A novel active disturbance rejection wave compensation platform control method and related device

Abstract

The application provides a novel active disturbance rejection wave compensation platform control method and related equipment, and belongs to the technical field of active disturbance rejection wave compensation platform control. The application comprises: constructing a second-order active disturbance rejection control model in a simulation environment, and adjusting the control parameters of the second-order active disturbance rejection control model by using a wave disturbance model; deploying the adjusted second-order active disturbance rejection control model to an industrial control platform, and configuring a control period and a fault safety logic; using the second-order active disturbance rejection control model to estimate the total disturbance of the system according to actual attitude data, and calculating the attitude compensation control amount of the upper platform in combination with the total disturbance of the system; kinematically back-solving the attitude compensation control amount to obtain length adjustment instructions of six electric branch chains; after checking the length adjustment instructions according to the fault safety logic, driving the electric branch chains to perform movement to enable the upper platform to maintain a horizontal attitude. The application can improve the operation safety and precision of a six-degree-of-freedom parallel wave compensation platform.

Description

Technical Field

[0001] This application relates to the field of control technology for self-disruption wave compensation platforms, and in particular to a novel control method and related equipment for self-disruption wave compensation platforms. Background Technology

[0002] With the development of offshore wind power, marine oil and gas operations, six-degree-of-freedom parallel wave compensation platforms, as core equipment for ensuring operational safety, need to maintain a stable horizontal attitude relative to the sea level under the disturbance of the hull caused by wind, waves, and swells (e.g., when boarding for wind turbine maintenance, the end of the platform's gangway must be precisely aligned with the wind turbine platform). Among related technologies, wave compensation schemes have three major problems: first, they rely on wave forecast models and precise platform dynamic models, resulting in severe model mismatch when facing random wave disturbances; second, they have weak anti-disturbance capabilities, with insufficient compensation accuracy in moderate waves and above (horizontal error often exceeds ±0.5°); and third, the control logic verified by simulation is difficult to adapt to offshore industrial control platforms, leading to high engineering implementation costs and long cycles.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0004] The main objective of this application is to propose a novel control method and related equipment for a self-disruption wave compensation platform, which can improve the operational safety and accuracy of a six-degree-of-freedom parallel wave compensation platform.

[0005] To achieve the above objectives, one aspect of this application proposes a novel control method for a self-disturbance rejection wave compensation platform, the method comprising the following steps: A second-order active disturbance rejection control model is constructed in a simulation environment, and the control parameters of the second-order active disturbance rejection control model are tuned using a wave disturbance model; the second-order active disturbance rejection control model is used to estimate and compensate for the total disturbance of the system. The tuned second-order active disturbance rejection control model is deployed to the industrial control platform, and the control cycle and fault-safe logic are configured. The industrial control platform collects actual attitude data from the attitude sensor. The second-order active disturbance rejection control model is used to estimate the total system disturbance based on the actual attitude data, and the attitude compensation control quantity of the upper platform is calculated in combination with the total system disturbance. The attitude compensation control quantity is subjected to inverse kinematic solution to obtain the length adjustment commands of the six electric branches; After verifying the length adjustment command according to the fault-safe logic, the electric branch is driven to perform movement to keep the upper platform in a horizontal position.

[0006] In some embodiments, the step of constructing a second-order active disturbance rejection control model in a simulation environment and tuning the control parameters of the second-order active disturbance rejection control model using a wave disturbance model includes: In the simulation environment, a second-order active disturbance rejection control model is constructed, which includes a tracking differentiator, an extended state observer, and a nonlinear state error feedback module; the simulation environment is the Simulink simulation environment. A wave disturbance model is integrated into the simulation environment to simulate the six-degree-of-freedom motion of the ship hull under different sea conditions. The output of the wave disturbance model is used as the disturbance input of the second-order active disturbance rejection control model to form a closed-loop simulation test environment. The second-order active disturbance rejection control model is run in the closed-loop simulation test environment. The model parameters are iteratively tuned using the data on the attitude maintenance effect of the upper platform to obtain control parameters so that the upper platform maintains a horizontal attitude under wave disturbance. The model parameter tuning process includes setting the time constant, bandwidth, observer bandwidth, scaling parameter, differential parameter, and extended state observer gain parameter for the four degrees of freedom: roll, pitch, yaw, and heave.

[0007] In some embodiments, deploying the tuned second-order active disturbance rejection control model to an industrial control platform and configuring the control cycle and fault-safe logic includes: The tuned second-order active disturbance rejection control model is deployed to the TwinCAT3 industrial control platform; In the TwinCAT3 industrial control platform, a sampling control cycle is configured for the second-order active disturbance rejection control model to match the EtherCAT communication cycle; In the TwinCAT3 industrial control platform, fault-safe logic for a six-degree-of-freedom parallel wave compensation platform is deployed. The fault-safe logic is deployed to trigger a safety action upon detection of any of the following abnormal conditions: The drive command or actual length of the electric chain exceeds the preset safety range. Communication with the sensor or driver is interrupted or times out; The collected posture data is invalid or exceeds the reasonableness threshold.

[0008] In some embodiments, the acquisition of actual attitude data from the attitude sensor via the industrial control platform includes: In the operating mode of the industrial control platform, based on the control cycle synchronized with the EtherCAT communication cycle, the actual attitude data measured by the attitude sensors installed on the six-degree-of-freedom parallel wave compensation platform is collected; the actual attitude data includes heave displacement, roll angle, pitch angle and bow angle.

[0009] In some embodiments, the step of using the second-order active disturbance rejection control model to estimate the total system disturbance based on the actual attitude data, and calculating the attitude compensation control quantity of the upper platform in conjunction with the total system disturbance, includes: The actual attitude data is input into the extended state observer of the second-order active disturbance rejection control model; The extended state observer is used to estimate the total disturbance of the system based on the actual attitude data and the control quantity output by the second-order active disturbance rejection control model, and simultaneously outputs attitude observations, angular velocity observations and total disturbance observations. The attitude compensation control quantity is calculated based on the error between the horizontal attitude reference command and the attitude observation value, the angular velocity observation value, and the total disturbance observation value. The total disturbance observation value is used to feedforward compensation for the total disturbance during the calculation process. The attitude compensation control quantity includes the desired heave displacement, desired roll angle, desired pitch angle, and desired yaw angle that the upper platform needs to achieve in the next control cycle.

[0010] In some embodiments, performing inverse kinematics on the attitude compensation control quantity to obtain the length adjustment commands of the six electric branches includes: Based on the attitude compensation control amount, determine the desired position and desired attitude of the upper platform; Based on the desired position and desired orientation of the upper platform, and combined with the geometric coordinates of the upper and lower platform hinge points in their respective platform coordinate systems, the theoretical lengths of the six electric branches connecting the corresponding upper and lower platform hinge points in the desired orientation are calculated using spatial geometric relationships or homogeneous coordinate transformation matrices. Based on the theoretical length and the current length of each of the electric branches, the length adjustment amount required for each electric branch is calculated, which serves as the length adjustment command for driving its servo motor.

