Disturbance compensation control method for heave compensation winch

Abstract

The invention discloses an interference compensation control method for a heave compensation winch. The method comprises the following steps: based on a state space model of a heave compensation winch system comprising a heave compensation winch and a pump station, establishing a backstepping controller through a backstepping control method; establishing a parameter online estimation module of the hydraulic motor of the heave compensation winch, and inputting and processing the initial identification parameters of the hydraulic motor and the dynamic regression vector of the hydraulic cylinder to obtain the identification parameters of the hydraulic motor updated in real time; and inputting the identification parameters and the operation parameters of the heave compensation winch into a backstepping controller, outputting a valve core displacement control instruction of a proportional servo valve of a pump station after processing, and further realizing interference compensation control of the heave compensation winch by controlling the pump station. By means of the method, high-precision tracking and robust stability control over the heave compensation winch system can be still kept under the conditions that the model is uncertain and disturbance is strong, and support is provided for the underwater high-precision operation requirement.

Description

Technical Field

[0001] This invention relates to a winch control method, which relates to the field of underwater operation control, and specifically to a heave compensation winch interference compensation control method. Background Technology

[0002] In marine engineering operations, ships and floating platforms experience significant heave motion under wave action. This heave disturbance is directly transmitted to the winch through the hoisting system, causing problems such as vertical vibration, tension fluctuations, and uncontrollable position of the hoisted load. As marine equipment develops towards deeper waters and greater precision, the control accuracy and stability of heave-compensating winches have become key factors affecting the efficiency and safety of underwater operations.

[0003] Existing heave compensation technologies mainly include three types: passive, active, and hybrid. Passive technologies rely on springs or energy storage mechanisms to absorb some of the heave energy; they are simple in structure but have limited compensation capabilities. Active technologies use a hydraulic motor winch to counteract the heave effect, achieving higher compensation accuracy, but their control performance heavily depends on the accuracy of the system model. In actual operating conditions, hydraulic systems suffer from valve control nonlinearity, leakage, friction, and volume variations. The load tension also changes constantly with water depth, sea state, and operational tasks, resulting in significant uncertainties and strong disturbances in the system. Traditional control methods (such as PID control and feedforward compensation) generally suffer from large steady-state errors, slow response, or oscillations when facing these time-varying disturbances and parameter uncertainties, making it difficult to meet the requirements for high-precision heave compensation.

[0004] Furthermore, heave-compensated winches need to simultaneously consider multi-objective performance of position, velocity, and tension during actual operation. However, the dynamics of hydraulic actuators are significantly affected by pressure changes, flow coupling, and load disturbances, making it challenging to establish accurate models. Therefore, there is an urgent need for a control method that can maintain high-precision tracking and robust stability even under conditions of model uncertainty and strong disturbances. Summary of the Invention

[0005] To address the problems existing in the background art, the present invention provides a heave compensation winch interference compensation control method.

[0006] The technical solution adopted in this invention is:

[0007] The heave compensation winch disturbance compensation control method of the present invention includes:

[0008] Step 1) Based on the state-space model of the heave compensation winch system, which includes the heave compensation winch and the pump station, establish the disturbance compensation backstepping controller of the heave compensation winch system using the backstepping control method.

[0009] Step 2) Establish an online parameter estimation module for the hydraulic motor of the heave compensation winch. Input the initial identification parameters of the hydraulic motor and the dynamic regression vector of the hydraulic cylinder of the heave compensation winch into the online parameter estimation module. The online parameter estimation module outputs the identification parameters of the hydraulic motor that are updated in real time.

[0010] Step 3) Input the real-time updated identification parameters of the hydraulic motor and the operating parameters of the heave compensation winch output by the online parameter estimation module into the interference compensation backstep controller. After processing, the controller outputs the valve core displacement control command of the proportional servo valve of the pump station. The pump station is connected to the hydraulic motor through the proportional servo valve, and then the interference compensation control of the heave compensation winch is realized by controlling the pump station.

[0011] In step 1), the disturbance compensation backstep controller of the heave compensation winch system includes a first-step virtual control quantity part, a second-step virtual control quantity part, and a nonlinear flow mapping part. The real-time updated identification parameters of the hydraulic motor and the operating parameters of the heave compensation winch output by the online parameter estimation module are input into the first-step virtual control quantity part, which processes and outputs virtual control thrust. The virtual control thrust is input into the second-step virtual control quantity part, which processes and outputs virtual control flow. The virtual control flow is processed by the nonlinear flow mapping part and outputs the displacement control command of the proportional servo valve of the pump station.

