Water surface unmanned ship motion control method and system based on PID integral sliding mode

Abstract

A kind of water unmanned ship motion control method and system based on PID integral sliding mode, by constructing unmanned ship physical model and obtaining simulation output information by system input, by calculating the error of simulation output information and expected output and using PID-based integral sliding mode control algorithm, the expected adjustment force and torque control signal is obtained, which is transmitted to the actuator to realize unmanned ship motion control.The present application combines PID control with sliding mode control, further combines the proportional, integral and differential elements with the sliding surface, so that the controller can flexibly adjust the control parameters under different dynamic characteristics requirements, while effectively accelerating the convergence speed of the system, with portability and deployability.

Description

Technical Field

[0001] This invention relates to a technology in the field of unmanned surface vessel (USV) control, specifically a motion control method and system based on PID integral sliding mode. Background Technology

[0002] Motion control is a core technology of unmanned surface vessels (USVs), and its performance plays a decisive role in the mission capabilities of USVs. Due to the complex and ever-changing operating environment of USVs, with strong external disturbances such as wind, waves, and currents at sea, traditional PID control often struggles to maintain ideal control performance when faced with these nonlinear and uncertain factors, potentially resulting in significant error accumulation, response delays, or frequent oscillations. Summary of the Invention

[0003] To address the aforementioned shortcomings of existing technologies, this invention proposes a motion control method and system for unmanned surface vessels based on PID integral sliding mode. By combining PID control with sliding mode control, the proportional, integral, and derivative components are further integrated with the sliding surface, enabling the controller to flexibly adjust control parameters under different dynamic characteristic requirements. At the same time, it can effectively accelerate the convergence speed of the system and has portability and deployability.

[0004] This invention is achieved through the following technical solution:

[0005] This invention relates to a motion control method for unmanned surface vessels (USVs) based on PID integral sliding mode. The method involves constructing a physical model of the USV and obtaining simulation output information through system input. By calculating the error between the simulation output information and the desired output, and using a PID-based integral sliding mode control algorithm, the desired adjustment force and torque control signals are obtained and transmitted to the actuator to achieve motion control of the USV.

[0006] This invention relates to a system for implementing the above method, comprising: an unmanned surface vessel (USV) input / output response unit, an USV controller construction unit, and a calculation and command generation unit, wherein: the USV input / output response unit obtains information such as speed and position based on the input control command; the USV controller construction unit calculates the required state error vector based on the current speed, position, and error information from the desired position; the calculation and command generation unit calculates the USV controller based on the obtained state error vector; and the obtained force and torque are converted to obtain the control command for the USV, enabling the USV to respond.

[0007] Technical effect

[0008] Compared with existing technologies, this invention, by introducing an integral sliding surface, effectively reduces the system's dependence on model parameters, achieving robust multi-vessel cooperative motion control and ensuring the formation remains unchanged. It not only fully utilizes its computing power to implement complex control logic but also facilitates real-time monitoring and parameter adjustment, improving the system's response flexibility. Furthermore, the control algorithm can be applied to real-vessel tests. Simultaneously, a hardware and software connection is constructed between the host computer and the unmanned surface vessel (USV). Through a highly reliable communication protocol, the host computer can send control commands to the USV and receive status feedback information, achieving closed-loop control of the system. Attached Figure Description

[0009] Figure 1 This is a flowchart of the present invention;

[0010] Figure 2 This is a flowchart of an implementation example;

[0011] Figures 3-8 This is a schematic diagram illustrating the effect of an example. Detailed Implementation

[0012] like Figure 1 As shown in the figure, this embodiment relates to a motion control method for unmanned surface vessels based on PID integral sliding mode, including:

[0013] Step 1: Construct a formation system model consisting of fully driven USVs composed of single-vessel motion models, specifically as follows: Where: η i =[x i ,y i ,z i ] T For the location information of the following ship, x i Let y be the eastward position of the i-th unmanned surface vessel in the geodetic coordinate system. i Let ψ be the northward position of the i-th unmanned surface vessel. i This is the heading angle. μ i It is η i The first derivative of ν. i =[u i ,v i ,r i ] T For the speed information of the following ship, u i Let v be the longitudinal velocity in the body coordinate system. i Let r be the lateral velocity of the unmanned surface vessel in its body coordinate system. i The bow roll rate is angular velocity. C is a positive definite inertial matrix. i (v i )=[0,0,c 13,i ;0,0,c 23,i ;c31,i ,c 32,i [0] represents the centripetal matrix and the Coriolis matrix, D i (v i )=[d 11,i ,0,0;0,d 22,i ,d 23,i ;0,d 32,i ,d 33,i ] represents the hydrodynamic damping matrix, where the parameters in the M, C, and D matrices are the model parameters of the unmanned surface vessel. g i =[g ui ,g vi ,g ri ] T For uncertain model dynamics, g ui For the uncertain model dynamics in the longitudinal velocity direction, g vi For the uncertain model dynamics in the transverse velocity direction, g ri For the uncertain dynamics of the heading angle, τ i =[τ ui ,τ vi ,τ ri ] T τ is the actual control input. ui For longitudinal thrust, τ vi For lateral thrust, τ ri For the turning torque, d i These represent the disturbance forces and torques caused by the external environment. Coordinate transformation matrix.