[0011] In some embodiments, after verifying the length adjustment command according to the fault-safe logic, driving the electric branch chain to perform movement to keep the upper platform in a horizontal position includes: In the industrial control platform, the deployed fault-safe logic is invoked to verify the length adjustment command generated by the inverse kinematics solution; Once the verification is successful, the length adjustment command is sent to the corresponding six servo drives; Each of the servo drivers drives the servo motor according to the received length adjustment command, thereby causing the corresponding electric chain to extend or retract; Based on the coordinated movement of the six electric branch chains, the spatial orientation of the upper platform is adjusted to counteract wave disturbances transmitted from the hull, and the upper platform maintains a stable horizontal attitude relative to the sea level.

[0012] To achieve the above objectives, another aspect of this application proposes a novel self-disturbance rejection wave compensation platform control system for implementing the method described above. The system includes: The first module is used to construct a second-order active disturbance rejection control model in a simulation environment and to tune the control parameters of the second-order active disturbance rejection control model using a wave disturbance model; the second-order active disturbance rejection control model is used to estimate and compensate for the total disturbance of the system. The second module is used to deploy the tuned second-order active disturbance rejection control model to the industrial control platform and configure the control cycle and fault-safe logic. The third module is used to collect actual attitude data from the attitude sensor through the industrial control platform. The fourth module is used to estimate the total system disturbance based on the actual attitude data using the second-order active disturbance rejection control model, and to calculate the attitude compensation control quantity of the upper platform in combination with the total system disturbance. The fifth module is used to perform inverse kinematics on the attitude compensation control quantity to obtain the length adjustment commands of the six electric branches; The sixth module is used to verify the length adjustment command according to the fault-safe logic, and then drive the electric branch to perform movement so that the upper platform maintains a horizontal posture.

[0013] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0014] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides a novel control method, system, electronic device, storage medium, and program product for an active disturbance rejection wave compensation platform. The application includes: constructing a second-order active disturbance rejection control model in a simulation environment and tuning the control parameters of the second-order active disturbance rejection control model using a wave disturbance model; deploying the tuned second-order active disturbance rejection control model to an industrial control platform and configuring the control cycle and fault-safe logic; using the second-order active disturbance rejection control model to estimate the total system disturbance based on actual attitude data, and calculating the attitude compensation control quantity of the upper platform in conjunction with the total system disturbance; performing inverse kinematics on the attitude compensation control quantity to obtain the length adjustment commands of the six electric branches; verifying the length adjustment commands according to the fault-safe logic, and then driving the electric branches to perform motion to keep the upper platform in a horizontal attitude. This application can improve the operational safety and accuracy of a six-degree-of-freedom parallel wave compensation platform. Attached Figure Description

[0017] Figure 1 This is a flowchart of a novel self-disturbance rejection wave compensation platform control method provided in the embodiments of this application; Figure 2a This is an overall control flowchart provided in the embodiments of this application; Figure 2b This is a flowchart of the ADRC control system for the wave compensation system provided in the embodiments of this application; Figure 3 This is a schematic diagram of the overall Simulink control model provided in the embodiments of this application; Figure 4 This is a schematic diagram of the internal connection relationship of the second-order ADRC core module provided in the embodiments of this application; Figure 5 This is a schematic diagram of the internal connection relationship of the Extended State Observer (ESO) provided in the embodiments of this application; Figure 6a This is a schematic diagram of the Pitch direction experiment results provided in the embodiments of this application; Figure 6b This is a schematic diagram of the relevant indicators of the Pitch direction experimental results provided in the embodiments of this application; Figure 7a This is a schematic diagram of the Roll direction experimental results provided in the embodiments of this application; Figure 7b This is a schematic diagram of the relevant indicators of the Roll direction experimental results provided in the embodiments of this application; Figure 8a This is a schematic diagram of the experimental results in the Yaw direction provided in the embodiments of this application; Figure 8b This is a schematic diagram of the relevant indicators of the experimental results in the Yaw direction provided in the embodiments of this application; Figure 9aThis is a schematic diagram of the experimental results in the Heave direction provided in the embodiments of this application; Figure 9b This is a schematic diagram of the relevant indicators of the experimental results in the Heave direction provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0021] 1) Six-DOF Parallel Wave Compensation Platform: A parallel mechanism device specifically designed for offshore operations. It consists of a lower platform fixed to the hull, an upper platform carrying operational functions (such as boarding gangways and equipment transfer), and six corrosion-resistant electric support chains connecting the two platforms. Its core function is to counteract the six-DOF motions (heave, roll, pitch, and bow) of the hull caused by waves, keeping the upper platform in a stable attitude relative to the sea level. Its six-DOF definitions are closely matched to the needs of offshore operations: heave (vertical translation to counteract vertical undulations), roll (rotation around the longitudinal axis to counteract lateral heeling), pitch (rotation around the lateral axis to counteract fore-and-aft heeling), and bow (rotation around the vertical axis to counteract horizontal torsion).

[0022] 2) Active Disturbance Rejection Control (ADRC): An advanced disturbance rejection control strategy that does not rely on a precise mathematical model of the controlled object. Its core design principle is "actively observing and compensating for internal and external disturbances." It mainly consists of three modules: a tracking differentiator (TD), an extended state observer (ESO), and a nonlinear state error feedback (NLSEF). The TD processes the horizontal attitude reference input of the upper platform, generating smooth tracking and differential signals (such as attitude-angular velocity) to avoid sudden input shocks. The ESO is the core, treating "external disturbances (such as carrier vibration and load changes) + internal system disturbances (such as chain friction and motor dead zones)" as the "total disturbance" and expanding it into a new system state, observing the upper platform's attitude, angular velocity, and total disturbance in real time. The NLSEF, based on the TD output and ESO observation results, calculates the nonlinear control law, incorporates disturbance compensation, and drives the actuators.

[0023] 3) Extended State Observer (ESO): A core submodule of ADRC addressing the "difficulty in modeling disturbances" problem. Based on platform control inputs (branch drive commands) and outputs (platform attitude), it constructs an extended state space containing "the original system state (attitude, angular velocity) + total disturbance." By designing the observer gain, it reconstructs the state variables and estimates the disturbance in real time. In this invention, the ESO structure includes a proportional element (-K, where K is the gain matrix, which needs to be tuned according to the platform's dynamic characteristics to ensure that the disturbance observation convergence speed meets control requirements) and an integral / differential element; the inputs are the branch drive commands and the platform attitude feedback, and the outputs are attitude observations, angular velocity observations, and total disturbance observations (directly used for NLSEF compensation).

[0024] 4) Wave Interference: Irregular waves in the marine environment, such as wind waves and swells, have different frequencies, wavelengths, and wave heights. These waves exert periodic or non-periodic forces on ships, causing them to move in six degrees of freedom, which in turn affects the equipment and operations on board. Wave interference is a major external disturbance factor that a six-degree-of-freedom parallel wave compensation platform needs to overcome, and its complexity and uncertainty increase the difficulty of platform control.

[0025] 5) Inverse Kinematics: This is the core kinematic calculation process for the Stewart platform in parallel mechanisms. It involves determining the target lengths of the six drive chains (electric cylinders) by combining the desired position (Z-coordinate) and attitude (roll, pitch, and yaw angles) of the end effector (upper platform) with the fixed geometric coordinates of the hinge points of the upper and lower platforms, through spatial geometric relationships or homogeneous transformation matrix operations. Its core function is to transform the "upper platform attitude command" into "chain motion command," which is a crucial link connecting the control algorithm and the actuator—without inverse kinematics, the attitude control quantities output by ADRC cannot directly drive the chain extension and retraction.