[0012] The first step of the virtual control quantity of the interference compensation backstepping controller is as follows:

[0013]

[0014]

[0015]

[0016]

[0017]

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] in, For virtual control of thrust, These are the backstepping control parameters used for model compensation and system stability. Robust control law to eliminate interference observation errors; It is the coefficient of viscous friction; The angular velocity of the hydraulic motor output shaft of the heave compensation winch; This represents the amplitude of the Coulomb frictional torque. It is a smoothing factor; To compensate for the external load torque of the heave winch; This represents the rotational inertia of the hydraulic motor. The desired angular acceleration; and These are the preset first and second feedback gains, respectively; The actual trajectory angular velocity of the heave compensation winch and ideal trajectory angular velocity The error between them, i.e., sliding mode-like variables; For robust control rate Compensation parameters; Coulomb friction coefficient; For symbolic functions A smooth approximation; and These are the actual trajectory angles of the heave-compensating winch and their derivatives, respectively. Let be the reference trajectory for the heave motion of the heave compensation winch system, and let its higher-order derivatives exist and be bounded. Its derivative, and These are the ideal working rope length and the heave compensation rope length of the heave compensation winch, respectively. The actual trajectory angle of the heave compensation winch and ideal trajectory angle The error between them Its derivative; This is the linear feedback gain.

[0024] The real-time updated identification parameters of the hydraulic motor output by the online parameter estimation module include the moment of inertia of the hydraulic motor. viscous friction coefficient Coulomb friction coefficient The operating parameters of the heave compensation winch include the actual trajectory angle of the heave compensation winch. Actual trajectory angular velocity Ideal trajectory angular velocity and external load torque .

[0025] The first virtual control quantity of the interference compensation backstepping controller satisfies the following constraint:

[0026]

[0027] in, for The time-varying part.

[0028] The second step of the virtual control quantity of the interference compensation backstepping controller is as follows:

[0029]

[0030]

[0031]

[0032]

[0033]

[0034]

[0035] in, This refers to virtual control flow, specifically valve core displacement control. and These are the nonlinear model compensation amount and the nonlinear robust compensation amount, respectively. The pressure build-up term caused by valve-controlled flow; This is the pressure relief item caused by the input and output flow of the actuator rotation; This is the pressure differential attenuation term caused by internal and external leakage, etc. To compensate for the desired pressure difference between the two chambers of the hydraulic cylinder of the heave winch; The preset third feedback gain; and These are the actual pressure differences between the two chambers of the hydraulic cylinder of the heave compensation winch. and the desired pressure difference between the two chambers The differential pressure tracking error and its derivative; For virtual control of thrust; The displacement of the hydraulic motor for the heave compensation winch.

[0036] The nonlinear flow mapping part of the interference compensation backstepping controller is as follows:

[0037]

[0038] in, For the valve core displacement control command of the proportional servo valve of the pump station; Saturation constraint; , and These are virtual control flows and their upper and lower limits.

[0039] In step 2), the online parameter estimation module for the hydraulic motor of the heave compensation winch is as follows:

[0040]

[0041]

[0042]

[0043]

[0044] in, For the identification parameters of the hydraulic motor that are updated in real time, θ i Let be the identification parameters of the hydraulic motor at time i; Let k be the cost function; k is the current time step. Forgetting factor; Let be the linear regression model at time i; Let be the dynamic regression vector of the hydraulic cylinder of the heave compensation winch at time i; T is the transpose. and These are the angular velocity and angular acceleration of the hydraulic motor output shaft, respectively. It is a smoothing factor; This represents the rotational inertia of the hydraulic motor. The coefficient of viscous friction, Coulomb friction coefficient;

[0045] Using the recursive least squares (RLS) algorithm to recursively identify the identification parameters of the hydraulic motor can achieve online real-time identification of key dynamic parameters of the hydraulic system, ensuring that the controller still has good adaptive capabilities under the condition of model uncertainty changes.

[0046] The identification parameter θ of the hydraulic motor is updated as follows:

[0047]

[0048]

[0049]

[0050] in, and The identification parameters of the hydraulic motor are updated at time k and time k-1, respectively; K k Calculate the gain P for the uncertainty at time k. k and P k-1 The covariances at time k and time k-1 are respectively; y k For the linear regression model at time k; φ kis the dynamic regression vector of the hydraulic cylinder of the heave compensation winch at time k; v is the measurement noise weighting term.

[0051] The electronic device of the present invention includes: a memory and a processor coupled to each other, wherein the memory stores program data, and the processor invokes the program data to execute the method described above.

[0052] The present invention provides a computer-readable storage medium having program data stored thereon, which, when executed by a processor, implements the method described above.

