An underactuated circular disc-shaped underwater unmanned vehicle motion control method, program, device and storage medium based on an adaptive backstepping sliding mode controller

Abstract

The present application aims at the motion control problem of an underactuated circular disc-shaped underwater unmanned vehicle in complex marine environment, establishes a kinematic model, a dynamic model and a six-degree-of-freedom motion model considering the existence of ocean current, and decouples the six-degree-of-freedom model into a horizontal plane model and a vertical plane dynamic control model, designs a depth and a heading angle adaptive backstepping sliding mode controller based on the backstepping method and the sliding mode variable structure algorithm respectively. In each motion control process, the present application updates the adaptive parameters of the heading angle adaptive backstepping sliding mode controller and the depth adaptive backstepping sliding mode controller through adaptive control rate, and corrects the update results of each adaptive parameter by using a mapping function, preventing the adaptive parameters from increasing infinitely by integral, and enhancing the stability of the system. The adaptive backstepping sliding mode controller designed by the present application has better control performance and robustness, and can better adapt to complex marine environment, so as to realize the precise control of the circular disc-shaped underwater unmanned vehicle.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of underwater unmanned vehicle control, and particularly relates to an underactuated circular disc-shaped underwater unmanned vehicle motion control method, program, equipment and storage medium based on an adaptive backstepping sliding mode controller. BACKGROUND

[0002] The circular disc-shaped underwater unmanned vehicle adopts a circular disc-shaped design, and can move in multiple degrees of freedom in water, especially vertically, through vertical and horizontal propellers installed on the body, and has the function of fixed-point hovering, similar to a helicopter on land. This design enables the circular disc-shaped underwater unmanned vehicle to have high mobility in the horizontal plane while having strong stability in the vertical plane. Therefore, the circular disc-shaped underwater unmanned vehicle has great advantages when working in scenarios such as high-precision horizontal movement, fixed-height and depth operation, operation and inspection near the seabed, and cruising between seabed stations.

[0003] Good motion control is a basic technical prerequisite for a submersible to complete underwater operations. However, the circular disc-shaped underwater unmanned vehicle has a large difficulty in controlling the heading angle due to its circular disc-shaped design. Traditional AUV vertical depth diving is often achieved through pitch motion, while the circular disc-shaped underwater unmanned vehicle can directly perform vertical diving, and the different motion methods will also lead to different motion controller designs. Therefore, it is of great significance to design a motion controller for the motion characteristics of the circular disc-shaped underwater unmanned vehicle to accurately control its pose and track the preset path.

[0004] Currently, the control methods used for AUVs mainly include PID control, sliding mode variable structure control, adaptive control, backstepping control, etc. PID control has a simple structure and low dependence on system models, and has strong applicability, so it is widely used in various industrial process controls. However, in complex and variable underwater environments, fixed-parameter PID control often cannot adapt to the strong nonlinear and time-varying characteristics of the submersible motion model parameters. At this time, PID control can be combined with other advanced control methods to improve control effectiveness.

[0005] Backstepping control decomposes a complex nonlinear system into multiple subsystems, designs Lyapunov functions and intermediate virtual control quantities for each subsystem, and then backstepping the entire system to design the control law, so that the entire closed-loop system meets the desired dynamic and static performance indicators. Backstepping control has a clear structure, is easy to design, and can guarantee the global stability of the closed-loop system, and is an effective tool for designing complex nonlinear system controllers, so it is widely used in AUV control.

[0006] Sliding mode variable structure control is a special nonlinear control method, which can make the system move along the preset state trajectory. Because the sliding mode can be designed and is independent of the parameters of the control object and disturbances, the sliding mode control has the advantages of fast response and high robustness, and is widely used in AUV control. However, after the system state trajectory reaches the sliding mode surface, the sliding mode variable structure control is difficult to strictly slide along the sliding mode surface, and will cross back and forth on both sides of the sliding mode surface, thereby causing the chattering problem. When applied to AUV control, due to the large uncertainty of the system model of AUV and the external environmental disturbance, the gain of the switching term of the sliding mode controller is prone to be too large, thereby causing the output chattering problem of the sliding mode controller to be more serious. In order to solve the chattering problem, many scholars have proposed solutions from different angles. A commonly used method is to replace the sign function with a saturation function, to use normal sliding mode control outside the boundary layer, and to use continuous state feedback control inside the boundary layer, to realize quasi-sliding mode control, thereby effectively weakening the chattering. Another commonly used method is to approximate the model uncertainty and external disturbance by using fuzzy function, adaptive method and disturbance observer, and to compensate, thereby effectively reducing the chattering in the sliding mode control. SUMMARY

[0007] The application provides an underactuated circular disc-shaped underwater unmanned vehicle motion control method, program, equipment and storage medium based on an adaptive backstepping sliding mode controller.

[0008] An underactuated circular disc-shaped underwater unmanned vehicle motion control method based on an adaptive backstepping sliding mode controller comprises the following steps:

[0009] Based on the backstepping method and the sliding mode variable structure algorithm, considering the uncertainty and external disturbance in the dynamic model of the underactuated circular disc-shaped underwater unmanned vehicle, a yaw angle adaptive backstepping sliding mode controller and a depth adaptive backstepping sliding mode controller containing fixed design parameters and adaptive parameters are designed.

