A drilling rig cylindrical coordinate robot fuzzy PID angle control method

Abstract

This invention discloses a fuzzy PID angle control method for a cylindrical coordinate manipulator of a drilling rig, comprising: constructing a hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of a subsea drilling rig; constructing a hydraulic motor control model of the cylindrical coordinate manipulator of the subsea drilling rig based on the hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of the subsea drilling rig; inputting a given input signal into the hydraulic motor control model of the cylindrical coordinate manipulator of the subsea drilling rig to obtain the current angle output value; and adaptively adjusting the parameters of the PID control according to fuzzy rules, so that the current angle output value better tracks the given value, thereby realizing the adjustment and control of the manipulator angle. This invention introduces fuzzy control to adjust the PID parameters in real time according to the error and rate of change of the angle feedback, responding to external disturbances more quickly, improving the dynamic response characteristics of the system, realizing more precise manipulator angle control, thereby improving the overall control accuracy and making it more adaptable to complex marine environments.

Description

Technical Field

[0001] This invention belongs to the technical field of angle control strategy for cylindrical coordinate manipulators of drilling rigs, and particularly relates to a fuzzy PID angle control method for cylindrical coordinate manipulators of subsea drilling rigs. Background Technology

[0002] Deep-sea drilling rigs are crucial technological equipment for marine scientific research and marine resource exploration and development, and are currently the primary means of conducting deep-sea geological sampling and exploration. Through these rigs, accurate and comprehensive deep-sea samples and data can be obtained, providing a scientific basis for resource exploration and development. Deep-sea drilling rigs typically operate at depths of several thousand meters on the seabed. A communication system transmits control signals, and an automatic control system on the surface controls the rig to complete a series of actions and achieve work objectives, exhibiting high integration and complexity.

[0003] As a key component of the subsea drilling rig system, the robotic arm, with its flexible joint structure and precise control capabilities, can perform complex operations within confined spaces, ensuring the accuracy of drilling work. The robotic arm can mimic the movements of a human hand, performing tasks such as grasping, transporting, and installing drill pipes, keeping the subsea drilling rig operating efficiently. The drill pipes and drill tools of the subsea drilling rig are arranged in a cylindrical shape, providing excellent fit with the cylindrical coordinate robotic arm. The cylindrical coordinate robotic arm consists of rotational and translational joints, providing a cylindrical workspace. In these operations, angle control is crucial to the performance of the cylindrical coordinate robotic arm of the subsea drilling rig. Angle control enables the robotic arm to precisely grasp, place, and rotate drill pipes and drill tools, facilitating the unloading, lowering, and retrieval of drill pipes and drill tools, improving the success rate and efficiency of operations.

[0004] Currently, most angle control methods for manipulators on subsea drilling rigs employ traditional PID control. However, the seabed environment is complex and variable, with numerous interfering factors. Traditional PID control suffers from poor environmental adaptability, weak anti-interference capabilities, and an inability to respond quickly to constantly changing operational demands, thus impacting control performance. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention proposes a fuzzy PID angle control method for a drilling rig cylindrical coordinate robot. Based on traditional PID angle control, fuzzy control is introduced to adjust the PID parameters in real time according to the angle feedback error and its rate of change, enabling faster response to external disturbances, improving the dynamic response characteristics of the system, achieving more precise robot angle control, thereby improving the overall control accuracy and making it more adaptable to complex marine environments.

[0006] This invention provides a fuzzy PID angle control method for a drilling rig cylindrical coordinate robot, comprising:

[0007] Construct a hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of a subsea drilling rig;

[0008] Based on the hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of the subsea drilling rig, a hydraulic motor control model for the cylindrical coordinate manipulator of the subsea drilling rig is constructed.

[0009] The given input signal is input to the hydraulic motor control model of the manipulator on the cylindrical surface of the subsea drilling rig to obtain the current angle output value;

[0010] The parameters of the PID control are adaptively adjusted according to fuzzy rules, so that the current angle output value can better track the given value, thereby realizing the adjustment and control of the robot's angle.

[0011] Optionally, the hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of the subsea drilling rig includes: an electric motor, a hydraulic pump, a pressure compensator, a proportional directional valve, a relief valve, and a hydraulic motor.