[0026] 6) Simulink: A graphical simulation tool developed by MathWorks.

[0027] 7) TwinCAT3: Beckhoff Real-Time Control and Automation Software Platform (Version 3). As an industrial real-time control software, it is the "brain" that deploys and runs algorithms verified in Simulink to actual hardware.

[0028] 8) TwinCAT3 PLC: A programmable logic controller based on the TwinCAT 3 environment.

[0029] 9) EtherCAT: Ethernet control automation technology, high-speed real-time communication bus, connects TwinCAT3 controller, attitude sensor and six servo drives to ensure synchronization of control commands and feedback data.

[0030] 10) Stewart: The Stewart platform (a classic six-degree-of-freedom parallel mechanism configuration) consists of an upper platform, a lower platform, and six independently extendable branches (electric cylinders), and is the basis for realizing complex spatial motion.

[0031] 11) 2ndADRC4: Active disturbance rejection controller (module) for second-order and fourth-order extended state observers. 2nd indicates that the controller is a second-order system (controlling position and velocity), ADRC is active disturbance rejection control, and 4 indicates that its internal extended state observer (ESO) is fourth-order, used to observe attitude, angular velocity, angular acceleration and total disturbance.

[0032] 12) uadrc: The output control quantity (signal variable name) of the ADRC controller. In the Simulink simulation model, it represents the theoretical control command (usually torque or desired acceleration / velocity) calculated by the ADRC controller to drive the controlled object.

[0033] 13) upperdctf1: Upper platform transfer function 1 (module / signal variable name), in the Simulink model, represents the simplified mathematical model of the dynamics of the upper platform (controlled object).

[0034] 14) yadrc: The actual output / feedback signal (variable name) of the ADRC control branch. In the Simulink model, it represents the output of the upper platform transfer function (upperdctf1).

[0035] 15) PID: Proportional-Integral-Derivative control, a traditional control method used as a benchmark.

[0036] 16) PLC: Programmable Logic Controller, refers to the core equipment form of industrial control.

[0037] 17) Beckhoff CX5240: Beckhoff CX5240 model embedded industrial PC, industrial controller hardware that actually runs TwinCAT3 and ADRC control programs.

[0038] 18) GVL: Global Variable List (in TwinCAT / PLC programming), a file used in TwinCAT3 projects to centrally define and manage global parameters and variables.

[0039] In related technologies, the control scheme has some limitations: First, it is highly model-dependent: traditional control requires the establishment of accurate "wave-platform" coupled dynamic models and wave prediction models, but the randomness of wave disturbances (such as sudden gusts causing a sharp increase in wave height) and nonlinearity (multi-frequency superposition) make it difficult for the model to match the actual working conditions in real time, and the compensation accuracy drops sharply in sea conditions of medium waves and above (horizontal error exceeds ±0.5°); Second, it has weak disturbance resistance: pure kinematic inverse control only derives the chain length through geometric relationships, without considering the dynamic characteristics of wave disturbances and internal disturbances of the system (such as increased chain friction caused by sea salt spray), and only uses static geometric relationships. The derivation of branch lengths lacks real-time closed-loop feedback and disturbance compensation mechanisms. When faced with dynamic wave disturbances, the branch action commands cannot be adjusted in real time with the disturbances, resulting in a lag in compensation response (>0.5s) and an inability to promptly offset wave impacts. Finally, there is a disconnect between simulation and engineering: most solutions only complete simulation verification in Simulink, but marine industrial control relies on platforms such as TwinCAT3. The simulation model (such as ideal wave disturbances and noise-free signals) differs greatly from the actual marine environment (electromagnetic interference, sensor drift caused by salt spray). The migration of control logic requires extensive secondary development, resulting in a long implementation cycle (usually >3 months) and high costs.

[0040] In view of this, developing an ADRC control scheme that is independent of wave models, has strong anti-disturbance capabilities, and can be efficiently adapted to offshore industrial platforms has become a core requirement for improving the operational safety and accuracy of six-degree-of-freedom parallel wave compensation platforms. This application provides a novel ADRC-based control method and related equipment for a six-degree-of-freedom parallel wave compensation platform, which solves the problem of maintaining the platform's horizontal position under random wave disturbances. The basic scheme is as follows: 1. Construct an ADRC control model for wave compensation scenarios in Simulink, integrate an extended state observer (ESO) to realize real-time observation of the total disturbance of internal disturbances (branch friction, elastic deformation, etc.) and external wave disturbances, and simulate hull disturbances under calm / medium / large wave states to verify the compensation effect of ADRC on waves; 2. Adapt the ADRC control logic and parameters verified by simulation to the TwinCAT3 industrial platform, and complete the parameter configuration, disturbance filtering, and fault-safe logic deployment for six-degree-of-freedom wave compensation in TwinCAT3; 3. The actual six-degree-of-freedom parallel wave compensation platform receives attitude sensor data through TwinCAT3, executes ADRC control commands, adjusts the length of the six electric branches to offset wave disturbances, and achieves horizontal maintenance of the upper platform.

[0041] Figure 1 This is an optional flowchart of a novel self-disturbance rejection wave compensation platform control method provided in this application embodiment. Figure 1 The method may include, but is not limited to, steps S101 to S106.

[0042] Step S101: Construct a second-order active disturbance rejection control model in the simulation environment, and use the wave disturbance model to tune the control parameters of the second-order active disturbance rejection control model; the second-order active disturbance rejection control model is used to estimate and compensate for the total disturbance of the system. Step S102: Deploy the tuned second-order active disturbance rejection control model to the industrial control platform and configure the control cycle and fault safety logic. Step S103: Collect the actual attitude data of the attitude sensor through the industrial control platform; Step S104: Using a second-order active disturbance rejection control model, estimate the total system disturbance based on the actual attitude data, and calculate the attitude compensation control quantity of the upper platform in combination with the total system disturbance. Step S105: Perform inverse kinematics solution on the attitude compensation control quantity to obtain the length adjustment commands of the six electric branches. Step S106: After verifying the length adjustment command according to the fail-safe logic, drive the electric support chain to perform movement so that the upper platform maintains a horizontal posture.

[0043] In steps S101 to S106 of the embodiments of this application, a second-order Active Disturbance Rejection Control (ADRC) model is constructed and tuned in a simulation environment to simulate the total disturbance characteristics inside and outside the system and optimize the controller; the optimized ADRC model is deployed to an industrial control platform and configured with real-time cycle and safety logic to complete the reliable porting and operation guarantee of the control algorithm from simulation to industrial real-time environment; the actual attitude data of the upper platform is collected based on the platform and input into the ADRC model to realize the real-time perception of system state and disturbance; the total disturbance is estimated by the ADRC model and the attitude compensation control quantity is calculated to realize active observation and feedforward compensation of anti-motion factors; the conversion from spatial attitude command to coordinated extension and contraction action of each branch is realized by performing inverse kinematic solution on the compensation control quantity; the motion control under safety constraints is realized by verifying the command according to the safety logic and driving the branch execution, and finally the core beneficial effect of maintaining the horizontal attitude of the upper platform stably in a wave disturbance environment is achieved.

