Heating control method and system for rice noodle extruding machine

Abstract

The invention provides a rice noodle extruding machine heating control method and system, and the method comprises the steps: taking the output power of a heater of each section of heating charging barrel, the flow of a cooling sleeve, and the rotating speed of a screw as the input control quantity of a prediction model, and taking the temperature measured value of each section of heating charging barrel collected by a temperature sensor as the state quantity; a prediction model is established, and the prediction model outputs a temperature prediction value of each section of the heating charging barrel; according to the given target temperature value of each section of the heating charging barrel and the temperature measured value of each section of the heating charging barrel, constructing a reference track; establishing a rolling optimization objective function according to the prediction model and the reference trajectory, and solving the objective function to obtain an optimal control quantity; and the optimal control quantity is transmitted to a PID controller, and the PID controller feeds back and adjusts the output power of the heater of each section of heating charging barrel, the flow of the cooling sleeve and the rotating speed of the screw rod according to the optimal control quantity. According to the method, the temperature control precision and stability of the rice noodle extruding machine are improved.

Description

Technical Field

[0001] The invention relates to a rice noodle extruder, in particular to a heating control method and system for the rice noodle extruder. Background Art

[0002] Temperature control during rice noodle processing is one of the main factors affecting its quality. As the carrier for temperature control during rice noodle processing, the rice noodle extruder is one of the key equipment in the rice noodle production line, and its performance directly affects the quality of the final product. During the extrusion process, the material passes through a heating barrel at different temperature ranges to achieve the required physical and chemical changes, thereby forming the desired rice noodle characteristics.

[0003] However, the heating control method of the existing rice noodle extruder often adopts simple PID and fuzzy PID control algorithms. However, due to the hysteresis, large inertia, nonlinearity and coupling of the rice noodle extruder, the existing temperature control effect is not ideal, and it is difficult to achieve accurate temperature regulation, especially when the material properties change, it is difficult to ensure the consistency and stability of the temperature; the physical and chemical properties of different raw materials vary greatly, and a single heating mode cannot adapt well to the needs of a variety of raw materials; the temperature control is not accurate enough, and overheating may occur during the heating process, increasing production costs. The existing technology has certain limitations in terms of control accuracy, system stability and production efficiency. Therefore, it is urgent to develop a method and system for controlling the temperature of the heating process of a rice noodle extruder to meet the production needs of higher quality standards. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention proposes a heating control method and system for a rice noodle extruder to solve the problems of low temperature control accuracy and poor stability of the existing rice noodle extruder.

[0005] In order to achieve the above object, the present invention provides a heating control method for a rice noodle extruder, wherein the rice noodle extruder body comprises a plurality of heating barrels, each of which is provided with a screw, a temperature sensor, a heater, and a cooling sleeve; the method comprises:

[0006] The output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the rotational speed of the screw are used as the input control quantities of the prediction model, and the actual temperature measured value of each section of the heating barrel collected by the temperature sensor is used as the state quantity to establish a prediction model, and the prediction model outputs the predicted temperature value of each section of the heating barrel; a reference trajectory is constructed according to the given target temperature value of each section of the heating barrel and the actual temperature measured value of each section of the heating barrel; a rolling optimization objective function is established according to the prediction model and the reference trajectory, and the objective function is solved to obtain the optimal control quantity; the optimal control quantity is transmitted to the PID controller, and the PID controller adjusts the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the rotational speed of the screw according to the optimal control quantity feedback.

[0007] In one embodiment of the present invention, each section of the heating barrel is arranged with multiple temperature sensors, multiple heaters, and multiple cooling sleeves, and the multiple temperature sensors, multiple heaters, and multiple cooling sleeves are evenly arranged along the length direction of the section of the heating barrel; the method also includes: for each section of the heating barrel, according to the position of each heater, further dividing it into multiple sections of sub-heating barrels; according to the output power of the heater of each section of the heating barrel and the flow rate of the cooling sleeve, adjusting the output power of the heater and the flow rate of the cooling sleeve of each section of the heating barrel.

