Flow smoothness control method for slurry lifting pump set under multiple working conditions

Abstract

The invention discloses a flow smoothness control method for a slurry lifting pump set under multiple working conditions, and relates to the field of flow control, and the method comprises the steps: obtaining a target flow, an actual flow, boundary layer data, a switching gain of a system and an input effect gain coefficient of the system; determining an error between the target flow and the actual flow, and taking the error as a sliding mode variable; determining a dynamic characteristic action gain coefficient of the system based on the actual flow; determining an equivalent control gain based on the input action gain coefficient of the system and the dynamic characteristic action gain coefficient of the system; determining a switching control gain based on the sliding mode variable, the switching gain and the boundary layer data; determining a control input gain based on the equivalent control gain and the switching control gain; and a control adjusting signal is generated based on the control input gain, and control over the flow of the slurry lifting pump set is completed based on the control adjusting signal. The flow of the slurry lifting pump set can be smoothly controlled, and the stability of the slurry lifting pump set is improved.

Description

Technical Field

[0001] The present application relates to the field of flow control, and in particular to a method for controlling flow smoothness of a mud lift pump group under multiple working conditions. Background Art

[0002] With the continuous growth of global energy demand, the development of deep-sea oil and gas resources has become a focus of attention for all countries. As an important means of marine exploration and development, deep-water drilling technology is facing increasingly severe technical challenges, especially in deep-sea areas with increasing water depth. Traditional drilling technology can no longer meet the operational needs in complex environments. In order to overcome these difficulties, deep-sea riserless drilling technology has gradually attracted attention as an innovative solution. Among them, the mud lifting system, as one of the key technologies, is responsible for returning the seabed mud to the platform through pipelines.

[0003] The mud lifting system usually involves multiple components to ensure that the mud can be efficiently and safely transported from one place to another. Among these components, the flow control system (such as the pump system) plays a vital role. In the prior art, when the pump system faces external disturbances, dynamic load changes and nonlinear characteristics of the system, the flow will be unstable, which further leads to the problem of poor system stability. Summary of the invention

[0004] The purpose of the present application is to provide a method for controlling the flow smoothness of a mud lift pump group under multiple operating conditions, which can smoothly control the flow of the mud lift pump group under multiple operating conditions, thereby improving the stability of the mud lift pump group.

[0005] To achieve the above objectives, this application provides the following solutions:

[0006] In a first aspect, the present application provides a method for controlling flow smoothness of a mud lift pump group under multiple working conditions, comprising:

[0007] Acquire the target flow rate and current data of the mud lift pump group; the current data of the mud lift pump group includes the actual flow rate, gain data and boundary layer data; the gain data includes the switching gain of the mud lift pump group and the input action gain coefficient of the mud lift pump group;

[0008] Determine the error between the target flow rate and the actual flow rate, and use the error as a sliding mode variable;

[0009] Determining whether the sliding mode variable reaches a set threshold;

[0010] When the sliding mode variable reaches the set threshold, no processing is performed;

[0011] When the sliding mode variable does not reach the set threshold, determining a dynamic characteristic action gain coefficient of the mud lift pump group based on the actual flow rate;

[0012] Determining an equivalent control gain based on an input action gain coefficient of the mud lift pump group and a dynamic characteristic action gain coefficient of the mud lift pump group;

[0013] determining a switching control gain based on the sliding mode variable, the switching gain and the boundary layer data;

[0014] determining a control input gain based on the equivalent control gain and the switching control gain;

[0015] A control adjustment signal is generated based on the control input gain, and the flow rate of the mud lift pump group under multiple working conditions is controlled based on the control adjustment signal.

[0016] Optionally, the sliding mode variable is expressed as:

[0017] s = c*(q_ref-q);

[0018] Among them, s is the sliding mode variable, q_ref is the target flow, q is the actual flow, and c is a constant.

[0019] Optionally, the dynamic characteristic action gain coefficient of the mud lift pump group is expressed as:

[0020] f_q=0.5*q;

[0021] Among them, f_q is the dynamic characteristic gain coefficient of the mud lift pump group, and q is the actual flow rate.