[0014]

[0015] In the aforementioned formation system composed of fully driven USVs, the kinematic trajectory of the virtual leader is: in: For leaders in the geodetic coordinate system The position and yaw angle vectors below, This refers to the horizontal and vertical positions in the geodetic coordinate system. For the leader in the body coordinate system The velocity vector below, Let R(ψ0) be the longitudinal and lateral velocities in the body coordinate system, and let R(ψ0) be the geodetic coordinate system. and body coordinate system The transformation matrix between them.

[0016] In the aforementioned formation system composed of fully driven USVs, the desired trajectory of the virtual leader is η. d The formation configuration is constructed with a virtual leader at its center, and the desired trajectory satisfies:

[0017] Assumption 1. Expected trajectory η dIt is a smooth, continuously differentiable curve that varies within a specified range.

[0018] Assumption 2. External disturbances are unknown and have an upper bound, and the upper bound is unknown.

[0019] In the aforementioned formation system composed of fully driven USVs, the trajectory tracking error of a single unmanned surface vessel is: e1 = η i -η d e1 represents the position error of the unmanned surface vessel; e2 represents the velocity error of the unmanned surface vessel (USV); the tracking error and cooperative position error of the USV formation are e 1i The cooperative speed error is e 2i e 1i =η i +Δ i -η d , Where: η i In unmanned surface vessel mode, Δ i For the formation of unmanned surface vessels (USVs), the desired position of the USVs is defined as η. d The expected speed is

[0020] Step 2: Construct a controller based on integral sliding mode, specifically as follows:

[0021] Among them: the error system based on integral sliding mode for a single unmanned surface vessel. Error system based on integral sliding mode for unmanned surface vessel formation α1, α2, α3 are the constructive positive constants, k1, k2, k3, k4, k5 are the constructive positive constants, and a ij The elements of the weighted adjacency matrix A are k3 and k4, which are the control gains and adaptive laws. k5 is a positive number to be set, and k5 is used as the control gain to prove stability. μ i For η i The first derivative.

[0022] Step 3: Control Calculation and Command Transmission: Inertial navigation information of the unmanned surface vessel (USV) is acquired via GPS / GNSS sensors, and the position error between the current position and the desired position is calculated. This position error information is transmitted to the controller from Step 2. Thrust is distributed using the calculated control force; that is, the force and torque information obtained by the controller is converted into the rotational speed and direction of each propeller. The rotational speed and direction information based on the thrust distribution are then transmitted to the propellers via network, serial port, and CAN bus communication.

[0023] Through specific experiments, a host computer was used to generate specific task instructions based on task requirements while analyzing the state data of each unmanned surface vessel (USV), such as position, speed, heading, and environmental sensor information, to ensure that the USVs maintained a good state. For example, simulations were conducted under the model parameters of the USVs shown in Table 1. The initial position of the USVs was defined as [0; 0], and the desired position was [100; 100]. The control parameters were set as α1 = 5, α2 = 0.1, α3 = 0.1.

[0024] k1=5, k2=0.1, k3=0.1, k4=0.5, k5=0.5.

[0025] Table 1 Model parameters of unmanned surface vessels

[0026]

[0027] Based on the above parameter settings, the following specific simulation process will be performed:

[0028] Step a: After the task is determined, instructions are issued through the wireless communication module. This stage uses TCP communication mode and a custom communication protocol to ensure the reliability of data transmission.

[0029] Step b: After receiving mission instructions, the unmanned surface vessel (USV) generates the desired position based on the specific instructions. The control module then calculates the error information and uses it to obtain the integral sliding surface. Based on the current position and the sliding surface, the control force and torque required to stabilize the system are calculated. The aforementioned higher-level instructions are then converted into specific thrust and rudder angles (considering different propulsion systems, such as twin propellers).

[0030] Step c: Upon receiving specific low-level instructions, the low-level controller immediately executes the response.

[0031] Step d: During the mission execution, the host computer monitors and displays the status of the unmanned surface vessel in real time, and updates the unmanned surface vessel's position information, speed, heading and other parameters in real time, so that the operator can more intuitively observe the system error.

[0032] Compared with existing technologies, this invention, through a PID-based sliding mode control strategy, can be applied in practical engineering. Furthermore, the proposed method only requires adjusting three sets of parameters, significantly improving system flexibility and exhibiting robust performance against external disturbances.