[0012] Optionally, the hydraulic motor model of the manipulator for the cylindrical coordinates of the subsea drilling rig includes: a controller module, a proportional amplification module, an electro-hydraulic proportional valve module, a hydraulic motor module, an execution module, and a detection feedback module.

[0013] Optionally, constructing the hydraulic motor model of the cylindrical coordinate manipulator of the subsea drilling rig includes:

[0014] Obtain the transfer function of the scaling module;

[0015] Obtain the transfer function of the electro-hydraulic proportional valve module;

[0016] The valve core displacement of the electro-hydraulic proportional valve module is obtained, and the angular displacement of the hydraulic motor is obtained in combination with external load interference.

[0017] Based on the angular displacement, obtain the transfer function of the angular displacement to the valve core displacement and the transfer function of the angular displacement to the external load torque;

[0018] The total transfer function is obtained based on the transfer function of the proportional amplification module, the transfer function of the electro-hydraulic proportional valve module, the transfer function of angular displacement to valve core displacement, and the transfer function of angular displacement to external load torque.

[0019] Based on the overall transfer function, the hydraulic motor control model of the manipulator in the cylindrical coordinate system of the subsea drilling rig is obtained.

[0020] Optionally, the method for obtaining the transfer function of the scaling module is as follows:

[0021]

[0022] Where U(s) is the input voltage of the proportional amplifier, I(s) is the input current of the proportional amplifier, and K... aThis refers to the proportional amplifier coefficient;

[0023] The method for obtaining the transfer function of the electro-hydraulic proportional valve module is as follows:

[0024]

[0025] Among them, X v Let I be the valve core displacement of the proportional valve, I be the input current of the electromagnet, s be the Laplace operator, and K be the displacement of the valve core. sv For the proportional valve displacement gain, ω sv The natural frequency of the proportional valve, ζ sv Proportional valve damping ratio;

[0026] The method for obtaining the angular displacement of a hydraulic motor is as follows:

[0027]

[0028] Among them, D m For the displacement of the hydraulic motor, θ m Kq is the hydraulic motor rotation angle, β is the proportional valve flow gain, and β is the hydraulic motor rotation angle. e T is the effective bulk elastic modulus of the working oil. L V is the external load torque. t J is the total volume of the hydraulic motor and its piping. t B is the total moment of inertia of the hydraulic motor and the load. m ω is the viscous damping coefficient. h Let ξ be the natural frequency of hydraulic pressure. h K is the hydraulic damping coefficient. ce This refers to the total flow rate of the hydraulic motor.

[0029] The method for obtaining the transfer function of angular displacement with respect to valve core displacement is as follows:

[0030]

[0031] Where, θ m (s) represents the angular displacement, X v (s) represents the valve core displacement;

[0032] The method for obtaining the transfer function of the angular displacement external load torque is as follows:

[0033]

[0034] Among them, T L (s) represents the external load torque;

[0035] The method for obtaining the total transfer function is as follows:

[0036]

[0037] Where G(s) is the total transfer function, U f (s) is the feedback signal, U e (s) represents the error signal.

[0038] Optionally, controlling the current angle output value using the fuzzy PID angle control method of the robotic arm includes:

[0039] Obtain the deviation and deviation rate between the current angle output value and the given angle;

[0040] The deviation and deviation rate are fuzzified, and correction coefficients are obtained by combining them with a fuzzy rule base;

[0041] The correction coefficients are defuzzified, and the final control parameters are obtained by combining them with the initial control parameters.

[0042] The current angle output value is controlled using the final control parameters.

[0043] Optionally, the method for controlling the parameters is as follows:

[0044]

[0045] Among them, K P K I K D These are the final control parameters of the PID controller, k. p k i k d These are the initial control parameters for the PID controller, ΔK P ΔK I and ΔK D These represent the parameter increments output by the fuzzy controller.

[0046] Compared with the prior art, the present invention has the following advantages and technical effects:

[0047] This invention introduces fuzzy control into traditional PID angle control, adjusting the PID parameters in real time based on the angle feedback error and its rate of change. This allows for a faster response to external disturbances, improves the dynamic response characteristics of the system, and enables more precise angle control of the robotic arm, thereby enhancing the overall control accuracy and making it more adaptable to complex marine environments.