[0022] Optionally, the equivalent control gain is expressed as:

[0023] u_eq = -f_q / g_q;

[0024] Among them, u_eq is the equivalent control gain, g_q is the input action gain coefficient of the mud lift pump group, and f_q is the dynamic characteristic action gain coefficient of the mud lift pump group.

[0025] Optionally, the switching control gain is expressed as:

[0026] u_sw = -k*sat(s / epsilon);

[0027] Among them, u_sw is the switching control gain, k is the switching gain of the mud lift pump group, epsilon is the boundary layer data, sat() is the saturation function, and s is the sliding mode variable.

[0028] Optionally, the control input gain is expressed as:

[0029] u=u_eq+u_sw;

[0030] Among them, u is the control input gain, u_eq is the equivalent control gain, and u_sw is the switching control gain.

[0031] According to the specific embodiments provided in this application, this application has the following technical effects:

[0032] The present application provides a method for controlling the flow smoothness of a mud lift pump group under multiple working conditions. By acquiring the target flow and the current data of the mud lift pump group, the equivalent control gain and the switching control gain are further determined, thereby determining the control input gain. A control adjustment signal is generated according to the control input gain. The flow of the mud lift pump group under multiple working conditions is controlled according to the control adjustment signal. This solves the problem of slow response speed and poor stability of the mud lift pump group caused by large flow fluctuations in the prior art, realizes the control of the flow of the mud lift pump group, ensures that the flow value of the mud lift pump group can quickly reach the target flow value, and further improves the stability of the mud lift pump group. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 A flow chart of a method for controlling flow smoothness of a mud lift pump group under multiple working conditions provided in one embodiment of the present application;

[0035] Figure 2 A schematic diagram of the relationship between rotation speed and flow rate provided in an embodiment of the present application;

[0036] Figure 3 A schematic diagram of the relationship between lift and flow provided in one embodiment of the present application;

[0037] Figure 4 A schematic diagram of a flow operation circuit provided in an embodiment of the present application;

[0038] Figure 5 A schematic diagram of a simulink model of a pump group provided in an embodiment of the present application;

[0039] Figure 6 A schematic diagram of a code flow provided for an embodiment of the present application;

[0040] Figure 7 It is a structural diagram of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0042] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0043] In an exemplary embodiment, Figure 1 As shown, a method for controlling flow smoothness of a mud lift pump group under multiple working conditions is provided, comprising the following steps 100 to 108. Among them:

[0044] Step 100, obtaining the target flow and current data of the mud lift pump group; the current data of the mud lift pump group includes the actual flow, gain data and boundary layer data; the gain data includes the switching gain of the mud lift pump group and the input action gain coefficient of the mud lift pump group.

[0045] Step 101, determine the error between the target flow and the actual flow, and use the error as a sliding mode variable. The sliding mode variable expression is:

[0046] s=c*(q_ref-q).

[0047] Among them, s is the sliding mode variable, q_ref is the target flow, q is the actual flow, and c is a constant.

[0048] Step 102: Determine whether the sliding mode variable reaches a set threshold.

[0049] Step 103: When the sliding mode variable reaches the set threshold, no processing is performed.

[0050] Step 104, when the sliding mode variable does not reach the set threshold, the dynamic characteristic effect gain coefficient of the mud lift pump group is determined based on the actual flow rate. The dynamic characteristic effect gain coefficient of the mud lift pump group is expressed as:

[0051] f_q=0.5*q.

[0052] Among them, f_q is the dynamic characteristic gain coefficient of the mud lift pump group.

[0053] Step 105, based on the input action gain coefficient of the mud lift pump group and the dynamic characteristic action gain coefficient of the mud lift pump group, an equivalent control gain is determined. The equivalent control gain expression is:

[0054] u_eq=-f_q / g_q.

[0055] Among them, u_eq is the equivalent control gain, and g_q is the input action gain coefficient of the mud lift pump group.