[0008] In one embodiment of the present invention, the prediction model is expressed as:

[0009]

[0010] Among them, y(k) represents the temperature prediction value corresponding to the k-th heating barrel, and u(k) represents the input control value corresponding to the k-th heating barrel. is a matrix describing the dynamic characteristics of the system; N is a positive integer representing the number of recursive steps;

[0011] Based on the output corresponding to the current heating barrel and the input control amount corresponding to the historical heating barrel, the output corresponding to the next heating barrel is predicted, and the output represents the temperature prediction value.

[0012] In one embodiment of the present invention, the reference trajectory is expressed as:

[0013] y c (k+1)=(1-α)y set (k)+αy(k)

[0014] Among them, y set (k) represents the target temperature value corresponding to the k-th heating barrel, y(k) represents the actual temperature value corresponding to the k-th heating barrel, and y c (k+1) is the reference trajectory, indicating the reference temperature value corresponding to the k+1th heating barrel.

[0015] In one embodiment of the present invention, the objective function is expressed as:

[0016]

[0017] Among them, J represents the objective function, Q is the temperature error weight coefficient, and R is the energy consumption weight coefficient.

[0018] In one embodiment of the present invention, the objective function is solved according to set constraints, which include: the power range of the heater of each section of the heating barrel, the flow range of the cooling sleeve, and the speed range of the screw.

[0019] In one embodiment of the present invention, the method further comprises: inputting the feed amount of each section of the heating barrel into the PID controller for feedforward compensation.

[0020] In addition, the present invention further provides a heating control system for a rice noodle extruder, the system comprising a rice noodle extruder body and a control unit, the rice noodle extruder body comprising a multi-section heating barrel, each section of the heating barrel is provided with a screw, a temperature sensor, a heater, and a cooling sleeve;

[0021] Wherein: the control unit comprises:

[0022] An information acquisition module is electrically connected to each section of the heating barrel to obtain the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw;

[0023] A main control module is electrically connected to the information acquisition module, and is used to start a temperature prediction program, including: receiving the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw as input control quantities of the prediction model, using the actual temperature value of each section of the heating barrel collected by the temperature sensor as the state quantity, and establishing a prediction model, wherein the prediction model outputs the temperature prediction value of each section of the heating barrel; constructing a reference trajectory according to the given target temperature value of each section of the heating barrel and the actual temperature value of each section of the heating barrel; establishing an objective function of rolling optimization according to the prediction model and the reference trajectory, and solving the objective function to obtain the optimal control quantity;

[0024] A PID controller, wherein the input end of the PID controller is electrically connected to the output end of the main control module, and the output end of the PID controller is electrically connected to the information acquisition module, so as to obtain the optimal control quantity, and adjust the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw according to the feedback of the optimal control quantity.

[0025] In one embodiment of the present invention, the control unit also includes a feedforward controller, which is electrically connected to the PID controller and is used to receive the feed amount of each section of the heating barrel as input to obtain a feedforward compensation amount, and input the feedforward compensation amount into the PID controller to compensate for the output of the PID controller.

[0026] In one embodiment of the present invention, the multi-stage heating barrel includes: a maturation section barrel, on which a plurality of temperature sensors, a plurality of heaters, and a plurality of cooling sleeves are arranged; an extrusion section barrel, connected to the output end of the maturation section barrel, on which a plurality of temperature sensors, a plurality of heaters, and a plurality of cooling sleeves are arranged.

[0027] It can be seen from the above scheme that the advantages of the present invention are:

[0028] The present invention discloses a heating control method for a rice noodle extruder, which combines model prediction with PID control, takes the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw as the input control quantity of the prediction model, takes the actual temperature value of each section of the heating barrel as the state quantity, and establishes a prediction model; and according to the given target temperature value of each section of the heating barrel and the actual temperature value of each section of the heating barrel, a reference trajectory is constructed; further, the objective function of rolling optimization is established in combination with the prediction model and the reference trajectory to obtain the optimal control quantity; finally, the optimal control quantity is transmitted to the PID controller, and the PID controller adjusts the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw according to the optimal control quantity feedback. The method jointly calculates the optimal control quantity of multiple sections of heating barrels, eliminates the coupling of multi-barrel heating, and realizes the prediction and advance control of future states, eliminates the hysteresis of the temperature control of the barrel of the rice noodle extruder, reduces the inertia of heating, significantly reduces the overshoot of the heating process, and improves the temperature control accuracy and stability of the rice noodle extruder. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] FIG. 1( a ) shows a schematic structural diagram of a multi-stage heating barrel of a rice noodle extruder body provided in one embodiment of the present invention;