[0048] For cylindrical coordinate manipulators operating in harsh environments such as subsea drilling rigs, the fuzzy PID control of this invention offers a short settling time and good stability even with significant changes in the manipulator's angle and torque. Furthermore, it can adaptively adjust the response speed based on the magnitude of the angle change; that is, the speed is faster when the angle deviation is large and slower when the angle deviation is small. Attached Figure Description

[0049] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0050] Figure 1 This is a flowchart of a fuzzy PID angle control method for a drilling rig cylindrical coordinate robot according to an embodiment of the present invention;

[0051] Figure 2 This is a three-dimensional view of the cylindrical coordinate robot arm of the subsea drilling rig according to an embodiment of the present invention;

[0052] Figure 3 This is a schematic diagram of an equivalent simplified model of the robotic arm according to an embodiment of the present invention;

[0053] Figure 4 This is a schematic diagram of the hydraulic system control of the robotic arm according to an embodiment of the present invention;

[0054] Figure 5 This is a block diagram of the hydraulic motor control according to an embodiment of the present invention;

[0055] Figure 6 This is a block diagram of the transfer function of the hydraulic motor system according to an embodiment of the present invention;

[0056] Figure 7 This is a block diagram of the angle control transfer function of the hydraulic motor system according to an embodiment of the present invention;

[0057] Figure 8 This is a fuzzy control structure diagram according to an embodiment of the present invention;

[0058] Figure 9 This is a diagram of the fuzzy PID control structure according to an embodiment of the present invention;

[0059] Figure 10 This is a membership function graph of the deviation e in an embodiment of the present invention;

[0060] Figure 11 This is a membership function graph of the deviation change rate ec in an embodiment of the present invention;

[0061] Figure 12 The deviation ΔK in the embodiment of the present invention P Membership function graph;

[0062] Figure 13 The deviation ΔK in the embodiment of the present invention I Membership function graph;

[0063] Figure 14 The deviation ΔK in the embodiment of the present invention D Membership function graph;

[0064] Figure 15This is an input / output surface view of an embodiment of the present invention;

[0065] Figure 16 These are simulation structure diagrams of various parts of the hybrid energy storage model predictive overall control method according to an embodiment of the present invention;

[0066] Figure 17 These are simulation structure diagrams of various parts of the PI control method for a hybrid energy storage system according to an embodiment of the present invention;

[0067] Figure 18 This is a simulation structure diagram of each part of the PI control method for a hybrid energy storage system under the first operating condition according to an embodiment of the present invention;

[0068] Figure 19 This is a simulation structure diagram of each part of the PI control method for a hybrid energy storage system under the second operating condition of this invention.

[0069] Figure 20 This is a comparison chart of the overall control voltage fluctuations of PI control and model prediction under the third operating condition of this invention. Detailed Implementation

[0070] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0071] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0072] This invention proposes a fuzzy PID angle control method for a drilling rig cylindrical coordinate robot, such as... Figure 1 As shown, the specific steps include:

[0073] Construct a hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of a subsea drilling rig;

[0074] Based on the hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of the subsea drilling rig, a hydraulic motor model of the cylindrical coordinate manipulator of the subsea drilling rig is constructed.

[0075] Input the preset voltage value into the hydraulic motor model of the manipulator on the cylindrical surface of the subsea drilling rig, and obtain the current angle output value;

[0076] The PID parameters are adaptively adjusted according to fuzzy rules to reduce the difference between the current angle output value and the given angle, thereby achieving the adjustment and control of the robot's angle.

[0077] Specifically, the formulation of fuzzy rules is usually based on engineering experiments and empirical summarization to develop a suitable fuzzy rule base. The main principles are as follows:

[0078] Deviation e refers to the difference between the current angle and the set angle; the rate of change of deviation ec reflects the trend of deviation over time, that is, the speed at which the difference between the current angle and the set angle changes. This value can be used to predict future deviation changes. For example, a large ec indicates that the system is rapidly approaching or moving away from the set point, while a small ec or close to zero indicates that the system may have approached a stable state.

[0079] Furthermore, the hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of the subsea drilling rig includes: an electric motor, a hydraulic pump, a pressure compensator, a proportional directional valve, a relief valve, and a hydraulic motor.