[0010] For each adaptive parameter, the initial limit value, the expected time and the expected sliding mode surface value are determined, and the adaptive control rate is designed for integration; the integral value of the adaptive parameter within the expected time is obtained, and the sliding mode surface value is calculated according to the integral value; if the integral value exceeds the initial limit value, or the sliding mode surface value exceeds the expected sliding mode surface value, the adaptive control rate of the adaptive parameter is redesigned; otherwise, the absolute value of the smaller one of the sliding mode surface value and the initial limit value is taken as the updated limit value of the adaptive parameter.

[0011] During each motion control process, the adaptive parameters of the heading angle adaptive backstepping sliding mode controller and the depth adaptive backstepping sliding mode controller are updated by the adaptive control law. The update results of each adaptive parameter are corrected by the mapping function to prevent the absolute value of the updated adaptive parameter from exceeding its update limit.

[0012] The heading angle adaptive backstepping sliding mode controller outputs the heading dimension control torque based on the input heading angle tracking error; the depth adaptive backstepping sliding mode controller outputs the depth dimension control torque based on the input depth tracking error; the underactuated disc-shaped underwater unmanned vehicle executes the heading and depth dimension control torques within the control step; the above process is repeated until both the heading angle tracking error and the depth tracking error meet the requirements.

[0013] Furthermore, the heading angle adaptive backstepping sliding mode controller specifically comprises:

[0014]

[0015]

[0016]

[0017]

[0018] in, To control the number of repetitions of the movement; , , , For the first Adaptive parameters of the heading angle adaptive backstepping sliding mode controller in secondary motion control; , , , These are the fixed design parameters for the heading angle adaptive backstepping sliding mode controller; This is a saturation function used to replace the sign function in the ideal sliding mode; The approach velocity of the heading angle adaptive backstepping sliding mode controller; The control torque in the heading dimension is the output of the heading angle adaptive backstepping sliding mode controller; For the first The heading angle tracking error of an underactuated disc-shaped underwater unmanned vehicle in secondary motion control. ; For the first The heading angle of an underactuated disc-shaped underwater unmanned vehicle in secondary motion control; For the desired heading angle, The desired heading angular acceleration; For the first The heading angular velocity of an underactuated disc-shaped underwater unmanned vehicle in secondary motion control; ; To control the step size.

[0019] Furthermore, the step of updating the adaptive parameters of the heading angle adaptive backstepping sliding mode controller through the adaptive control law specifically involves:

[0020]

[0021]

[0022]

[0023]

[0024] in, , , , is the fixed design parameter for the heading angle adaptive backstepping sliding mode controller; Proj is the mapping function. , This is the update limit value for the adaptive parameter M.

[0025] Furthermore, the depth-adaptive backstepping sliding mode controller specifically comprises:

[0026]

[0027]

[0028]

[0029]

[0030] in, , , For the first Adaptive parameters of depth adaptive backstepping sliding mode controller in secondary motion control; , , , Fixed design parameters for the depth-adaptive backstepping sliding mode controller; The approach speed of the depth-adaptive backstepping sliding mode controller; The depth-dimensional control torque output by the depth-adaptive backstepping sliding mode controller; For the first Depth tracking error in sub-motion control of underactuated disc-shaped underwater unmanned vehicles. ; For the first Depth of an underactuated circular disc-shaped underwater unmanned vehicle in secondary motion control for a desired depth, for a desired vertical acceleration; for a first vertical acceleration of an underactuated circular disc-shaped underwater unmanned vehicle in secondary motion control .

[0031] Further, the adaptive parameters of the depth adaptive backstepping sliding mode controller are updated through adaptive control rate, specifically:

[0032]

[0033]

[0034]

[0035] wherein, , , are fixed design parameters of the depth adaptive backstepping sliding mode controller; .

[0036] Further, the underactuated circular disc-shaped underwater unmanned vehicle executes the control moment in the bow direction dimension and the control moment in the depth dimension within a control step length , after a time, the bow angle , the bow angle velocity , the depth , and the vertical acceleration of the underactuated circular disc-shaped underwater unmanned vehicle are obtained;

[0037] the bow angle tracking error and the depth tracking error are calculated;

[0038] according to preset bow angle tracking error threshold and depth tracking error threshold , if and , the iteration is stopped, and the motion control of the underactuated circular disc-shaped underwater unmanned vehicle is completed.

[0039] Further, the motion control process specifically includes the following steps:

[0040] Step 1: obtaining the bow angle , the bow angle velocity , the depth , and the vertical acceleration ; obtaining a desired heading angle of an underactuated circular-disk-shaped underwater unmanned vehicle , a desired heading angle acceleration , a desired depth , a desired vertical acceleration ;

[0041] initializing a control number , initializing an adaptive parameter of a heading angle adaptive backstepping sliding mode controller , , , ; initializing an adaptive parameter of a depth adaptive backstepping sliding mode controller , , ;

[0042] Step 2: calculating a heading angle tracking error of the underactuated circular-disk-shaped underwater unmanned vehicle in the current control and a depth tracking error ;

[0043] if and , stopping iteration, completing motion control of the underactuated circular-disk-shaped underwater unmanned vehicle; otherwise, performing Step 3;

[0044] Step 3: inputting the heading angle tracking error to the heading angle adaptive backstepping sliding mode controller to obtain a control moment in the heading direction in the current control ;

[0045] Step 4: inputting the depth tracking error to the depth adaptive backstepping sliding mode controller to obtain a control moment in the depth direction in the current control ;

[0046] Step 5: updating the adaptive parameter of the heading angle adaptive backstepping sliding mode controller , , , ; updating the adaptive parameter of the depth adaptive backstepping sliding mode controller , , ;

[0047] Step 6: the propeller of the underactuated circular-disk-shaped underwater unmanned vehicle executes the control moment in the heading direction and the control moment in the depth direction , and executes Time, the heading angle of the underactuated round disc-shaped underwater unmanned vehicle is acquired , the heading angle velocity , the depth , the vertical acceleration , and returning to step 2.