[0030] FIG1( b ) shows a cross-sectional view of the barrel of the ripening section of FIG1( a );

[0031] FIG1( c ) shows a cross-sectional view of the extrusion barrel of FIG1( c );

[0032] Figure 2 The schematic diagram of the structure of the heating control system of the rice noodle extruder is shown;

[0033] Figure 3 The overall flow chart of the heating control method of the rice noodle extruder provided by one embodiment of the present invention is shown;

[0034] Figure 4 The heating control schematic diagram of the rice noodle extruder is shown.

[0035] The reference numerals are as follows:

[0036] 1: Rice noodle extruder body;

[0037] 10: Heating barrel;

[0038] 10A: Ripening section barrel;

[0039] 10B: extrusion section barrel;

[0040] 11: temperature sensor;

[0041] 12: heater;

[0042] 13: cooling sleeve;

[0043] 14: feeding port;

[0044] 15: discharge port;

[0045] 16: screw;

[0046] 2: control unit;

[0047] 21: information acquisition module;

[0048] 22: main control module;

[0049] 23: PID controller;

[0050] 24: feedforward controller;

[0051] 3: Human-computer interaction terminal. DETAILED DESCRIPTION

[0052] In order to make the above features and effects of the present invention more clearly understood, embodiments are given below and described in detail with reference to the accompanying drawings.

[0053] First see Figure 1(a)-Figure 1(c) FIG1(a) shows a schematic diagram of the structure of a multi-stage heating barrel of a rice noodle extruder body provided by an embodiment of the present invention; FIG1(b) shows a cross-sectional view of the barrel of the ripening section of FIG1(a); and FIG1(c) shows a cross-sectional view of the barrel of the extrusion section of FIG1(c). For the rice noodle extruder, the rice noodle extruder body 1 includes a multi-stage heating barrel 10, each of which is provided with a screw (not shown in the figure), a temperature sensor 11, a heater 12, and a cooling sleeve 13.

[0054] In some embodiments, Figure 1(a)-Figure 1(c)As shown in , in actual application, the multi-stage heating barrel 10 includes a multi-stage ripening barrel 10A and a multi-stage extrusion barrel 10B connected to the output end of the multi-stage ripening barrel 10A. Each of the ripening barrels 10A is arranged with multiple temperature sensors 11, multiple heaters 12, and multiple cooling sleeves 13, and the multiple temperature sensors 11, multiple heaters 12, and multiple cooling sleeves 13 are evenly arranged along the length direction on the ripening barrel 10A. Similarly, the extrusion barrel 10B is evenly arranged with multiple temperature sensors 11, multiple heaters 12, and multiple cooling sleeves 13, and the multiple temperature sensors 11, multiple heaters 12, and multiple cooling sleeves 13 are evenly arranged along the length direction on the extrusion barrel 10B. In this embodiment, multiple temperature sensors are evenly arranged along the length direction of the heating barrel, which can realize real-time temperature monitoring of different positions. This helps to more accurately understand the temperature distribution in the heating barrel, thereby performing more precise temperature control. In addition, based on the data feedback from the multi-point temperature sensor, the control unit can adjust the output power of each heater to ensure the uniformity of the temperature distribution in the heating barrel. This helps to avoid local overheating or overcooling and improve the stability and consistency of product quality. In addition, the uniform arrangement of multiple heaters allows the heating power of the heating barrel to be flexibly adjusted according to actual needs. When rapid heating is required, multiple heaters can be turned on at the same time; when the temperature is close to the set value, the output power of some heaters can be appropriately reduced to achieve more efficient energy utilization. At the same time, by accurately controlling the output power of the heater, unnecessary energy waste can be avoided. Evenly arranged heaters also help reduce heat loss and improve the heating efficiency of the entire rice noodle extruder heating system. In addition, the uniform arrangement of multiple cooling sleeves makes the cooling effect more uniform and efficient. When the temperature in the heating barrel reaches the set value, the cooling sleeve can quickly take away the heat and reduce the barrel temperature, thereby ensuring the smooth progress of the production process. At the same time, effective cooling measures help to reduce the operating temperature of the heating barrel and reduce the impact of thermal stress on equipment materials, thereby extending the service life of the equipment. In this embodiment, since the temperature sensor, heater and cooling sleeve are evenly arranged along the length direction, the load of each component is relatively balanced, which helps to reduce the failure rate. Even if a component fails, other components can continue to work normally, ensuring the continuity and stability of production.