[0044] In some embodiments, step S101 may include, but is not limited to, steps S111 to S114: Step S111: In the simulation environment, construct a second-order active disturbance rejection control model that includes a tracking differentiator, an extended state observer, and a nonlinear state error feedback module; the simulation environment is the Simulink simulation environment. Step S112: Integrate the wave disturbance model in the simulation environment to simulate the six-degree-of-freedom motion of the hull under different sea conditions. Use the output of the wave disturbance model as the disturbance input of the second-order active disturbance rejection control model to form a closed-loop simulation test environment. Step S113: Run the second-order active disturbance rejection control model in the closed-loop simulation test environment. Iteratively tune the model parameters using the attitude maintenance effect data of the upper platform to obtain control parameters so that the upper platform can maintain a horizontal attitude under wave disturbance. Step S114, the model parameter tuning process includes setting the time constant, bandwidth, observer bandwidth, scale parameter, differential parameter and extended state observer gain parameter for the four degrees of freedom of roll, pitch, yaw and heave.

[0045] In steps S111 to S114 of the embodiments of this application, step S111 performs modular and visual controller modeling by "constructing a second-order ADRC model containing three major modules: TD, ESO, and NLSF in Simulink," realizing a precise engineering expression of the core control concept of "active disturbance rejection," and providing a clear structural foundation for subsequent algorithm implementation and parameter tuning. The TD module is used to smooth the expected "horizontal attitude command" and avoid command mutations; the construction of the ESO module establishes a mathematical framework for unifying internal and external disturbances into a "total disturbance" for observation; the design of the NLSF module defines the fusion mechanism of error nonlinear combination and disturbance compensation. Step S112 performs high-fidelity marine disturbance environment simulation by "integrating wave disturbance models and simulating ship motion under different sea conditions," realizing the potential ability of the ADRC algorithm to cope with random and complex wave disturbances in a safe, low-cost, and repeatable virtual environment, and generating a standard test dataset for parameter tuning. Three typical sea states—calm, medium waves, and large waves—are set up to simulate the periodic or non-periodic forces (heave, roll, pitch, etc.) exerted on the ship under these conditions, serving as the disturbance input sources for the ADRC controller. Step S113 performs data-driven controller performance optimization by "running the ADRC model in a closed-loop simulation environment and iteratively tuning parameters based on the attitude-maintaining effect of the upper platform." This achieves optimal matching between the dynamic response characteristics (such as convergence speed, overshoot, and steady-state accuracy) of the ADRC controller and the actual dynamic characteristics and disturbance rejection requirements of the wave compensation platform, thereby theoretically ensuring control accuracy. In this embodiment, parameters are continuously adjusted, and the roll angle curve of the upper platform in the simulation is observed until its fluctuation amplitude is suppressed within ±0.1° under simulated large wave disturbances, thus achieving the preset "level maintenance" performance index. Step S114 performs refined parameter configuration for each of the four degrees of freedom (roll, pitch, yaw, and heave), setting time constants, bandwidth, and a series of gain parameters for each. This enables differentiated control based on the motion characteristics of different degrees of freedom (such as rotation and translation, and inertia differences), thereby comprehensively improving the overall attitude stability accuracy of the platform under multidimensional disturbances, rather than local optimization in a single direction. Larger bandwidths and gains are set for the "heave" degree of freedom, which has a slower response and is significantly affected by waves, to improve its compensation response speed. For the "yaw" degree of freedom, which has strong coupling and model uncertainty, the ESO gain parameters are optimized to ensure the accuracy of its disturbance observation.

[0046] In some embodiments, step S102 may include, but is not limited to, steps S201 to S203: Step S201: Deploy the tuned second-order active disturbance rejection control model to the TwinCAT3 industrial control platform; Step S202: In the TwinCAT3 industrial control platform, configure a sampling control cycle for the second-order active disturbance rejection control model that matches the EtherCAT communication cycle; Step S203: Deploy fault-safe logic for the six-degree-of-freedom parallel wave compensation platform in the TwinCAT3 industrial control platform; The fault-safe logic is deployed to trigger safety actions when any of the following abnormal conditions are detected: The drive command or actual length of the electric chain exceeds the preset safety range. Communication with the sensor or driver is interrupted or times out; The collected posture data is invalid or exceeds the reasonableness threshold.

[0047] In steps S201 to S203 of this embodiment, the calibrated ADRC model is deployed to the TwinCAT3 platform to perform engineering transformation from simulation model to industrial real-time code, enabling the control algorithm to run stably and accurately in an industrial hard real-time environment. The 2ndADRC4 module, after parameter tuning in Simulink, is transformed into a periodically executable PLC function block (such as FB_ADRC_Controller) in TwinCAT3 through code generation or logic rewriting, making it the core part of the control program. By configuring a control cycle in TwinCAT3 that strictly matches the EtherCAT communication cycle (e.g., 0.001s), the entire system achieves hard real-time synchronization, ensuring that key actions such as sensor data acquisition, complex ADRC calculations, and drive command issuance are completed strictly in sequence within a short time, eliminating control lag or jitter caused by timing errors and guaranteeing real-time control. In this embodiment, the TwinCAT3 task cycle is set to 1ms and synchronized with the EtherCAT master station cycle. In this way, IMU (Inertial Measurement Unit) data is read at the beginning of the cycle, the ADRC algorithm completes calculations in the middle of the cycle, and the new branch length command is sent to all servo drives via the EtherCAT network before the end of the cycle. By deploying targeted fail-safe logic in TwinCAT3 to perform continuous state monitoring and safety interlocking during runtime, the system can automatically and quickly enter a safe state when risks such as hardware failure, communication anomalies, or software anomalies occur, preventing equipment damage or secondary accidents and ensuring the safety of personnel and equipment. The fail-safe logic in this embodiment addresses "branch over-limit": continuously monitoring the encoder feedback value of each electric cylinder, if its length approaches the mechanical limit (e.g., >95% of the maximum stroke), immediately triggering a safety stop and locking all drives. Addressing "communication timeout": setting a "watchdog" timer for each EtherCAT slave (e.g., each servo drive), if no valid message is received within a specified period, the node is determined to have failed, and the motor enable is immediately cut off. Regarding "invalid data": The roll angle data returned by the attitude sensor is checked for reasonableness. If the value jumps to a range far beyond the physical possibility (e.g., >45°), it is determined to be a sensor malfunction. The data is discarded and the valid value of the previous cycle is used or a safety shutdown is triggered.

[0048] In some embodiments, step S103 may include, but is not limited to, step S301: Step S301: In the operation mode of the industrial control platform, based on the control cycle synchronized with the EtherCAT communication cycle, the actual attitude data measured by the attitude sensor installed on the six-degree-of-freedom parallel wave compensation platform is collected; the actual attitude data includes heave displacement, roll angle, pitch angle and bow angle.