[0048] A computer device comprises a memory, a processor and a computer program stored in the memory, and the processor executes the computer program to realize the steps of the above-mentioned underactuated round disc-shaped underwater unmanned vehicle motion control method based on an adaptive backstepping sliding mode controller.

[0049] A computer readable storage medium has a computer program stored thereon, and the computer program is executed by a processor to realize the steps of the above-mentioned underactuated round disc-shaped underwater unmanned vehicle motion control method based on an adaptive backstepping sliding mode controller.

[0050] A computer program product comprises computer instructions, and the computer instructions are executed by a processor to realize the steps of the above-mentioned underactuated round disc-shaped underwater unmanned vehicle motion control method based on an adaptive backstepping sliding mode controller.

[0051] The present application has the following beneficial effects:

[0052] The present application aims at the motion control problem of an underactuated round disc-shaped underwater unmanned vehicle in a complex marine environment, establishes a kinematic model, a dynamic model and a six-degree-of-freedom motion model considering the existence of sea currents, and decouples the six-degree-of-freedom model into a horizontal plane model and a vertical plane dynamic control model, and designs depth and heading angle adaptive backstepping sliding mode controllers based on backstepping and sliding mode variable structure algorithms respectively. In each motion control process, the adaptive parameters of the heading angle adaptive backstepping sliding mode controller and the depth adaptive backstepping sliding mode controller are updated through adaptive control, and the update results of each adaptive parameter are corrected by using a mapping function to prevent the adaptive parameters from increasing infinitely by integral, and the stability of the system is enhanced.

[0053] The stability of the closed-loop system of the present application can be proved by using Lyapunov theory, and through simulation experiments, pool experiments and field experiments, it is verified that the adaptive backstepping sliding mode controller designed in the present application has better control performance and robustness, and can better adapt to complex marine environments, and can realize precise control of the round disc-shaped underwater unmanned vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 is a motion state depth control simulation result graph.

[0055] Figure 2 is a depth control simulation result graph under the existence of sea currents.

[0056] Figure 3 Figure for simulation results of heading angle control for moving state.

[0057] Figure 4 Figure for simulation results of heading angle control for fixed direction random size current.

[0058] Figure 5 Figure for depth comparison experiment results.

[0059] Figure 6 Figure for heading angle comparison experiment results.

[0060] Figure 7 Figure for variable depth tracking experiment results.

[0061] Figure 8 Figure for variable heading angle tracking experiment results.

[0062] Figure 9 Figure for homing experiment results. DETAILED DESCRIPTION

[0063] The application will be further described below in combination with the drawings.

[0064] The application estimates the parameters of a circular disc-shaped underwater unmanned vehicle system online through an adaptive method, designs adaptive backstepping sliding mode controllers for depth and heading angle based on backstepping method and sliding mode variable structure algorithm respectively, and proves the stability of the closed loop system by Lyapunov theory. Finally, the superiority of the proposed control algorithm is verified through simulation experiment, pool experiment and field experiment. The application solves the problem of accurate control of a circular disc-shaped underwater unmanned vehicle in a complex marine environment.

[0065] The motion model of the heading angle can be written as:

[0066]

[0067] Let , , the above formula can be rewritten as:

[0068]

[0069]

[0070]

[0071] wherein, represents a linear resistance coefficient, represents a quadratic resistance coefficient, represents a controller gain, and represents the modeling error of the yaw angle control model and unknown external disturbance. The system states x1and x2, i.e. the yaw angle and the yaw angle velocity, are measurable.

[0072] For the yaw motion model, the control objective is to make x1→ x 1d .

[0073] Define the tracking position error , the error derivative is:

[0074]

[0075] Define the Lyapunov candidate function , its derivative is:

[0076]

[0077] To make negative definite, introduce a virtual control variable = , where is a positive design parameter.

[0078] Define the virtual control error:

[0079]

[0080] That is, = - .

[0081] The virtual error derivative is:

[0082]

[0083] At this time:

[0084]

[0085] If → 0, then is negative definite.

[0086] Define the sliding mode surface switching function = , where is a positive design parameter.

[0087]

[0088] Since > 0, obviously, if = 0, then = 0, = 0 and negative, the next step design is needed.

[0089] Definition of Lyapunov candidate function

[0090]

[0091] Then we have:

[0092]

[0093]

[0094] where, .

[0095] Using the exponential approach law, the controller can be designed as:

[0096]

[0097] , ;

[0098] Then:

[0099]

[0100] According to the Lyapunov stability theory, positive definite and negative, then [ , ] ⊤ → 0, t → ∞.

[0101] But we do not know the specific value of , , , , only know their approximate range, so we need to use their estimates , , , to replace. In order to facilitate the design of the adaptive controller, we make the following assumptions.

[0102] Assumption one: the bow control system parameters , , unknown but bounded, their upper and lower limits can be represented as:

[0103]

[0104] where, , , , , , All are known empirically.

[0105] Assumption two: the yaw angle control system parameters , , All are fixed, i.e. = 0, = 0, = 0. The unknown disturbance term is a slow time-varying disturbance.

