Flow smoothness control method for mud-lifting pump group under multiple working conditions

Abstract

The application discloses a mud lifting pump group multi-working condition flow smoothness control method, relates to the flow control field, and comprises the following steps: acquiring a target flow, an actual flow, boundary layer data, switching gain of a system and input action 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; generating a control adjustment signal based on the control input gain, and completing the control of the mud lifting pump group flow based on the control adjustment signal. The application can control the flow of the mud lifting pump group smoothly, and improve the stability of the mud lifting pump group.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of flow control, in particular to a flow smoothness control method of a mud hoisting pump set under multiple working conditions. BACKGROUND

[0002] With the continuous growth of global energy demand, the development of deep-sea oil and gas resources has become the focus of attention of various countries. Deepwater drilling technology, as an important means of offshore exploration and development, is facing increasingly severe technical challenges, especially in deep-sea areas with increasing water depth. Traditional drilling technology has been unable to meet the operational requirements in complex environments. In order to overcome these difficulties, deep-sea riserless drilling technology, as an innovative solution, has gradually attracted attention. The mud hoisting system, as one of the key technologies, is responsible for the function of returning the mud on the seabed to the platform through the pipeline.

[0003] The mud hoisting 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 crucial role. In the prior art, the pump system may experience unstable flow when facing external disturbances, dynamic load changes, and internal nonlinear characteristics of the system, further leading to poor system stability. SUMMARY

[0004] The purpose of the present application is to provide a flow smoothness control method of a mud hoisting pump set under multiple working conditions, which can control the flow of the mud hoisting pump set under multiple working conditions, thereby improving the stability of the mud hoisting pump set.

[0005] To achieve the above-mentioned purpose, the present application provides the following solutions:

[0006] In a first aspect, the present application provides a flow smoothness control method of a mud hoisting pump set under multiple working conditions, comprising:

[0007] obtaining a target flow and current data of the mud hoisting pump set; the current data of the mud hoisting pump set includes actual flow, gain data and boundary layer data; the gain data includes switching gain of the mud hoisting pump set and input action gain coefficient of the mud hoisting pump set;

[0008] determining the error between the target flow and the actual flow, and taking the error as a sliding mode variable;

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

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

[0011] determining a kinetic characteristic action gain coefficient of the mud-lifting pump set based on the actual flow rate when the sliding mode variable does not reach the set threshold value;

[0012] determining an equivalent control gain based on the input action gain coefficient of the mud-lifting pump set and the kinetic characteristic action gain coefficient of the mud-lifting pump set;

[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] generating a control adjustment signal based on the control input gain, and completing control on the flow rate of the mud-lifting pump set under multiple working conditions based on the control adjustment signal.

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

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

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

[0019] Optionally, the kinetic characteristic action gain coefficient of the mud-lifting pump set is expressed as:

[0020] f_q = 0.5 * q;

[0021] wherein f_q is the kinetic characteristic action gain coefficient of the mud-lifting pump set, and q is the actual flow rate.

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

[0023] u_eq = -f_q / g_q;

[0024] wherein u_eq is the equivalent control gain, g_q is the input action gain coefficient of the mud-lifting pump set, and f_q is the kinetic characteristic action gain coefficient of the mud-lifting pump set.

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

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

[0027] wherein u_sw is the switching control gain, k is the switching gain of the mud-lifting pump set, epsilon is the boundary layer data, sat() is a 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] Wherein, u is control input gain, u eq is equivalent control gain, and u sw is switching control gain.

