle (AUV), determining the actual command rudder angle corresponding to the virtual command rudder angle is a key step to achieve precise control. The virtual command rudder angle is an ideal rudder angle calculated by the controller according to the current state data and the desired state parameters, used to guide the motion of the AUV. However, due to the influence of various factors such as fluid dynamics, mechanical hysteresis, sensor noise, etc., direct use of the virtual command rudder angle may not completely achieve the desired motion effect. Therefore, it is necessary to convert the virtual command rudder angle into the actual command rudder angle, which can be converted into the actual command rudder angle by a preset conversion matrix.

[0036] Step S5, determining the target residual value between the virtual command rudder angle and the actual driving rudder angle in different directions, and based on the target residual value and the pre-set residual threshold value, determining the fault condition of the rudder.

[0037] Specifically, the target residual value is obtained by calculating the difference between the virtual command rudder angle and the actual driving rudder angle, reflecting the deviation between the actual motion of the AUV and the desired motion. If the target residual value exceeds the pre-set residual threshold value, it may indicate that the rudder has a fault. The residual threshold value is pre-set according to the normal operation range and fault tolerance of the system, used to distinguish between normal deviation and fault deviation. By comparing the target residual value with the residual threshold value, it can be judged whether the rudder is working normally. If the residual value continuously exceeds the threshold value, the system can further diagnose the fault type, such as sticking, failure, etc., and take corresponding measures, such as switching to a backup system or adjusting the control strategy, to ensure the safe operation of the AUV.

[0038] Specifically, to accurately detect the rudder failure, different residual threshold values need to be defined according to the different residual situations of the AUV in the vertical, horizontal and roll directions, respectively. The residual threshold values are +ε1 for the vertical direction, +ε2 for the horizontal direction, and +ε3 for the roll direction. In the fault-free stage, when the AUV is in steady operation, the residual threshold values are obtained by the following method: According to the residual value estimated by the disturbance observer and the set threshold value, the corresponding AUV rudder failure judgment rule is formulated: When , it means that the target residual value exceeds the positive residual threshold value, and is represented by the '+' symbol.

[0039] When , it means that the target residual value exceeds the negative residual threshold value, and is represented by the '-' symbol.

[0040] When , it means that the target residual value is within the residual threshold value range, and is represented by the '0' symbol.

[0041] The specific rudder failure judgment rule is shown in Table 1.

[0042] Table 1 Rudder failure judgment rule If the symbol combination of the target residual value is not within the range defined in the above Table 1, it means that this state combination is invalid, which may be caused by system abnormalities or noise interference. By setting reasonable residual threshold values and comparing the target residual value estimated by the disturbance observer with the residual threshold values, the failure condition of the AUV rudder can be effectively detected. This fault judgment method based on symbol combination not only can quickly identify the fault type, but also can avoid false positives, improve the reliability and safety of the system.

[0043] Step S7, in the case of rudder failure, based on the actual command rudder angle and the target residual value, the stuck angle corresponding to the fault rudder is determined.

[0044] Specifically, when a certain rudder is confirmed to have a fault, it is necessary to determine the stuck angle of the faulty rudder based on the actual command rudder angle and the target residual value. The actual command rudder angle is the ideal rudder angle calculated by the controller according to the current state and the desired state, while the target residual value is estimated by the disturbance observer, reflecting the deviation between the actual rudder angle and the desired rudder angle. By weighted summing the target residual value and subtracting it from the actual command rudder angle, an estimated stuck angle can be obtained. This angle represents the actual stuck position of the rudder, deviating from the ideal position. By accurately estimating the stuck angle, the severity of the fault can be better understood, and appropriate measures can be taken to restore or compensate the function of the rudder, thereby ensuring the stable operation of the AUV.

[0045] The rudder fault detection method provided by the embodiment can obtain the current state data and the desired state data of the vehicle, and calculate the virtual command rudder angles in different directions based on these data, which provides preliminary instructions for rudder control. The virtual command rudder angles are converted into actual command rudder angles to drive the rudder to adjust more accurately. Next, the target residual value between the virtual command rudder angle and the actual driving rudder angle is calculated and compared with the preset residual threshold to determine whether the rudder has a fault. If a rudder fault is detected, the stuck angle of the faulty rudder will be calculated based on the actual command rudder angle and the target residual value. The embodiment not only can effectively detect rudder faults, but also can identify and locate the specific rudder that has a stuck fault and quantify the real-time stuck angle of the faulty rudder.

[0046] Figure 2 The flowchart of the determination method of the virtual command rudder angle in the vertical direction provided by the embodiment of the present application, when the direction is the vertical direction, the current state data includes the current vertical velocity, the current pitch angular velocity, the current pitch angle and the current depth, and the desired state data includes the desired depth; the flowchart can include the following steps: Step S111, determining the depth difference between the current depth and the desired depth, and integrating the depth difference to obtain a depth integral term.