[0033] The above-described specific implementations can be partially adjusted by those skilled in the art in different ways without departing from the principles and purpose of the present invention. The scope of protection of the present invention is defined by the claims and is not limited to the above-described specific implementations. All implementation schemes within the scope of the claims are bound by the present invention.

Claims

1. A PID integral sliding mode based motion control method for unmanned surface vehicle on water, characterized in that, The unmanned ship physical model is constructed, simulation output information is obtained through system input, an error between the simulation output information and expected output is calculated, an expected adjustment force and torque control signal is obtained by using a PID-based integral sliding mode control algorithm, and the control signal is transmitted to an executing mechanism to realize unmanned ship motion control. The PID-based integral sliding mode control algorithm refers to obtaining inertial navigation information of the unmanned ship by using a sensor, calculating position error information of the position and an expected position, and transmitting the position error information to an integral sliding mode-based controller for calculation. The integral sliding mode-based controller specifically refers to: Among them: the error system of a single unmanned surface vessel based on integral sliding mode. Error system of unmanned surface vessel formation based on integral sliding mode , For constructed positive constants, For constructed positive constants, Weighted adjacency matrix elements, To control the gain, an adaptive law , Let be a positive number to be set, and The control gain was used to demonstrate stability. for The first derivative, For the positional error of the unmanned surface vessel, For the speed error of the unmanned surface vessel, For the tracking error and coordinated position error of the unmanned surface vessel formation, For the cooperative speed error, It is a positive definite inertial matrix. For the centripetal matrix and the Coriolis matrix, Here, M represents the hydrodynamic damping matrix, and the parameters in the M, C, and D matrices are the model parameters of the unmanned surface vessel. This is the speed information of the following ship.

2. The PID integral sliding mode based motion control method for unmanned surface vehicle on water surface according to claim 1, characterized in that, The physical model of the unmanned ship refers to a single-ship motion model full-drive USV formation system model, specifically: Wherein: is position information of the following ship, is the eastward position of the i-th unmanned ship in the geodetic coordinate system, is the northward position of the i-th unmanned ship, is the heading angle, is the first derivative of , is the longitudinal velocity in the body coordinate system, is the lateral velocity in the body coordinate system of the unmanned ship, is the yaw angular velocity, is the uncertain model dynamics, is the uncertain model dynamics in the longitudinal velocity direction, is the uncertain model dynamics in the lateral velocity direction, is the uncertain dynamics of the heading angle, is the actual control input, is the longitudinal thrust, is the lateral thrust, is the turning moment, is the disturbance force and moment caused by the external environment, and the coordinate conversion matrix .

3. The PID integral sliding mode based motion control method for unmanned surface vehicle on water surface according to claim 2, characterized in that, In the aforementioned fully driven USV formation system, the kinematic trajectory of the virtual leader is as follows: ,in: For leaders in the geodetic coordinate system The position and yaw angle vectors below, To determine the horizontal and vertical positions in the geodetic coordinate system, For the leader in the body coordinate system The velocity vector below, Let the longitudinal and lateral velocities be in the body coordinate system. Geodetic coordinate system and body coordinate system The transformation matrix between them; The expected trajectory of the virtual leader in the full-drive USV formation system is The formation configuration is constructed with the virtual leader as the center, and the expected trajectory satisfies: the expected trajectory is a smooth and continuously derivable curve, and is changed within a specified range, and the external disturbance is unknown and has an upper bound, and the upper bound is unknown.

4. The PID integral sliding mode based motion control method for unmanned surface vehicle on water surface according to claim 1, characterized in that, The error of the simulation output information and the expected output includes: in the full-drive USV formation system, the unmanned ship single-ship trajectory tracking error is: , , , Wherein: is the state of the unmanned ship, is the formation of the unmanned ship, and the expected position of the unmanned ship is , the expected speed is .

5. The PID integral sliding mode based motion control method for unmanned surface vehicle on water surface according to claim 1, characterized in that, The transmission to the executing mechanism refers to converting force and torque information obtained by the PID-based integral sliding mode control algorithm into rotating speeds and directions of each propeller, transmitting the rotating speed and direction information of the thrust distribution to the propeller through network, serial port and CAN bus communication.

6. A PID integral sliding mode based motion control system for an unmanned surface vehicle on water surface, implementing the method of any one of claims 1-5, characterized in that, It comprises: An unmanned ship input / output response unit, an unmanned ship controller construction unit and a calculation and instruction generation unit, wherein the unmanned ship input / output response unit obtains speed and position according to input control instructions, the unmanned ship controller construction unit calculates a required state error vector according to the speed, position and error information from the expected position at the current time, the calculation and instruction generation unit calculates the unmanned ship controller according to the obtained state error vector, the obtained force and torque are converted to obtain the control instructions of the unmanned ship, and the unmanned ship is caused to respond.

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