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

[0032] The application provides a flow smoothness control method for a mud lifting pump set under multiple working conditions. The target flow and the current data of the mud lifting pump set are obtained, and the equivalent control gain and the switching control gain are further determined, so as to determine the control input gain. The control adjustment signal is generated according to the control input gain, and the flow of the mud lifting pump set under multiple working conditions is controlled according to the control adjustment signal. The problem of slow response speed and poor stability of the mud lifting pump set caused by large flow fluctuation in the prior art is solved, the flow control of the mud lifting pump set is realized, the target flow value of the mud lifting pump set flow can be quickly reached, and the stability of the mud lifting pump set is further improved. BRIEF DESCRIPTION OF DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the embodiments of the application or the related art, the drawings needed to be used in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0034] Figure 1 A flow chart of a flow smoothness control method for a mud lifting pump set under multiple working conditions provided by an embodiment of the application is shown in the figure.

[0035] Figure 2 A speed-flow relationship diagram provided by an embodiment of the application is shown in the figure.

[0036] Figure 3 A head-flow relationship diagram provided by an embodiment of the application is shown in the figure.

[0037] Figure 4 A flow operation circuit diagram provided by an embodiment of the application is shown in the figure.

[0038] Figure 5 A pump set simulink model diagram provided by an embodiment of the application is shown in the figure.

[0039] Figure 6 A code flow diagram provided by an embodiment of the application is shown in the figure.

[0040] Figure 7 A structural diagram of a computer device provided by an embodiment of the application is shown in the figure. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the protection scope of the present application.

[0042] The above purposes, features and advantages of the present application will be more obvious and easy to understand. The present application will be described in further detail below with reference to the drawings and specific embodiments.

[0043] In one exemplary embodiment, as shown in FIG. 1, a flow smoothness control method under multiple working conditions of a mud lifting pump set is provided, including the following steps 100 to 108. Wherein: Figure 1

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

[0045] Step 101, determining an error between the target flow and the actual flow, and taking the error as a sliding mode variable. Wherein, the expression of the sliding mode variable is:

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

[0047] Wherein, 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, determining 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, determining the dynamic characteristic action gain coefficient of the mud lifting pump set based on the actual flow. Wherein, the expression of the dynamic characteristic action gain coefficient of the mud lifting pump set is:

[0051] f_q = 0.5 * q.

[0052] Wherein, f_q is the dynamic characteristic action gain coefficient of the mud lifting pump set.

[0053] ​In step 105, the equivalent control gain is determined based on the input action gain coefficient of the mud-lifting pump set and the kinetic characteristic action gain coefficient of the mud-lifting pump set. The expression of the equivalent control gain is as follows:

[0054] u_eq = -f_q / g_q.

[0055] wherein u_eq is the equivalent control gain, and g_q is the input action gain coefficient of the mud-lifting pump set.

[0056] In step 106, the switching control gain is determined based on the sliding mode variable, the switching gain, and the boundary layer data. The expression of the switching control gain is as follows:

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

[0058] wherein u_sw is the switching control gain, k is the switching gain of the mud-lifting pump set, epsilon is the boundary layer data, and sat() is a saturation function.

[0059] In step 107, the control input gain is determined based on the equivalent control gain and the switching control gain. The expression of the control input gain is as follows:

[0060] u = u_eq + u_sw.

[0061] wherein u is the control input gain.

[0062] In step 108, the control adjustment signal is generated based on the control input gain, and the control of the flow of the mud-lifting pump set is completed based on the control adjustment signal.

[0063] The implementation of the above steps 100 to 108 can make the flow of the mud-lifting pump set in multiple working conditions be smoothly controlled, thereby improving the stability of the mud-lifting pump set.

[0064] In another exemplary embodiment of the present application, the effectiveness of the method provided by the present application is further illustrated by taking the control of the pump system by using the mud-lifting pump set flow smoothness control method in multiple working conditions provided by the present application as an example. Based on this, the mud-lifting pump set flow smoothness control process in multiple working conditions includes:

[0065] Firstly, the modeling of the pump set model is performed in the Simulink environment (Simulink platform), wherein the pump set model includes core components such as a centrifugal pump, a ball valve, a pipeline, and a fluid attribute module. By constructing the pump set model, the physical behavior, fluid characteristics, and dynamic response of the pump system of the deep-sea mud-lifting pump can be accurately simulated. The construction of the pump set model includes the following steps:

[0066] First, pump module setting: the pump module (e.g., a centrifugal pump module) in the Simulink environment can accurately simulate the physical behavior of the pump, which includes pump characteristic curves, efficiency curves, and flow-head relationships. The pump module is parameterized using experimental data, and the pump parameters are set by the relationship between differential pressure and brake power and pump delivery characteristics, where the selected pump rated speed is 1800 r / min, and the resulting angular velocity is 188 rad / s. The density of the subsea mud is affected by many factors, and the embodiment assumes that the mud density is 1200 kg / m 3 . Based on the Fluent flow channel model, the discrete data of the flow rate and head as a function of rotational speed at pump start-up can be obtained as shown in Figure 2 and Figure 3 . According to the discrete data of the flow rate as a function of rotational speed, the relationship between flow rate and rotational speed can be derived as: Q = 0.0976N - 0.9728, where Q is the flow rate of the pump system, and N is the rotational speed of the pump.

[0067] Second, valve module setting: for example, the valve module in this embodiment is a ball valve module in the Simulink environment, which can accurately simulate the on-off behavior and flow characteristics of the ball valve, especially the relationship between opening degree change and flow rate, which helps to accurately predict the fluid dynamic behavior of the pump system. Through the pre-defined ball valve module, users can quickly create and configure the ball valve model without having to write code from scratch or design complex models. Users can adjust multiple parameters of the ball valve, such as on-off time, maximum flow rate, and valve characteristic curves, to meet different simulation needs. The ball valve module simulates the effect of the ball valve on the flow rate in the hydraulic network. The ball valve is composed of a valve seat and a ball, and the valve seat can be round, sharp, or conical. 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 a physical signal input. A positive displacement can increase the gap between the ball and the valve seat, allowing more liquid to flow.

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

[0069] To further simplify the model, the pipe module can not only simulate the pipe itself, but also simulate the local resistance related to the pipe (such as elbows, fittings, inlet and outlet losses, etc.). The pipe connection port A and port B are hydraulic protection ports, and when the fluid flows from the pipe 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. The rated flow of the pipe is set to 2000L / min, and the cross-sectional area is 15688mm 2 .

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

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

[0072] When single pump operation, A pump operation, B pump stop, open 1# valve and 5# valve, and close 2# valve, 3# valve and 4# valve. When single pump operation changes to double pump parallel operation, first open 1# valve and 5# valve, close 4# valve, and open 2# valve and 3# valve during operation. When single pump operation changes to double pump series operation, first open 1# valve and 5# valve, close 2# valve, and close 1# valve during operation, open 3# valve and 4# valve. In each working condition, the flow is collected in real time by setting the flow meter module, and the flow is simulated in real time combined with the pump system model. By observing the flow fluctuation 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 a large flow fluctuation, which seriously affects the stability of the pump system, causing the pump set to be unable to operate stably, so during the process of flow change, the input of the pump system needs to be adjusted in time to ensure the flow is smooth.

[0073] Two, on the basis of the above pump system model, further construction and improvement can be obtained as Figure 5The improved system model can be used to simulate the flow control and working condition switching of deep-sea mud lifting process. The improved system model mainly includes pump, flow meter, pressure gauge, valve, mud tank, controller and sensor, etc. The components are connected by pipeline to form a closed loop system. The pump A is connected with a speed sensor and the speed of the pump A is controlled by an input module. The controlled speed signal is input to the pump A. The fluid output by the pump A is monitored by the flow meter 1 and connected to the pressure gauge 1 to measure the pressure at the outlet of the pump A. The flow is adjusted by the valve 1 and the valve 5 and enters the main pipeline. The pump B is located in the center of the improved system model and runs in parallel with the pump A. The output fluid is monitored by the flow meter 2 and connected to the pressure gauges 3 and 4 to measure the corresponding pressure values. The control input of the pump B also adjusts its operating state. Multiple valves are provided in the improved system model to adjust the fluid flow path and system working condition by opening and closing different valves. The total flow is monitored by the flow meter 3 and the mud tank of the system is located in the middle of the model to simulate the storage and supply process of the mud. Figure 5 The oscilloscope in the improved system model is used to measure the voltage and current at each position in the model to evaluate the electrical performance of the system. The digital display is used to display the operating state and parameters of the system, including flow, pressure, power, etc.