[0049] Step S301, as illustrated in this embodiment, involves explicitly collecting attitude sensor data installed on the upper platform to directly measure the state feedback of the controlled object. This provides the ADRC's extended state observer with a true controlled variable input, enabling it to accurately evaluate the control effect. Based on this, it inversely infers and estimates the total internal and external disturbances of the system, forming the physical basis of the core mechanism of "disturbance observation based on output feedback." This embodiment directly uses a combination of tilt sensors and accelerometers / encoders installed at the geometric center of the upper platform to measure the actual roll angle (e.g., +0.5 degrees), pitch angle (e.g., -0.3 degrees), and heave displacement (e.g., +12 mm) of the upper platform relative to the inertial coordinate system (or reference horizontal plane). These data (not the lower platform data) are directly sent to the feedback input of the ADRC controller. This embodiment not only collects the roll and pitch angles that determine whether the platform is level, but also the yaw angle that affects the orientation of the working equipment, and the heave displacement that affects the working height. The combination of these physical quantities constitutes the conditions for controlling the upper platform's attitude and achieving compensation.

[0050] In some embodiments, step S104 may include, but is not limited to, steps S401 to S403: Step S401: Input the actual attitude data into the extended state observer of the second-order active disturbance rejection control model; Step S402: Using the extended state observer, based on the actual attitude data and the control quantity output by the second-order active disturbance rejection control model, estimate the total disturbance of the system, and simultaneously output the attitude observation value, angular velocity observation value and total disturbance observation value. Step S403: Based on the error between the horizontal attitude reference command and the attitude observations, the angular velocity observations, and the total disturbance observations, the attitude compensation control quantity is calculated and generated. The total disturbance observations are used to feedforward compensation for the total disturbance during the calculation process. The attitude compensation control quantity includes the desired heave displacement, desired roll angle, desired pitch angle, and desired yaw angle that the upper platform needs to achieve in the next control cycle.

[0051] Steps S401 to S403 of this embodiment, by "inputting the actual attitude data and the control quantity of the previous cycle into the extended state observer," perform real-time reconstruction of the system state and total disturbance based on the input and output data. This achieves dynamic estimation of the "total disturbance," including unmodeled dynamics (such as chain friction) and external strong disturbances (such as random wave force), without relying on a precise mathematical model, and quantifies it into a usable observation value, thereby solving the problem of "difficulty in modeling disturbances" in complex systems. In this embodiment, the ESO receives the actual roll angle of the upper platform (such as 0.8 degrees measured by a sensor) and the control torque command calculated in the previous control cycle for compensation. Through an internal algorithm, it outputs the total disturbance observation value z3 (e.g., an equivalent disturbance torque value) in real time. This value includes the combined effect of influencing factors such as current wave impact and chain nonlinear friction. By explicitly defining the desired pose included in the attitude compensation control quantity, the abstract control quantity is concretized into geometric instructions. This provides clear and unambiguous input to the subsequent inverse kinematics module, allowing the output of the control algorithm to be accurately translated into the coordinated extension and retraction of six electric cylinders. This completes the key interface definition from the "control domain" to the "execution domain." For example, the ADRC controller in this embodiment does not ultimately output an abstract force or torque vector, but a set of explicit geometric instructions: desired heave displacement = +5mm, desired roll angle = 0 degrees, desired pitch angle = 0 degrees, desired yaw angle = current value held. This set of instructions can be directly input into the inverse kinematics program.

[0052] In some embodiments, step S105 may include, but is not limited to, steps S501 to S503: Step S501: Determine the desired position and desired attitude of the upper platform based on the attitude compensation control variables. Step S502: Based on the desired position and desired attitude of the upper platform, and combined with the geometric coordinates of the upper platform hinge point and the lower platform hinge point in their respective platform coordinate systems, the theoretical lengths of the six electric branches connecting the corresponding upper platform hinge point and the lower platform hinge point under the desired pose are calculated by using spatial geometric relationships or homogeneous coordinate transformation matrices. Step S503: Based on the theoretical length and the current length of each electric branch, calculate the length adjustment amount required for each electric branch, and use it as the length adjustment command to drive its servo motor.

[0053] Steps S501 to S503 of this embodiment determine the desired pose of the upper platform based on the attitude compensation control quantity and perform a geometric interpretation of the control command. This converts the abstract mathematical compensation quantity (such as force / torque or increment) output by the ADRC controller into the target position (X, Y, Z coordinates) and target orientation (roll, pitch, bow Euler angles) of the upper platform in three-dimensional space, providing input for subsequent geometric calculations. By combining the coordinates of the fixed hinge point, the theoretical length of the branches is solved using spatial geometry or homogeneous transformation to perform the inverse kinematics calculation of the parallel mechanism. This determines the required length of each of the six electric branches based on the target pose of the upper platform. This is the mathematical calculation for spatial compensation motion, transforming the spatial pose problem into six independent length scalar problems. By calculating the length adjustment amount based on the theoretical length and the current length and performing incremental position command generation, the servo driver is provided with a direct change in the position setpoint (or absolute position). The drive motor moves smoothly to the target position along the shortest path, avoiding sudden changes or erroneous movements that may occur due to the unknown current position when directly using the theoretical length.

[0054] In some embodiments, step S106 may include, but is not limited to, steps S601 to S604: Step S601: In the industrial control platform, the deployed fault-safe logic is invoked to verify the length adjustment command generated by the inverse kinematics solution; Step S602: After the verification is passed, the length adjustment command is sent to the corresponding six servo drives; In step S603, each servo driver drives the servo motor according to the received length adjustment command, thereby driving the corresponding electric chain to extend or retract. Step S604: Based on the coordinated movement of the six electric support chains, adjust the spatial orientation of the upper platform to cancel out the wave disturbances transmitted from the hull, and maintain a stable horizontal attitude of the upper platform relative to the sea level.

[0055] Steps S601 to S604, as illustrated in this embodiment, involve calling fault-safe logic before issuing instructions to verify and intercept execution software security. This prevents potentially dangerous instructions (such as overtravel or sudden changes) from reaching the actuator, adding a crucial safety barrier to the core control process and preventing safety accidents such as equipment collisions and overloads caused by algorithm anomalies, communication errors, or sensor failures. The physical realization of the spatial motion synthesis by adjusting the upper platform's pose through the coordinated stretching motion of six branches to offset disturbances involves synthesizing six one-dimensional linear motions into the three-dimensional rigid body motions (translation and rotation) required by the upper platform using the principle of parallel mechanism. This physically generates compensating motion opposite to the direction of wave disturbances, which is the physical manifestation of the entire wave compensation function.

[0056] This application also provides a novel self-disturbance rejection wave compensation platform control system for implementing the aforementioned method. The system includes: The first module is used to construct a second-order active disturbance rejection control model in a simulation environment and to tune the control parameters of the second-order active disturbance rejection control model using a wave disturbance model; the second-order active disturbance rejection control model is used to estimate and compensate for the total disturbance of the system. The second module is used to deploy the tuned second-order active disturbance rejection control model to the industrial control platform and configure the control cycle and fault-safe logic. The third module is used to collect the actual attitude data of the attitude sensor through the industrial control platform; The fourth module is used to estimate the total system disturbance based on the actual attitude data using a second-order active disturbance rejection control model, and to calculate the attitude compensation control quantity of the upper platform in combination with the total system disturbance. The fifth module is used to perform inverse kinematics on the attitude compensation control variables to obtain the length adjustment commands of the six electric branches. The sixth module is used to verify the length adjustment command according to the fail-safe logic, and then drive the electric branch chain to perform the movement so that the upper platform maintains a horizontal posture.

