Obstacle avoidance tracking control method and system for submarine cable laying robot with input saturation

Abstract

The invention discloses an obstacle avoidance tracking control method and system for a submarine cable laying robot with input saturation. The method comprises the following steps: constructing a robot kinematics and dynamics model; a tracking error is calculated based on the reference trajectory and the real-time position, and transient and steady-state performance of the error is ensured through a performance constraint function; designing an obstacle avoidance signal based on an artificial potential field method; combining the performance constraint signal, the speed information and the obstacle avoidance signal to design a virtual control law; designing a fuzzy adaptive law to estimate and compensate unknown disturbance and uncertainty of the system; and finally, a saturation auxiliary system is introduced to construct a final saturation control input so as to limit the amplitude of the actuator and reduce the loss. According to the invention, input saturation, external disturbance and model uncertainty can be effectively processed, and high-precision and strong-robustness obstacle avoidance trajectory tracking control is realized.

Description

Technical Field

[0001] This invention relates to the field of control of submarine cable-laying robots, and in particular to a method and system for obstacle avoidance and tracking control of submarine cable-laying robots with input saturation. Background Technology

[0002] In recent years, with the increasing demand for marine resource development, various underwater equipment has developed rapidly. Performing engineering tasks in deep water, especially tracked submarine cable-laying robots, can be remotely operated via umbilical cables from surface vessels. Submarine cable-laying robots can perform complex unmanned operations such as submarine cable installation, maintenance, and inspection. However, in the complex marine operating environment, submarine cable-laying robots inevitably encounter various static and dynamic obstacles. In this situation, path tracking and obstacle avoidance control to avoid multiple obstacles becomes a challenge. Currently, although submarine cable-laying robots have many advantages in completing actual marine tasks, existing technologies still have the following problems:

[0003] In existing research on submarine cable-laying robots, their motion is subject to many uncertainties, inevitably leading to encounters with various obstacles. Furthermore, due to the difficulty in obtaining information about the actual seabed operating environment, most existing control methods neglect environmental disturbances, resulting in unsatisfactory trajectory tracking control performance in practical applications. To address these issues, it is necessary to establish tracking error constraints and introduce performance constraint functions to mitigate the impact of external disturbances on the submarine cable-laying robot, thereby achieving precise control. In addition, existing tracking control methods do not consider the wear and tear on actuator components caused by excessively large amplitudes in the tracking controller. Therefore, a robust input-saturated tracking controller for submarine cable-laying robots should be designed to reduce actuator component wear and improve the stability of tracking control. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for obstacle avoidance and tracking control of a submarine cable-laying robot with input saturation. It combines fuzzy adaptive control algorithm with performance constraint control theory, proposes obstacle avoidance and tracking control technology for submarine cable-laying robots, and realizes obstacle avoidance and tracking control of submarine cable-laying robots.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] A method for obstacle avoidance and tracking control of a submarine cable-laying robot with input saturation includes the following steps:

[0007] Step 1: Construct a motion model for the submarine cable-laying robot;

[0008] Step 2: Based on the motion model, the given reference trajectory, and the real-time position information of the submarine cable laying robot, calculate the position tracking error and the heading tracking error, and introduce a performance constraint function to constrain the position tracking error and the heading tracking error to obtain the performance constraint signal.

[0009] Step 3: Based on the performance constraint signal, the real-time speed information of the submarine cable-laying robot, and the obstacle avoidance signal designed to avoid obstacles, design a virtual controller; the virtual controller outputs virtual control signals, including longitudinal velocity virtual control signals and angular velocity virtual control signals;

[0010] Step 4: Based on the virtual control signal, obstacle avoidance signal, and real-time speed information of the submarine cable laying robot, design parameter adaptive laws to estimate unknown disturbances and uncertainties in the system; the parameter adaptive laws include longitudinal velocity adaptive laws and angular velocity adaptive laws.

[0011] Step 5: Based on the virtual control signal, parameter adaptive law, and obstacle avoidance signal, and combined with the saturation auxiliary system designed to suppress the amplitude of the actuator input, design the saturation control input that will ultimately act on the submarine cable laying robot.