[0053] This invention establishes a complete state-space model encompassing the coupling relationship between hydraulic drive characteristics and winch dynamics. To improve the control accuracy of heave-compensated winches in complex sea conditions, a DIARC (Direct / Indirect Adaptive Robust Control) method based on disturbance suppression is proposed. This method distinguishes and models two main types of disturbances encountered in actual operations: one is the external heave disturbance caused by the heave motion of the hull due to waves, and the other is the internal dynamic disturbance caused by hydraulic leakage, friction changes, and load fluctuations. By explicitly introducing nominal compensation terms related to heave motion, load torque, and hydraulic parameters into the control law, and combining this with an equivalent disturbance description of internal uncertainties and unmodeled dynamics, the influence of these disturbances on system performance is suppressed through a combination of feedforward compensation and robust feedback, thereby improving the motion tracking accuracy of the winch in dynamic sea conditions. Based on this, the present invention adopts the robust DIARC control strategy and designs a compensation controller with stability guarantee. It consists of a nominal dynamic compensation term, a feedforward compensation term based on disturbance equivalent modeling, and a robust stability term. Its output is directly used to drive the winch actuator to achieve fast and accurate control of the target position or tension.

[0054] The beneficial effects of this invention are:

[0055] The method of this invention can effectively alleviate the problem of reduced compensation accuracy caused by factors such as hull heave disturbance, cable tension changes and hydraulic system nonlinearity. It can maintain high-precision tracking and robust stability control of the heave compensation winch system even under uncertain model conditions and strong disturbances, thus providing support for the needs of high-precision underwater operations. Attached Figure Description

[0056] Figure 1 This is a flowchart of the method of the present invention;

[0057] Figure 2 This is a control framework diagram of the present invention;

[0058] Figure 3This is a graph showing the tracking results of the angle, angular velocity, and pressure curves of chamber A and chamber B under the DIARC control of this invention.

[0059] Figure 4 This is a schematic diagram of the angle tracking difference and angular velocity difference of the DIARC control of the present invention;

[0060] Figure 5 This is a comparison diagram of the position tracking effects of DIARC control and PID control in this invention. Detailed Implementation

[0061] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0062] In its practical implementation, this invention was verified through Matlab / Simulink simulation based on a mathematical model of a heave-compensating winch system. Regarding simulation parameter settings, the external load was assumed to be 500 kg. The simulation considered the disturbance caused by changes in the cable tension of the heave-compensating winch due to environmental variations, and simulations were performed for typical sea state inputs. The tracking performance and differential pressure regulation capability of the backstepping controller were analyzed. Furthermore, the proposed heave-compensating winch DIARC control method was compared with a traditional backstepping controller that does not employ online parameter identification and only uses fixed nominal parameters to verify the control effect of the proposed method under heave disturbance conditions.

[0063] The parameters of the constant pressure pump station selected in this invention are shown in Table 1 below:

[0064] Table 1

[0065] Maintain pressure Maximum pressure Maximum flow 25MPa 31.5MPa 66L / MIN

[0066] The proportional servo valve selected in this invention is the Hengli 4WRA(E) type direct-acting proportional directional valve, and its parameters are shown in Table 2 below:

[0067] Table 2

[0068] Specification Maximum pressure Maximum flow 6 / 10 31.5MPa 75L / min

[0069] The parameters of the winch support platform selected in this invention are shown in Table 3 below:

[0070] Table 3

[0071] Fixed pulley off the ground pulley bore pulley diameter Pulley corner 998mm 40mm 200mm 66°

[0072] The parameters of the heave compensation winch selected in this invention are shown in Table 4 below:

[0073] Table 4

[0074] model pull Rope speed Work pressure Oil supply flow ST08-10 10KN 0-45M / MIN 11MPa 56L / min wire rope diameter number of floors Rope capacity Motor model Reduction ratio 8mm 1 10M BMR-125 5.23

[0075] like Figure 1 and Figure 2 As shown, the heave compensation winch interference compensation control method of the present invention is as follows:

[0076] First, based on the state-space model of the heave compensation winch system, which includes a heave compensation winch and a pumping station, an disturbance compensation backstepping controller for the heave compensation winch system is established using the backstepping control method.