[0057] The following is a detailed description and explanation of the solutions in the embodiments of the present invention, using specific application examples: 1. Controlled object and overall system architecture of this application embodiment: The controlled object of this invention is a six-degree-of-freedom parallel wave compensation platform (Stewart configuration). The upper and lower platforms are constructed of high-strength aluminum alloy to reduce platform weight while ensuring structural strength. The six branches utilize electric cylinders, and the servo motors are permanent magnet synchronous servo motors with matching drivers, enabling high-precision position and speed control. The lower platform reproduces wave-like motion based on attitude parameters transmitted from the ship; the upper platform must maintain a horizontal attitude.

[0058] The overall system architecture is divided into a Simulink simulation layer and a TwinCAT3 actual control layer: the Simulink simulation layer completes the ADRC control model building, parameter tuning, and simulation verification; the TwinCAT3 actual control layer realizes the engineering porting of the simulation model and completes the attitude stabilization control of the actual platform. The overall ADRC control flowchart is shown below. Figure 2a and Figure 2b As shown.

[0059] 2. Building the ADRC control model in Simulink: 2.1 Branch differentiation in the control model: like Figure 3In the Simulink overall control model, the ADRC control branch is the core control link, and its signal flow is as follows: upper platform reference input (horizontal attitude command) → 2ndADRC4 module (second-order ADRC core) → uadrc (ADRC output control quantity) → upper platform overall transfer function (integrating inverse kinematics and platform body) → upperdctf1 transfer function (actual attitude output of upper platform) → yadrc actual attitude (ADRC branch feedback signal) → 2ndADRC4 module (forming a closed loop). The PID control branch and the pure inverse kinematics branch are comparison and verification branches and do not participate in actual engineering control. Their signal flow is not included in the core control logic during actual control.

[0060] 2.2 Construction of the second-order ADRC core module (2ndADRC4): 2ndADRC4 is the core execution module of ADRC control. Its inputs are "upper platform reference attitude command r" and "upper platform actual attitude y" (yadrc), and its output is the control quantity u (uadrc). Internally, it contains a gain circuit, a summation circuit, and an ESO submodule. The signal flow is as follows: Error calculation: The reference attitude r of the upper platform and the attitude observation value (z1) output by ESO are input into the subtractor to calculate the error signal (e=r-z1); Gain adjustment: The error signal e passes through a "-K gain stage" (K is the gain coefficient, determined by parameter tuning) to obtain -K. e; Multi-signal summation: -K The attitude angular velocity observation value z2 (after -K gain) output by e and the total disturbance observation value z3 (after -K gain) and the control quantity u (after feedback and -K gain) are input together into the summing stage to obtain the intermediate signal S; Control output: The intermediate signal S passes through a -K gain circuit to obtain the final control quantity u, which is then output to the "Upper Platform Transfer Function 1" module in Simulink. The internal connections of the 2ndADRC4 module are as follows: Figure 4 As shown.

[0061] 2.3 Extended State Observer (ESO) Design: ESO is the core subunit of the 2ndADRC4 module, used for real-time estimation of the platform's attitude, attitude angular velocity, and total disturbance. Its inputs are the "actual attitude y of the platform" and the "control quantity u" output by 2ndADRC4. The outputs are z1 (attitude observation), z2 (attitude angular velocity observation), and z3 (total disturbance observation). Internally, it includes a subtractor, a gain circuit, a summation circuit, and an integration circuit (1 / s). The specific structure is as follows: Observation error calculation: The actual attitude y of the upper platform and the attitude observation value z1 output by ESO are input into a subtractor to calculate the observation error e=y. z1; Gain allocation: The observation error e passes through " After the K-gain stage, the signal is divided into three parallel channels, denoted as... K e; Integral chain operation: in the first path K e is directly input into the first summation stage, and after integration (1 / s), the attitude observation value z1 is obtained; the second path... K e and control quantity u (via The K-gain is input into the second summing stage, and then combined with the output of z1, the attitude angular velocity observation value z2 is obtained through the integration stage (1 / s); the third path K The input e is the third summation stage, which, combined with the output of z2, is integrated (1 / s) to obtain the total disturbance observation value z3; Observation feedback: z1, z2, and z3 are synchronously fed back to the corresponding links in the 2ndADRC4 main module to complete the observation closed loop.

[0062] The internal connection relationships of the ESO submodules are as follows: Figure 5 As shown.

[0063] 3. Parameter tuning of ADRC controller: The parameters of the ADRC controller include basic ADRC parameters and parameters specific to each direction. The parameter tuning is based on the preset logic in the Twincat3 PLC. The specific parameters are as follows: 3.1 ADRC Basic Parameters: The expansion order is set to 4. This 4th order setting enables accurate observation of core state variables and disturbances without causing computational overload during the control cycle due to an excessively high order. The controller gain is set to 1, which is the baseline gain value for the ADRC controller, used to ensure the initial linearity of the control output. The sampling period is set to 0.001s. This period strictly matches the EtherCAT real-time communication period of the Twincat3 PLC, ensuring complete synchronization of the timing of sensor attitude data acquisition, ADRC control operation, and electric branch drive command output. This guarantees the real-time performance of the control commands and avoids control lag caused by period mismatch.

[0064] 3.2 Specific parameters for each degree of freedom: For the four degrees of freedom of the platform—pitch, roll, yaw, and heave—the parameters are tuned separately. Taking the pitch degree of freedom as an example: the time constant is set to 2500; the bandwidth is 10 / (extension order × time constant × sampling period), a formula derived from engineering tuning experience of ADRC control; the observer bandwidth is set to twice the bandwidth, following the engineering principle that "the observer response speed is faster than the controller closed-loop response speed"; the state error feedback parameters include two, among which kp is set... The bandwidth is set to 1.2 times the square of the bandwidth. This value ensures the steady-state accuracy of attitude control in the pitch direction and reduces steady-state error. kd is set to 16 times the bandwidth to suppress overshoot during attitude adjustment and achieve fast, error-free tracking. The ESO gain parameters include three values: 3 times the observer bandwidth, 0.6 times the square of the observer bandwidth, and 7 times the cube of the observer bandwidth. These three gain parameters correspond to the observation weights of pitch direction attitude, angular velocity, and total disturbance, respectively. The differentiated power values ​​can match the convergence priority of different observation dimensions. The parameter tuning logic for roll, yaw, and heave degrees of freedom is consistent with pitch. After parameter tuning, simulation verification in Simulink is required to ensure that the platform maintains a horizontal attitude under different disturbance intensities.