[0080] Specifically, the cylindrical coordinate robot of the subsea drilling rig is a crucial component for completing the actions of gripping drill rods and drill strings, and drilling. The 3D model is as follows: Figure 2 As shown, the abstract simplified structure diagram is as follows: Figure 3 As shown, it has three degrees of freedom and four movements: rotation, extension, vertical movement, and gripper closing and releasing. The rotation function is driven by an electro-hydraulic valve-controlled hydraulic motor, with an angle from 0 to 360 degrees. Vertical and extension movements are achieved by hydraulic cylinders. Among the movements performed by the robotic arm, the rotation movement is one of the most important; the accuracy of the rotation angle determines whether subsequent sequential movements can be performed correctly.

[0081] Hydraulic system and control of robotic arm rotary mechanism, such as Figure 4 As shown, the system mainly consists of an electric motor, a hydraulic pump, a pressure compensator, a proportional directional valve, a relief valve, and a hydraulic motor. The system's working principle is as follows: The opening of the proportional valve is controlled by an input signal, thereby adjusting the amount of oil flowing through the hydraulic motor and achieving precise control of its speed and direction. The control strategy employs a position feedback closed-loop system. This system continuously detects and feeds back position data through sensors. If a deviation between the set position and the actual position is detected, the system will adjust via solenoid valves and actuators. Furthermore, due to the limited tank volume of the underwater hydraulic system, a pressure compensator is installed to automatically adjust to the ambient pressure at different depths, compensating in real time for changes in oil volume caused by oil elasticity, temperature variations, or flow differences during the operation of asymmetrical cylinders.

[0082] Furthermore, the hydraulic motor model of the cylindrical coordinate manipulator for the subsea drilling rig includes: a controller module, a proportional amplifier module, an electro-hydraulic proportional valve module, a hydraulic motor module, an execution module, and a detection feedback module.

[0083] Specifically, the rotary hydraulic system of the cylindrical coordinate manipulator of the subsea drilling rig is a complex system composed of several hydraulic components. This complex system can be equivalently represented by multiple standard links. By analyzing the transfer functions of these standard links, an equivalent model of the entire system can be obtained. The structure of the manipulator control system is as follows: Figure 5 As shown, it mainly includes the controller, proportional amplifier, electro-hydraulic proportional valve, hydraulic motor, actuator, and detection feedback.

[0084] Furthermore, the construction of the hydraulic motor model for the cylindrical coordinate manipulator of the subsea drilling rig includes:

[0085] Obtain the transfer function of the scaling module;

[0086] Obtain the transfer function of the electro-hydraulic proportional valve module;

[0087] The valve core displacement of the electro-hydraulic proportional valve module is obtained, and the angular displacement of the hydraulic motor is obtained by combining the external load interference.

[0088] Based on the angular displacement, obtain the transfer function of the angular displacement to the valve core displacement and the transfer function of the angular displacement to the external load torque;

[0089] The overall transfer function is obtained based on the transfer function of the proportional amplifier module, the transfer function of the electro-hydraulic proportional valve module, the transfer function of angular displacement to valve core displacement, and the transfer function of angular displacement to external load torque.

[0090] Based on the overall transfer function, obtain the cylindrical coordinate model of the manipulator and hydraulic motor of the subsea drilling rig.

[0091] The specific construction method is as follows:

[0092] (1) Modeling of proportional amplifier and proportional valve:

[0093] The proportional amplifier is used to activate the proportional valve. A voltage-to-current converter with high output impedance is considered a proportional amplification stage, ensuring that the electrical signal can be effectively converted and drive the proportional valve. Its transfer function is:

[0094]

[0095] Where U(s) is the input voltage of the proportional amplifier, I(s) is the input current of the proportional amplifier, and K... a This refers to the proportional amplifier coefficient or gain.

[0096] The valve core displacement of the solenoid valve is proportional to the input current of the proportional electromagnet, and the valve core displacement determines the flow rate entering the actuator. In engineering, the proportional valve is regarded as a second-order circuit, and its transfer function is shown in equation (2).

[0097]

[0098] In the formula, K sv For the proportional valve displacement gain, ω sv The natural frequency of the proportional valve, ζ sv Proportional valve damping ratio.