[0074] The corresponding system state during working condition switching is as follows: in single pump operation condition, the pump A operates alone, the valves 1 and 5 are opened, and the valves 2, 3 and 4 are closed. The fluid flows to the main pipeline through the pump A only, and the flow and pressure are monitored by the flow meter 1 and the pressure gauge 1. In parallel pump operation condition, the pumps A and B operate simultaneously, the valves 1 and 5 remain open, and the valves 2 and 3 are opened. The flow is collected through the two pumps and enters the main pipeline, and the flow meters 1, 2 and 3 monitor the flow data in parallel state. In series pump operation condition, the fluids output by the pumps A and B run through the series pipeline. First, the valves 3, 4 and 5 are opened, and the 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 the pressure gauge.

[0075] Three, based on the mud lifting pump group multi-working condition flow smoothness control method provided in the present application, a sliding mode controller module is designed. Since there is no ready-made sliding mode controller module in the Simulink environment, the MATLAB Function module is selected to realize the sliding mode control logic, and the powerful calculation function of MATLAB is fully utilized to write a custom control algorithm. The specific design process of the sliding mode controller module is as follows:

[0076] The design of the sliding mode surface, which represents the error between the target flow rate and the actual flow rate, reflects the deviation between the current state and the desired state of the pump system, where the sliding mode variable is linearly related to the flow rate error. The sliding mode surface is generated based on the sliding mode variable, which is the core of the sliding mode control and its design directly affects the performance of the controller and the stability of the system.

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

[0078] The design of the switching control gain, which is achieved through the sat(x) function, a saturation function that limits the control input to within the range of [-1, 1], thereby avoiding the situation where large fluctuations in the control signal cause the pump system to become unstable or produce excessive oscillations. Based on this, the boundary layer data is introduced to introduce a moderate nonlinearity in the sliding mode control to alleviate the chattering phenomenon that may occur in traditional sliding mode control, where the boundary layer data is usually taken as 1%-10% of the sliding mode surface variable s, and then adjusted by observing the chattering. The parameter k represents the switching gain, which controls the speed of convergence to the sliding mode surface. Too large may introduce larger chattering, and too small 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, which is used to adjust the speed of the pump to achieve smooth control of the flow rate. There is a clear dynamic relationship 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, changing the power supply parameters (such as voltage, frequency, or current) of the motor to adjust the actual speed of the pump. The speed of the pump directly affects the output flow rate of the pump, and the two are in direct proportion. In the Simulink environment, we implement the above controller algorithm through the MATLAB Function module, which receives the target flow rate and the actual flow rate as input ports 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 rate q_ref and the actual flow rate q data; then, calculating the sliding mode variable s = c*(q_ref-q) based on the target flow rate q_ref and the actual flow rate q data, and calculating the dynamic equation of the pump system based on the actual flow rate 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. Based on the dynamic characteristic action gain coefficient of the pump system and the input action gain coefficient of the pump system, the equivalent control gain u_eq = -f_q / g_q is determined. Based on the sliding mode variable, the switching gain and the boundary layer data, the switching control gain u_sw = -k*sat(s / epsilon) is determined. Finally, the control input gain u = u_eq + u_sw is calculated 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 up in the improved pump system model and connected to the output of the MATLAB Function module. The Unit Delay module is used to delay the signal by one time step, saving the state information of the previous time step in the discrete-time system. The Unit Delay module delays the processing of the MATLAB Function module's output signal so that the previous signal value can be used in the controller calculation process, thus implementing the discrete-time sliding mode control algorithm and ensuring the stability and correctness of the control calculation.

