Valve-pump combined liquid supply system for fully mechanized coal mining face and optimal control method of valve-pump combined liquid supply system

Abstract

The invention relates to the technical field of hydraulic liquid supply systems for fully-mechanized coal mining faces of coal mines, in particular to a valve-pump combined liquid supply system for a fully-mechanized coal mining face and an optimal control method of the valve-pump combined liquid supply system for the fully-mechanized coal mining face. The unloading valve comprises a main valve, a one-way valve, a pilot valve and a stepping motor used for controlling the opening degree of the pilot valve. A damping hole is formed between the input end of the main valve and the input end of the pilot valve. A flow sensor is installed on the hydraulic pipeline between the one-way valve and the hydraulic supports, pressure sensors used for detecting liquid supply pressure are installed on the hydraulic supports respectively, and the flow sensor, the pressure sensors, the variable frequency motor and the stepping motor are in signal connection with a controller respectively. The system adopts an optimal control method to dynamically adjust the output parameters of the emulsion pump and the unloading valve. The problems that a fully mechanized coal mining face hydraulic system is large in oil pressure fluctuation, self-adaptive adjustment cannot be achieved, and energy is wasted are well solved.

Description

Technical Field

[0001] The present invention relates to the technical field of the hydraulic liquid supply system for fully mechanized coal mining faces, and specifically to a combined valve-pump liquid supply system for fully mechanized coal mining faces and an optimal control method therefor. Background Art

[0002] A fully mechanized coal mining face in a coal mine refers to a coal mining face equipped with fully mechanized equipment underground in the coal mine. The characteristics of such a face are that a coal shearer is used for coal mining, a flexible scraper conveyor is used as the face transportation equipment, and the face roof support uses hydraulic supports, and the gate belt conveyor is equipped. Among them, the power of the hydraulic supports comes from the high-pressure oil provided by the emulsion pump.

[0003] Currently, in the application process of the hydraulic system for fully mechanized coal mining faces in coal mines, the following problems generally exist:

[0004] 1) Due to its own structural limitations, the electromagnetic unloading valve has low control accuracy. Frequent opening and closing cause large fluctuations in the pressure of the hydraulic system, thereby affecting the stability and reliability of the hydraulic supports. The lack of a real-time adjustment mechanism makes the liquid supply pressure unable to be dynamically adjusted according to the pressure losses at different positions of the working face, resulting in uneven liquid supply pressures for the hydraulic supports at various places in a long working face, differences in the initial support forces, and weakening the overall support effect.

[0005] 2) The control method of the variable-frequency motor driving the emulsion pump has insufficient accuracy and cannot accurately adjust the output flow of the pump according to actual needs, resulting in a large amount of energy waste. The traditional liquid supply system has poor adaptability in the complex and changeable fully mechanized coal mining face in a coal mine, especially in areas with complex geological conditions and frequent changes in pressure requirements. It cannot achieve real-time response and adjustment, resulting in unstable working performance of the system under different pressure requirements.

[0006] 3) The frequent mechanical actions of the magnetic unloading valve exacerbate the wear of the components, reduce the reliability of the system, increase the maintenance frequency and cost, and are not conducive to the long-term stable operation of the equipment. The traditional fixed-displacement pump and electromagnetic unloading valve have a slow response speed when the liquid supply demand changes. Especially in case of emergency, they cannot be adjusted in time to meet the real-time liquid supply demand of the working face, affecting the production efficiency.

[0007] 4) The traditional hydraulic system lacks intelligent control functions, is difficult to integrate and share data with other intelligent coal mine equipment, and cannot improve the overall efficiency and accuracy of the liquid supply system through big data analysis or automation means. The existing liquid supply system also has significant deficiencies in energy conservation and emission reduction. It is difficult to achieve precise control of power and flow, resulting in low energy utilization rate, high emissions and operating costs, and not meeting the development requirements of green energy conservation in the coal mining industry. Summary of the Invention

[0008] The object of the present invention is to provide a valve-pump combined liquid supply system for a fully-mechanized coal mining face and its optimal control method, which is used to solve the problems of large oil pressure fluctuations, inability to adaptively adjust, and energy waste in the hydraulic system of the coal mine fully-mechanized coal mining face in the prior art.