[0099] (2) Modeling of the hydraulic valve-controlled motor system:

[0100] In order to gain a deeper understanding of the dynamic characteristics of the hydraulic motor power mechanism and optimize the control strategy, this embodiment constructs its mathematical model and makes the following assumptions:

[0101] ① The pipeline design is short and thick, thus ignoring pressure loss and dynamic effects;

[0102] ②The internal and external leakage fluid flow state of the hydraulic motor is regarded as laminar flow, and the fluid density and temperature remain unchanged;

[0103] ③ The proportional valve is considered an ideal spool valve;

[0104] ④ The pressure of the main oil circuit of the hydraulic system remains constant, and the return oil pressure is assumed to be zero to prevent additional pressure loss;

[0105] ⑤ The bulk modulus of hydraulic oil remains constant under different system pressures;

[0106] ⑥ Ignore the elastic deformation between the motor and the load.

[0107] The linearized flow equation for the electro-hydraulic proportional valve of the hydraulic motor is shown in equation (3):

[0108] q L =K q x v -K c p L (3)

[0109] q L Kq is the proportional valve load flow rate, and x is the proportional valve flow gain. v Where Kc is the proportional valve spool displacement, p is the proportional valve flow-pressure coefficient, and p is the proportional valve spool displacement. L The load pressure is given by the Laplace transform:

[0110] Q L =K q X v -K c P L (4)

[0111] The flow continuity equation for a hydraulic motor is given by equation (5):

[0112]

[0113] D mFor the displacement of the hydraulic motor, θ m C is the rotation angle of the hydraulic motor. tm Total leakage coefficient of hydraulic motor, V t β is the total volume of the hydraulic motor and its piping. e Let be the effective bulk elastic modulus of the working oil. Equation (6) can be obtained through Laplace transformation:

[0114]

[0115] The equation for balancing the output torque and load torque of a hydraulic motor is shown in equation (7):

[0116]

[0117] Among them, J t B is the total moment of inertia of the hydraulic motor and the load. m G is the viscous damping coefficient, G is the load torque spring stiffness, and T is the viscous damping coefficient. L This represents the external load torque. After the Lagrange transformation, we obtain equation (8):

[0118] D m P L =J t θ m s 2 +B m θ m +Gθ m +T L (8)

[0119] By combining equations (4), (6), and (8), the expression for the total output angular displacement of the motor under the combined action of valve core displacement and external load interference is shown in equation (9).

[0120]

[0121] From equation (9), it can be seen that the output angular displacement of the hydraulic motor is related to physical quantities such as inertial load, hydraulic fluid compression motor leakage, and elastic load. Simplifying equation (9), when G = 0, and...

[0122]

[0123] We can obtain:

[0124]

[0125] Where, ω h The natural frequency of hydraulic pressure,

[0126] ξ h This is the hydraulic damping coefficient.

[0127] Let be the speed amplification factor, which is dimensionless. From formula (11), the transfer function of the motor output angular displacement to the valve core displacement can be obtained as:

[0128]

[0129] The transfer function of the motor's output angular displacement to the external load torque is:

[0130]

[0131] Angle θ m (s) and rotational speed ω m The relationship between them is ω m =dθ m / dt, after Laplace transform, yields θ m (s)=ω m s, Equations (12) and (13) can be transformed into:

[0132]

[0133] The sensor circuit can be considered a proportional circuit, and the sensor gain K can be obtained. f :

[0134]

[0135] Based on the transformation relationship between joint space and drive space, the mathematical model of the hydraulic motor angle position control system can be obtained, such as... Figure 6 As shown, U1 and θ1 are the system setpoint and output values, respectively, and the system transfer function is:

[0136]

[0137] The parameters of the hydraulic motor system are shown in Table 1. Substituting the data from Table 1 into the hydraulic motor system structure diagram, we can obtain... Figure 7 .

[0138] Table 1

[0139]

[0140] Since the robot operates in the deep seabed, the force exerted during the rotation process is relatively large. Therefore, it is necessary to consider the combined effect of torque during the rotation process of the robot. Its expression is shown in equation (19).

[0141]

[0142] In the formula, T q T is the driving torque of the hydraulic motor. f The torque T is the torque generated by the resistance of seawater. mLet J be the torque generated by each frictional force, J be the moment of inertia, and B be the viscous damping coefficient.