[0047] Specifically, the depth difference Δζ = desired depth ζ d - current depth ζ. This depth difference reflects the deviation between the current depth of the AUV and the desired depth. In order to eliminate the steady-state static error, i.e. to ensure that the AUV can accurately maintain the desired depth after a long time of operation, the depth difference is integrated. The integral term can help the AUV to maintain around the desired depth, especially when the external disturbance (such as water flow change) or internal parameter (such as buoyancy, rudder control, etc.) changes, the introduction of this integral term can effectively reduce the static error, and the final depth integral term is ∫(ζ d - ζ)dt.

[0048] Step S113, determine the vertical direction control gain matched with the current vertical speed, current pitch angle speed, current pitch angle, depth difference value and depth integral term.

[0049] Specifically, in order to facilitate the research and analysis of the dynamic characteristics of an autonomous underwater vehicle (AUV), the dynamic characteristics of the AUV are simplified as a six-degree-of-freedom rigid body model, and the kinematics and dynamics equations thereof are established based on Newton's law. Please refer to Figure 3 , three translational degrees of freedom: translational motion along the x, y, z axes. Three rotational degrees of freedom: rotational motion around the x, y, z axes (pitch, yaw, roll). In order to further simplify the model, the originally nonlinear and coupled dynamic model of each degree of freedom is decoupled into a linearized dynamic model in the vertical, horizontal and roll directions. The vertical direction mainly considers the vertical motion, including the vertical speed, pitch angle speed, pitch angle and depth. The horizontal direction mainly considers the motion in the horizontal plane, including the lateral speed, yaw angle speed and yaw angle. The roll direction mainly considers the rotational motion around the body axis, including the roll angle speed and roll angle. Different linearized state space equations are obtained for different directions.

[0050] Vertical direction: wherein, is the derivative of the vertical direction state vector (i.e. the rate of change of the state variable); x v is the vertical direction state variable, x v =[w,q,θ,ζ];w is the vertical speed; q is the pitch angle speed; θ is the pitch angle; ζ is the depth; A v and B v are the linearized system matrices; δ vd is the virtual command rudder angle in the vertical direction, i.e. the control input in the vertical direction; σ v =[σ v1 ,σ v2 ,0,0] T ,σ v1 is the disturbance of the vertical force, affecting the vertical speed and the depth, σ v2 is the disturbance of the pitch moment, affecting the pitch angle speed and the pitch angle; a v11 , a v12 , a v13 , a v21 , a v22 , a v23 are the dynamic coefficients describing the mutual influence between the system states; u is the speed in the X direction; b v1 and b v2 are the dynamic coefficients describing the influence of the control input on the system states.

[0051] The vertical direction control gain k1 = [k w ,k q ,k θ ,k ζ ] is calculated by the LQR method, k1 = lqr(A v ,B v ,Q v ,R v ); wherein Q v is a vertical direction state weight matrix; R v is a vertical direction control input weight matrix. The LQR method can find the optimal control gain k1, so that the system meets the dynamic performance requirements while minimizing the control energy consumption.

[0052] Step S115, according to the vertical direction control gain, respectively determine the vertical target item matched with the current vertical speed, the current pitch angle speed, the current pitch angle, the depth difference and the depth integral term.

[0053] Specifically, -k w w is the vertical target item matched with the current vertical speed; -k q q is the vertical target item matched with the current pitch angle speed; -k θ θ is the vertical target item matched with the current pitch angle; k ζ (ζ d -ζ) is the vertical target item matched with the depth difference; k i ∫(ζ d -ζ)dt is the vertical target item matched with the depth integral term.

[0054] Step S117, add all the vertical target items to obtain the virtual command rudder angle in the vertical direction.

[0055] δ vd = -k w w - k q q - k θ θ + kζ(ζ d -ζ) + k i ∫(ζ d -ζ)dt Wherein, δ vd is the virtual command rudder angle in the vertical direction, used to guide the vertical movement of the AUV to reach the desired depth; k w ,k q ,k θ ,k ζ are the vertical direction control gains, and k i is the integral gain, used to eliminate the steady-state error of the system, generally taking a small value (for example, between 0.01-0.1).

[0056] The embodiment determines the depth difference between the current depth and the expected depth, and integrates the depth difference to obtain a depth integral term, which helps to eliminate steady-state error and ensure that the AUV can be stably maintained near the expected depth for a long time. Next, according to the current vertical speed, the pitch angle speed, the pitch angle, the depth difference and the depth integral term, the corresponding control gain is determined, which can be adjusted according to different state variables to optimize the control effect. Subsequently, according to the obtained control gain, the corresponding vertical target term is calculated for each state variable, which is used to accurately adjust the motion in the vertical direction. Finally, all the vertical target terms are weighted and summed to obtain the virtual command rudder angle in the vertical direction, which will be used as the control input to adjust the rudder of the AUV, so as to realize accurate control of the depth of the AUV.

[0057] Figure 4 The determination method flowchart of the horizontal direction corresponding virtual command rudder angle provided by the embodiment of the application, when the direction is horizontal, the current state data includes the current lateral speed, the current yaw angle speed and the current yaw angle, and the expected state data includes the expected yaw angle; the flowchart can include the following steps: Step S131, determining the yaw angle difference between the current yaw angle and the expected yaw angle, and integrating the yaw angle difference to obtain a yaw angle integral term.