[0082] Furthermore, to facilitate debugging and testing, this application uses the SignalBuilder module in the Simulink environment to set the ideal reference curve. The SignalBuilder module allows the creation of piecewise linear signal sources and enables rapid switching between different signal groups within the pump system model. This allows for simulating target flow signals under different operating conditions and testing the pump system's responsiveness and stability under various conditions.

[0083] Based on the above description, through the cooperation of the pump module, the valve module, the pipeline module, the fluid attribute module, the sliding mode control module, the Unit Delay module and the Signal Builder module, the target flow can be tracked in real time, and the control input can be dynamically adjusted according to the pump system state. The simulation results show that, after the optimization of the sliding mode control module, the pump system can effectively suppress the flow fluctuation and improve the flow stability. The sliding mode control algorithm shows strong robustness, and in the process of switching from single pump to parallel or series connection of double pumps, the flow mutation caused by the change of working conditions can be effectively eliminated, the dynamic instability caused by pressure fluctuation can be suppressed, and the flow requirement under different working conditions can be met. Through the sliding mode control, the output of the pump system not only has high precision, but also can maintain good stability under external disturbance and parameter change, which verifies the effectiveness and superiority of the mud lifting pump group multi-working condition flow smoothness control method provided in the application in flow smoothness control.

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

[0085] The application controls the error of the pump system by defining the sliding mode surface variable, ensures that the pump system can quickly converge to the target value under the action of disturbance, and thus realizes the stability control of the flow. The mud lifting pump group multi-working condition flow smoothness control method provided in the application is composed of equivalent control and switching control, wherein the equivalent control part adjusts the control input to keep the pump system state close to the sliding mode surface variable, and the switching control part suppresses the chattering phenomenon that may occur in the traditional sliding mode control by introducing the boundary layer data. By optimizing the control parameters such as the sliding mode surface variable, the equivalent control gain and the 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 to define the difference between the target flow and the actual flow as the error, and to minimize the error as the optimization target. By adjusting the control parameters such as the sliding mode surface variable, the equivalent control gain and the switching control gain, the error is gradually reduced. When the error reaches the minimum, the pump system can realize accurate flow tracking, and the dynamic response and steady-state performance are significantly improved.

[0086] The mud lifting pump group multi-working condition flow smoothness control method provided in the application can not only be widely applied to the flow control of the deep-sea mud pump system, but also be popularized to other industrial systems requiring accurate flow control, such as hydraulic pipelines and chemical fluid conveying systems. The mud lifting pump group multi-working condition flow smoothness control method provided in the application can significantly improve the stability of system operation, reduce the risk of equipment damage and maintenance cost, and always maintain the stability of system performance in the environment with large dynamic load and external disturbance, and has important engineering application value.

[0087] Based on the above description, the mud lifting pump group multi-working condition flow smoothness control method provided in the application has the following advantages under working condition switching and complex environmental disturbance:

[0088] (1) Strong robustness, no matter how the parameters of the mud lifting pump group change, the mud lifting pump group multi-working condition flow smoothness control method can maintain the stability and performance of the system.

[0089] (2) Fast dynamic response, the mud lifting pump group multi-working condition flow smoothness control method can make the state of the mud lifting pump group quickly converge to the sliding mode surface and slide along the sliding mode surface by designing the sliding mode surface variable and the equivalent control gain, and the dynamic response speed is relatively fast.

[0090] (3) Simple design, the mud lifting pump group multi-working condition flow smoothness control method does not need complex model parameters, only needs to design the sliding mode surface, the equivalent control gain and the switching control gain, and can realize the flow control of the mud lifting pump group, and the accuracy requirement of the mud lifting pump group is relatively low.