[0106] After using the estimated parameters, the yaw angle controller can be redesigned as:

[0107]

[0108] where, .

[0109] The yaw angle system parameter adaptive law is designed as:

[0110]

[0111] Define the Lyapunov candidate function:

[0112]

[0113] where, ., , , .

[0114] Since , at this time can be rewritten as:

[0115]

[0116] And derivative is:

[0117]

[0118] According to assumption two, the disturbance term is a slow time-varying disturbance, small, when taking is a large value, can be considered:

[0119]

[0120] Then derivative can be rewritten as:

[0121]

[0122] According to Lyapunov stability theory, Semi-negative, , , , , , are stable, that is, bounded. Then is also bounded, since is uniformly continuous in time t, → 0, t→∞, then → 0, → 0. The closed-loop system error tends to zero, that is, is asymptotically stable. Since the stability of the system is independent of the initial time, so is uniformly asymptotically stable, while is a radial unbounded function, so is globally uniformly asymptotically stable.

[0123] It is worth noting that only and can be proved to tend to 0 as t→∞, and it cannot be obtained that the estimated parameters and disturbance errors , , , tend to 0, only the boundedness of the estimation error can be guaranteed. Therefore, in order to prevent the estimated parameters , , from being too large and causing the controller output signal to be too large, the present application modifies the adaptive law by using a mapping adaptive algorithm:

[0124]

[0125] where The mapping algorithm is expressed as follows:

[0126]

[0127] That is, when exceeds the maximum value, if there is a tendency to continue to increase, that is, , then take to avoid continuing to increase; when is lower than the minimum value, if there is a tendency to continue to decrease, that is, , then take to avoid continuing to decrease.

[0128] It should be noted that the use of adaptive mapping algorithm can guarantee in ≤ 0, the analysis is as follows:

[0129] when and hour, , ,and ,but ;

[0130] when and hour, , ,and ,

[0131] but ;

[0132] In other cases .

[0133] Estimated parameters and The analysis using the adaptive mapping algorithm is the same as above.

[0134] Therefore, the stability analysis results of the heading angle error remain unchanged after adopting the adaptive mapping algorithm.

[0135] It is also worth noting that, This would cause the controller to chatter, therefore this invention uses a saturation function. To replace the sign function in the ideal sliding mode The saturation function is defined as:

[0136]

[0137] in It is a positive design constant, called the boundary layer.

[0138] The design of the heading angle adaptive backstepping sliding mode controller is now complete. This method can be used for the heading motion control of underactuated disc-shaped underwater unmanned vehicles.

[0139] For the depth motion model, the control objective is to make → It is designed in the same way as the heading angle adaptive backstepping sliding mode controller, using the same sliding mode switching surface function and Lyapunov candidate function, but with slight differences.

[0140] The derivative of the sliding mode switching function s in the design of a depth adaptive backstepping sliding mode controller is:

[0141]

[0142] in, .

[0143] With the exponential approach law and the assumption of system parameters, the depth adaptive backstepping sliding mode controller can be designed as:

[0144]

[0145] where,

[0146] Input design parameters , state variables of the system , target value of rudder angle , estimated value of linear resistance coefficient , estimated value of quadratic resistance coefficient , estimated value of heading angle control model modeling error and unknown external disturbance , estimated value of controller gain , approach speed , saturation function , output torque after the rudder angle controller , and then converted into the speed of each propeller by thrust distribution.

[0147] The depth control system parameter adaptive law is designed as:

[0148]

[0149] The depth error stability analysis is similar to the heading angle adaptive backstepping sliding mode controller design, and the depth error is also globally uniformly asymptotically stable.

[0150] So far, the depth adaptive backstepping sliding mode controller is designed. This method can be used for depth motion control of the underactuated circular disc-shaped underwater unmanned vehicle.

[0151] Based on the above theoretical derivation, the underactuated circular disc-shaped underwater unmanned vehicle motion control method based on the adaptive backstepping sliding mode controller provided by the application comprises the following steps:

[0152] Step 1: design a heading angle adaptive backstepping sliding mode controller and a depth adaptive backstepping sliding mode controller containing fixed design parameters and adaptive parameters;

[0153] The fixed design parameters of the heading angle adaptive backstepping sliding mode controller are: , , , , , , , ; the adaptive parameters are: , , ,

[0154] Fixed design parameters of the depth adaptive backstepping sliding mode controller: , , , , , , Adaptive parameters: , , ;

[0155] Step 2: For each adaptive parameter, determine its initial limit value, expected time and expected sliding surface value, design the adaptive control rate for integration; obtain the integral value of the adaptive parameter within the expected time, and calculate the sliding surface value according to the integral value; if the integral value exceeds the initial limit value, or the sliding surface value exceeds the expected sliding surface value, redesign the adaptive control rate of the adaptive parameter; otherwise, take the absolute value of the smaller one of the sliding surface value and the initial limit value as the updated limit value of the adaptive parameter;

[0156] Step 3: Initialize the control times , obtain the initial time of the underactuated circular disc-shaped underwater unmanned vehicle at the initial time , the heading angle , the depth , the vertical acceleration ; obtain the expected heading angle , the expected heading angle acceleration , the expected depth , the expected vertical acceleration ;

[0157] Set the approach speed of the heading angle adaptive backstepping sliding mode controller ;

[0158] Set the approach speed of the depth adaptive backstepping sliding mode controller ;

[0159] Initialize the adaptive parameters of the heading angle adaptive backstepping sliding mode controller , , , ;