[0009] To achieve the above object, the present invention provides the following technical solution: A valve-pump combined liquid supply system for a fully-mechanized coal mining face, including an oil tank, an emulsion pump with an input end connected to the oil tank, a variable-frequency motor for driving the emulsion pump, an unloading valve connected to the output end of the emulsion pump, and a hydraulic support with an inlet end connected to the unloading valve and a return end connected to the oil tank. The unloading valve includes a main valve with an input end connected to the output end of the emulsion pump, a check valve connected between the output end of the main valve and the inlet end of the hydraulic support, a pilot valve for controlling the opening degree of the main valve, and a stepper motor for controlling the opening degree of the pilot valve. There is a damping hole between the input end of the main valve and the input end of the pilot valve;

[0010] A flow sensor is installed on the hydraulic pipeline between the check valve and the hydraulic support, and pressure sensors for detecting the liquid supply pressure are respectively installed at the hydraulic support. The flow sensor, pressure sensors, variable-frequency motor, and stepper motor are respectively connected to a controller in a signal manner.

[0011] Preferably, a safety valve is installed at the output end of the emulsion pump.

[0012] Preferably, a throttle orifice is provided between the output end of the emulsion pump and the pilot valve.

[0013] An optimal control method for a valve-pump combined liquid supply system for a fully-mechanized coal mining face includes the following steps:

[0014] S1. Establish a mathematical model of the valve-pump combined liquid supply system;

[0015] S1.1 Establish a mathematical model of the valve-pump combined liquid supply system, covering the main components including the variable-frequency motor, emulsion pump, and unloading valve. Based on the hydraulic transmission principle and dynamic equations, describe the relationship between the input, output, and state variables of the system, and establish the relationship between the rotational speed of the variable-frequency motor and the output flow and pressure of the emulsion pump, and the relationship between the stepper motor controlling the opening degree of the unloading valve and the flow and pressure drop through the valve as:

[0016]

[0017] Where: Q p —— The flow measured by the flow sensor;

[0018] n p —— The rotational speed of the variable-frequency motor;

[0019] Ps —— The pressure measured by the pressure sensor;

[0020] n s is the displacement of the stepper motor;

[0021] S1.2 Transform the above formula into:

[0022]

[0023] Then the state variable is x = [Q p , P s ; T , and the input variable is u = [n p , n s ;

[0024] S1.3 Define the required flow rate and pressure of the hydraulic support as and To solve the tracking problem of the above system by establishing an augmented system, the augmented system is established in the following form:

[0025]

[0026] S1.4 Transform the above formula into:

[0027]

[0028] S2. Establish the cost function;

[0029] To optimize the system performance, define the cost function to measure the degree of deviation of the system state from the target value and the control energy consumption. According to the optimal control theory, define the system cost function as:

[0030] V(X) = ∫0 t (X(τ) T QX(τ) + u(τ) T Ru(τ))dτ;

[0031] In the formula: Q and R are the weight coefficient matrices of the state and input respectively, and both are positive definite;

[0032] S3. Solve the controller based on the critic neural network;

[0033] Use the critic neural network to approximate the value function and obtain the optimal control strategy through online learning. Design a single-hidden-layer feedforward neural network as the critic network, with the input being the system state X and the system input u, and the output being the estimated value of the value function The single-layer critic neural network is:

[0034] V(X) = W T φ(X) + ε;

[0035] Where: W——neural network error;

[0036] φ(X)——activation function;

[0037] ε——neural network error;

[0038] The change in the cost function of the system at time t0 can be written as:

[0039]

[0040] Combined with a single-layer evaluator neural network, the Bellman equation can be further written as:

[0041]

[0042] Where: ε0 = ε(t) - ε(t - t0) is the neural network error;

[0043] Make the following definition for the Bellman equation:

[0044]

[0045] Represent the above equation by defining a group of low-pass filters:

[0046]

[0047] Define auxiliary variables According to the single-layer evaluator neural network, it is necessary to online estimate and update the weights of the value function;

[0048] Using the state information of the system and the auxiliary variables, establish the adaptive law of the weights as:

[0049]

[0050] Where: η > 0——learning gain;

[0051] When the neural network weight W converges, the estimated cost function can be obtained

[0052] Derive the optimal control law according to the approximate value function:

[0053]

[0054] S4. Implementation and application of the controller;

[0055] Embed the designed optimal control algorithm into the controller, initialize the weights of the neural network, the parameters of the controller, and the weight matrices Q and R of the cost function. Through the pressure sensor and the flow sensor, obtain the system state X(t) in real time, input the current state X(t) and the input signal u into the critic neural network, and calculate the value function estimate and its gradient Calculate the control input u * (t) according to the optimal control strategy, generate control instructions for the variable-frequency motor and the stepping motor, transfer the control instructions to the actuator, adjust the emulsion pump and the unloading valve, and realize the control of the system. The system feeds back the new state to realize closed-loop control.

[0056] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0057] 1. The valve-pump combined liquid supply system for fully-mechanized mining face and its optimal control method involved in the present invention propose an innovative liquid supply system combining a hydraulic pump driven by a variable-frequency motor and a digital unloading valve. The stepping motor is used to precisely adjust the opening of the unloading valve, realizing precise adjustment of the pressure and flow of the hydraulic support, while improving the response speed of the system to the emergency liquid supply demand and ensuring the production efficiency.

[0058] 2. The valve-pump combined liquid supply system for fully-mechanized mining face and its optimal control method involved in the present invention can stably output the liquid supply pressure, avoid power waste, and ensure the green energy-saving goal of the coal mine liquid supply system.

[0059] 3. The valve-pump combined liquid supply system for fully-mechanized mining face and its optimal control method involved in the present invention obtain the liquid supply data in real time through the pressure sensor and the flow sensor, design the control algorithm through the optimal control theory, combine the Bellman equation and the critic neural network, realize the dynamic real-time optimal control of the liquid supply system, and can dynamically adjust the output pressure and flow according to the pressure requirements at different positions of the coal mine fully-mechanized mining face, solving the problem that the traditional system cannot adapt to complex working conditions.

[0060] 4. The valve-pump combined liquid supply system for fully-mechanized mining face and its optimal control method involved in the present invention reduce the frequent actions of mechanical components, reduce the wear and maintenance frequency of equipment, and improve the long-term operation stability of the liquid supply system. Description of the Drawings

[0061] Figure 1 is a schematic structural diagram of the valve-pump combined liquid supply system for the fully-mechanized mining face of the present invention;

[0062] Figure 2 is a control flow chart of the valve-pump combined liquid supply system for the fully-mechanized mining face of the present invention.

[0063] In the figure: 1 - variable-frequency motor;

[0064] 2 - Emulsion pump;

[0065] 3 - Safety valve;

[0066] 4 - Throttle orifice;

[0067] 5 - Unloading valve; 501 - Damping hole; 502 - Pilot valve; 503 - Stepper motor; 504 - Main valve; 505 - Check valve;

[0068] 6 - Controller;

[0069] 7 - Flow sensor;

[0070] 8 - Hydraulic support;

[0071] 9 - Pressure sensor;

[0072] 10 - Oil tank. Specific embodiments

[0073] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0074] Please refer to Figure 1-2 , the present invention provides a technical solution for a combined valve - pump liquid supply system in a fully - mechanized coal mining face, including an oil tank 10, an emulsion pump 2 with an input end connected to the oil tank 10, a variable - frequency motor 1 for driving the emulsion pump 2, an unloading valve 5 connected to the output end of the emulsion pump 2, and a hydraulic support 8 with an inlet end connected to the unloading valve 5 and a return end connected to the oil tank 10. The variable - frequency motor 1 drives the emulsion pump 2 to operate, and the output emulsion enters the unloading valve 5.