[0058] Specifically, the yaw angle difference ΔΨ = expected yaw angle Ψ d -current yaw angle Ψ, which reflects the deviation between the current yaw angle and the expected yaw angle of the AUV. In order to eliminate the steady-state static error, that is, to ensure that the AUV can accurately maintain the expected yaw angle after a long time of running, the yaw angle difference is integrated to avoid the accumulation of yaw error during long-term running, thereby improving the stability of the heading, and finally the yaw angle integral term is obtained as ∫(Ψ d -Ψ)dt.

[0059] Step S133, determining the horizontal direction control gain matched with the current lateral speed, the current yaw angle speed, the yaw angle difference and the yaw angle integral term.

[0060] Specifically, in the horizontal direction: wherein, is the derivative of the horizontal direction state vector (i.e. the rate of change of the state variable); x h is the horizontal direction state variable, x h =[v, r, Ψ]; v is the lateral speed; r is the yaw angle speed; Ψ is the yaw angle; A h and B h are the linearized system matrices; δhd is the virtual command rudder angle in the horizontal direction, i.e., the control input in the horizontal direction; σ h = [σ h1 , σ h2 , 0] T , σ h1 is the disturbance of the horizontal force, affecting the lateral velocity, σ h2 is the disturbance of the yawing moment, affecting the yaw angular velocity and the yaw angle; a h11 , a h12 , a h21 , a h22 are the dynamic coefficients, describing the mutual influence between the system states; b h1 and b h2 are the dynamic coefficients, describing the influence of the control input on the system states.

[0061] The horizontal direction control gain k2 = [k v , k r , k Ψ ] is calculated by the LQR method, k2 = lqr(A h , B h , Q h , R h ); wherein Q h is the horizontal direction state weight matrix; R h is the horizontal direction control input weight matrix. The LQR method can find the optimal control gain k2, so that the system meets the dynamic performance requirements while minimizing the control energy consumption.

[0062] Step S135, according to the horizontal direction control gain, respectively determine the horizontal target item matched with the current lateral velocity, the current yaw angular velocity, the yaw angle difference value and the yaw angle integral term.

[0063] Specifically, -k v v is the horizontal target item matched with the current lateral velocity; -k r r is the horizontal target item matched with the current yaw angular velocity; k Ψ (Ψ d -Ψ) is the horizontal target item matched with the yaw angle difference value; k ih ∫(Ψ d -Ψ)dt is the horizontal target item related to the yaw angle integral term.

[0064] Step S137, add all the horizontal target items to obtain the virtual command rudder angle in the horizontal direction.

[0065] δ hd = -k v v - k r r + k Ψ (Ψd -Ψ)+k ih ∫(Ψ d -Ψ)dt wherein δ hd is the virtual command rudder angle in the horizontal direction, which makes the movement in the horizontal direction more stable and ensures that the AUV can quickly and accurately tend to and maintain the desired yaw angle; k v ,k r ,k Ψ is the horizontal direction control gain; k ih is the integral gain, which is used to eliminate the steady-state error of the system and is generally taken as a small value (for example, between 0.01 and 0.1).

[0066] The embodiment calculates the yaw angle difference between the current yaw angle and the desired yaw angle, and integrates it to obtain the yaw angle integral term, which helps to eliminate the long-term steady-state error. Then, according to the current lateral velocity, yaw angular velocity, yaw angle difference and yaw angle integral term, the corresponding horizontal direction control gain is determined. These gain values optimize the control input to improve the accuracy of the AUV heading control. Then, according to these gain values, the horizontal target terms matching the current lateral velocity, yaw angular velocity, yaw angle difference and yaw angle integral term are determined respectively. These target terms play a role in adjusting and correcting in the horizontal control. Finally, by adding all the horizontal target terms, the virtual command rudder angle in the horizontal direction is obtained as the control input to guide the AUV to adjust the rudder, thereby realizing accurate heading control.

[0067] Figure 5 The determination method flowchart of the virtual command rudder angle in the roll direction provided by the embodiment of the application, when the direction is the roll direction, the current state data includes the current roll angular velocity and the current roll angle, and the desired state data includes the desired roll angle; the flowchart can include the following steps: Step S151, determining the roll angle difference between the current roll angle and the desired roll angle, and integrating the roll angle difference to obtain the roll angle integral term.

[0068] Specifically, This roll angle difference reflects the deviation between the current roll angle and the desired roll angle of the AUV. In order to eliminate the steady-state error, i.e., to ensure that the AUV can accurately maintain the desired roll angle after a long time of operation, the roll angle difference is integrated, and the final roll angle integral term is

[0069] Step S153, determining the roll direction control gain matching the current roll angular velocity, the roll angle difference and the roll angle integral term.

[0070] Specifically, the roll direction: wherein, is the derivative of the roll direction state vector (i.e., the rate of change of the state variable); x r is the roll direction state variable, p is the roll angular velocity; is the roll angle; A r and B r is the linearized system matrix; δ rd is the virtual command rudder angle in the roll direction, i.e., the control input in the roll direction; σ r = [σ r1 , 0] T , σ r1 is the disturbance of the roll moment, affecting the roll angular velocity and the roll angle; a r11 , a r12 are the dynamic coefficients describing the mutual influence between the system states; b r1 is the dynamic coefficient describing the influence of the control input on the system states.