[0143] The hydrodynamic resistance is shown in equation (20):

[0144]

[0145] In the formula, C f ρ is the seawater damping coefficient. h Seawater density, A e Let v be the water-facing area of ​​the actuator, and v be the speed of the actuator.

[0146] The expression for the resistance torque of water acting on the region is shown in equation (21):

[0147]

[0148] In the formula, (r1,r2) is the area of ​​effect, r is the radius of the area, and h is the height of the area of ​​effect.

[0149] The expression for the resultant torque of friction is shown in equation (22):

[0150]

[0151] In the formula, p max q represents the maximum peak pressure, and q represents the displacement of the hydraulic motor.

[0152] Furthermore, controlling the current angle output value using the fuzzy PID angle control method of the robotic arm includes:

[0153] Obtain the current angle output value and the deviation and deviation rate between the current angle output value and the given angle;

[0154] The deviation and deviation rate are fuzzified, and the correction coefficient is obtained by combining the fuzzy rule base.

[0155] The correction coefficients are defuzzified, and the final control parameters are obtained by combining the initial control parameters.

[0156] The current angle output value is controlled using the final control parameters.

[0157] Specifically, fuzzy control is a nonlinear control technique with good robustness. A fuzzy controller structure diagram is shown below. Figure 8 As shown, it mainly consists of fuzzification, fuzzy rule base, fuzzy inference, and defuzzification. Combining fuzzy control with traditional PID control results in fuzzy PID control. This control method can adaptively adjust the PID parameters according to customized fuzzy rules, enabling it to adapt to changing control systems. The schematic diagram of fuzzy PID is shown below. Figure 9 As shown.

[0158] The inputs to a fuzzy PID controller are the system deviation e and the rate of change of the system deviation ec. After fuzzification and a customized fuzzy rule base, the correction coefficient ΔK can be obtained. P ΔK I and ΔK D Then, after defuzzification, the incremental values ​​of the PID controller parameters can be obtained, and the parameters of the PID controller can be adjusted in real time. The corrected PID parameters are shown in equation (23).

[0159]

[0160] K P K I K D These are the final control parameters of the PID controller;

[0161] k p k i k d These are the initial control parameters for the PID controller;

[0162] ΔK P ΔK I and ΔK D These are the parameter increments for the PID controller;

[0163] In this system, the fuzzy PID angle controller for the robotic arm is a two-input, three-output system. Based on the actual system design and operation, as well as simulation experiments, the value ranges of each input and output variable are set as follows:

[0164] e∈[-350, 350], ec∈[-1000, 1000], ΔK P ∈[-3, 10], ΔK I ∈[-0.5, 0.5], ΔK D ∈[-0.05, 0.05].

[0165] The universe of discourse for the fuzzy controller is divided into {NB, NM, NS, ZO, PS, PM, PB}, representing negative large, negative medium, negative small, zero, positive small, positive medium, and positive large, respectively. Furthermore, a triangular membership function is used, which exhibits strong linear adjustment capability. The membership functions for each universe of discourse are as follows: Figure 10-14 As shown.

[0166] The formulation of fuzzy rules is usually based on engineering experiments and empirical summarization to develop a suitable fuzzy rule base. The main principles are as follows:

[0167] Deviation e refers to the difference between the current angle and the set angle; the rate of change of deviation ec reflects the trend of deviation over time, that is, the speed at which the difference between the current angle and the set angle changes. This value can be used to predict future deviation changes. For example, a large ec indicates that the system is rapidly approaching or moving away from the set point, while a small ec or close to zero indicates that the system may have approached a stable state.

[0168] When e is large, it is necessary to reduce the error, improve the system's fast response, and appropriately increase ΔK. P And reduce ΔK I .

[0169] When e and ec are equal, ΔK P Slightly decrease, ΔK I and ΔK D medium.

[0170] When e is small, overshoot is prevented and system stability is improved. ΔK is moderately increased. P ΔK D The value of ΔK varies when ec is small. D Increase; when ec is large, ΔK D Decrease.