[0055] In addition, further reference Figure 1(a)-Figure 1(c) As shown in the figure, the ripening section barrel 10A and the extrusion section barrel 10B are also provided with a feeding port 14 and a discharging port 15. The feeding port 14 and the discharging port 15 are designed by the prior art, and the present invention will not make a detailed introduction to this.

[0056] In addition, in this embodiment, the multi-stage heating barrel 10 is not only included in the ripening stage barrel 10A and the extrusion stage barrel 10B, but other heating barrels may also be provided according to actual needs.

[0057] Based on the above Figure 1(a)-Figure 1(c) The disclosed multi-stage heating barrel structure of the rice noodle extruder body, the invention specifically provides a heating control system for the rice noodle extruder, reference Figure 2 As shown, Figure 2 The schematic diagram of the heating control system of the rice noodle extruder is shown. The heating control system of the rice noodle extruder comprises a rice noodle extruder body 1 and a control unit 2. The rice noodle extruder body 1 comprises a plurality of heating barrels 10. Each heating barrel 10 is provided with a screw (not shown in the figure), a temperature sensor 11, a heater 12, and a cooling sleeve 13.

[0058] The control unit 2 includes an information acquisition module 21 , a main control module 22 , a PID controller 23 , and a feedforward controller 24 .

[0059] The information acquisition module 21 is electrically connected to each section of the heating barrel to obtain the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the rotation speed of the screw.

[0060] The main control module 22 is electrically connected to the information acquisition module 21, and is used to start a temperature prediction program, including: receiving the output power of the heater 12 of each section of the heating barrel, the flow rate of the cooling sleeve 13, and the rotation speed of the screw 16 as the input control quantity of the prediction model, and using the actual temperature value of each section of the heating barrel collected by the temperature sensor 11 as the state quantity to establish a prediction model, and the prediction model outputs the temperature prediction value of each section of the heating barrel; constructing a reference trajectory according to the given target temperature value of each section of the heating barrel and the actual temperature value of each section of the heating barrel; establishing a rolling optimization objective function according to the prediction model and the reference trajectory, and solving the objective function to obtain the optimal control quantity.

[0061] A PID controller 23, the input end of which is electrically connected to the output end of the main control module 22, and the output end of which is electrically connected to the information acquisition module 21, for obtaining the optimal control quantity, and adjusting the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw according to the feedback of the optimal control quantity.

[0062] The feedforward controller 24 is electrically connected to the PID controller 23, and cooperates with the PID controller 23. The feedforward controller 24 is used to receive the feed amount of each section of the heating barrel as input to obtain a feedforward compensation amount, and input the feedforward compensation amount to the PID controller to compensate for the output of the PID controller.

[0063] In addition, in some embodiments, the heater 11 is electrically connected to the control unit 2 through a relay, and the relay is controlled to control the opening and closing of the heater. The cooling sleeve is electrically connected to the control unit through a solenoid valve, and the flow of the cooling sleeve is controlled by controlling the conduction of the solenoid valve.

[0064] In this embodiment, the opening states of multiple heaters can be flexibly adjusted according to actual needs. When rapid temperature rise is required, multiple heaters can be turned on at the same time; when the temperature is close to the set value, the output power of some heaters can be appropriately reduced to achieve more efficient energy utilization. In addition, the opening states of multiple cooling sleeves can be flexibly adjusted in conjunction with the heaters according to actual needs to control the heat of the heating barrel.