[0091] (4) Global stability, the mud lifting pump group multi-working condition flow smoothness control method can ensure the stability of the mud lifting pump group in the global range, and is not limited to local stability.

[0092] In an exemplary embodiment, a computer device, which can be a server or a terminal, is provided, and an internal structure diagram of the computer device can be as shown in Figure 7As shown in the figure. The computer device includes a processor, a memory, an input / output interface (I / O for short) and a communication interface. Among them, the processor, the memory and the input / output interface are connected through the 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 capability. 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 external devices. The communication interface of the computer device is used to communicate with external terminals through network connection. The computer program is executed by the processor to realize a flow smoothness control method of a mud lifting pump set under multiple working conditions.

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

[0094] In an exemplary embodiment, a computer readable storage medium is provided, storing a computer program, which is executed by a processor to realize the steps in each of the method embodiments described above.

[0095] In an exemplary embodiment, a computer program product is provided, including a computer program, which is executed by a processor to realize the steps in each of the method embodiments described above.

[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 for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant regulations.

[0097] Those skilled 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. The computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to 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 storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0098] The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., without being limited thereto.

[0099] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combinations of the technical features do not exist contradictory, they should be considered as the scope of the present application.

[0100] The principles and implementation modes of the present application are described by applying specific examples herein, and the above-mentioned embodiments are only used to help understand the method and its core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range can be changed. In conclusion, the content of the present application should not be understood as a limitation.

Claims

1. A method for flow smoothness control of a mud-lifting pump set under multiple operating conditions, characterized in that, The flow smoothness control method of the mud lifting pump group under multiple working conditions comprises: acquiring a target flow and current data of the mud lifting pump group; the current data of the mud lifting pump group comprises an actual flow, gain data and boundary layer data; the gain data comprises a switching gain of the mud lifting pump group and an input action gain coefficient of the mud lifting pump group; determining an error between the target flow and the actual flow, and taking the error as a sliding mode variable; determining whether the sliding mode variable reaches a set threshold value; when the sliding mode variable reaches the set threshold value, no processing is performed; when the sliding mode variable does not reach the set threshold value, determining a kinetic characteristic action gain coefficient of the mud lifting pump group based on the actual flow; determining an equivalent control gain based on the input action gain coefficient of the mud lifting pump group and the kinetic characteristic action gain coefficient of the mud lifting 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; generating a control adjustment signal based on the control input gain, and completing the control of the flow of the mud lifting pump group under multiple working conditions based on the control adjustment signal.

2. The flow smoothness control method for multiple operating conditions of a mud-lifting pump set according to claim 1, characterized in that, The sliding mode variable is expressed as: ； wherein, is a sliding mode variable, is a target flow rate, is an actual flow rate, is a constant.

3. The flow smoothness control method for multiple operating conditions of a mud-lifting pump set according to claim 1, characterized in that, The kinetic characteristic action gain coefficient of the mud lifting pump group is expressed as: ； wherein, is the gain factor for the mud-lifting pump set dynamics, is the actual flow rate.

4. The method for flow smoothness control of the mud-lifting pump set under multiple operating conditions according to claim 1, characterized in that, The equivalent control gain is expressed as: ； wherein, is the equivalent control gain, is the input action gain coefficient of the mud-lifting pump set, is the dynamics characteristic action gain coefficient of the mud-lifting pump set.

5. The method for flow smoothness control of the mud-lifting pump set under multiple operating conditions according to claim 1, characterized in that, The switching control gain is expressed as: ； wherein, is a switching control gain, is a switching gain for the mud-lifting pump set, is a boundary layer data, is a saturation function, is a sliding mode variable.

6. The flow smoothness control method for multiple operating conditions of a mud-lifting pump set according to claim 1, characterized in that, The control input gain is expressed as: ； wherein, is a control input gain, is an equivalent control gain, is a switching control gain.

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