[0065] 4. Specific implementation steps (ADRC compensation effect verification): This experiment verifies the attitude stabilization performance of a real six-degree-of-freedom platform (a six-degree-of-freedom parallel wave-compensated platform) under ADRC control. The experimental environment is a laboratory double-layer parallel six-degree-of-freedom platform (which can simulate ship motion). Simulink simulation verification was performed before the experiment: wave disturbances of different intensities (lower platform attitude input) were simulated in Simulink, and the upper platform attitude outputs of the ADRC, PID, and pure inverse kinematics branches were compared to verify the attitude stabilization accuracy and disturbance rejection of the ADRC branch. The specific experimental steps are as follows: 4.1 Experimental Preparation: 1. Hardware check: Confirm that the power modules, electric cylinder servo drivers, attitude sensors, and EtherCAT communication cables of the upper and lower platforms of the six-degree-of-freedom platform are properly connected and there are no loose connections or faults. 2. Software preparation: Open the TwinCAT3 software, connect the PLC hardware (Beckhoff CX5240), and confirm that the communication status is normal (no error codes).

[0066] 4.2 Platform power-on and axis enable: 1. Power on: First turn on the main power switch of the lower platform (to power the ship attitude simulation module), then turn on the main power switch of the upper platform (to power the electric cylinder servo system), and wait 30 seconds until the hardware initialization is complete (the servo driver indicator light will be solid green). 2. Axis enable operation: Adjust Twincat3 to run mode, and then in the main program of Twincat3, find the upper and lower platform enable, and write them to TRUE in sequence to enable the 12 axes of the upper and lower platforms.

[0067] 4.3 Initial position calibration: 1. In the Twincat3 MAIN main program, write the initial position movement of the upper and lower platforms to TRUE, and the platforms will automatically execute the initial position movement: the initial length of each axis of the lower platform is set to 938mm, and the initial length of each axis of the upper platform is set to 695mm.

[0068] 2. Position Confirmation: Observe the posture data of the upper and lower platforms using Twincat to confirm that the initial position has been reached and remains stable.

[0069] 4.4 Reading vessel attitude data and enabling ADRC compensation on the lower platform: 1. Lower platform attitude data reading: Start file reading, read the attitude parameters in the file, and then perform wave simulation motion according to the attitude parameters in the file; 2. ADRC Compensation Enabled: Manually write compensation to TRUE in the MAIN main program. The ADRC control algorithm in the compensation will start, and the upper platform will start outputting compensation commands based on the attitude error of the lower platform.

[0070] 4.5 Verification of Dynamic Compensation Effect: 1. Motion process monitoring: The system runs continuously for 5 minutes, recording the attitude data of the upper and lower platforms in real time via an oscilloscope: the lower platform moves with the simulated waves according to preset parameters, while the upper platform is compensated in real time by ADRC control; 2. Data recording: Save attitude data every 0.001s, focusing on recording the roll / pitch error and heave error of the platform, and calculate the average error and maximum error; 3. Effect Judgment: After the experiment, the data was analyzed. If the average roll / pitch error of the platform was ≤ ±0.1° and the maximum error was ≤ ±0.2°, and the average heave error was ≤ ±5mm and the maximum error was ≤ ±8mm, the ADRC compensation effect was judged to be good, meeting the requirements for maintaining horizontal attitude. Furthermore, the same experiment was repeated using PID control as compensation. The experimental results show that the present invention can significantly improve the compensation accuracy and response speed of the six-degree-of-freedom parallel wave compensation platform, meeting the needs of high-precision operations at sea.

[0071] 4.6 Experiment terminated: 1. Stop the wave simulator; the lower platform stops moving and returns to its initial position. 2. In the MAIN program of TwinCAT3, disable ADRC compensation and lower platform file reading, and write FALSE to enable the upper and lower platforms to stop enabling the 12 axes. 3. Disconnect the main power supply to the upper and lower platforms in sequence, shut down the TwinCAT3 software and attitude monitoring software, and organize the experimental data.

[0072] 5. Experimental Results: Pitch direction experimental results reference Figure 6a Reference to relevant metrics of the Pitch direction experiment results Figure 6b Reference for Roll direction experimental results Figure 7a Reference to relevant indicators of Roll direction experimental results Figure 7b Reference for experimental results in the Yaw direction Figure 8a Reference to relevant indicators of experimental results in the Yaw direction Figure 8b Reference for experimental results in the Heave direction Figure 9a Reference to relevant indicators of experimental results in the Heave direction Figure 9b It can be seen that ADRC control can achieve extremely high-precision attitude stabilization in all four core degrees of freedom: pitch, roll, yaw, and heave. Specifically, the pitch compensation accuracy reaches 98.71%, the roll and yaw accuracies exceed 97% respectively, and the heave displacement error is stabilized at the millimeter level. Compared with pure inverse kinematics, ADRC reduces the errors of each degree of freedom; compared with traditional PID control, it further reduces the error. These quantitative data fully demonstrate that ADRC, with its extended state observer's real-time estimation and active compensation capability for the total system disturbance, significantly improves the platform's anti-interference ability, tracking accuracy, and overall stability under complex wave disturbances.

[0073] Advantages of this application: 1. Improve attitude stabilization accuracy under complex disturbances: Direct technical effect: The ESO module of the ADRC controller can estimate the sum of internal disturbances (branch elastic deformation, joint friction) and external disturbances (wave disturbances) in real time and complete the compensation.

[0074] Reasoning process: Compared with the sensitivity of PID control to parameters and the uncompensated characteristics of pure kinematic inverse solution to disturbances, the ESO module does not rely on an accurate system model. It can dynamically track the changes in total disturbance and output compensation, so that the control output of ADRC can offset the combined effects of internal and external disturbances, and ultimately achieve the horizontal attitude maintenance of the upper platform under strong wave disturbances, thus improving the attitude stability accuracy.

[0075] 2. Reduce dependence on system models: Direct technical benefits: ADRC control does not rely on a precise dynamic model of the platform; it only requires identification to obtain a simplified overall transfer function.

[0076] Reasoning process: Existing LQR-LADRC control relies on a linearized dynamic model, which leads to performance degradation during large-angle attitude adjustments. In contrast, the ADRC control of this invention only needs to identify the overall transfer function through input and output data, without the need to establish a complex dynamic model. Even if the platform's characteristics change due to load variations or component wear, the ESO can still compensate through disturbance estimation, ensuring stable control performance.

[0077] 3. Possesses signal noise immunity and real-time disturbance observation capabilities: Direct technical effect: An attitude signal rate filtering stage has been added to the control logic.

[0078] Reasoning process: The attitude signals collected by the sensors are susceptible to noise from ship vibrations. Traditional control schemes can cause control jitter due to noise amplification. The rate filtering stage of this invention can suppress sudden noise, ensure the stability of the ADRC controller input signal, and indirectly improve the accuracy of the controller's disturbance prediction and compensation. Furthermore, the rate filtering stage suppresses sensor noise, and the ESO observes the total disturbance in real time. The two work together to ensure the stability of the control signal and the timeliness of disturbance compensation.

[0079] Key points of this application: 1. Adapted to the second-order ADRC controller structure of the Stewart platform (including ESO modules with specific topologies).

[0080] 2. Signal flow direction and model building method of ADRC control branch in Simulink.

[0081] 3. ADRC control logic porting scheme based on TwinCAT3PLC (including GVL parameter mapping and state machine scheduling).

[0082] 4. ADRC sub-degree-of-freedom parameter tuning strategy for a six-degree-of-freedom platform.