[0171] The fuzzy rules for fuzzy PID are shown in Table 2, with ΔK representing the values ​​from left to right. P ΔK I and ΔK D The rules. The membership function with two inputs and three outputs is as follows: Figure 10-14 As shown, the input and output surface views are as follows: Figure 15 As shown.

[0172] Table 2

[0173]

[0174] The following is in conjunction with the appendix Figure 16-20 This embodiment will be described in detail:

[0175] Based on the mathematical model of the hydraulic motor control system for the cylindrical coordinate manipulator shown in the figure, this embodiment uses Matlab / Simulink software to build the model and simulate and verify the control strategy. In the control strategy section, both traditional PID control and fuzzy PID control are employed, and the two control methods are compared. The comparison is further divided into different operating conditions: the first condition is a single angle step, the second condition is multiple consecutive angle step steps, and the third condition incorporates the variation of the combined torque of the load torque and the disturbance torque to simulate the variable disturbance environment on the seabed.

[0176] (1) In the first working condition, the simulation model for controlling the robot angle using traditional PID control and fuzzy PID control is as follows: Figure 16-17 As shown. The initial k p =10,k i =0.5, k d =0.05. The angle is set to step from the initial 0 degrees to 40 degrees in 1 second. The control effects under the two control methods are as follows: Figure 18 As shown in the figure, when the robot arm angle jumps within a small range, the fuzzy PID response speed is faster and the adjustment time is shorter.

[0177] (2) In the second operating condition, the angle is continuously varied to verify the performance of the two control methods. The initial state is 0 degrees, the angle steps to 40 degrees at 1 second, to 340 degrees at 3 seconds, and then to 140 degrees at 5 seconds. The control effects of the two control methods are as follows: Figure 19 As shown in the figure, when the robot arm angle changes continuously, the fuzzy PID control is superior to the traditional PID control in terms of speed and stability, especially when the angle change is large, where the traditional PID control has a larger overshoot and a longer settling time. The results also show that with fuzzy PID control, the response speed can be adaptively adjusted according to the magnitude of the step difference as the angle changes stepwise. When the angle deviation changes significantly, the response speed is faster; when the angle deviation is small, the response speed is slightly slower. In contrast, the adaptive adjustment capability of traditional PID control is poor.

[0178] (3) In the third operating condition, a continuously varying composite torque consisting of load torque and disturbance torque is added to the second operating condition where the angle changes continuously. The initial torque is set to 0, then jumps to 50 N·m at 1s, to 250 N·m at 3s, and then to 150 N·m at 5s. The control effects of the two control methods in the third operating condition are as follows: Figure 20 As shown in the figure, it can be concluded that under torque variation and disturbance, fuzzy PID control not only has certain advantages in response speed, but also has better stability than traditional PID control when the torque step change is large, that is, when a large disturbance occurs. Traditional PID control shows a large overshoot in angle.

[0179] In summary, based on the simulation results of the three operating conditions, it can be concluded that for the cylindrical coordinate manipulator of the subsea drilling rig operating in a relatively harsh environment, the fuzzy PID control has a shorter settling time and better stability under conditions of large changes in the manipulator's angle and torque. Furthermore, it can adaptively adjust the response speed according to the magnitude of the angle change; that is, the speed is faster when the angle deviation is larger and slower when the angle deviation is smaller.

[0180] This embodiment takes a cylindrical coordinate manipulator for a subsea drilling rig as the research object. When controlling its angle, traditional PID control suffers from poor environmental adaptability, weak anti-interference ability, and an inability to respond quickly to constantly changing operational requirements, thus affecting control performance. Based on the modeling of the manipulator's hydraulic system, fuzzy control is introduced to adjust the PID parameters in real time according to the angle feedback error and its rate of change. Finally, a simulation model is built in Matlab / Simulink, simulating three working conditions, and the fuzzy PID and traditional PID are compared and analyzed. Simulation results show that the proposed fuzzy PID angle control strategy for the manipulator has better dynamic performance and anti-interference ability, thereby improving the overall control accuracy and making it more adaptable to complex marine environments.