[0012] Furthermore, step 1 specifically includes:

[0013] The input signal for the submarine cable-laying robot is the input signal. and path parameters The output signal is the location information of the submarine cable-laying robot. and speed information ;

[0014] The motion model of the submarine cable-laying robot is described by the following system of differential equations:

[0015] (1)

[0016] in, It is the position-deflection angle vector of the submarine cable-laying robot. This indicates the two-dimensional coordinate position of the submarine cable-laying robot. These are the x and y coordinates, respectively. For deflection angle, Represents the differential symbol;

[0017] This represents the velocity vector in the coordinate system of the submarine cable-laying robot; where Indicates longitudinal velocity. Indicates angular velocity;

[0018] ,in and These are the control inputs for the longitudinal and rotational directions of the submarine cable-laying robot. and It is a control input with saturation limits. It is a saturation function;

[0019] ,in , and These represent the resistance experienced by the left and right tracks, respectively. This represents the force exerted by the suspension cable on the robot. This represents the angle between the robot's suspension rope and the direction of motion; This represents the component of the reaction force exerted by the nozzle on the robot in the direction of the robot's motion. The angle between the nozzle and the spray arm is... The angle between the jet arm and the direction of motion is ; Indicates drag resistance; , This represents the distance from the center of the track to the geometric center of the robot. Indicates steering resistance torque;

[0020] , and Disturbance by ocean currents and satisfying , , and They represent and The upper bound of is an unknown positive constant; , and This represents the gain coefficient of the controller;

[0021] This represents the uncertainty term in the anti-ocean current motion model;

[0022] , , and The parameter matrices are represented as follows:

[0023] ,

[0024] ,

[0025] ,

[0026]

[0027] in, , These represent the total mass and moment of inertia of the submarine cable-laying robot underwater, respectively. This indicates the coefficient of friction between the left track and the soil in the forward direction; This indicates the coefficient of friction between the right track and the soil in the forward direction; and These represent the left and right tracks, respectively. Indicates the moment of inertia of the track; Indicates the traction coefficient; ( () indicates the traction input of the left and right tracks; This indicates the radius of rotation of the track drive wheel.

[0028] Furthermore, step 2 specifically includes:

[0029] The input signal to the performance constraint module is a given reference trajectory. Location information of submarine cable-laying robots The output signal is a performance constraint signal. and ;

[0030] During the tracking process, Indicates the reference trajectory. Indicates path parameters, Representing the time variable, the position error is defined as:

[0031] (2)

[0032] in, , , Indicates the position x-coordinate error; Represents the x-coordinate of the desired position; Indicates the error in the ordinate of the position; Represents the ordinate of the desired position; This represents the position error; the heading tracking error is:

[0033] (3)

[0034] in, It is the error of the horizontal coordinate of the position. and position ordinate error The relevant ideal heading angle, and , The arctangent function is represented, and the error constraints are constructed as follows:

[0035] (4)

[0036] in, and This represents the boundary function to be defined, and Boundary function and The following conditions must be met:

[0037] (5)

[0038] To ensure tracking error and To optimize performance and convergence accuracy, a performance function is designed; therefore, a construction is performed. and as follows:

[0039] (6)

[0040] in, , , These are design parameters. For the predetermined performance function, To improve convergence accuracy, and It is an auxiliary parameter related to tracking error.

[0041] Furthermore, in step 2, the following logarithmic barrier function is introduced to ensure constraint (4):

[0042] (7)

[0043] Among them, and The barrier function represents the position error; The barrier function represents the heading tracking error; Represents intermediate variables and , Represents intermediate variables and , Describe the natural logarithm function; if and only if hour, ;when , ;when , Therefore, the azimuth angle tracking error Converging to a compact set containing the origin Inside;

[0044] Using equation (7), for and Differentiation has , ,in,

[0045] (8)

[0046] in, and This indicates a pre-set time control signal; Indicates the time remaining until the scheduled time; This indicates the predetermined time signal for the angle.

[0047] Furthermore, in step 3, the design steps for the obstacle avoidance signal are as follows:

[0048] The input signal to the virtual controller module is the position information of the submarine cable-laying robot. The output signal is an obstacle avoidance signal. and ;

[0049] (9)

[0050] in, This indicates that the submarine cable-laying robot is in Potential energy value under distance difference; The potential energy value represents the potential energy of the submarine cable-laying robot and the first The potential energy value of each obstacle; , , , This indicates the submarine cable-laying robot and the first The distance difference between the obstacles This indicates the planar position of the submarine cable-laying robot. Indicates the planar position of the obstacle. Indicates the specific planar location of the obstacle. Indicates the first An obstacle, Indicates the detection range relative to obstacles; Indicates the minimum safe collision avoidance radius with respect to obstacles; right Differentiating, we get:

[0051] (10)

[0052] in, Therefore, when hour, For monotonically decreasing, when hour, It is infinite; in addition, when hour, The obstacle avoidance signal is designed as follows:

[0053] (11)

[0054] (12)

[0055] in, , These represent repulsive obstacle avoidance signals in the direction of velocity and angular velocity, respectively.