[0160] Initialize the adaptive parameters of the depth adaptive backstepping sliding mode controller , , ;

[0161] Set the control step size a heading angle tracking error threshold a depth tracking error threshold ;

[0162] Step 4: calculate the heading angle tracking error of the underactuated circular disc-shaped underwater unmanned vehicle in the current control and the depth tracking error ;

[0163]

[0164]

[0165] If and , stop iteration, complete the motion control of the underactuated circular disc-shaped underwater unmanned vehicle; otherwise, perform step 5;

[0166] Step 5: input the heading angle tracking error to the heading angle adaptive backstepping sliding mode controller to obtain the control moment of the heading dimension in the current control ;

[0167]

[0168]

[0169]

[0170]

[0171] wherein, , , ;

[0172] Step 6: input the depth tracking error to the depth adaptive backstepping sliding mode controller to obtain the control moment of the depth dimension in the current control ;

[0173]

[0174]

[0175]

[0176]

[0177] wherein, , , ;

[0178] Step 7: updating the adaptive parameter of the heading angle adaptive backstepping sliding mode controller 、 、 、 ; updating the adaptive parameter of the depth adaptive backstepping sliding mode controller 、 、 ;

[0179]

[0180]

[0181]

[0182]

[0183]

[0184]

[0185]

[0186] wherein, , , ;

[0187] Proj is a mapping function, , is the update limit value of the adaptive parameter M; through the above steps, the adaptive parameter can be reasonably limited to prevent the adaptive parameter from increasing infinitely by integration, and the stability of the system is enhanced.

[0188] Step 8: the propeller of the underactuated circular disc-shaped underwater unmanned vehicle executes the control moment in the heading dimension and the control moment in the depth dimension , executes for a period of time, and then the heading angle , the heading angle velocity , the depth , the vertical acceleration of the underactuated circular disc-shaped underwater unmanned vehicle are obtained, and the step 4 is returned.

[0189] Embodiment 1:

[0190] In order to verify the effectiveness of the present application, simulation experiments, pool experiments and field experiments are respectively carried out for the designed adaptive backstepping sliding mode controller.

[0191] Firstly, the simulation experiment is carried out, which is as follows:

[0192] (I) Depth Control Simulation Experiment:

[0193] Two simulation scenarios were designed: one with motion and the other with ocean currents. The design parameters of the PID controller, SMC controller, and adaptive backstepping sliding mode controller remained constant in both sets of experiments. The depth-direction PID controller used a PID module provided in the Simlink library, and its controller structure was as follows: Furthermore, a conditional integral anti-saturation method was employed. In the simulation experiment, the disc-shaped underwater unmanned vehicle was set to a zero initial state, and the desired depth was a square wave signal with an amplitude of 3m and a pulse width of 50%. The controller output saturation was 400. The design parameters of the PID controller were adjusted using Simulink PID Tuner to achieve relatively optimal parameters that balance response speed and robustness.

[0194] (1) Motion state depth control

[0195] The basic rotational speed of the dual horizontal thrusters was set to 1500 r / min to provide forward propulsion. The simulation results are as follows: Figure 1 As shown, the steady-state performance of the three controllers is basically the same as that under pure depth control in still water conditions. The PID controller and the adaptive backstepping sliding mode controller have no steady-state error, while the SMC controller has a certain steady-state error.

[0196] (2) Ocean currents have depth control

[0197] Based on the depth control experiment under motion conditions, a random ocean current with a velocity of 0-0.3 m / s and a direction of 60°-120° was added to conduct depth control experiments under the presence of the ocean current. This was to fully verify the robustness of the designed depth adaptive backstepping sliding mode controller to external disturbances such as ocean currents. The simulation results are as follows: Figure 2 As shown. The speed and direction of the ocean current in this experiment are as follows. Figure 2 As shown in (c), the magnitude and direction of the ocean current are random. Although this invention assumes that the ocean current is only a planar current and has no vertical current, the pitch angle and roll of the disc-shaped underwater unmanned vehicle will fluctuate to some extent under the action of the ocean current force, such as... Figure 2 As shown in (e) and (f), the horizontal forward velocity also affects the vertical motion of the disc-shaped underwater unmanned vehicle. The adaptive backstepping sliding mode controller proposed in this invention considers kinematic modeling errors from the initial design stage, thus performing better in depth control tasks under complex pitch fluctuation conditions, such as... Figure 2 As shown in (a), both the PID controller and the SMC controller fluctuate around the desired depth, failing to achieve stable depth control; the adaptive backstepping sliding mode controller...

[0198] Not only is the dynamic response faster, but the steady-state performance is also better, allowing it to stabilize at the desired depth. FromFigure 2 It can also be seen in Fig. 8 (b) that the adaptive backstepping sliding mode controller has less chattering than the SMC controller when the desired depth is near, because the adaptive backstepping sliding mode controller can adaptively adjust the controller parameters and disturbance estimation, thus effectively reducing the chattering.

[0199] From the two groups of experiments, it can be seen that the designed depth adaptive backstepping sliding mode controller performs well in different task environments and has strong robustness.