[0071] The roll direction control gain is calculated by the LQR method k2 = lqr(A r , B r , Q r , R r ); wherein, Q r is the roll direction state weight matrix; R r is the roll direction control input weight matrix. The LQR method can find the optimal control gain k3, so that the system meets the dynamic performance requirements while minimizing the control energy consumption.

[0072] Step S155, according to the roll direction control gain, respectively determine the roll target item matched with the current roll angular velocity, roll angle difference and roll angle integral item.

[0073] Specifically, -k p p is the roll target item matched with the current roll angular velocity; is the roll target item matched with the roll angle difference; is the roll target item matched with the roll angle integral item: Step S157, add all the roll target items to obtain the virtual command rudder angle in the roll direction.

[0074] wherein, δ rdThe virtual command rudder angle in the roll direction makes the movement in the roll direction more stable, and ensures that the AUV can quickly and accurately tend to and maintain the desired roll angle. p , The roll direction control gain; The integral gain is used to eliminate the steady-state error of the system, and is generally taken as a small value (for example, between 0.01 and 0.1).

[0075] It should be noted that the dynamic coefficients are shown in Table 2.

[0076] Table 2 Dynamic coefficients coefficient value coefficient value a v11 ]]> -0.4726 a h22 ]]> -0.4818 a v12 ]]> 0.3474 a r11 ]]> -0.6023 a v13 ]]> 0.0482 a r12 ]]> -0.8236 a v21 ]]> 0.5906 b v1 ]]> -0.2032 a v22 ]]> -0.4762 b v2 ]]> 0.1143 a v23 ]]> -1.7362 b h1 ]]> 0.3374 a h11 ]]> -0.4726 b h2 ]]> 0.4818 a h12 ]]> -0.3642 b r1 ]]> -3.1623 a h21 ]]> 0.5906 The embodiment determines the roll angle difference between the current roll angle and the desired roll angle, and integrates the roll angle difference to obtain a roll angle integral term, so as to accurately evaluate and correct the roll error of the AUV; then, the roll angular velocity, the roll angle difference and the roll angle integral term are used to calculate a roll direction control gain that adapts to the system requirements, so as to ensure that the system can quickly and effectively adjust the roll angle at any time; then, based on the control gain, a roll target term matched with each control variable is calculated, so as to further refine the control strategy; finally, the target terms are added to obtain a virtual command rudder angle, which is used as the control input of the AUV, so as to realize accurate control of the roll angle by adjusting the rudder surface.

[0077] Figure 6 A flowchart of step S3 provided by the embodiment of the application can include the following steps: Step S31, the virtual command rudder angles in different directions are combined to form a virtual command rudder angle vector.

[0078] Specifically, the virtual command rudder angles in different directions are combined to form a virtual command rudder angle vector vird : wherein, δ vd is the virtual command rudder angle in the vertical direction; δ hd is the virtual command rudder angle in the horizontal direction; and δ rd is the virtual command rudder angle in the roll direction.

[0079] Step S33, a conversion matrix is used to convert the virtual command rudder angle vector into an actual command rudder angle vector; wherein the actual command rudder angle vector includes an actual command rudder angle corresponding to each rudder angle.

[0080] Specifically, the conversion relationship is: wherein, δ 1d , δ2d ,δ 3d ,δ 4d is the actual rudder angle of the X-rudder. Please refer to Fig. 4 for details. Figure 7

[0081] In order to convert the virtual rudder angle into the actual rudder angle of the X-rudder, a pseudo-inverse method is used to design a distribution algorithm: Δx d = H T (HH T ) -1 Δ vird where H is the conversion matrix.

[0082] The final actual rudder angle X of the X-rudder is used to control the motion of the AUV, achieving precise multi-dimensional control.

[0083] In this embodiment, the virtual rudder angles in different directions are combined into a virtual rudder angle vector. This virtual rudder angle vector effectively integrates the control requirements in each direction, thereby providing a unified control basis for subsequent rudder angle adjustment. Then, through a pre-set conversion matrix, the virtual rudder angle vector is converted into an actual rudder angle vector. This conversion process ensures that each rudder angle can correspond to an actual control instruction, achieving precise matching between the virtual instruction and the actual rudder angle, thereby optimizing the motion control of the AUV and making it more accurate and efficient in multi-dimensional attitude control.

[0084] Figure 8 The flowchart of step S5 provided by the embodiment of the present application can include the following steps: Step S51, for any direction, determine the error difference value between the virtual rudder angle and the actual driving rudder angle.

[0085] Specifically, the residual error estimate respectively represent the residual error estimates in the vertical direction, the horizontal direction and the roll direction.

[0086] For the error difference value in the vertical direction = virtual rudder angle vd - actual driving rudder angle v ; for the error difference value in the horizontal direction = virtual rudder angle hd - actual driving rudder angle h ; for the error difference value in the roll direction = virtual rudder angle rd - actual driving rudder angle r .

[0087] ​Step S53, subtract the disturbance term corresponding to any direction from the error difference value to obtain an initial residual value.