[0056] Furthermore, in step 3, the design steps for the virtual control signal are as follows:

[0057] The input signal to the virtual controller module is a performance constraint signal. and Speed ​​information of submarine cable-laying robots The output signal is the virtual control signal. and ;

[0058] The specific design is as follows:

[0059] First, by differentiating equations (7) and (8) respectively, we can obtain:

[0060] (13)

[0061] (14)

[0062] Based on this, we get:

[0063] (15)

[0064] (16)

[0065] The following error is defined:

[0066] (17)

[0067] (18)

[0068] in, and These represent longitudinal velocity error and angular velocity error, respectively. and This represents the output error of the first-order filter; and Indicates the filtered signal; and This indicates the virtual control signals to be designed; let and The filter is passed sequentially through a first-order low-pass filter combined with a time constant. and The design is as follows: , ;in, , ,right and Differentiating, we get:

[0069] (19)

[0070] in, and Let each represent a continuous function. , ; and Represents positive numbers;

[0071] Design virtual control signals and as follows:

[0072] (20)

[0073] (twenty one)

[0074] in, , These are design parameters. , It is a guarantee Design parameters.

[0075] Furthermore, step 4 specifically includes:

[0076] The input signal to the adaptive law module is the speed information of the submarine cable-laying robot. Obstacle avoidance signals and Virtual control signals and The output signal is a parameter adaptive law. and path parameters ;

[0077] For unknown function terms in the system:

[0078] (twenty two)

[0079] in, For uncertain terms, and These represent the uncertainties in the directions of velocity and angular velocity, respectively.

[0080] Using fuzzy logic systems to approximate and We can obtain: , ,in, yes The optimal parameter vector, yes The optimal parameter vector, Therefore For a continuous function of a variable, Therefore For a continuous function of a variable, and Let these represent vectors with velocity and angular velocity as variables, respectively. and To approximate the error, satisfy and , and It is a positive number;

[0081] Design an adaptive law with the following parameters:

[0082] (twenty three)

[0083] (twenty four)

[0084] in, , Indicates design parameters, and This represents the control gain matrix of the design;

[0085] Define path velocity error as , It is the expected speed. These are path parameters, and the path parameter update law is designed. for:

[0086] (25).

[0087] Furthermore, step 5 specifically includes:

[0088] The input signal to the disturbance observer is a virtual control signal. and Parameter adaptive law and Obstacle avoidance signals and The output saturation signal is for saturation control. and ;

[0089] Design saturation auxiliary parameters and To reduce the impact of input saturation:

[0090]

[0091] in, , , , These are design parameters. satisfy , This is the gain coefficient of the controller;

[0092] Design the following intermediate control signal:

[0093] (26)

[0094] (27)

[0095] in, These are positive design parameters;

[0096] The saturation control signal is:

[0097]

[0098] in, , It is an intermediate control signal. This indicates the maximum value of the controller input. This represents the minimum value input to the controller.

[0099] An obstacle avoidance and tracking control system for a submarine cable-laying robot with input saturation for implementing the control method, comprising:

[0100] The model creation module is used to build motion models of the submarine cable-laying robot.

[0101] The performance constraint module is used to calculate the position tracking error and heading tracking error based on the motion model, the given reference trajectory and the real-time position information of the submarine cable laying robot, and introduce a performance constraint function to constrain the errors to obtain the performance constraint signal.

[0102] The obstacle avoidance module is used to design obstacle avoidance signals based on the position information of the submarine cable laying robot to avoid obstacles.

[0103] The virtual controller module is used to design virtual control signals based on performance constraint signals, real-time speed information of the submarine cable laying robot, and obstacle avoidance signals. The virtual control signals include longitudinal velocity virtual control signals and angular velocity virtual control signals.

[0104] The adaptive law module is designed to estimate the parameter adaptive law for unknown disturbances and uncertainties in the system based on virtual control signals, obstacle avoidance signals and real-time speed information of the submarine cable laying robot.

[0105] The saturated input module is used to design the saturated control input that ultimately acts on the submarine cable-laying robot, based on virtual control signals, parameter adaptive laws, and obstacle avoidance signals, combined with a saturated auxiliary system designed to suppress the amplitude of actuator input.

[0106] Beneficial effects: Compared with the prior art, the present invention has the following outstanding advantages:

[0107] In existing research on submarine cable-laying robots, their motion is subject to many uncertainties, inevitably leading to encounters with various obstacles. Furthermore, due to the difficulty in obtaining information about the actual seabed operating environment, most existing control methods neglect environmental obstacle factors, resulting in unsatisfactory trajectory tracking control performance in practical applications. To address these issues, it is necessary to establish tracking error constraints and introduce performance constraint functions to mitigate the impact of external disturbances on the submarine cable-laying robot, thereby achieving precise control. In addition, existing tracking control methods do not consider the wear and tear on actuator components caused by excessively large amplitudes in the tracking controller. Therefore, a robust input-saturated tracking controller for submarine cable-laying robots should be designed to reduce actuator component wear and improve the stability of tracking control.

[0108] First, this invention incorporates an artificial barrier function, taking into account the influence of the attraction and repulsion forces of obstacles in the designed artificial barrier function on the submarine cable-laying robot, so that the submarine cable-laying robot can accurately avoid collisions with obstacles.