[0077] When establishing the state-space equations for the heave-compensating winch system, the dynamic equations of the hydraulic motor are first established as follows:

[0078]

[0079] in, This is the sum of the rotational inertia of the hydraulic motor rotor due to the inertial load on the motor shaft; and These are the angular velocity and angular acceleration of the hydraulic motor output shaft, respectively. The displacement (m) of the hydraulic motor 3 / rad), which is the volume of oil discharged or drawn in per unit rotation angle, reflecting the proportionality coefficient of pressure difference converted into torque; and These refer to the pressures at the high-pressure and low-pressure ports of the hydraulic motor, respectively. is the coefficient of viscous friction, which characterizes the internal resistance torque that is proportional to the angular velocity; is the Coulomb friction coefficient, which characterizes the magnitude of dry friction torque independent of velocity; For symbolic functions The smooth approximation is used to avoid discontinuities in numerical simulations; The external load torque is the resistance torque on the motor shaft, calculated from the wire rope tension, drum radius, and external damping of the heave-compensating winch. This is used to model disturbance terms, encompassing factors that are difficult to express mathematically accurately.

[0080] Then, the flow-pressure equation for the hydraulic motor is established as follows:

[0081]

[0082] in, and These are the derivatives of the pressures at the high-pressure and low-pressure ports of the hydraulic motor, respectively. It is the equivalent bulk modulus of hydraulic oil, reflecting the compressibility of the oil; The equivalent volume of the high and low pressure chambers and their pipelines is given. Due to the symmetry of the hydraulic motor, the high pressure end... and low voltage side Similarly, constants are used to express the macroscopic equivalent constant volume on the high-pressure side and the constant volume on the low-pressure side; and These are the flow rates entering the high-pressure chamber and the low-pressure chamber, respectively. The total leakage coefficient represents the characteristics of oil leakage between cavities. and The total error in modeling leakage from cavity A to cavity B and from cavity B to cavity A is respectively, covering the high-frequency dynamics of systems that cannot be modeled.

[0083] Subtracting the two equations, we get:

[0084]

[0085] in, and These are the pressure difference and its derivative in chambers A and B of the hydraulic cylinder of the heave compensation winch, respectively. and These represent the pressure difference between the inlet and outlet of the hydraulic motor and its rate of change of load pressure difference, respectively. The difference between the flow rates entering the high-pressure chamber and the low-pressure chamber represents the net flow rate supplied by the proportional servo valve to the high-pressure port of the hydraulic motor of the heave compensation winch, and is the input variable of the system. The total error is modeled for leakage, covering high-frequency dynamics of systems that cannot be modeled.

[0086] The net flow rate supplied by the proportional servo valve to the high-pressure port of the hydraulic motor of the heave compensation winch is as follows:

[0087]

[0088] in, The sensitivity of the valve core displacement of the proportional servo valve in the pumping station to the flow rate is expressed as the amount of flow rate change caused by each 1m movement of the valve core. This refers to the valve core displacement of the proportional servo valve in the pump station. This describes the effect of the pressure difference across the valve port on the flow rate.

[0089] Combining the above equations, we can obtain the following state-space equations:

[0090]

[0091] Based on the dynamic model of the valve-controlled hydraulic motor, the dynamic equations of the system can be written as follows:

[0092]

[0093]

[0094] in, and These are the angles of the heave compensation winch and their derivatives. and These are the angular velocities and derivatives of the heave-compensating winch, respectively. This represents the rotational inertia of the hydraulic motor. This represents the amplitude of the Coulomb frictional torque. It is a smoothing factor; The pressure build-up term caused by valve-controlled flow; This is the pressure relief item caused by the input and output flow of the actuator rotation; This is the pressure differential attenuation term caused by internal and external leakage, etc.

[0095] The final state-space model of the heave compensation winch system is as follows:

[0096]

[0097] This invention constructs a disturbance-compensated backstepping controller based on the backstepping method, based on a system dynamics model, to achieve high-precision tracking of the angular displacement of a valve-controlled hydraulic motor. The method decomposes the mechanical and hydraulic dynamics step-by-step, and obtains the final valve core displacement command through virtual control quantities and error feedback design, achieving stable control of pressure difference and angular velocity. The disturbance-compensated backstepping controller of the heave compensation winch system includes a first-step virtual control quantity part, a second-step virtual control quantity part, and a nonlinear flow mapping part. The real-time updated identification parameters of the hydraulic motor output from the online parameter estimation module and the operating parameters of the heave compensation winch are input into the first-step virtual control quantity part, which processes and outputs a virtual control thrust. The virtual control thrust is input into the second-step virtual control quantity part, which processes and outputs a virtual control flow rate. The virtual control flow rate is then processed by the nonlinear flow mapping part and output as the displacement control command for the proportional servo valve of the pump station.