[0056] Step 106, based on the sliding mode variable, the switching gain and the boundary layer data, determine the switching control gain. The switching control gain expression is:

[0057] u_sw = -k*sat(s / epsilon).

[0058] Among them, u_sw is the switching control gain, k is the switching gain of the mud lift pump group, epsilon is the boundary layer data, and sat() is the saturation function.

[0059] Step 107, based on the equivalent control gain and the switching control gain, determine the control input gain. The control input gain expression is:

[0060] u=u_eq+u_sw。

[0061] Where u is the control input gain.

[0062] Step 108, generating a control adjustment signal based on the control input gain, and completing the control of the flow rate of the mud lift pump group based on the control adjustment signal.

[0063] By implementing the above steps 100 to 108 , the flow rate of the mud lift pump group under multiple working conditions can be smoothly controlled, thereby improving the stability of the mud lift pump group.

[0064] In another exemplary embodiment of the present application, the flow smoothness control method of the mud lift pump group under multiple working conditions provided by the present application is used to control the pump system as an example to further illustrate the effectiveness of the method provided by the present application. Based on this, the flow smoothness control process of the mud lift pump group under multiple working conditions includes:

[0065] First, the pump group model is built in the Simulink environment (Simulink platform), where the pump group model includes core components such as centrifugal pumps, ball valves, pipelines, and fluid property modules. By building the pump group model, the physical behavior, fluid characteristics, and dynamic response of the deep-sea mud lifting pump can be accurately simulated. The construction of the pump group model includes the following steps:

[0066] First, the pump module setting: The pump module in the Simulink environment (for example, a centrifugal pump module can be used) can accurately simulate the physical behavior of the pump, where the pump module includes the pump characteristic curve, efficiency curve and flow-head relationship. The pump module is parameterized using experimental data, and the pump parameters are set by the relationship between the pressure difference and the braking power and the pump delivery characteristics. The rated speed of the selected pump is 1800r / min, and the angular velocity is 188rad / s. The density of the seabed mud is affected by many factors. This embodiment assumes that the mud density is 1200kg / m 3 Based on the Fluent flow channel model, we can get Figure 2 and Figure 3 The discrete data of flow rate and head changing with speed when the pump is started is shown. Based on the discrete data of flow rate changing with speed, the relationship between flow rate and speed can be derived as: Q = 0.0976N-0.9728, where Q is the flow rate of the pump system and N is the speed of the pump.

[0067] Second, valve module setting: For example, in this embodiment, the valve module is a ball valve module in the Simulink environment. The ball valve module can accurately simulate the switching behavior and flow characteristics of the ball valve, especially the relationship between the opening change and the flow, which helps to accurately predict the fluid dynamic behavior of the pump system. Through the predefined ball valve module, users can quickly create and configure ball valve models without writing code from scratch or designing complex models. Users can adjust multiple parameters of the ball valve, such as switching time, maximum flow system, and valve characteristic curve to meet different simulation requirements. The ball valve module simulates the effect of the ball valve on the flow in the hydraulic network. Among them, the ball valve consists of a valve seat and a sphere, and the valve seat can be round, sharp or conical, etc. The connection ports of the ball valve are the inlet and outlet of the valve, respectively, and the displacement of the ball valve is set by the physical signal input. Positive displacement can increase the gap between the ball and the valve seat, allowing more liquid to flow.

[0068] Third, the pipe module setting: The pipe module in the Simulink environment represents the hydraulic pipe with a circular cross-section as a series of identical lumped parameter segments connected in series, making it possible to approximate the behavior of distributed parameter elements (such as long hydraulic pipes, etc.) in a lumped parameter simulator. The greater the number of segments, the higher the approximation of the lumped parameter model to the distributed parameter model. Considering the factors that affect the pipeline, such as friction loss, fluid inertia and compressibility, each segment is composed of resistance tube, fluid inertia and constant volume chamber building blocks.