[0088] Specifically, for the initial residual value in the vertical direction: For the initial residual value in the horizontal direction: For the initial residual value in the roll direction: Step S55, filtering the initial residual value to obtain a filtered target residual value.

[0089] Specifically, for the target residual value in the vertical direction: For the target residual value in the horizontal direction: For the target residual value in the roll direction: where g ob is the bandwidth of the disturbance observer; s is the frequency of the disturbance observer.

[0090] It should be noted that in actual operation, the acceleration information of the AUV has a large noise disturbance, which makes it impossible to directly use the accelerometer information. At the same time, the real-time driving rudder angle of the AUV cannot be directly collected by the sensor. In order to solve these problems, a disturbance observer based on Laplace transform is designed. By transforming the decoupled dynamics equations of the AUV in the vertical motion plane, the horizontal motion plane and the roll direction into the frequency domain, the residual value of the virtual command rudder angle and the real-time driving rudder angle is estimated by using the virtual command rudder angle information and the real-time state information (current state data of the autonomous underwater vehicle) obtained by the sensor. The performance core of the disturbance observer depends on the frequency domain shaping design of the low-pass filter Q(s). Its functional architecture contains three levels: filtering high-frequency noise: filtering high-frequency noise in the frequency domain, suppressing sensor noise and unmodeled high-frequency dynamics, and ensuring the robustness of the disturbance observer. Dynamics model regularization: smoothing the ill-conditioned gain characteristics of the inverse model at high frequencies to avoid observation distortion caused by the numerical differentiation explosion effect. Balance dynamic response performance and robustness: the higher the bandwidth, the faster the disturbance estimation, but at the same time, the more sensitive to high-frequency errors.

[0091] To ensure the accuracy of the estimation and eliminate high-frequency noise, the interference observer Q(s) adopts a first-order low-pass filter structure, and the core design principle is to keep the gain coefficient as 1 in the effective working frequency band, so as to completely retain the useful signal components. In the high-frequency noise frequency band, the gain is quickly attenuated, and the gain tends to 0. Through this frequency shaping mechanism, various noise interferences mixed in the measurement signal are effectively filtered out.

[0092] Therefore, the above formula can be converted as follows: For the target residual value in the vertical direction: For the target residual value in the horizontal direction: For the target residual value in the roll direction: Through this design, the interference observer can effectively suppress noise interference in actual operation, improving the control accuracy and robustness of the AUV.

[0093] In this embodiment, by determining the error difference between the virtual command rudder angle and the actual driving rudder angle, the deviation of the autonomous underwater vehicle in each direction can be accurately identified. Then, subtract the disturbance term related to each direction to eliminate the influence of external disturbance from the error difference, and obtain the initial residual value. This process helps to remove the interference of noise. Finally, by filtering the initial residual value, the filtered target residual value is obtained, which further eliminates high-frequency noise and ensures stability and accuracy.

[0094] Figure 9 The flowchart of step S7 provided by the embodiment of the present application can include the following steps: Step S71, acquiring the fault rudder and determining the actual fault command rudder angle corresponding to the fault rudder and the target fault residual value in different directions.

[0095] Specifically, the faulty rudder is identified and determined. For each faulty rudder, its corresponding actual fault command rudder angle δ id , δ id is the actual fault command rudder angle of the i-th rudder of the X rudder and the target fault residual value in different directions

[0096] Step S73, determining the target weighted residual value matched with the target fault residual value.

[0097] Specifically, the target weighted residual value is calculated according to the target fault residual value and the corresponding elements of the conversion matrix H. The specific formula is: wherein H 1i is the value of the i-th column of the first row of the conversion matrix H; H 2i is the value of the i-th column of the second row of the conversion matrix H; H 3i is the value of the i-th column of the third row of the conversion matrix H.

[0098] Step S75, determine the average weighted residual corresponding to the target weighted residual.

[0099] Specifically, the target weighted residual is divided by 3 to obtain the average weighted residual: Step S77, determine the angle difference between the actual fault command rudder angle and the average weighted residual as the corresponding jamming angle of the fault rudder.

[0100] Specifically, the jamming angle refers to the deviation of the rudder angle caused by the failure or fault of the fault rudder. By calculating the actual fault command rudder angle and the average weighted residual, a more accurate rudder angle adjustment value, i.e. the jamming angle, can be obtained. When calculating the jamming angle, subtracting the average weighted residual helps to eliminate the influence caused by disturbances or errors, and thus obtains a more accurate rudder correction value.

[0101] Jamming angle: The embodiment determines the fault rudder and obtains the corresponding actual fault command rudder angle and target fault residual value in different directions, which provides basic information for subsequent fault compensation. Then, by weighting calculation of the target fault residual value and the corresponding elements in the conversion matrix, the target weighted residual is obtained, thereby quantifying the influence of rudder failure on each direction. Further, by calculating the average value of the target weighted residual, a stable residual index is obtained, which reduces the influence of single direction error and ensures the balance. Finally, by comparing the angle difference between the actual fault command rudder angle and the average weighted residual, the jamming angle of the fault rudder is accurately determined.