[0065] In addition, in some embodiments, in order to facilitate system operation and visualization of monitoring information, a human-computer interaction terminal 3 is added to the heating control system of the rice noodle extruder. The interactive interface of the human-computer interaction terminal 3 can display the actual measured temperature values ​​of each section of the heating barrel and the current working status of the heater, cooling sleeve, and screw in real time.

[0066] Using the above-mentioned rice noodle extruder heating control system, an embodiment of the present invention specifically discloses a rice noodle extruder heating control method, specifically referring to Figure 3 , Figure 4 As shown in Figure 3 The overall flow chart of the heating control method of the rice noodle extruder is shown. Figure 4 The heating control principle diagram of the rice noodle extruder of the present invention is shown. The heating control method of the rice noodle extruder will be introduced in detail below in combination with the heating control system of the rice noodle extruder.

[0067] A heating control method for a rice noodle extruder, the method adopts a method combining model predictive control and PID control, and the method specifically comprises the following steps:

[0068] Step S1, using the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw as the input control quantities of the prediction model, and using the actual temperature measured value of each section of the heating barrel collected by the temperature sensor as the state quantity, to establish a prediction model, and the prediction model outputs the predicted temperature value of each section of the heating barrel.

[0069] In this embodiment, an extrusion test is conducted on a rice noodle extruder, and data is collected with the output power of the heater of each heating barrel, the flow rate of the cooling sleeve, the speed of the screw, and the feed amount as the target, and pre-processing is performed.

[0070] The preprocessed data is further used to establish a prediction model with the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw as the input control quantities of the prediction model, and the actual temperature measured value of each section of the heating barrel collected by the temperature sensor as the state quantity. The prediction model outputs the predicted temperature value of each section of the heating barrel.

[0071] Specifically, the prediction model is expressed as:

[0072]

[0073] Among them, y(k) represents the temperature prediction value corresponding to the k-th heating barrel, and u(k) represents the input control value corresponding to the k-th heating barrel. It is a matrix that describes the dynamic characteristics of the system; N is a positive integer representing the number of recursive steps.

[0074] In this embodiment, for the prediction model, the output corresponding to the heating barrel in the current stage is recursively predicted based on the output corresponding to the heating barrel in the historical stage and the input control amount corresponding to the heating barrel in the next stage, and the output represents the temperature prediction value.

[0075] Step S2: construct a reference trajectory according to the given target temperature value of each section of the heating barrel and the measured temperature value of each section of the heating barrel.

[0076] In this embodiment, in addition to the prediction model, a reference trajectory is further constructed based on the given target temperature value of each section of the heating barrel and the measured temperature value of each section of the heating barrel. Specifically, the reference trajectory is expressed as:

[0077] y c (k+1)=(1-α)y set (k)+αy(k)

[0078] Among them, y set (k) represents the target temperature value corresponding to the k-th heating barrel, y(k) represents the actual temperature value corresponding to the k-th heating barrel, and y c (k+1) is the reference trajectory, indicating the reference temperature value corresponding to the k+1th heating barrel.

[0079] Step S3: establishing an objective function of rolling optimization according to the prediction model and the reference trajectory, and solving the objective function to obtain an optimal control amount.

[0080] In this embodiment, after the prediction model and the reference trajectory are constructed respectively through the above steps S2 and S3, the objective function of rolling optimization is further established by combining the prediction model and the reference trajectory, and the optimal control amount is obtained by solving the objective function. Specifically, the objective function is expressed as:

[0081]

[0082] Among them, J represents the objective function, Q is the temperature error weight coefficient, and R is the energy consumption weight coefficient.

[0083] In addition, in some embodiments, in order to prevent the input control quantity from exceeding the rated value, constraints are set, which include the power range of the heater of each section of the heating barrel, the flow range of the cooling sleeve, the speed range of the screw, etc., and the objective function is solved in combination with the constraints.

[0084] In this embodiment, by eliminating y(k+j) in the objective function, the optimization problem about u(k+j) can be obtained, and by solving minJ, the optimal control amount can be obtained, that is, the optimal control amount includes the optimal output power of the heater of each section of the heating barrel, the optimal flow rate of the cooling sleeve, and the optimal speed of the screw. That is, the optimal control amount includes the total optimal output power of the heater of each section of the heating barrel, the total optimal flow rate of the cooling sleeve, and the total optimal speed of the screw.