[0069] In order to further simplify the model, the pipeline module can simulate not only the pipeline itself, but also the local resistance associated with the pipeline (such as elbows, pipe fittings, inlet and outlet losses, etc.). Pipeline connection port A and port B are hydraulic protection ports respectively. When the fluid flows from the pipeline connection port A to port B, the flow rate is positive and the pressure loss is p = pA-pB, where pA is the pressure at port A and pB is the pressure at port B. Set the rated flow rate of the pipeline to 2000L / min and the cross-sectional area to 15688mm 2 .

[0070] Fourth, fluid property module settings: The fluid property module in the Simulink environment specifies the fluid properties for all components in a specific circuit. If there is no hydraulic fluid block in the circuit, the properties of the custom hydraulic fluid block will be used by default. This application uses mud as the fluid, where the density of the mud is 1200kg / m 3 , flow rate is 2000L / min, flow velocity is 1.88628m / s, and viscosity is 0.12681Pa·s.

[0071] Through the above steps, a pump system model including key components such as pump module, pipeline module and valve module can be constructed. On this basis, by setting the initial conditions and boundary conditions of the pump system model, the dynamic behavior of flow under different working conditions can be simulated. Among them, the flow operation loop of the pump system model is as follows: Figure 4 As shown. Based on Figure 4 The structure of the pump system model is shown, and the control process under different working conditions can be described as:

[0072] When a single pump is running, pump A is running, pump B is stopped, valves 1# and 5# are opened, and valves 2#, 3# and 4# are closed. When a single pump is running and double pumps are running in parallel, valves 1# and 5# are opened first, valve 4# is closed, and valves 2# and 3# are opened during the operation. When a single pump is running and double pumps are running in series, valves 1# and 5# are opened first, valve 2# is closed, and valves 1# and 3# are closed during the operation, and valves 3# and 4# are opened. Under each working condition, the flow rate is collected in real time by setting the flow meter module, and the real-time flow rate simulation is performed in combination with the pump system model. By observing the flow fluctuations of the pump system model under different working conditions, its stability and response speed are analyzed. For example, when the actual working condition is switched, the pump system often produces large flow fluctuations, which seriously affects the stability of the pump system and causes the pump group to be unable to operate stably. Therefore, in the process of drastic flow changes, it is necessary to adjust the input of the pump system in time to ensure stable flow.

[0073] Second, further improvement on the above pump system model can be obtained as follows Figure 5The improved system model shown in the figure can be mainly used to simulate the flow control and working condition switching of deep-sea mud lifting process. Among them, the improved system model mainly includes components such as pumps, flow meters, pressure gauges, valves, mud tanks, controllers and sensors, and each component is connected to each other through pipelines to form a closed-loop system. Among them, pump A is connected to a speed sensor, and the speed of pump A is controlled by an input module. The controlled speed signal is input to pump A. The fluid output by pump A passes through flow meter 1 to realize flow monitoring. At the same time, it is connected to pressure gauge 1 to measure the pressure at the outlet of pump A, and further adjusts the flow through valve 1 and valve 5 and enters the main pipeline. Pump B is located in the center of the improved system model, parallel to pump A. When running, the output fluid is monitored by flow meter 2, and pressure gauges 3 and pressure gauges 4 are connected to measure the corresponding pressure values. The control input of pump B also adjusts its operating state. Multiple valves are set in the improved system model, and the fluid flow path and system working condition are adjusted by opening and closing different valves. The pipeline monitors the total flow through flow meter 3. The mud tank of the system is located in the middle of the model to simulate the storage and supply process of mud. like Figure 5 The oscilloscope is used to measure the voltage and current of various parts in the model to evaluate the electrical performance of the system. The digital display is used to display the operating status and parameters of the system, including flow, pressure, power, etc.

[0074] The corresponding system status when the working condition is switched is as follows: In the single pump operation condition, pump A runs alone, valve 1 and valve 5 are open, valve 2, valve 3 and valve 4 are closed, and the fluid flows to the main pipeline only through pump A. Flow meter 1 and pressure gauge 1 monitor the flow and pressure. In the dual pump parallel operation condition, pump A and pump B run at the same time, valve 1 and valve 5 remain open, and valve 2 and valve 3 are opened at the same time. The flow is collected into the main pipeline through the two pumps, and flow meters 1, 2 and 3 monitor the flow data in the parallel state. In the dual pump series operation condition, the fluid output by pump A and pump B runs through the series pipeline. First, valve 3, valve 4 and valve 5 are opened, and valve 1 is closed. The flow flows through the two pumps in turn and the total flow and pressure data are measured by the flow meter and pressure gauge.