[0102] The specific implementation of the present application will be described below in combination with a specific application scenario. In the simulation model, the expected depth of the AUV is set to 1 m, the expected yaw angle is set to 57.3°, the expected roll angle is set to 0°, and the uncertainty disturbance (σ v1 , σ v2 , σ h1 , σ h2 , σ r1 , σ r2) are all 0.01sin(t). Through the LQR control algorithm, the AUV completes dynamic adjustment within 0-20 seconds and maintains stability within 20-50 seconds. At 50 seconds, the rudder 1 has a mechanical jamming fault, and the jamming angle is fixed at 20°. The total simulation time is 100 seconds, and the sampling time is 0.1 seconds.

[0103] The simulation results show that: Figure 10 It can be seen from the figure that, when the rudder 1 fails, the AUV deviates from the normal running track, and the depth, yaw angle, roll angle and other states change significantly. The light gray area in the figure indicates the steady-state running stage of the AUV, and the dark area indicates the rudder failure running stage of the AUV. It can be seen from the figure that, due to the failure of the rudder 1, the actual rudder angle of the AUV tail X rudder driven by the LQR control algorithm changes, and no longer maintains the original steady-state rudder angle. The light gray area in the figure indicates the steady-state running stage of the AUV, and the dark area indicates the rudder failure running stage of the AUV. It can be seen from the figure that, due to the failure of the rudder 1, the actual rudder angle of the AUV tail X rudder driven by the LQR control algorithm changes, and no longer maintains the original steady-state rudder angle. Figure 11 Figure 12 It can be seen from the figure that the target residual value estimated by the disturbance observer remains within the residual threshold range when the rudder is normally running, and the system judges that the AUV is in a normal state. However, when the rudder fails, the fault detection system detects that the target residual value exceeds the residual threshold within 1 second, and accurately identifies the specific position of the faulty rudder through the defined fault judgment rule table. At the same time, the system estimates the approximate jamming angle of the rudder through the calculation of the jamming angle formula. The light gray area in the figure indicates the steady-state running stage of the AUV, and the dark area indicates the rudder failure running stage of the AUV.

[0104] The simulation verification results show that the embodiments of the present application can quickly and accurately detect the rudder failure and effectively estimate the jamming angle, thereby ensuring the control and stable running of the AUV in the failure condition.

[0105] Correspondingly, refer to Figure 13 for a block diagram of a rudder fault detection device provided by the embodiments of the present application, which is applied to an autonomous underwater vehicle, and the device comprises: a virtual instruction determination unit 101, configured to acquire current state data and expected state data of the autonomous underwater vehicle, and determine virtual instruction rudder angles in different directions based on the current state data and the expected state data; an actual instruction determination unit 103, configured to determine actual instruction rudder angles corresponding to the virtual instruction rudder angles; a fault condition determination unit 105, configured to determine target residual values between the virtual instruction rudder angles and actual driving rudder angles in different directions, and determine a fault condition of the rudder based on the target residual values and a pre-set residual threshold value; ​The jamming angle determination unit 107 is configured to determine a jamming angle corresponding to the faulty rudder in the case of a fault of the rudder, based on the actual command rudder angle and the target residual value.

[0106] In some optional embodiments, when the direction is the vertical direction, the current state data includes a current vertical speed, a current pitch angular speed, a current pitch angle, and a current depth, and the desired state data includes a desired depth; the virtual command determination unit 101 includes: determining a depth difference value of the current depth and the desired depth, and integrating the depth difference value to obtain a depth integral term; determining a vertical direction control gain matched with the current vertical speed, the current pitch angular speed, the current pitch angle, the depth difference value, and the depth integral term; determining a vertical target term matched with the current vertical speed, the current pitch angular speed, the current pitch angle, the depth difference value, and the depth integral term, respectively, according to the vertical direction control gain; adding all the vertical target terms to obtain a virtual command rudder angle in the vertical direction.

[0107] In some optional embodiments, when the direction is the horizontal direction, the current state data includes a current lateral speed, a current yaw angular speed, and a current yaw angle, and the desired state data includes a desired yaw angle; the virtual command determination unit 101 includes: determining a yaw angle difference value of the current yaw angle and the desired yaw angle, and integrating the yaw angle difference value to obtain a yaw angle integral term; determining a horizontal direction control gain matched with the current lateral speed, the current yaw angular speed, the yaw angle difference value, and the yaw angle integral term; determining a horizontal target term matched with the current lateral speed, the current yaw angular speed, the yaw angle difference value, and the yaw angle integral term, respectively, according to the horizontal direction control gain; adding all the horizontal target terms to obtain a virtual command rudder angle in the horizontal direction.

[0108] In some optional embodiments, when the direction is the roll direction, the current state data includes a current roll angular speed and a current roll angle, and the desired state data includes a desired roll angle; the virtual command determination unit 101 includes: determining a roll angle difference value of the current roll angle and the desired roll angle, and integrating the roll angle difference value to obtain a roll angle integral term; determining a roll direction control gain matched with the current roll angular speed, the roll angle difference value, and the roll angle integral term, and determining a roll target term matched with the current roll angular speed, the roll angle difference value, and the roll angle integral term, respectively, according to the roll direction control gain; The virtual command rudder angles in different directions are added to obtain a virtual command rudder angle vector.