[0098] The first step of the virtual control quantity of the disturbance compensation backstepping controller is as follows:

[0099]

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106]

[0107]

[0108]

[0109] in, For virtual control of thrust, These are the backstepping control parameters used for model compensation and system stability. Robust control law to eliminate interference observation errors; It is the coefficient of viscous friction; The angular velocity of the hydraulic motor output shaft of the heave compensation winch; This represents the amplitude of the Coulomb frictional torque. It is a smoothing factor; To compensate for the external load torque of the heave winch; This represents the rotational inertia of the hydraulic motor. The desired angular acceleration; and These are the preset first and second feedback gains, respectively; The actual trajectory angular velocity of the heave compensation winch and ideal trajectory angular velocity The error between them, i.e., sliding mode-like variables; For robust control rate Compensation parameters; Coulomb friction coefficient; For symbolic functions A smooth approximation; and These are the actual trajectory angles of the heave-compensating winch and their derivatives, respectively. Let be the reference trajectory for the heave motion of the heave compensation winch system, and let its higher-order derivatives exist and be bounded. Its derivative, and These are the ideal working rope length and the heave compensation rope length of the heave compensation winch, respectively. The actual trajectory angle of the heave compensation winch and ideal trajectory angle The error between them Its derivative; This is the linear feedback gain.

[0110] The real-time updated identification parameters of the hydraulic motor output by the online parameter estimation module include the moment of inertia of the hydraulic motor. viscous friction coefficient Coulomb friction coefficient The operating parameters of the heave compensation winch include the actual trajectory angle of the heave compensation winch. Actual trajectory angular velocity Ideal trajectory angular velocity and external load torque .

[0111] In order to Approaching zero, based on a state-space model, an disturbance-compensated backstepping controller is designed to achieve the ideal output force. As the control input for trajectory tracking, it enables the system control error to converge.

[0112] The first virtual control quantity of the disturbance compensation backstepping controller satisfies the following constraint:

[0113]

[0114] in, for The time-varying part.

[0115] The second step of the virtual control quantity part of the disturbance compensation backstepping controller is as follows:

[0116]

[0117]

[0118]

[0119]

[0120]

[0121]

[0122] in, This refers to virtual control flow, specifically valve core displacement control. and These are the nonlinear model compensation amount and the nonlinear robust compensation amount, respectively. The pressure build-up term caused by valve-controlled flow; This is the pressure relief item caused by the input and output flow of the actuator rotation; This is the pressure differential attenuation term caused by internal and external leakage, etc. To compensate for the desired pressure difference between the two chambers of the hydraulic cylinder of the heave winch; The preset third feedback gain; and These are the actual pressure differences between the two chambers of the hydraulic cylinder of the heave compensation winch. and the desired pressure difference between the two chambers The differential pressure tracking error and its derivative; For virtual control of thrust; The displacement of the hydraulic motor for the heave compensation winch.

[0123] In terms of controller parameter settings, the feedback gain of this invention is selected as: k1=0.2, k2=0.02, k3=0.005.

[0124] The nonlinear flow mapping part of the interference compensation backstepping controller is as follows:

[0125]

[0126] in, For the valve core displacement control command of the proportional servo valve of the pump station; Saturation constraint; , and These are virtual control flows and their upper and lower limits.

[0127] To ensure that the actuator meets physical constraints, saturation constraints must be applied to the control input.

[0128] Then, an online parameter estimation module for the hydraulic motor of the heave compensation winch is established, as follows:

[0129]

[0130]

[0131]

[0132]

[0133] in, For the identification parameters of the hydraulic motor that are updated in real time, θ i Let be the identification parameters of the hydraulic motor at time i; Let k be the cost function; k is the current time step. The forgetting factor is 0 < λ ≤ 1. When =1, there is no forgetting; Let be the linear regression model at time i; Let be the dynamic regression vector of the hydraulic cylinder of the heave compensation winch at time i; T is the transpose. and These are the angular velocity and angular acceleration of the hydraulic motor output shaft, respectively. It is a smoothing factor; This represents the rotational inertia of the hydraulic motor. The coefficient of viscous friction, is the Coulomb friction coefficient.

[0134] Set the cost function at time k to the weighted sum of squared errors, such that at time k, using the data from times 1, 2, ..., k, the identification parameter θ is estimated to minimize the weighted sum of squared errors.

[0135] Using the recursive least squares (RLS) algorithm to recursively identify the identification parameters of the hydraulic motor can achieve online real-time identification of key dynamic parameters of the hydraulic system, ensuring that the controller still has good adaptive capabilities under the condition of model uncertainty changes.

[0136] To obtain the key dynamic parameters of the heave compensation winch system under actual operating conditions and improve the adaptive capability of the subsequent controller to system uncertainties, this embodiment proposes an online parameter estimation module consisting of offline parameter estimation (initial value determination) and online parameter estimation (RLS real-time update). The overall idea is as follows: first, a reasonable initial range or initial values ​​of parameters are given based on the system's dynamic model; then, during equipment operation, the parameters are updated online using a recursive least squares algorithm, enabling the estimated values ​​to track changes in system characteristics in real time. An initial range value is needed to make the online parameter estimation module more accurate and stable.