[0075] Third, based on the flow smoothness control method of the mud lift pump group under multiple working conditions provided in this application, a sliding mode controller module is designed. Since there is no ready-made sliding mode controller module in the Simulink environment, this embodiment chooses to use the MATLAB Function module to implement the sliding mode control logic, making full use of MATLAB's powerful computing function to write a custom control algorithm. The specific design process of the sliding mode controller module is as follows:

[0076] Design of sliding surface, sliding mode variable represents the error between target flow and actual flow, reflecting the deviation between the current state of the pump system and the expected state, where there is a linear relationship between the sliding mode variable and the flow error. The sliding surface is generated based on the sliding mode variable. The sliding surface is the core of sliding mode control, and its design directly affects the performance of the controller and the stability of the system.

[0077] The design of equivalent control gain, the goal of equivalent control is to keep the pump system state on the sliding surface to ensure that the pump system can stably track the target flow. The role of equivalent control is to gradually approach the sliding surface of the pump system by adjusting the control input, and to minimize the impact of external disturbances on the pump system state. In this embodiment, the input action gain coefficient of the improved system model can be set to 1, but in actual applications, the specific value can be set according to actual needs and is not a specific limitation of this application.

[0078] The switching control gain is designed through the sat(x) function. The sat(x) function is a saturation function, which limits the control input to the range of [-1, 1], thereby avoiding the instability of the pump system or excessive oscillation when the control signal fluctuates greatly. Based on this, the boundary layer data is introduced to realize the introduction of moderate nonlinear factors in the sliding mode control, and alleviate the jitter phenomenon that may occur in the traditional sliding mode control. The boundary layer data is usually taken as 1%-10% of the sliding surface variable s, and then specifically adjusted by observing the jitter. The parameter k represents the switching gain, which controls the speed of convergence to the sliding surface. If it is too large, it may introduce larger jitter, and if it is too small, it will cause the pump system to respond slowly.

[0079] The output signal of the sliding mode control module, i.e., the control input gain, is obtained by adding the equivalent control gain and the switching control gain. The control input gain is used to adjust the speed of the pump, thereby achieving smooth control of the flow rate. There is a clear dynamic correlation between the control input gain, the speed of the pump, and the flow rate. The control input gain, as the output signal of the sliding mode control module, acts on the motor of the pump through the motor driver, changes the power supply parameters of the motor (such as voltage, frequency or current), and thus adjusts the actual speed of the pump. The speed of the pump directly affects the output flow of the pump, and the two are in direct proportion. In the Simulink environment, we implemented the above controller algorithm through the MATLAB Function module. The input port of the module receives the target flow rate and the actual flow rate, and outputs the control signal according to the calculation results.

[0080] The code implementation process of the sliding mode control module is as follows Figure 6As shown, it includes: first, reading the target flow q_ref and the actual flow q data; then, calculating the sliding mode variable s=c*(q_ref-q) based on the target flow q_ref and the actual flow q data, and calculating the dynamic equation of the pump system based on the actual flow q data, wherein the dynamic equation of the pump system includes the dynamic characteristic action gain coefficient f_q=0.5*q of the pump system, and the input action gain coefficient g_q=1 of the pump system. Determine the equivalent control gain u_eq=-f_q / g_q based on the dynamic characteristic action gain coefficient of the pump system and the input action gain coefficient of the pump system. Determine the switching control gain u_sw=-k*sat(s / epsilon) based on the sliding mode variable, the switching gain and the boundary layer data. Finally, calculate the control input gain u=u_eq+u_sw based on the equivalent control gain and the switching control gain.