[0109] Secondly, the trajectory tracking control effect of the submarine cable-laying robot in practical applications is not ideal. To solve these problems, it is necessary to establish tracking error constraints and introduce performance constraint functions to mitigate the impact of external disturbances on the submarine cable-laying robot, so as to achieve precise control.

[0110] Third, existing tracking control methods do not take into account the problem that the large amplitude of the tracking controller will cause damage to the actuator components. Therefore, a robust input saturation tracking controller for submarine cable laying robots should be designed to reduce the damage to the actuator components. Attached Figure Description

[0111] Figure 1 This is a flowchart of the method of the present invention.

[0112] Figure 2 This is a schematic diagram of the controller structure of the submarine cable-laying robot.

[0113] Figure 3 This is a two-dimensional planar diagram showing the trajectory tracking of a submarine cable-laying robot in an actual mission.

[0114] Figure 4This is a graph showing the relative distance error between the submarine cable-laying robot and its tracking trajectory.

[0115] Figure 5 This is a graph showing the relative angle error between the submarine cable-laying robot and its tracking trajectory.

[0116] Figure 6 It is the longitudinal saturation input signal of the submarine cable-laying robot. The curve graph.

[0117] Figure 7 It is the saturation input signal of the rotation direction of the submarine cable-laying robot. The curve graph. Detailed Implementation

[0118] The invention will now be further explained with reference to the accompanying drawings.

[0119] This invention designs a method and system for obstacle avoidance and tracking control of a submarine cable-laying robot with input saturation. The method flow is as follows: Figure 1 As shown, the system structure is as follows: Figure 2 As shown. In the trajectory tracking control of the submarine cable-laying robot, the given reference trajectory, reference distance, reference relative azimuth angle signal, and position vector of the submarine cable-laying robot are... The information is transmitted to the performance constraint module and the obstacle avoidance module. The performance constraint module analyzes and calculates the performance constraint parameters based on the input information. and This information is then transmitted to the virtual controller module. Simultaneously, the obstacle avoidance module analyzes and processes the input information to obtain obstacle avoidance signals. and The virtual controller module will receive obstacle avoidance signals. and The signal is fed to the saturation input module. Simultaneously, the velocity vector of the submarine cable-laying robot... The information is transmitted to the virtual controller module, which analyzes and processes the input information to obtain the virtual controller. and The virtual controller module will receive the virtual control signals. and The inputs are respectively sent to the saturation input module and the adaptive module. Simultaneously, the velocity vector of the submarine cable-laying robot... The information is fed to the adaptive law module, which analyzes and calculates the adaptive parameters based on the input information. The signal is then fed to the saturation input module, which analyzes and processes the external input signal to obtain the control signal. and Finally, the saturated input module transmits the input control signal to the submarine cable-laying robot. The design goal of this invention is to enable the submarine cable-laying robot trajectory tracking control system to effectively overcome the influence of obstacles after introducing saturated input and performance constraint control methods, and to further achieve stable operation of the submarine cable-laying robot after combining with predetermined performance theories.

[0120] like Figure 1 As shown, the present invention provides an obstacle avoidance and tracking control method for a submarine cable-laying robot with input saturation, comprising the following steps:

[0121] Step 1: Construct a motion model for the submarine cable-laying robot; specific steps include:

[0122] The input signal for the submarine cable-laying robot is the input signal. and path parameters The output signal is the location information of the submarine cable-laying robot. and speed information ;

[0123] The motion model of the submarine cable-laying robot is described by the following system of differential equations:

[0124] (1)

[0125] in, It is the position-deflection angle vector of the submarine cable-laying robot. This indicates the two-dimensional coordinate position of the submarine cable-laying robot. These are the x and y coordinates, respectively. For deflection angle, Represents the differential symbol;

[0126] This represents the velocity vector in the coordinate system of the submarine cable-laying robot; where Indicates longitudinal velocity. Indicates angular velocity;

[0127] ,in and These are the control inputs for the longitudinal and rotational directions of the submarine cable-laying robot. and It is a control input with saturation limits. It is a saturation function;

[0128] ,in , and These represent the resistance experienced by the left and right tracks, respectively. This represents the force exerted by the suspension cable on the robot. This represents the angle between the robot's suspension rope and the direction of motion; This represents the component of the reaction force exerted by the nozzle on the robot in the direction of the robot's motion. The angle between the nozzle and the spray arm is... The angle between the jet arm and the direction of motion is ; Indicates drag resistance; , This represents the distance from the center of the track to the geometric center of the robot. Indicates steering resistance torque;

[0129] , and Disturbance by ocean currents and satisfying , , and They represent and The upper bound of is an unknown positive constant; , and This represents the gain coefficient of the controller;

[0130] This represents the uncertainty term in the anti-ocean current motion model;

[0131] , , and The parameter matrices are represented as follows:

[0132] ,

[0133] ,

[0134] ,

[0135]

[0136] in, , These represent the total mass and moment of inertia of the submarine cable-laying robot underwater, respectively. This indicates the coefficient of friction between the left track and the soil in the forward direction; This indicates the coefficient of friction between the right track and the soil in the forward direction; and These represent the left and right tracks, respectively. Indicates the moment of inertia of the track; Indicates the traction coefficient; ( () indicates the traction input of the left and right tracks; This indicates the radius of rotation of the track drive wheel.