[0181] The above are merely preferred embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A fuzzy PID angle control method for a drilling rig cylindrical coordinate robot, characterized in that, include: Construct a hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of a subsea drilling rig; Based on the hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of the subsea drilling rig, a hydraulic motor control model for the cylindrical coordinate manipulator of the subsea drilling rig is constructed. The given input signal is input to the hydraulic motor control model of the manipulator on the cylindrical surface of the subsea drilling rig to obtain the current angle output value; The parameters of the PID control are adaptively adjusted according to fuzzy rules, so that the current angle output value can better track the given value, thereby realizing the adjustment and control of the robot's angle. The hydraulic model of the rotary mechanism of the cylindrical coordinate manipulator of the subsea drilling rig includes: an electric motor, a hydraulic pump, a pressure compensator, a proportional directional valve, a relief valve, and a hydraulic motor; The hydraulic motor model of the cylindrical coordinate manipulator of the subsea drilling rig includes: a controller module, a proportional amplifier module, an electro-hydraulic proportional valve module, a hydraulic motor module, an execution module, and a detection feedback module; The construction of the hydraulic motor model for the cylindrical coordinate manipulator of the subsea drilling rig includes: Obtain the transfer function of the scaling module; Obtain the transfer function of the electro-hydraulic proportional valve module; The valve core displacement of the electro-hydraulic proportional valve module is obtained, and the angular displacement of the hydraulic motor is obtained in combination with external load interference. Based on the angular displacement, obtain the transfer function of the angular displacement to the valve core displacement and the transfer function of the angular displacement to the external load torque; The total transfer function is obtained based on the transfer function of the proportional amplification module, the transfer function of the electro-hydraulic proportional valve module, the transfer function of angular displacement to valve core displacement, and the transfer function of angular displacement to external load torque. Based on the overall transfer function, obtain the hydraulic motor control model of the manipulator in the cylindrical coordinates of the subsea drilling rig; The method for obtaining the transfer function of the scaling module is as follows: Where U(s) is the input voltage of the proportional amplifier, I(s) is the input current of the proportional amplifier, and K... a This refers to the proportional amplifier coefficient; The method for obtaining the transfer function of the electro-hydraulic proportional valve module is as follows: Among them, X v Let I be the valve core displacement of the proportional valve, I be the input current of the electromagnet, s be the Laplace operator, and K be the displacement of the valve core. sv For the proportional valve displacement gain, ω sv The natural frequency of the proportional valve, ζ sv Proportional valve damping ratio; The method for obtaining the angular displacement of a hydraulic motor is as follows: Among them, D m For the displacement of the hydraulic motor, θ m Kq is the hydraulic motor rotation angle, β is the proportional valve flow gain, and β is the hydraulic motor rotation angle. e T is the effective bulk elastic modulus of the working oil. L V is the external load torque. t J is the total volume of the hydraulic motor and its piping. t B is the total moment of inertia of the hydraulic motor and the load. m ω is the viscous damping coefficient. h Let ξ be the natural frequency of hydraulic pressure. h K is the hydraulic damping coefficient. ce This refers to the total flow rate of the hydraulic motor. The method for obtaining the transfer function of angular displacement with respect to valve core displacement is as follows: in, It is an angular displacement. This refers to the valve core displacement; The method for obtaining the transfer function of the angular displacement external load torque is as follows: in, For external load torque, It is angular displacement; The method for obtaining the total transfer function is as follows: Where G(s) is the system function, U f (s) is the feedback signal, U e (s) is the error signal.

2. The fuzzy PID angle control method for a drilling rig cylindrical coordinate robot according to claim 1, characterized in that, The PID parameters are adaptively adjusted according to fuzzy rules to reduce the difference between the current angle output value and the set angle, thereby achieving the adjustment and control of the robot's angle. Obtain the deviation and deviation rate between the current angle output value and the given angle; The deviation and deviation rate are fuzzified, and correction coefficients are obtained by combining them with a fuzzy rule base; The correction coefficients are defuzzified, and the final control parameters are obtained by combining them with the initial control parameters. The current angle output value is controlled using the final control parameters.

3. The fuzzy PID angle control method for a drilling rig cylindrical coordinate robot according to claim 2, characterized in that, The method for controlling the parameters is as follows: Among them, K P K I K D These are the final control parameters of the PID controller, k. p k i k d These are the initial control parameters for the PID controller, ΔK P ΔK I and ΔK D These represent the parameter increments output by the fuzzy controller.

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