[0075] Among them, the unloading valve 5 includes a main valve 504 with an input end connected to the output end of the emulsion pump 2, a check valve 505 connected between the output end of the main valve 504 and the inlet end of the hydraulic support 8, a pilot valve 502 for controlling the opening degree of the main valve 504, and a stepper motor 503 for controlling the opening degree of the pilot valve 502. A damping hole 501 is provided between the input end of the main valve 504 and the input end of the pilot valve 502. A flow sensor 7 is installed on the hydraulic pipeline between the check valve 505 and the hydraulic support 8, and pressure sensors 9 for detecting the liquid supply pressure are respectively installed at the hydraulic support 8. The flow sensor 7, the pressure sensor 9, the variable - frequency motor 1, and the stepper motor 503 are respectively connected to a controller 6 in a signal - connection manner.

[0076] In summary, the stepping motor 503 precisely controls the opening degree of the pilot valve 502 according to the instructions of the controller 6. The adjustment of the pilot valve 502 changes the pressure difference across the main valve 504, thereby controlling the opening degree of the main valve 504 and precisely regulating the flow rate and pressure of the emulsion liquid passing through the unloading valve 5. The damping orifice 501 is used to reduce pressure surges and ensure smooth valve operation. The check valve 505 ensures unidirectional flow of the emulsion liquid and prevents backflow.

[0077] As the core of the system, the controller 6 receives real-time data from the pressure sensor 9 and the flow sensor 7. The pressure sensor 9 monitors the actual liquid supply pressure of the hydraulic support 8; the flow sensor 7 monitors the actual flow rate output by the emulsion liquid pump 2. According to different actions of the hydraulic support 8, the controller 6 tracks and adjusts different preset pressure and flow rate target values, combines the data fed back by the sensors, and uses the optimal control algorithm to calculate in real time the optimal rotational speed of the variable-frequency motor 1 and the optimal opening degree of the unloading valve 5.

[0078] In a long-distance working face, due to pressure losses and pressure fluctuations, the liquid supply pressures of the hydraulic supports 8 at different positions of the working face are different. The unloading valve 5 adjusts the output pressure of the emulsion liquid pump 2 according to the data fed back by the pressure sensors 9 of different hydraulic supports 8. The variable-frequency motor 1 adjusts its rotational speed according to the flow rate required for the actions of the hydraulic support 8 to ensure sufficient liquid supply and minimize the flow rate overflowing from the main valve 504 of the unloading valve 5, so as to reduce energy consumption.

[0079] The adjusted high-pressure emulsion liquid is transported to the hydraulic support 8 through the hydraulic pipeline to provide the required hydraulic power for it, realizing the support and adjustment functions of the hydraulic support 8. The excess emulsion liquid flows back to the oil tank 10 through the hydraulic pipeline, forming a closed hydraulic circuit.

[0080] Through the combined control of the variable-frequency motor 1 and the stepping motor 503, the entire system realizes precise adjustment of the output of the emulsion liquid pump 2 and the opening degree of the unloading valve 5, meeting the hydraulic requirements at different positions and different times in the fully mechanized coal mining face. At the same time, the application of the optimal control algorithm improves the response speed and control accuracy of the system, reduces energy consumption, and extends the service life of the equipment.

[0081] A safety valve 3 is installed at the output end of the emulsion liquid pump 2. During use, the emulsion liquid output by the emulsion liquid pump 2 first passes through the safety valve 3, which is used to release pressure when the system pressure is too high to protect the safety of the system.

[0082] A throttle orifice 4 is provided between the output end of the emulsion liquid pump 2 and the pilot valve 502 to achieve the effect of stable flow rate and reduced pressure fluctuations.

[0083] In order to further improve the control accuracy and response speed of the valve-pump combined liquid supply system, an optimal control method for the valve-pump combined liquid supply system used in the fully mechanized coal mining face is applied, which includes the following steps:

[0084] S1. Establish a mathematical model of the valve-pump combined liquid supply system;

[0085] S1.1 Establish a mathematical model of the valve-pump combined liquid supply system, covering the main components including the variable-frequency motor 1, the emulsion pump 2, and the unloading valve 5. Based on the hydraulic transmission principle and the dynamic equation, describe the relationship between the input, output, and state variables of the system, and establish the relationship between the rotational speed of the variable-frequency motor 1 and the output flow and pressure of the emulsion pump 2, as well as the relationship between the control of the opening of the unloading valve 5 by the stepping motor 503 and the flow and pressure drop through the valve as:

[0086]