[0109] In some optional embodiments, the actual command determination unit 103 comprises: The virtual command rudder angles in different directions are added to obtain a virtual command rudder angle vector. The virtual command rudder angle vector is converted into an actual command rudder angle vector by using a preset conversion matrix; wherein the actual command rudder angle vector comprises an actual command rudder angle corresponding to each rudder angle.

[0110] In some optional embodiments, the fault condition determination unit 105 comprises: For any direction, an error difference value between the virtual command rudder angle and the actual driving rudder angle is determined; The disturbance term corresponding to any direction is subtracted from the error difference value to obtain an initial residual value; The initial residual value is filtered to obtain a filtered target residual value.

[0111] In some optional embodiments, the stiction angle determination unit 107 comprises: A fault rudder is obtained, and an actual fault command rudder angle corresponding to the fault rudder and target fault residual values in different directions are determined; A target weighted residual value matching the target fault residual value is determined; An average weighted residual value corresponding to the target weighted residual value is determined; An angle difference value between the actual fault command rudder angle and the average weighted residual value is determined as a stiction angle corresponding to the fault rudder.

[0112] Further function descriptions of the above-mentioned various modules and units are the same as those of the above-mentioned corresponding embodiments, and will not be described here.

[0113] The rudder fault detection device in the embodiment is presented in the form of a functional unit, wherein the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory executing one or more software or fixed programs, and / or other devices that can provide the above-mentioned functions.

[0114] Please refer to Figure 14 , Figure 14 A structural schematic diagram of a computer device provided in the embodiment of the present application, as shown in Figure 14As shown, the computer device includes one or more processors 10, memory 20, and interfaces 30 for the various components to communicate with one another. The various components communicate through the use of the various buses, and can be mounted on a common motherboard or in other manners as appropriate. The processor 10 can process instructions for execution within the computer device, including instructions stored in the memory 20 or elsewhere to implement routines for displaying graphical information, such as a GUI on an external input / output device, such as a display device coupled to the interface 30. In some embodiments, multiple processors and / or multiple buses can be employed as appropriate, as will be appreciated by those skilled in the art. Additionally, various components of the computer device can be used for processing instructions according to the embodiments, as will be appreciated. The computer device can be one of a plurality of computer devices in communication with one another through a network, as is common in an enterprise setup, for example. Figure 14 The processor 10 is taken as an example in the embodiments.

[0115] The processor 10 can be a central processing unit, a network processor, or a combination thereof. The processor 10 can further include a hardware chip. The hardware chip can be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device can be a complex programmable logic device, a field programmable logic device, a general array logic, or any combination thereof.

[0116] The memory 20 stores instructions that are executable by the at least one processor 10, so as to enable the at least one processor 10 to perform the method shown in the embodiments.

[0117] The memory 20 can include a program storage area and a data storage area. The program storage area can store an operating system, application programs required by at least one function, and the like. The data storage area can store data created according to the use of the computer device, and the like. In addition, the memory 20 can include a high-speed random access memory, and can further include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some alternative embodiments, the memory 20 can optionally include a memory that is remotely arranged with respect to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0118] The memory 20 can include a volatile memory, such as a random access memory, and can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid state disk. The memory 20 can further include a combination of the above-mentioned kinds of memories.

[0119] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or communication networks.

[0120] The embodiments of the present application further provide a computer readable storage medium, and the method according to the embodiments of the present application can be implemented in hardware, firmware, or recorded in a storage medium, or stored in a remote storage medium or a non-transitory machine readable storage medium and downloaded to a local storage medium through network, so that the method described herein can be processed by such software on a storage medium using a general purpose computer, a special purpose processor, or programmable or special hardware. The storage medium can be a disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid state disk, etc. Further, the storage medium can also include a combination of the above-mentioned memories. It can be understood that the computer, the processor, the microprocessor controller, or the programmable hardware includes a storage component that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is implemented.

[0121] The apparatus and units illustrated in the above embodiments can be specifically implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0122] For the convenience of description, the above apparatus is described in various units by function. Of course, the functions of the units can be implemented in the same or more software and / or hardware in the implementation of the present application.

[0123] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, an apparatus. Therefore, the present application can adopt a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt a computer program product in the form of being implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0124] The present application is described with reference to flowcharts and / or block diagrams of the methods, devices, and apparatuses according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks in the flowcharts and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, a special purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus produce a machine that implements the flowcharts and / or block diagrams. The computer program instructions can also be stored in a computer readable storage medium that can guide the computer program instructions to be executed by a computer or other programmable data processing apparatus.Figure 1 one or more processes and / or blocks Figure 1 means for performing the function specified by the block or blocks.

[0125] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to function in a Figure 1 one or more processes and / or blocks Figure 1 means for performing the function specified by the block or blocks.

[0126] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the Figure 1 one or more processes and / or blocks Figure 1 means for performing the function specified by the block or blocks.

[0127] It is also noted that the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0128] Each of the embodiments in the present specification is described in progressive manner, and the same or similar parts among the embodiments can be mutually referred to, and each of the embodiments mainly explains the difference from other embodiments. In particular, for the device embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiments.