[0137] Step 2: Based on the motion model, the given reference trajectory, and the real-time position information of the submarine cable-laying robot, calculate the position tracking error and the heading tracking error, and introduce a performance constraint function to constrain the position tracking error and the heading tracking error, thereby obtaining the performance constraint signal; the specific steps include:

[0138] The input signal to the performance constraint module is a given reference trajectory. Location information of submarine cable-laying robots The output signal is a performance constraint signal. and ;

[0139] During the tracking process, Indicates the reference trajectory. Indicates path parameters, Representing the time variable, the position error is defined as:

[0140] (2)

[0141] in, , , Indicates the position x-coordinate error; Represents the x-coordinate of the desired position; Indicates the error in the ordinate of the position; Represents the ordinate of the desired position; This represents the position error; the heading tracking error is:

[0142] (3)

[0143] in, It is the error of the horizontal coordinate of the position. and position ordinate error The relevant ideal heading angle, and , The arctangent function is represented, and the error constraints are constructed as follows:

[0144] (4)

[0145] in, and This represents the boundary function to be defined, and Boundary function and The following conditions must be met:

[0146] (5)

[0147] To ensure tracking error and To optimize performance and convergence accuracy, a performance function is designed; therefore, a construction is performed. and as follows:

[0148] (6)

[0149] in, , , These are design parameters. For the predetermined performance function, To improve convergence accuracy, and It is an auxiliary parameter related to tracking error.

[0150] The following logarithmic barrier function is introduced to ensure constraint (4):

[0151] (7)

[0152] Among them, and The barrier function represents the position error; The barrier function represents the heading tracking error; Represents intermediate variables and , Represents intermediate variables and , Describe the natural logarithm function; if and only if hour, ;when , ;when , Therefore, the azimuth angle tracking error Converging to a compact set containing the origin Inside;

[0153] Using equation (7), for and Differentiation has , ,in,

[0154] (8)

[0155] in, and This indicates a pre-set time control signal; Indicates the time remaining until the scheduled time; This indicates the predetermined time signal for the angle.

[0156] Step 3: Based on the performance constraint signal, the real-time speed information of the submarine cable-laying robot, and the obstacle avoidance signal designed to avoid obstacles, design a virtual controller; the virtual controller outputs virtual control signals, including longitudinal velocity virtual control signals and angular velocity virtual control signals; specific steps include:

[0157] The design steps for obstacle avoidance signals are as follows:

[0158] The input signal to the virtual controller module is the position information of the submarine cable-laying robot. The output signal is an obstacle avoidance signal. and ;

[0159] (9)

[0160] in, This indicates that the submarine cable-laying robot is in Potential energy value under distance difference; The potential energy value represents the potential energy of the submarine cable-laying robot and the first The potential energy value of each obstacle; , , , This indicates the submarine cable-laying robot and the first The distance difference between the obstacles This indicates the planar position of the submarine cable-laying robot. Indicates the planar position of the obstacle. Indicates the specific planar location of the obstacle. Indicates the first An obstacle, Indicates the detection range relative to obstacles; Indicates the minimum safe collision avoidance radius with respect to obstacles; right Differentiating, we get:

[0161] (10)

[0162] in, Therefore, when hour, For monotonically decreasing, when hour, It is infinite; in addition, when hour, The obstacle avoidance signal is designed as follows:

[0163] (11)

[0164] (12)

[0165] in, , These represent repulsive obstacle avoidance signals in the direction of velocity and angular velocity, respectively.

[0166] The design steps for virtual control signals are as follows:

[0167] The input signal to the virtual controller module is a performance constraint signal. and Speed ​​information of submarine cable-laying robots The output signal is the virtual control signal. and ;

[0168] The specific design is as follows:

[0169] First, by differentiating equations (7) and (8) respectively, we can obtain:

[0170] (13)

[0171] (14)

[0172] Based on this, we get:

[0173] (15)

[0174] (16)

[0175] The following error is defined:

[0176] (17)

[0177] (18)

[0178] in, and These represent longitudinal velocity error and angular velocity error, respectively. and This represents the output error of the first-order filter; and Indicates the filtered signal; and This indicates the virtual control signals to be designed; let and The filter is passed sequentially through a first-order low-pass filter combined with a time constant. and The design is as follows: , ;in, , ,right and Differentiating, we get:

[0179] (19)

[0180] in, and Let each represent a continuous function. , ; and Represents positive numbers;

[0181] Design virtual control signals and as follows:

[0182] (20)

[0183] (twenty one)

[0184] in, , These are design parameters. , It is a guarantee Design parameters.