[0087] Where: Q p —— The flow measured by the flow sensor 7;

[0088] n p —— The rotational speed of the variable-frequency motor 1;

[0089] P s —— The pressure measured by the pressure sensor 9;

[0090] n s Is the displacement of the stepping motor 503;

[0091] S1.2 Transform the above formula into:

[0092]

[0093] Then the state quantity is x = [Q p , P s T , and the input quantity is u = [n p , n s ;

[0094] S1.3 Define the required flow and pressure of the hydraulic support 8 as And To achieve the tracking problem of the above system by establishing an augmented system, the augmented system is established in the following form:

[0095]

[0096] S1.4 Transform the above formula into:

[0097]

[0098] S2. Establish a cost function; ​

[0099] To optimize the system performance, a cost function is defined to measure the degree of deviation of the system state from the target value and the control energy consumption. According to the optimal control theory, the system cost function is defined as:

[0100] V(X) = ∫0 t (X(τ) T QX(τ) + u(τ) T Ru(τ))dτ;;

[0101] Where: Q and R are the weight coefficient matrices of the state and input respectively, and both are positive definite;

[0102] S3. Solve the controller based on the critic neural network;

[0103] Since the HJB equation is difficult to solve analytically, a critic neural network is used to approximate the value function, and the optimal control strategy is obtained through online learning. A single-hidden-layer feedforward neural network is designed as the critic network, with the system state X and the system input u as the inputs and the estimated value of the value function as the output The single-layer critic neural network is:

[0104] V(X) = W T φ(X) + ε;

[0105] Where: W - neural network error;

[0106] φ(X) - activation function;

[0107] ε - neural network error;

[0108] The change in the cost function at time t0 of the system (Bellman equation) can be written as:

[0109]

[0110] Combined with the single-layer critic neural network, the Bellman equation can be further written as:

[0111]

[0112] Where: ε0 = ε(t) - ε(t - t0) is the neural network error;

[0113] For the convenience of subsequent calculations, the following definitions are made for the Bellman equation:

[0114]

[0115] To minimize the neural network error, a set of low-pass filters are defined to represent the above equation:

[0116]

[0117] Define auxiliary variables According to the single-layer critic neural network, it is necessary to perform online estimation and update of the weights of the value function;

[0118] Using the state information of the system and the auxiliary variables, an adaptive law for the weights is established as:

[0119]

[0120] where: η>0 - learning gain;

[0121] When the neural network weights W converge, the estimated cost function can be obtained

[0122] According to the approximate value function, the optimal control law is derived:

[0123]

[0124] S4. Implementation and application of the controller 6;

[0125] Embed the designed optimal control algorithm into the controller 6, initialize the neural network weights, controller parameters, and the cost function weight matrices Q and R. Through the pressure sensor 9 and the flow sensor 7, the system state X(t) is obtained in real time. Input the current state X(t) and the input signal u into the critic neural network to calculate the value function estimate and its gradient Calculate the control input u according to the optimal control strategy * (t), generate control instructions for the variable-frequency motor 1 and the stepping motor 503. The control instructions are transmitted to the actuator to adjust the emulsion pump 2 and the unloading valve 5 to achieve the control of the system. The system feeds back the new state to achieve closed-loop control.

[0126] This method realizes the precise control of the hydraulic system by establishing a mathematical model of the system, designing a cost function, constructing the Hamilton-Jacobi-Bellman (HJB) equation, and using the critic neural network to solve the optimal control strategy.

[0127] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0128] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A valve-pump combined liquid supply system for a fully-mechanized coal mining face, comprising an oil tank (10), an emulsion pump (2) with an input end connected to the oil tank (10), a variable-frequency motor (1) for driving the emulsion pump (2), an unloading valve (5) connected to the output end of the emulsion pump (2), and a hydraulic support (8) with an inlet end connected to the unloading valve (5) and a return end connected to the oil tank (10), characterized in that: The unloading valve (5) includes a main valve (504) with its input end connected to the output end of the emulsion pump (2), a check valve (505) connected between the output end of the main valve (504) and the liquid inlet end of the hydraulic support (8), a pilot valve (502) for controlling the opening degree of the main valve (504), and a stepper motor (503) for controlling the opening degree of the pilot valve (502). A damping hole (501) is provided between the input end of the main valve (504) and the input end of the pilot valve (502). A flow sensor (7) is installed on the hydraulic pipeline between the check valve (505) and the hydraulic support (8). Pressure sensors (9) for detecting the liquid supply pressure are respectively installed at the hydraulic support (8). The flow sensor (7), pressure sensors (9), frequency conversion motor (1), and stepper motor (503) are respectively connected to a controller (6) by signals.