[0200] (II) Simulation experiment of heading angle control:

[0201] Two simulation scenarios are designed, namely the motion state and the existence of random size sea current in fixed direction. The design parameters of the PID controller, the SMC controller and the adaptive backstepping sliding mode controller remain unchanged in the three groups of experiments. In the simulation experiment, the disc-shaped underwater unmanned vehicle is set to zero initial state, the desired depth is 3m, and the desired heading angle is the step sequence signal with amplitude [40°, 80°, 120°, 60°, 0°, -60°, -90°, 0°, 90°, 120°] and time interval 10s. The gradient variable desired signal will maximize the simulation of the actual working heading angle control requirements. The heading angle controller output is saturated to 600r / min, which is 20% of the maximum speed of the horizontal thruster.

[0202] The design parameters of the PID controller are the relatively optimal parameters adjusted by the PID Tuner to balance the response speed and robustness.

[0203] (1) Heading angle control in motion state

[0204] The simulation results of heading angle control in motion state are shown in Fig. 8 (a) and Fig. 8 (b). The adaptive backstepping sliding mode controller reaches the steady state first in the whole tracking process, and has the best control effect without dynamic overshoot. The control effects of the three heading angle controllers in motion state are relatively good. Figure 3 Figure 3 The heading angle control in motion state produces a certain sideslip angle, as shown in Fig. 8 (e).

[0205] (2) Heading angle control in the presence of sea current with fixed direction and random size

[0206] To test the effect of the three heading angle controllers under the disturbance of sea current, this experiment adds a sea current with fixed direction of east, i.e. 90°, and speed size of 0-0.3m / s. The sea current speed is described in Fig. 8 (e). The simulation results of heading angle are shown in Fig. 8 (a) and Fig. 8 (b). Figure 4 Figure 4 ​​As shown in (a), the PID controller fails to stably track the desired angle for most of the time, exhibiting significant oscillations around the desired angle. In contrast, the SMC controller and the adaptive backstepping sliding mode controller can maintain relatively stable tracking around the desired angle, with errors within 0.6°. The adaptive backstepping sliding mode controller shows relatively smaller errors and better dynamic performance than the SMC controller. Figure 4 As can be seen from the controller output curve in (b), the adaptive backstepping sliding mode controller exhibits less chattering than the SMC controller. Notably, all three controllers converge to the desired angle within the timeframes of 50-60s (desired angle -90°) and 80-90s (desired angle 90°), at which point the heading angle is parallel to the ocean current direction, consistent with the actual movement of a submersible in ocean currents. Throughout the heading angle adjustment process, except for the initial depth adjustment phase, the pitch and roll angles remain generally within 5°. Furthermore, when the heading angle stabilizes, the pitch and roll angles remain near 0°, consistent with the assumptions made when establishing the heading angle control model.

[0207] The simulation experiments above demonstrate that the designed adaptive backstepping sliding mode controller can track the desired signal even under model uncertainty and ocean current interference. In particular, for controller parameters measured in the absence of ocean currents and interference, PID and SMC controllers fail to function well under current interference, while the adaptive backstepping sliding mode controller maintains a certain level of performance. The adaptive backstepping sliding mode controller exhibits stronger robustness, which is crucial for the practical application of disc-shaped underwater unmanned vehicles (UUVs), as it is difficult to adjust controller parameters on-site; typically, controller parameters are measured at zero speed.

[0208] Secondly, a water tank experiment was conducted, as follows:

[0209] (I) Comparative Experiment of Adaptive Backstepping Sliding Mode Controller and PID Controller:

[0210] In the depth control experiment, the disc-shaped underwater drone first rests on the bottom of the circular pool and then rises to the desired depth. In the heading angle control experiment, the disc-shaped underwater drone is set at a fixed depth, and then the desired heading angle is set. Since the initial state of the heading angle cannot be guaranteed to be the same in the comparative experiments, the comparative experiments of the PID controller and the adaptive backstepping sliding mode controller mainly analyze the steady-state results. The comparative experiments will select the data segment after the first arrival at the desired value for analysis, and the control effect will be evaluated using the mean absolute error and maximum absolute error indices.

[0211] The results of the depth contrast experiment are as follows Figure 5and Table 1. PID controller depth control shows a trend of convergence before 200s, and the overshoot of oscillation is continuously reduced, but the overshoot gradually increases after 200s, which may be because the underwater unmanned vehicle changes its buoyancy due to water entering the cavity inside the shell, thus changing the dynamic parameters of the underwater unmanned vehicle system, so the PID controller control effect is unstable, which also reflects the inability of the conventional PID controller to face complex changes underwater. The depth gradually converges to the expected value under the action of the adaptive backstepping sliding mode controller, and stabilizes near the expected value, and the depth oscillation overshoot under the action of the adaptive backstepping sliding mode controller is lighter than that of the PID controller. As can be seen from the results in Table 1, the maximum absolute tracking error of the depth under the adaptive backstepping sliding mode controller is only 36% of that of the PID controller, and the average absolute error is only 20% of that of the PID controller, which effectively illustrates the steady-state performance advantage of the adaptive backstepping sliding mode controller.

[0212]

[0213] The heading angle contrast experiment results are shown in Figure 6 and Table 2. It can be seen that the heading angle under the action of the PID controller and the adaptive backstepping sliding mode controller can converge near the expected value, but the heading angle under the action of the PID controller oscillates densely and has a large amplitude near the expected value, while the heading angle under the action of the adaptive backstepping sliding mode controller has a small oscillation after converging to the expected value. Table 2 also shows the steady-state performance advantage of the adaptive backstepping sliding mode controller for the heading angle, and the average absolute error of the heading angle under the adaptive backstepping sliding mode controller is reduced by 34% compared with the PID controller.