[0185] Step 4: Based on the virtual control signal, obstacle avoidance signal, and real-time velocity information of the submarine cable-laying robot, design parameter adaptive laws to estimate unknown disturbances and uncertainties in the system; the parameter adaptive laws include longitudinal velocity adaptive laws and angular velocity adaptive laws; specific steps include:

[0186] The input signal to the adaptive law module is the speed information of the submarine cable-laying robot. Obstacle avoidance signals and Virtual control signals and The output signal is a parameter adaptive law. and path parameters ;

[0187] For unknown function terms in the system:

[0188] (twenty two)

[0189] in, For uncertain terms, and These represent the uncertainties in the directions of velocity and angular velocity, respectively.

[0190] Using fuzzy logic systems to approximate and We can obtain: , ,in, yes The optimal parameter vector, yes The optimal parameter vector, Therefore For a continuous function of a variable, Therefore For a continuous function of a variable, and Let these represent vectors with velocity and angular velocity as variables, respectively. and To approximate the error, satisfy and , and It is a positive number;

[0191] Design an adaptive law with the following parameters:

[0192] (twenty three)

[0193] (twenty four)

[0194] in, , Indicates design parameters, and This represents the control gain matrix of the design;

[0195] Define path velocity error as , It is the expected speed. These are path parameters, and the path parameter update law is designed. for:

[0196] (25).

[0197] Step 5: Based on the virtual control signal, parameter adaptive law, and obstacle avoidance signal, and combined with the saturation auxiliary system designed to suppress the actuator input amplitude, design the final saturation control input acting on the submarine cable-laying robot; specific steps include:

[0198] The input signal to the disturbance observer is a virtual control signal. and Parameter adaptive law and Obstacle avoidance signals and The output saturation signal is for saturation control. and ;

[0199] Design saturation auxiliary parameters and To reduce the impact of input saturation:

[0200]

[0201] in, , , , These are design parameters. satisfy , This is the gain coefficient of the controller;

[0202] Design the following intermediate control signal:

[0203] (26)

[0204] (27)

[0205] in, These are positive design parameters;

[0206] The saturation control signal is:

[0207]

[0208] in, , It is an intermediate control signal. This indicates the maximum value of the controller input. This represents the minimum value input to the controller.

[0209] like Figure 2 As shown, the present invention provides an obstacle avoidance and tracking control system for a submarine cable-laying robot with input saturation, comprising:

[0210] The model creation module is used to build motion models of the submarine cable-laying robot.

[0211] The performance constraint module is used to calculate the position tracking error and heading tracking error based on the motion model, the given reference trajectory and the real-time position information of the submarine cable laying robot, and introduce a performance constraint function to constrain the errors to obtain the performance constraint signal.

[0212] The obstacle avoidance module is used to design obstacle avoidance signals based on the position information of the submarine cable laying robot to avoid obstacles.

[0213] The virtual controller module is used to design virtual control signals based on performance constraint signals, real-time speed information of the submarine cable laying robot, and obstacle avoidance signals. The virtual control signals include longitudinal velocity virtual control signals and angular velocity virtual control signals.

[0214] The adaptive law module is designed to estimate the parameter adaptive law for unknown disturbances and uncertainties in the system based on virtual control signals, obstacle avoidance signals and real-time speed information of the submarine cable laying robot.

[0215] The saturated input module is used to design the saturated control input that ultimately acts on the submarine cable-laying robot, based on virtual control signals, parameter adaptive laws, and obstacle avoidance signals, combined with a saturated auxiliary system designed to suppress the amplitude of actuator input.

[0216] Simulation results are as follows Figure 3-7 As shown. Figure 3 This is a two-dimensional planar trajectory tracking curve of the submarine cable-laying robot based on actual task requirements. The graph shows that the submarine cable-laying robot has completed the obstacle avoidance task. Figure 4 This is a graph showing the relative distance error between the submarine cable-laying robot and the trajectory it follows. Analysis of the graph shows that the relative distance error can converge to near zero while avoiding obstacles. Figure 5 This is a graph showing the relative angle error between the submarine cable-laying robot and the trajectory it follows. Analysis of the graph shows that the relative angle error can converge to near zero while avoiding obstacles. Figure 6-7 These represent the longitudinal saturation input signals for submarine cable laying, respectively. and rotation direction saturation input signal The graph shows that the saturated input signal is limited to a specified range. The simulation results and tables show that the designed trajectory tracking controller for the submarine cable-laying robot can avoid the influence of obstacles and meet the performance constraints, ultimately achieving the expected requirements for the trajectory tracking task of the submarine cable-laying robot.