[0137] First, the torque balance equation of the hydraulic motor is expressed as:

[0138]

[0139] then:

[0140]

[0141] in, It is a linear regression model.

[0142] Because the sign function is non-differentiable, substitution is possible. The above dynamic relationships are then organized to obtain the identification parameter vector θ. The target for identification is the regression vector in the fluid dynamics of the hydraulic cylinder (or actuator). This yields the standard linear regression model. , .

[0143] To obtain the friction coefficient of the hydraulic cylinder, frictional force data at different operating speeds were measured. Using the MATLAB optimization toolbox, curve fitting was employed to identify the friction model parameters. By fitting the linear phase of the frictional force according to the frictional force modeling formula, the initial parameter values ​​of the hydraulic cylinder were obtained. 15.6 kN.m 2 , The value is 26577.404 N (m / s). The value is 363.643 N. In terms of the order of magnitude of friction, compared with land-based hydraulic cylinders, underwater cylinders generally have a larger preload due to the need for bidirectional sealing, resulting in significantly greater friction.

[0144] The identification parameter θ of the hydraulic motor is updated as follows:

[0145]

[0146]

[0147]

[0148] in, and The identification parameters of the hydraulic motor are updated at time k and time k-1, respectively; K k Calculate the gain P for the uncertainty at time k. k and P k-1 The covariances at time k and time k-1 are respectively; y k For the linear regression model at time k; φ k is the dynamic regression vector of the hydraulic cylinder of the heave compensation winch at time k; v is the measurement noise weight term, which is set to 1.

[0149] The overall result is the old parameters plus gain multiplied by the prediction error. Based on this, the system is iteratively updated to obtain the desired parameters.

[0150] The initial identification parameters of the hydraulic motor and the dynamic regression vector of the hydraulic cylinder of the heave compensation winch are input into the online parameter estimation module, which outputs the identification parameters of the hydraulic motor that are updated in real time.

[0151] The specific simulation parameters of the heave compensation winch of the present invention are shown in Table 5 below:

[0152] Table 5

[0153] Simulation parameters Parameter value Simulation parameters Parameter value <![CDATA[J m0 ]]> <![CDATA[15.6kN.m 2 ]]> <![CDATA[K q ]]> <![CDATA[1×10 -4 m 3 / m]]> <![CDATA[B m0 ]]> 26577.404 N / (N·m·s / rad) <![CDATA[K c ]]> <![CDATA[1×10 -8 m 3 / m]]> VH <![CDATA[1×10 -3 m 3 ]]> <![CDATA[D m ]]> <![CDATA[1.098×10 -4 m 3 / rad]]> VL <![CDATA[1×10 -3 m 3 ]]> esp <![CDATA[1×10 -1 ]]> <![CDATA[C t ]]> <![CDATA[7×10 -11 m 3 ]]> <![CDATA[T c0 ]]> 363.643 NM

[0154] Among them, K q K is the flow-displacement coefficient of the proportional servo valve. c VH is the leakage coefficient of the proportional servo valve; VL is the high-pressure chamber volume; VH is the low-pressure chamber volume; esp is the friction term smoothing parameter; C t This represents the leakage coefficient of the hydraulic motor.

[0155] Finally, the real-time updated identification parameters of the hydraulic motor and the operating parameters of the heave compensation winch, output by the online parameter estimation module, are input into the interference compensation backstep controller. After processing, the controller outputs the valve core displacement control command of the proportional servo valve of the pump station. The pump station is connected to the hydraulic motor through the proportional servo valve, thereby realizing the interference compensation control of the heave compensation winch by controlling the pump station.

[0156] like Figure 3As shown, based on the DIARC angle, angular velocity, and A-cavity / B-cavity tracking results, it can be seen that when the desired trajectory changes periodically, the system output angle can quickly and accurately track the reference angle curve with small steady-state error and stable dynamic response. The angular velocity curve is consistent with the desired change trend, without obvious oscillations or divergence. Simultaneously, the pressures in chambers A and B can be reasonably adjusted according to the system's motion state during the control process, with smooth pressure changes and no sudden changes or abnormal fluctuations. This indicates that the proposed DIARC control method can still ensure the system's stability and robustness even under parameter uncertainties and external disturbances.

[0157] like Figure 4 As shown, the results of the angle tracking error and angular velocity error indicate that the overall amplitude of the angle tracking error is small, mainly distributed near zero, and does not show a continuous increasing trend, indicating that the system has good steady-state tracking performance. Meanwhile, the angular velocity tracking error remains within a small range during system operation, only experiencing brief fluctuations when the reference trajectory changes rapidly, and it can quickly decay and recover stability without causing system oscillations or instability.