[0214]

[0215] (II) Change tracking experiment:

[0216] In the variable depth tracking experiment, the initial state of the disc-shaped underwater unmanned vehicle is sitting on the pool bottom, and then the expected depth is set to 4m→3m→2m→1m, so that the disc-shaped underwater unmanned vehicle gradually floats up, and the experimental results are shown in Figure 7 From Figure 7 (a), it can be seen that the actual depth can reach near the expected depth in the four tracking segments, but there is a certain oscillation in the first three tracking segments, and the maximum tracking error is about 0.3m, while in the last segment, the actual depth can converge well to the expected depth, which is because the adaptive backstepping sliding mode controller needs time to adaptively adjust the estimated parameters, and the control performance will gradually improve, so there is a certain oscillation error in the early stage. When enough time has passed, it can be ensured to converge to the expected value. The change curve of the attitude angle in the experiment is shown in Figure 7As shown in (b), the roll and pitch angles are basically stable around 0°, while the heading angle has a large oscillation error due to the change in depth.

[0217] In the variable heading angle tracking experiment, the depth was adjusted to the desired depth of 4m, and then the desired heading angle was set from 170° to 120° to 70°. The experimental results are as follows. Figure 8 As shown. From Figure 8 As can be seen in (a), in all three desired depth segments, the actual heading angle converges well to the desired depth, with a steady-state error not exceeding 2°. The first heading angle dynamic oscillation time is longer than the latter two segments because the depth is also adjusted during the heading angle control in the first segment, and the two are coupled and influence each other. From Figure 8 As shown in (b), after the depth stabilizes at 4m, i.e., after 300s, the dynamic performance of the heading angle also stabilizes. In both experiments, the roll angle and pitch angle are basically stable within 2°, which indicates that the disc-shaped underwater unmanned vehicle is subjected to restoring torque.

[0218] Finally, field tests were conducted, as follows:

[0219] Two experiments were conducted in the field, starting from different locations within the reservoir. The target returned to the beacon location. A self-contained GPS device was mounted on the disc-shaped underwater drone to record its trajectory information. The experimental results are as follows: Figure 9 As shown in Figure 9(a), the GPS trajectory diagram indicates that in both experiments, the disc-shaped underwater drone was able to return to the beacon location from different starting points, successfully completing its homing mission. The scene after the disc-shaped underwater drone returned to the beacon is shown in Figure 9(a). Figure 9 As shown in (b). Figure 9 The GPS track in (a) can also be compared with... Figure 9 Comparing (c) and (d), the SlantRange curves in both experiments showed a gradual decreasing trend, indicating that the disc-shaped underwater drone was indeed consistently approaching the beacon. The SlantRange curves in both experiments exhibited numerous outliers, likely due to the small size of the reservoir and the resulting multipath effect, thus leading to errors in the piUSBL acoustic positioning. Figure 9 Figures (e) and (f) show that the expected heading angle of trajectory 1 deviates somewhat from the actual heading angle, i.e., HDOA is not 0; while the expected heading angle of trajectory 2 basically follows the actual heading angle, with HDOA stabilizing around 0°. This is consistent with the trajectory results of the disc-shaped underwater unmanned vehicle. Figure 9As can be seen from Fig. 4, the trajectory of Experiment 2 is closer to a straight line, while the trajectory of Experiment 1 deviates from the straight line path. The roll angle in both experiments is basically stable within 10°, while the pitch angle is stable within 20°-30°, because the roll dimension has a restoring effect, while the pitch dimension is affected by the restoring force, but the disc-shaped configuration is also affected by the lift and other forces and moments during the forward movement of the disc-shaped underwater unmanned vehicle, and the installation position deviation of the two horizontal thrusters also produces a pitch moment, so the pitch angle deviation is greater than the roll angle.

[0220] The above description is merely preferred embodiments of the present application but not for limiting the present application. For the person skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A motion control method for an underactuated disc-shaped underwater unmanned vehicle based on an adaptive backstepping sliding mode controller, characterized in that: Based on the backstepping method and sliding mode variable structure algorithm, considering the uncertainties and external disturbances in the dynamic model of the underactuated disc-shaped underwater unmanned vehicle, a heading angle adaptive backstepping sliding mode controller and a depth adaptive backstepping sliding mode controller with fixed design parameters and adaptive parameters are designed. For each adaptive parameter, determine its initial limit value, desired time, and desired sliding surface value, design an adaptive control law for integration; obtain the integral value of the adaptive parameter within the desired time, and calculate the sliding surface value based on the integral value; If the integral value exceeds the initial limit, or the sliding surface value exceeds the expected sliding surface value, the adaptive control law of the adaptive parameter is redesigned; otherwise, the smaller absolute value between the sliding surface value and the initial limit is taken as the updated limit value of the adaptive parameter. During each motion control process, the adaptive parameters of the heading angle adaptive backstepping sliding mode controller and the depth adaptive backstepping sliding mode controller are updated by the adaptive control law. The update results of each adaptive parameter are corrected by the mapping function to prevent the absolute value of the updated adaptive parameter from exceeding its update limit. The heading angle adaptive backstepping sliding mode controller outputs the heading dimension control torque based on the input heading angle tracking error; the depth adaptive backstepping sliding mode controller outputs the depth dimension control torque based on the input depth tracking error; the underactuated disc-shaped underwater unmanned vehicle executes the heading and depth dimension control torques within the control step; the above process is repeated until both the heading angle tracking error and the depth tracking error meet the requirements.