[0083] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method.

[0084] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0085] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0086] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0087] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0088] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0089] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0090] This application provides a novel self-disturbance wave compensation platform control method, system, electronic device, storage medium, and program product. Through a technical closed loop of "simulation-deployment-sensing-decision-conversion-execution-guarantee", it enables the upper platform of a six-degree-of-freedom parallel wave compensation platform to maintain a high-precision and high-stability horizontal operating posture in a random and highly disturbed marine environment.

[0091] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0092] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0093] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0094] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0095] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0096] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0097] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0098] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0099] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0100] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A novel control method for a self-disturbance rejection wave compensation platform, characterized in that, The method includes the following steps: A second-order active disturbance rejection control model is constructed in a simulation environment, and the control parameters of the second-order active disturbance rejection control model are tuned using a wave disturbance model; the second-order active disturbance rejection control model is used to estimate and compensate for the total disturbance of the system. The tuned second-order active disturbance rejection control model is deployed to the industrial control platform, and the control cycle and fault-safe logic are configured. The industrial control platform collects actual attitude data from the attitude sensor. The second-order active disturbance rejection control model is used to estimate the total system disturbance based on the actual attitude data, and the attitude compensation control quantity of the upper platform is calculated in combination with the total system disturbance. The attitude compensation control quantity is subjected to inverse kinematic solution to obtain the length adjustment commands of the six electric branches; After verifying the length adjustment command according to the fault-safe logic, the electric branch is driven to perform movement to keep the upper platform in a horizontal position.

2. The method according to claim 1, characterized in that, The step of constructing a second-order active disturbance rejection control model in a simulation environment and tuning the control parameters of the second-order active disturbance rejection control model using a wave disturbance model includes: In the simulation environment, a second-order active disturbance rejection control model is constructed, which includes a tracking differentiator, an extended state observer, and a nonlinear state error feedback module; the simulation environment is the Simulink simulation environment. A wave disturbance model is integrated into the simulation environment to simulate the six-degree-of-freedom motion of the ship hull under different sea conditions. The output of the wave disturbance model is used as the disturbance input of the second-order active disturbance rejection control model to form a closed-loop simulation test environment. The second-order active disturbance rejection control model is run in the closed-loop simulation test environment. The model parameters are iteratively tuned using the data on the attitude maintenance effect of the upper platform to obtain control parameters so that the upper platform maintains a horizontal attitude under wave disturbance. The model parameter tuning process includes setting the time constant, bandwidth, observer bandwidth, scaling parameter, differential parameter, and extended state observer gain parameter for the four degrees of freedom: roll, pitch, yaw, and heave.

3. The method according to claim 1, characterized in that, The step of deploying the tuned second-order active disturbance rejection control model to the industrial control platform and configuring the control cycle and fault-safe logic includes: The tuned second-order active disturbance rejection control model is deployed to the TwinCAT3 industrial control platform; In the TwinCAT3 industrial control platform, a sampling control cycle is configured for the second-order active disturbance rejection control model to match the EtherCAT communication cycle; In the TwinCAT3 industrial control platform, fault-safe logic for a six-degree-of-freedom parallel wave compensation platform is deployed. The fault-safe logic is deployed to trigger a safety action upon detection of any of the following abnormal conditions: The drive command or actual length of the electric chain exceeds the preset safety range. Communication with the sensor or driver is interrupted or times out; The collected posture data is invalid or exceeds the reasonableness threshold.

4. The method according to claim 1, characterized in that, The acquisition of actual attitude data from the attitude sensor via the industrial control platform includes: In the operating mode of the industrial control platform, based on the control cycle synchronized with the EtherCAT communication cycle, the actual attitude data measured by the attitude sensors installed on the six-degree-of-freedom parallel wave compensation platform is collected; the actual attitude data includes heave displacement, roll angle, pitch angle and bow angle.

5. The method according to claim 1, characterized in that, The step of using the second-order active disturbance rejection control model to estimate the total system disturbance based on the actual attitude data, and calculating the attitude compensation control quantity of the upper platform in conjunction with the total system disturbance, includes: The actual attitude data is input into the extended state observer of the second-order active disturbance rejection control model; The extended state observer is used to estimate the total disturbance of the system based on the actual attitude data and the control quantity output by the second-order active disturbance rejection control model, and simultaneously outputs attitude observations, angular velocity observations and total disturbance observations. The attitude compensation control quantity is calculated based on the error between the horizontal attitude reference command and the attitude observation value, the angular velocity observation value, and the total disturbance observation value. The total disturbance observation value is used to feedforward compensation for the total disturbance during the calculation process. The attitude compensation control quantity includes the desired heave displacement, desired roll angle, desired pitch angle, and desired yaw angle that the upper platform needs to achieve in the next control cycle.

6. The method according to claim 1, characterized in that, The inverse kinematics solution of the attitude compensation control quantity yields six length adjustment commands for the electric branch chains, including: Based on the attitude compensation control amount, determine the desired position and desired attitude of the upper platform; Based on the desired position and desired orientation of the upper platform, and combined with the geometric coordinates of the upper and lower platform hinge points in their respective platform coordinate systems, the theoretical lengths of the six electric branches connecting the corresponding upper and lower platform hinge points in the desired orientation are calculated using spatial geometric relationships or homogeneous coordinate transformation matrices. Based on the theoretical length and the current length of each of the electric branches, the length adjustment amount required for each electric branch is calculated, which serves as the length adjustment command for driving its servo motor.

7. The method according to claim 1, characterized in that, After verifying the length adjustment command according to the fault-safe logic, driving the electric branch chain to perform movement to keep the upper platform in a horizontal position includes: In the industrial control platform, the deployed fault-safe logic is invoked to verify the length adjustment command generated by the inverse kinematics solution; Once the verification is successful, the length adjustment command is sent to the corresponding six servo drives; Each of the servo drivers drives the servo motor according to the received length adjustment command, thereby causing the corresponding electric chain to extend or retract; Based on the coordinated movement of the six electric branch chains, the spatial orientation of the upper platform is adjusted to counteract wave disturbances transmitted from the hull, and the upper platform maintains a stable horizontal attitude relative to the sea level.

8. A novel self-disturbance-rejecting wave compensation platform control system, used to implement the method as described in any one of claims 1 to 7, characterized in that, The system includes: The first module is used to construct a second-order active disturbance rejection control model in a simulation environment and to tune the control parameters of the second-order active disturbance rejection control model using a wave disturbance model; the second-order active disturbance rejection control model is used to estimate and compensate for the total disturbance of the system. The second module is used to deploy the tuned second-order active disturbance rejection control model to the industrial control platform and configure the control cycle and fault-safe logic. The third module is used to collect actual attitude data from the attitude sensor through the industrial control platform. The fourth module is used to estimate the total system disturbance based on the actual attitude data using the second-order active disturbance rejection control model, and to calculate the attitude compensation control quantity of the upper platform in combination with the total system disturbance. The fifth module is used to perform inverse kinematics on the attitude compensation control quantity to obtain the length adjustment commands of the six electric branches; The sixth module is used to verify the length adjustment command according to the fault-safe logic, and then drive the electric branch to perform movement so that the upper platform maintains a horizontal posture.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

Images