[0081] like Figure 5 As shown in the figure, a Unit Delay module is set in the improved pump system model and connected to the output end of the MATLAB Function module. The Unit Delay module is used to delay the signal by one time step and save the state information of the previous time step in the discrete time system. The function of the Unit Delay module is to delay the output signal of the MATLAB Function module so that the previous signal value can be used in the calculation process of the controller, thereby realizing the discrete time sliding mode control algorithm and ensuring the stability and correctness of the control calculation.

[0082] In addition, for the convenience of debugging and testing, this application uses the SignalBuilder module in the Simulink environment to set the ideal reference curve. The Signal Builder module allows the creation of piecewise linear signal sources and the ability to quickly switch between different signal groups in the pump system model, thereby simulating target flow signals under different working conditions and testing the responsiveness and stability of the pump system under various conditions.

[0083] Based on the above description, through the synergy of the pump module, valve module, pipeline module, fluid property module, sliding mode control module, Unit Delay module and Signal Builder module, the target flow can be tracked in real time, and the control input can be dynamically adjusted according to the state of the pump system. The simulation results show that after the optimization of the sliding mode control module, the pump system can effectively suppress flow fluctuations and improve flow stability. The sliding mode control algorithm shows strong robustness. In the process of switching from a single pump to a dual pump in parallel or in series, it can effectively eliminate the sudden change of flow caused by changes in operating conditions, suppress the dynamic instability caused by pressure fluctuations, and adapt to the flow requirements under different operating conditions. Through sliding mode control, the output of the pump system not only has a high accuracy, but also can maintain good stability under external disturbances and parameter changes, verifying the effectiveness and superiority of the flow smoothness control method of the mud lift pump group under multiple working conditions provided in this application in flow smoothness control.

[0084] The experimental results show that the flow smoothness control method of the mud lift pump group under multiple working conditions of the present application can still maintain the high robustness and good control effect of the system under various external disturbances and system parameter changes. Compared with the traditional control method, the flow smoothness control method of the mud lift pump group under multiple working conditions provided by the present application can more effectively cope with the complex and changeable working conditions in the deep-sea environment, and ensure that the pump system can achieve stable and accurate flow control under various operating conditions.

[0085] The present application controls the error of the pump system by defining sliding surface variables, ensuring that the pump system can quickly converge to the target value under disturbance, thereby achieving smoothness control of the flow rate. The flow smoothness control method of the mud lift pump group under multiple working conditions of the present application consists of two parts: equivalent control and switching control. Among them, the equivalent control part keeps the pump system state close to the sliding surface variable by adjusting the control input, while the switching control suppresses the chattering phenomenon that may occur in the traditional sliding mode control by introducing boundary layer data. By optimizing control parameters such as sliding surface variables, equivalent control gain and switching control gain, the dynamic response and steady-state performance of the pump system can be effectively improved. The specific method of optimizing these parameters is: the difference between the target flow rate and the actual flow rate is defined as the error, and the error is minimized as the optimization target, and the error is gradually reduced by adjusting the sliding surface variables, equivalent control gain and switching control gain and other control parameters. When the error is minimized, the pump system can achieve accurate flow tracking, and at the same time, the dynamic response and steady-state performance are significantly improved.

[0086] The flow smoothness control method of the mud lift pump group under multiple working conditions proposed in this application can not only be widely used in the flow control of deep-sea mud pump systems, but also can be extended to other industrial systems that require precise flow control, such as hydraulic pipelines and chemical fluid delivery systems. The flow smoothness control method of the mud lift pump group under multiple working conditions provided in this application can significantly improve the stability of system operation, reduce the risk of equipment damage and reduce maintenance costs, and always maintain the stability of system performance in an environment with large dynamic loads and external disturbances, and has important engineering application value.

[0087] Based on the above description, the flow smoothness control method of the mud lift pump group under multiple working conditions of the present application has the following advantages under working condition switching and complex environmental disturbances:

[0088] (1) Strong robustness. No matter how the parameters of the mud lift pump group change, the flow smoothness control method of the mud lift pump group under multiple working conditions can maintain the stability and performance of the system.