2. The valve-pump combined liquid supply system for fully-mechanized coal mining face according to claim 1, wherein: A safety valve (3) is installed at the output end of the emulsion pump (2).

3. The valve-pump combined liquid supply system for fully-mechanized coal mining face according to claim 1, characterized in that: A throttle port (4) is provided between the output end of the emulsion pump (2) and the pilot valve (502).

4. The optimal control method for the valve-pump combined liquid supply system for the fully-mechanized coal mining face according to claim 1, characterized in that, It includes the following steps: S1. Establish a mathematical model of the valve-pump combined liquid supply system; S1.1 Establish a mathematical model of the valve-pump combined liquid supply system, covering the main components including the frequency conversion motor (1), emulsion pump (2), and unloading valve (5). Based on the hydraulic transmission principle and dynamic equations, describe the relationship between the input, output, and state variables of the system, and establish the relationship between the rotational speed of the frequency conversion motor (1) and the output flow and pressure of the emulsion pump (2), and the relationship between the stepper motor (503) controlling the opening degree of the unloading valve (5) and the flow and pressure drop through the valve as: Where: Q p —— The flow rate measured by the flow sensor (7); n p —— rotational speed of the variable-frequency motor (1); P s —— the pressure measured by the pressure sensor (9); n s is the displacement of the stepper motor (503); S1.2 Transform the above formula into: Then the state variable is x = [Q p , P s T , and the input variable is u = [n p , n s ;​ S1.3 Define the required flow rate and pressure of the hydraulic support (8) as and The tracking problem of the above system is realized by establishing an augmented system, and the augmented system is established in the following form: S1.4 Transform the above formula into: S2. Establish a cost function; To optimize the system performance, define a cost function to measure the degree of deviation of the system state from the target value and the control energy consumption. According to the optimal control theory, define the system cost function as: In the formula: Q and R are respectively the weight coefficient matrices of the state and input, and both are positive definite; S3. Solve the controller based on the critic neural network; Approximate the value function using an evaluator neural network and obtain the optimal control strategy through online learning. Design a single-hidden-layer feedforward neural network as the evaluator network, with the system state X and the system input u as the inputs and the estimated value of the value function as the output. The single-layer evaluator neural network is as follows: V(X) = W T φ(X) + ε; In the formula: W - neural network error; φ(X) - activation function; ε —— Neural network error; The change in the cost function of the system at t time 0 can be written as: Combined with a single-layer critic neural network, the Bellman equation can be further written as: In the formula: ε0 = ε(t) - ε(t - t0) is the neural network error; Make the following definitions for the Bellman equation: Represent the above formula by defining a group of low-pass filters: Define auxiliary variables According to the single-layer evaluator neural network, it is necessary to perform online estimation and update of the weights of the value function; Using the state information and auxiliary variables of the system, establish the adaptive law of the weights as: In the formula: η > 0 - learning gain; When the neural network weights W converge, the estimated cost function can be obtained. Derive the optimal control law according to the approximate value function: S4. Implementation and application of the controller (6); Embed the designed optimal control algorithm into the controller (6), initialize the neural network weights, controller parameters, and the cost function weight matrices Q and R. Through the pressure sensor (9) and the flow sensor (7), obtain the system state X(t) in real time, input the current state X(t) and the input signal u into the critic neural network, and calculate the value function estimate and its gradient Calculate the control input u according to the optimal control strategy * (t), generate the control instructions for the variable-frequency motor (1) and the stepping motor (503), transfer the control instructions to the actuator, adjust the emulsion pump (2) and the unloading valve (5), realize the control of the system, and the system feeds back the new state to realize the closed-loop control.

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