[0158] like Figure 5 The figure shows the comparison results of position tracking using PID and DIARC. It can be seen that, under the same point-to-point reference trajectory conditions, the heave compensation winch system using the traditional PID control method exhibits certain tracking lag and steady-state error during position tracking. In contrast, the disturbance compensation control method based on DIARC proposed in this invention can effectively suppress the influence of uncertainties such as external load disturbances and internal pressure fluctuations in the hydraulic system during the operation of the heave compensation winch system, enabling the winch position trajectory to track the reference curve more accurately, resulting in a smoother overall dynamic response and a significantly reduced steady-state error. Furthermore, the variation in position tracking error shows that the disturbance compensation control method based on DIARC maintains a small tracking error throughout the entire motion process, with fast error convergence and no obvious oscillations, demonstrating good robustness and stability.

[0159] The simulation results show that the heave compensation winch disturbance compensation control method proposed in this invention has good control performance under complex working conditions. It can not only effectively improve the position tracking accuracy of the winch system, but also enhance the system's adaptability to time-varying external loads and uncertainties in hydraulic parameters, providing a strong guarantee for the stable operation of the heave compensation winch in complex working conditions.

[0160] This invention first addresses the operational characteristics of heave-compensated winch systems in marine environments by constructing a state-space model of the system, including the heave-compensated winch and pump station. Compared to conventional winch systems, heave-compensated winches need to handle periodic disturbances caused by ship heave and hydraulic system pressure fluctuations. Therefore, the model must simultaneously describe: winch turntable dynamics, hydraulic motor two-chamber pressure and flow equations, and the dynamic relationship between the winch and cable tension. Furthermore, the equivalent disturbance exerted on the system by sea state heave is incorporated into the model. The resulting state-space equations fully reflect the dynamic coupling relationship between the hydraulic system, mechanical system, and external environment. Then, an online estimation module for hydraulic motor dynamic parameters based on recursive least squares (RLS) is established. Utilizing real-time measurement signals from the hydraulic motor, including estimated values ​​of angular velocity and angular acceleration, and observations such as high and low pressure chambers, a regression model is constructed between the hydraulic motor output torque and the winch mechanical dynamics. Based on this model, the key dynamic parameters of the system, including moment of inertia, viscous damping coefficient, and Coulomb friction coefficient, are estimated online using the recursive least squares (RLS) algorithm. The online estimation module can reflect the dynamic characteristics changes caused by hydraulic system leakage, friction variations, and load changes, providing the controller with real-time updated model parameters. This ensures that the nominal compensation term in the control law continuously matches the actual system, thereby improving control accuracy and robustness. Finally, based on the state-space model and backstepping control strategy, a disturbance-compensated backstepping controller is designed to ensure the overall stability of the control system. The observed disturbance values ​​are fed forward into the controller for disturbance compensation, enabling precise control of the heave-compensated winch under disturbances.

[0161] Compared with existing technologies, this invention establishes a state-space equation for heave compensation winches and designs online parameter estimation based on this equation. This is used to observe unknown external environmental forces and pressure disturbances of the unmeasurable seawater pressure compensator. The stability of the overall system is ensured by a backstepping controller, and the position control accuracy of the underwater electro-hydraulic actuator is improved by feedforward compensation of the disturbance observer's observation value, thus providing a guarantee for underwater operations.

[0162] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A heave compensation winch disturbance compensation control method, characterized in that, include: Step 1) Based on the state-space model of the heave compensation winch system, which includes the heave compensation winch and the pump station, establish the disturbance compensation backstepping controller of the heave compensation winch system using the backstepping control method. Step 2) Establish an online parameter estimation module for the hydraulic motor of the heave compensation winch. Input the initial identification parameters of the hydraulic motor and the dynamic regression vector of the hydraulic cylinder of the heave compensation winch into the online parameter estimation module. The online parameter estimation module outputs the identification parameters of the hydraulic motor that are updated in real time. Step 3) Input the real-time updated identification parameters of the hydraulic motor and the operating parameters of the heave compensation winch output by the online parameter estimation module into the disturbance compensation backstep controller. After processing, output the valve core displacement control command of the proportional servo valve of the pump station, and then realize the disturbance compensation control of the heave compensation winch by controlling the pump station.