2. The motion control method for an underactuated disc-shaped underwater unmanned vehicle based on an adaptive backstepping sliding mode controller according to claim 1, characterized in that: The heading angle adaptive backstepping sliding mode controller is specifically as follows: in, To control the number of repetitions of the movement; , , , For the first Adaptive parameters of the heading angle adaptive backstepping sliding mode controller in secondary motion control; , , , These are the fixed design parameters for the heading angle adaptive backstepping sliding mode controller; This is a saturation function used to replace the sign function in the ideal sliding mode; The approach velocity of the heading angle adaptive backstepping sliding mode controller; The control torque in the heading dimension is the output of the heading angle adaptive backstepping sliding mode controller; For the first The heading angle tracking error of an underactuated disc-shaped underwater unmanned vehicle in secondary motion control. ; For the first The heading angle of an underactuated disc-shaped underwater unmanned vehicle in secondary motion control; For the desired heading angle, The desired heading angular acceleration; For the first The heading angular velocity of an underactuated disc-shaped underwater unmanned vehicle in secondary motion control; ; To control the step size.

3. The motion control method for an underactuated disc-shaped underwater unmanned vehicle based on an adaptive backstepping sliding mode controller according to claim 2, characterized in that: The adaptive parameters of the heading angle adaptive backstepping sliding mode controller are updated by the adaptive control law, specifically as follows: in, , , , is the fixed design parameter for the heading angle adaptive backstepping sliding mode controller; Proj is the mapping function. , This is the update limit value for the adaptive parameter M.

4. The motion control method for an underactuated disc-shaped underwater unmanned vehicle based on an adaptive backstepping sliding mode controller according to claim 3, characterized in that: The depth-adaptive backstepping sliding mode controller is specifically as follows: in, , , For the first Adaptive parameters of depth adaptive backstepping sliding mode controller in secondary motion control; , , , Fixed design parameters for the depth-adaptive backstepping sliding mode controller; The approach speed of the depth-adaptive backstepping sliding mode controller; The depth-dimensional control torque output by the depth-adaptive backstepping sliding mode controller; For the first Depth tracking error in sub-motion control of underactuated disc-shaped underwater unmanned vehicles. ; For the first Depth of underactuated disc-shaped underwater unmanned vehicle in secondary motion control; For the desired depth, The desired vertical acceleration; For the first Vertical acceleration of underactuated disc-shaped underwater unmanned vehicle in secondary motion control; .

5. The motion control method for an underactuated disc-shaped underwater unmanned vehicle based on an adaptive backstepping sliding mode controller according to claim 4, characterized in that: The process of updating the adaptive parameters of the depth adaptive backstepping sliding mode controller through an adaptive control law is specifically as follows: in, , , Fixed design parameters for the depth-adaptive backstepping sliding mode controller; .

6. The motion control method for an underactuated disc-shaped underwater unmanned vehicle based on an adaptive backstepping sliding mode controller according to claim 5, characterized in that: Underactuated disc-shaped underwater unmanned vehicle in control step size Internal execution of control torque in the bow dimension Control torque in depth dimension , After a certain period of time, obtain the heading angle of the underactuated disc-shaped underwater unmanned vehicle. angular velocity of the bow ,depth Vertical acceleration ; Calculate heading angle tracking error With depth tracking error ; Based on the preset heading angle tracking error threshold With depth tracking error threshold ,like and If the iteration stops, the motion control of the underactuated disc-shaped underwater unmanned vehicle is completed.

7. The motion control method for an underactuated disc-shaped underwater unmanned vehicle based on an adaptive backstepping sliding mode controller according to claim 6, characterized in that: The motion control process specifically includes the following steps: Step 1: Obtain the heading angle of the underactuated disc-shaped underwater unmanned vehicle at the initial moment. angular velocity of the bow ,depth Vertical acceleration Obtain the desired heading angle of the underactuated disc-shaped underwater unmanned vehicle. Desired heading angular acceleration Expected depth Desired vertical acceleration ; Initialize control count Initialize the adaptive parameters of the heading angle adaptive backstepping sliding mode controller. , , , Initialize the adaptive parameters of the depth adaptive backstepping sliding mode controller. , , ; Step 2: Calculate the current number of... The heading angle tracking error of the underactuated disc-shaped underwater unmanned vehicle in secondary control. With depth tracking error ; like and If the iteration is successful, stop the iteration and complete the motion control of the underactuated disc-shaped underwater unmanned vehicle; otherwise, proceed to step 3. Step 3: Track the heading angle error Input to the heading angle adaptive backstepping sliding mode controller to obtain the current [number]th [axis]. Control torque in the forward dimension of secondary control ; Step 4: Reduce depth tracking error The input is fed into the depth adaptive backstepping sliding mode controller to obtain the current... Control torque in the depth dimension of secondary control ; Step 5: Update the adaptive parameters of the heading angle adaptive backstepping sliding mode controller. , , , Update the adaptive parameters of the depth adaptive backstepping sliding mode controller. , , ; Step 6: The thrusters of the underactuated disc-shaped underwater unmanned vehicle execute the control torque in the forward dimension. Control torque in depth dimension ,implement After a certain period of time, obtain the heading angle of the underactuated disc-shaped underwater unmanned vehicle. angular velocity of the bow ,depth Vertical acceleration Return to step 2.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 7.

10. A computer program product comprising computer instructions, characterized in that: When executed by a processor, the computer instructions implement the steps of the method according to any one of claims 1 to 7.

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