[0129] The above only describes the embodiments of the present application and is not intended to limit the present application. The present application can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the scope of the claims of the present application.

[0130] Although the embodiments of the present application are described in conjunction with the accompanying drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present application, and such modifications and changes shall fall within the scope defined by the appended claims.

Claims

1. A method for detecting a steering gear failure, characterized in that: Applied to an autonomous underwater vehicle, the method comprises: acquiring current state data and desired state data of the autonomous underwater vehicle, and determining virtual command rudder angles in different directions based on the current state data and the desired state data; Determining an actual command rudder angle corresponding to the virtual command rudder angle; determining target residual values ​​between the virtual command steering angle and the actual driven steering angle in different directions, and determining a fault condition of the steering gear based on the target residual values ​​and a preset residual threshold; In the case that the steering gear has a fault, a stuck angle corresponding to the faulty steering gear is determined based on the actual command steering angle and the target residual value.

2. The method according to claim 1, characterized in that When the direction is a vertical direction, the current state data includes a current vertical velocity, a current pitch angular velocity, a current pitch angle, and a current depth; the desired state data includes a desired depth; and the method for determining the virtual command rudder angle includes: determining a depth difference between the current depth and the desired depth, and integrating the depth difference to obtain a depth integral term; determining a vertical direction control gain that matches the current vertical velocity, the current pitch angular velocity, the current pitch angle, the depth difference, and the depth integral term; determining, according to the vertical direction control gain, vertical target terms that match the current vertical velocity, the current pitch angular velocity, the current pitch angle, the depth difference, and the depth integral term; All the vertical target items are added together to obtain the virtual command rudder angle in the vertical direction.

3. The method according to claim 1, characterized in that When the direction is horizontal, the current state data includes a current lateral velocity, a current yaw angular velocity, and a current yaw angle, and the desired state data includes a desired yaw angle; and the method for determining the virtual command rudder angle includes: Determining a yaw angle difference between the current yaw angle and the desired yaw angle, and integrating the yaw angle difference to obtain a yaw angle integral term; Determining a horizontal direction control gain that matches the current lateral velocity, the current yaw angular velocity, the yaw angle difference, and the yaw angle integral term; determining, according to the horizontal direction control gain, horizontal target items that match the current lateral velocity, the current yaw angular velocity, the yaw angle difference, and the yaw angle integral item; All the horizontal target items are added together to obtain the virtual command rudder angle in the horizontal direction.

4. The method according to claim 1, wherein When the direction is a rolling direction, the current state data includes a current rolling angular velocity and a current rolling angle, and the desired state data includes a desired rolling angle; and the method for determining the virtual command steering angle includes: determining a roll angle difference between the current roll angle and the desired roll angle, and integrating the roll angle difference to obtain a roll angle integral term; determining a roll direction control gain that matches the current roll angular velocity, the roll angle difference, and the roll angle integral term; determining, according to the roll direction control gain, roll target terms that match the current roll angular velocity, the roll angle difference, and the roll angle integral term; All the roll target items are added together to obtain the virtual command steering angle in the roll direction.

5. The method according to claim 1, wherein The determining of the actual command steering angle corresponding to the virtual command steering angle includes: The virtual command rudder angles in different directions are combined into a virtual command rudder angle vector; The virtual command steering angle vector is converted into an actual command steering angle vector using a preset conversion matrix; wherein the actual command steering angle vector includes the actual command steering angle corresponding to each steering angle.

6. The method according to claim 1, characterized in that Determining target residual values ​​between the virtual command steering angle and the actual driving steering angle in different directions includes: For any direction, determining the error difference between the virtual command steering angle and the actual driving steering angle; Subtracting the disturbance term corresponding to any direction from the error difference to obtain an initial residual value; The initial residual value is filtered to obtain a filtered target residual value.

7. The method according to claim 1, characterized in that The determining, based on the actual command steering angle and the target residual value, a stuck angle corresponding to a faulty steering gear having a fault, includes: Obtaining a faulty steering gear, and determining an actual fault command steering angle corresponding to the faulty steering gear and target fault residual values ​​in different directions; determining a target weighted residual that matches the target fault residual value; Determining an average weighted residual corresponding to the target weighted residual; The angle difference between the actual fault command steering angle and the average weighted residual is determined as the stuck angle corresponding to the faulty steering gear.

8. A steering gear fault detection device, characterized in that: Applied to an autonomous underwater vehicle, the device comprises: a virtual instruction determination unit, configured to obtain current state data and desired state data of the autonomous underwater vehicle, and determine virtual instruction steering angles in different directions based on the current state data and the desired state data; and an actual instruction determination unit, configured to determine an actual instruction steering angle corresponding to the virtual instruction steering angle; a fault condition determination unit, configured to determine target residual values ​​between the virtual command steering angle and the actual driven steering angle in different directions, and determine a fault condition of the steering gear based on the target residual values ​​and a preset residual threshold; The stuck angle determining unit is used to determine a stuck angle corresponding to the faulty steering gear based on the actual command steering angle and the target residual value when the steering gear fails.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the steering gear fault detection method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the steering gear fault detection method according to any one of claims 1 to 7.

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