2. The heave compensation winch interference compensation control method according to claim 1, characterized in that: In step 1), the interference compensation backstep controller of the heave compensation winch system includes a first-step virtual control quantity part, a second-step virtual control quantity part, and a nonlinear flow mapping part. The real-time updated identification parameters of the hydraulic motor and the operating parameters of the heave compensation winch output by the online parameter estimation module are input into the first-step virtual control quantity part, processed and output as virtual control thrust. The virtual control thrust is input into the second-step virtual control quantity part, processed and output as virtual control flow. The virtual control flow is processed by the nonlinear flow mapping part and output as displacement control command for the proportional servo valve of the pump station.

3. The heave compensation winch interference compensation control method according to claim 2, characterized in that: The first step of the virtual control quantity of the interference compensation backstepping controller is as follows: in, For virtual control of thrust, These are the backstepping control parameters. For robust control law; It is the coefficient of viscous friction; The angular velocity of the hydraulic motor output shaft of the heave compensation winch; This represents the amplitude of the Coulomb frictional torque. It is a smoothing factor; To compensate for the external load torque of the heave winch; This represents the rotational inertia of the hydraulic motor. The desired angular acceleration; and These are the preset first and second feedback gains, respectively; The actual trajectory angular velocity of the heave compensation winch and ideal trajectory angular velocity The error between; For robust control rate Compensation parameters; Coulomb friction coefficient; For symbolic functions A smooth approximation; and These are the actual trajectory angles of the heave-compensating winch and their derivatives, respectively. The reference trajectory for the heave motion of the heave compensation winch system. and These are the ideal working rope length and the heave compensation rope length of the heave compensation winch, respectively. The actual trajectory angle of the heave compensation winch and ideal trajectory angle The error between; The real-time updated identification parameters of the hydraulic motor output by the online parameter estimation module include the moment of inertia of the hydraulic motor. viscous friction coefficient Coulomb friction coefficient The operating parameters of the heave compensation winch include the actual trajectory angle of the heave compensation winch. Actual trajectory angular velocity Ideal trajectory angular velocity and external load torque .

4. The heave compensation winch interference compensation control method according to claim 3, characterized in that: The first virtual control quantity of the interference compensation backstepping controller satisfies the following constraint: in, This is the time-varying part.

5. The heave compensation winch interference compensation control method according to claim 2, characterized in that: The second step of the virtual control quantity of the interference compensation backstepping controller is as follows: in, To control traffic virtually, and These are the nonlinear model compensation amount and the nonlinear robust compensation amount, respectively. To build pressure items; This is a pressure relief item; This is the differential pressure attenuation term; To compensate for the desired pressure difference between the two chambers of the hydraulic cylinder of the heave winch; The preset third feedback gain; and These are the actual pressure differences between the two chambers of the hydraulic cylinder of the heave compensation winch. and the desired pressure difference between the two chambers The differential pressure tracking error and its derivative; For virtual control of thrust; The displacement of the hydraulic motor for the heave compensation winch.

6. The heave compensation winch interference compensation control method according to claim 2, characterized in that: The nonlinear flow mapping part of the interference compensation backstepping controller is as follows: in, For the valve core displacement control command of the proportional servo valve of the pump station; Saturation constraint; , and These are virtual control flows and their upper and lower limits.

7. The heave compensation winch interference compensation control method according to claim 1, characterized in that: In step 2), the online parameter estimation module for the hydraulic motor of the heave compensation winch is as follows: in, For the identification parameters of the hydraulic motor that are updated in real time, θ i Let be the identification parameters of the hydraulic motor at time i; Let k be the cost function; k is the current time step. Forgetting factor; Let be the linear regression model at time i; Let be the dynamic regression vector of the hydraulic cylinder of the heave compensation winch at time i; T is the transpose. and These are the angular velocity and angular acceleration of the hydraulic motor output shaft, respectively. It is a smoothing factor; This represents the rotational inertia of the hydraulic motor. The coefficient of viscous friction is... Coulomb friction coefficient; The recursive least squares (RLS) algorithm is used to recursively identify the identification parameters of the hydraulic motor.

8. The heave compensation winch interference compensation control method according to claim 7, characterized in that: The identification parameter θ of the hydraulic motor is updated as follows: in, and The identification parameters of the hydraulic motor are updated at time k and time k-1, respectively; K k Calculate the gain P for the uncertainty at time k. k and P k-1 The covariances at time k and time k-1 are respectively; y k For the linear regression model at time k; φ k is the dynamic regression vector of the hydraulic cylinder of the heave compensation winch at time k; v is the measurement noise weighting term.

9. An electronic device, characterized in that, include: A memory and a processor are coupled to each other, wherein the memory stores program data, and the processor invokes the program data to perform the method as described in any one of claims 1-8.

10. A computer-readable storage medium storing program data thereon, characterized in that, When the program data is executed by the processor, it implements the method as described in any one of claims 1-8.

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