[0217] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for obstacle avoidance and tracking control of a submarine cable-laying robot with input saturation, characterized in that: Includes the following steps: Step 1: Construct a motion model for the submarine cable-laying robot; Step 2: Based on the motion model, the given reference trajectory, and the real-time position information of the submarine cable laying robot, calculate the position tracking error and the heading tracking error, and introduce a performance constraint function to constrain the position tracking error and the heading tracking error to obtain the performance constraint signal. Step 3: Based on the performance constraint signal, the real-time speed information of the submarine cable-laying robot, and the obstacle avoidance signal designed to avoid obstacles, design a virtual controller; the virtual controller outputs virtual control signals, including longitudinal velocity virtual control signals and angular velocity virtual control signals; Step 4: Based on the virtual control signal, obstacle avoidance signal and the real-time speed information of the submarine cable laying robot, design a parameter adaptive law to estimate the unknown disturbances and uncertainties in the system. The parameter adaptive law includes the longitudinal velocity adaptive law and the angular velocity adaptive law; Step 5: Based on the virtual control signal, parameter adaptive law, and obstacle avoidance signal, and combined with the saturation auxiliary system designed to suppress the amplitude of the actuator input, design the saturation control input that will ultimately act on the submarine cable laying robot.

2. The method according to claim 1, characterized in that: Step 1 specifically includes: The input signal for the submarine cable-laying robot is the input signal. and path parameters The output signal is the location information of the submarine cable-laying robot. and speed information ; The motion model of the submarine cable-laying robot is described by the following system of differential equations: （1） in, It is the position-deflection angle vector of the submarine cable-laying robot. This indicates the two-dimensional coordinate position of the submarine cable-laying robot. These are the x and y coordinates, respectively. For deflection angle, Represents the differential symbol; This represents the velocity vector in the coordinate system of the submarine cable-laying robot; where Indicates longitudinal velocity. Indicates angular velocity; ,in and These are the control inputs for the longitudinal and rotational directions of the submarine cable-laying robot. and It is a control input with saturation limits. It is a saturation function; ,in , and These represent the resistance experienced by the left and right tracks, respectively. This represents the force exerted by the suspension cable on the robot. This represents the angle between the robot's suspension rope and the direction of motion; This represents the component of the reaction force exerted by the nozzle on the robot in the direction of the robot's motion. The angle between the nozzle and the spray arm is... The angle between the jet arm and the direction of motion is ; Indicates drag resistance; , This represents the distance from the center of the track to the geometric center of the robot. Indicates steering resistance torque; , and Disturbance by ocean currents and satisfying , , and They represent and The upper bound of is an unknown positive constant; , and This represents the gain coefficient of the controller; This represents the uncertainty term in the anti-ocean current motion model; , , and The parameter matrices are represented as follows: ， ， ， in, , These represent the total mass and moment of inertia of the submarine cable-laying robot underwater, respectively. This indicates the coefficient of friction between the left track and the soil in the forward direction; This indicates the coefficient of friction between the right track and the soil in the forward direction; and These represent the left and right tracks, respectively. Indicates the moment of inertia of the track; Indicates the traction coefficient; ( () indicates the traction input of the left and right tracks; This indicates the radius of rotation of the track drive wheel.

3. The method according to claim 1, characterized in that: Step 2 specifically includes: The input signal to the performance constraint module is a given reference trajectory. Location information of submarine cable-laying robots The output signal is a performance constraint signal. and ; During the tracking process, Indicates the reference trajectory. Indicates path parameters, Representing the time variable, the position error is defined as: （2） in, , , Indicates the position x-coordinate error; Represents the x-coordinate of the desired position; Indicates the error in the ordinate of the position; Represents the ordinate of the desired position; This represents the position error; the heading tracking error is: （3） in, It is the error of the horizontal coordinate of the position. and position ordinate error The relevant ideal heading angle, and , The arctangent function is represented, and the error constraints are constructed as follows: （4） in, and This represents the boundary function to be defined, and Boundary function and The following conditions must be met: （5） To ensure tracking error and To optimize performance and convergence accuracy, a performance function is designed; therefore, a construction is performed. and as follows: （6） in, , , These are design parameters. For the predetermined performance function, To improve convergence accuracy, and It is an auxiliary parameter related to tracking error.

4. The method according to claim 3, characterized in that: In step 2, the following logarithmic barrier function is introduced to ensure constraint (4): （7） Among them, and The barrier function represents the position error; The barrier function represents the heading tracking error; Represents intermediate variables and , Represents intermediate variables and , Describe the natural logarithm function; if and only if hour, ;when , ;when , Therefore, the azimuth angle tracking error Converging to a compact set containing the origin Inside; Using equation (7), for and Differentiation has , ,in, （8） in, and This indicates a pre-set time control signal; Indicates the time remaining until the scheduled time; This indicates the predetermined time signal for the angle.