[0089] (2) Fast dynamic response. The flow smoothness control method of the mud lift pump group under multiple working conditions designs the sliding surface variables and equivalent control gains, so that the state of the mud lift pump group can quickly converge to the sliding surface and slide along the sliding surface, and the dynamic response speed is fast.

[0090] (3) The design is simple. The flow smoothness control method of the mud lift pump group under multiple working conditions does not require complex model parameters. It only needs to design the sliding surface, equivalent control gain and switching control gain to achieve flow control of the mud lift pump group. The accuracy requirement for the mud lift pump group is relatively low.

[0091] (4) Global stability: The flow smoothness control method of the mud lift pump group under multiple working conditions can ensure the stability of the mud lift pump group in the global range, not limited to local stability.

[0092] In an exemplary embodiment, a computer device is provided. The computer device may be a server or a terminal. The internal structure diagram thereof may be as follows: Figure 7As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store flow smoothness control data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a flow smoothness control method for a mud lift pump group under multiple working conditions is implemented.

[0093] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. In an exemplary embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above-mentioned method embodiments when executing the computer program.

[0094] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0095] In an exemplary embodiment, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0096] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0097] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0098] The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. The non-relational database may include a distributed database based on blockchain, etc., but is not limited thereto. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but is not limited thereto.

[0099] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0100] This article uses specific examples to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for controlling flow smoothness of a mud lift pump group under multiple working conditions, characterized in that: The flow smoothness control method of the mud lift pump group under multiple working conditions includes: Acquire the target flow rate and current data of the mud lift pump group; the current data of the mud lift pump group includes the actual flow rate, gain data and boundary layer data; the gain data includes the switching gain of the mud lift pump group and the input action gain coefficient of the mud lift pump group; Determine the error between the target flow rate and the actual flow rate, and use the error as a sliding mode variable; Determining whether the sliding mode variable reaches a set threshold; When the sliding mode variable reaches the set threshold, no processing is performed; When the sliding mode variable does not reach the set threshold, determining a dynamic characteristic action gain coefficient of the mud lift pump group based on the actual flow rate; Determining an equivalent control gain based on an input action gain coefficient of the mud lift pump group and a dynamic characteristic action gain coefficient of the mud lift pump group; determining a switching control gain based on the sliding mode variable, the switching gain and the boundary layer data; determining a control input gain based on the equivalent control gain and the switching control gain; A control adjustment signal is generated based on the control input gain, and the flow rate of the mud lift pump group under multiple working conditions is controlled based on the control adjustment signal.

2. The flow smoothness control method of a mud lift pump group under multiple working conditions according to claim 1 is characterized in that: The sliding mode variable is expressed as: s = c*(q_ref-q); Among them, s is the sliding mode variable, q_ref is the target flow, q is the actual flow, and c is a constant.

3. The flow smoothness control method of a mud lift pump group under multiple working conditions according to claim 1 is characterized in that: The dynamic characteristic action gain coefficient of the mud lift pump group is expressed as: f_q=0.5*q; Among them, f_q is the dynamic characteristic gain coefficient of the mud lift pump group, and q is the actual flow rate.

4. The flow smoothness control method of a mud lift pump group under multiple working conditions according to claim 1 is characterized in that: The equivalent control gain is expressed as: u_eq = -f_q / g_q; Among them, u_eq is the equivalent control gain, g_q is the input action gain coefficient of the mud lift pump group, and f_q is the dynamic characteristic action gain coefficient of the mud lift pump group.

5. The flow smoothness control method of a mud lift pump group under multiple working conditions according to claim 1 is characterized in that: The switching control gain is expressed as: u_sw = -k*sat(s / epsilon); Among them, u_sw is the switching control gain, k is the switching gain of the mud lift pump group, epsilon is the boundary layer data, sat() is the saturation function, and s is the sliding mode variable.

6. The method for controlling flow smoothness of a mud lift pump group under multiple working conditions according to claim 1, characterized in that: The control input gain is expressed as: u=u_eq+u_sw; Among them, u is the control input gain, u_eq is the equivalent control gain, and u_sw is the switching control gain.

Images