5. The method according to claim 1, characterized in that: In step 3, the design steps for the obstacle avoidance signal are as follows: The input signal to the virtual controller module is the position information of the submarine cable-laying robot. The output signal is an obstacle avoidance signal. and ; （9） in, This indicates that the submarine cable-laying robot is in Potential energy value under distance difference; The potential energy value represents the potential energy of the submarine cable-laying robot and the first The potential energy value of each obstacle; , , , This indicates the submarine cable-laying robot and the first The distance difference between the obstacles Indicates the planar position of the submarine cable-laying robot. Indicates the planar position of the obstacle. Indicates the specific planar location of the obstacle. Indicates the first An obstacle, Indicates the detection range relative to obstacles; Indicates the minimum safe collision avoidance radius with respect to obstacles; right Differentiating, we get: （10） in, Therefore, when hour, For monotonically decreasing, when hour, It is infinite; in addition, when hour, The obstacle avoidance signal is designed as follows: （11） （12） in, , These represent repulsive obstacle avoidance signals in the direction of velocity and angular velocity, respectively.

6. The method according to claim 1 or 5, characterized in that: In step 3, the design steps for the virtual control signal are as follows: The input signal to the virtual controller module is a performance constraint signal. and Speed ​​information of submarine cable-laying robots The output signal is the virtual control signal. and ; The specific design is as follows: First, by differentiating equations (7) and (8) respectively, we can obtain: （13） （14） Based on this, we get: （15） （16） The following error is defined: （17） （18） in, and These represent longitudinal velocity error and angular velocity error, respectively. and This represents the output error of the first-order filter; and Indicates the filtered signal; and This indicates the virtual control signals to be designed; let and The filter is passed sequentially through a first-order low-pass filter combined with a time constant. and The design is as follows: , ;in, , ,right and Differentiating, we get: （19） in, and Let each represent a continuous function. , ; and Represents positive numbers; Design virtual control signals and as follows: （20） （21） in, , These are design parameters. , It is a guarantee Design parameters.

7. The method according to claim 1, characterized in that: Step 4 specifically includes: The input signal to the adaptive law module is the speed information of the submarine cable-laying robot. Obstacle avoidance signals and Virtual control signals and The output signal is a parameter adaptive law. and path parameters ; For unknown function terms in the system: （22） in, For uncertain terms, and These represent the uncertainties in the directions of velocity and angular velocity, respectively. Using fuzzy logic systems to approximate and We can obtain: , ,in, yes The optimal parameter vector, yes The optimal parameter vector, Therefore For a continuous function of a variable, Therefore For a continuous function of a variable, and Let these represent vectors with velocity and angular velocity as variables, respectively. and To approximate the error, satisfy and , and It is a positive number; Design an adaptive law with the following parameters: （23） （24） in, , Indicates design parameters, and This represents the control gain matrix of the design; Define path velocity error as , It is the expected speed. These are path parameters, and the path parameter update law is designed. for: （25）。 8. The method according to claim 1, characterized in that: Step 5 specifically includes: The input signal to the disturbance observer is a virtual control signal. and Parameter adaptive law and Obstacle avoidance signals and The output saturation signal is for saturation control. and ; Design saturation auxiliary parameters and To reduce the impact of input saturation: in, , , , These are design parameters. satisfy , This is the gain coefficient of the controller; Design the following intermediate control signal: （26） （27） in, These are positive design parameters; The saturation control signal is: in, , It is an intermediate control signal. This indicates the maximum value of the controller input. This represents the minimum value input to the controller.

9. A control system for an obstacle avoidance and tracking robot with input saturation for implementing the control method of claim 1, characterized in that: include: The model creation module is used to build motion models of the submarine cable-laying robot. The performance constraint module is used to calculate the position tracking error and heading tracking error based on the motion model, the given reference trajectory and the real-time position information of the submarine cable laying robot, and introduce a performance constraint function to constrain the errors to obtain the performance constraint signal. The obstacle avoidance module is used to design obstacle avoidance signals based on the position information of the submarine cable-laying robot to avoid obstacles. The virtual controller module is used to design virtual control signals based on performance constraint signals, real-time speed information of the submarine cable laying robot, and obstacle avoidance signals. The virtual control signals include longitudinal velocity virtual control signals and angular velocity virtual control signals. The adaptive law module is designed to estimate the parameter adaptive law for unknown disturbances and uncertainties in the system based on virtual control signals, obstacle avoidance signals and real-time speed information of the submarine cable laying robot. The saturated input module is used to design the saturated control input that ultimately acts on the submarine cable-laying robot, based on virtual control signals, parameter adaptive laws, and obstacle avoidance signals, combined with a saturated auxiliary system designed to suppress the amplitude of actuator input.

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