[0085] In addition, as shown in FIG1 , in practice, each section of the heating barrel is usually arranged with multiple temperature sensors, multiple heaters, and multiple cooling sleeves, and the multiple temperature sensors, multiple heaters, and multiple cooling sleeves are evenly arranged along the length direction of the section of the heating barrel. Therefore, for each section of the heating barrel, the section of the heating barrel can be further divided into multiple sections of sub-heating barrels according to the position of each heater. After determining the total optimal output power of the heater, the total optimal flow rate of the cooling sleeve, and the total optimal speed of the screw for each section of the heating barrel, the optimal output power of each heater, the optimal flow rate of each cooling barrel, and the optimal speed of each screw can be further determined according to the arrangement of the heater, cooling barrel, and screw on the section of the heating barrel.

[0086] Step S4, transmitting the optimal control amount to a PID controller, and the PID controller adjusts the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw according to the optimal control amount feedback.

[0087] In this embodiment, reference is made to Figure 4 As shown in , after obtaining the optimal control quantity, the optimal control quantity is input into the PID controller, and the PID controller adjusts the output power of the heater of each heating barrel, the flow rate of the cooling sleeve, and the speed of the screw according to the optimal control quantity feedback.

[0088] In addition, in this embodiment, as mentioned above, according to the total optimal output power of the heater of each section of the heating barrel, the total optimal flow rate of the cooling sleeve, and the total optimal speed of the screw, the output power of each heater of each section of the heating barrel, the flow rate of each cooling sleeve, and the speed of each screw can also be feedback-adjusted.

[0089] In addition, further reference Figure 4 As shown in , since the feed amount has a great influence on the temperature, in one embodiment, the collected feed amount of each section of the heating barrel is further input into the feedforward controller, and the feedforward control is coordinated with the PID control. The feedforward controller receives the feed amount of each section of the heating barrel as input to obtain a feedforward compensation amount, and the feedforward compensation amount is input into the PID controller to compensate for the output of the PID controller.

[0090] In summary, the present invention discloses a heating control method for a rice noodle extruder, which combines model prediction with PID control, takes the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw as the input control quantity of the prediction model, and takes the measured temperature value of each section of the heating barrel as the state quantity to establish a prediction model; and constructs a reference trajectory according to the given target temperature value of each section of the heating barrel and the measured temperature value of each section of the heating barrel; further combines the prediction model and the reference trajectory to establish the objective function of rolling optimization to obtain the optimal control quantity; finally, the optimal control quantity is transmitted to the PID controller, and the PID controller adjusts the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw according to the optimal control quantity feedback. This method combines multiple sections of heating barrels to calculate the optimal control quantity, eliminates the coupling of multi-barrel heating, and realizes the prediction and advance control of future states, eliminates the hysteresis of the temperature control of the barrel of the rice noodle extruder, reduces the inertia of heating, significantly reduces the overshoot of the heating process, and improves the temperature control accuracy and stability of the rice noodle extruder.

[0091] In addition, it should be noted that the heating control method of the rice noodle extruder disclosed in the present invention is not limited to being executed in the order of the above steps S1-S4. It can reorder, add or delete steps. As long as the expected results of the technical solution of the present invention can be achieved, the present invention is not limited here.

[0092] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A heating control method for a rice noodle extruder, wherein the rice noodle extruder body comprises a multi-stage heating barrel, characterized in that: Each section of the heating barrel is provided with a screw, a temperature sensor, a heater, and a cooling sleeve; the method comprises: The output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw are used as the input control quantities of the prediction model, and the actual temperature value of each section of the heating barrel collected by the temperature sensor is used as the state quantity to establish a prediction model, and the prediction model outputs the predicted temperature value of each section of the heating barrel; A reference trajectory is constructed according to the given target temperature value of each section of the heating barrel and the measured temperature value of each section of the heating barrel; Establishing an objective function of rolling optimization according to the prediction model and the reference trajectory, and solving the objective function to obtain an optimal control amount; The optimal control quantity is transmitted to the PID controller, and the PID controller adjusts the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw according to the optimal control quantity feedback.

2. The method according to claim 1, characterized in that in: Each section of the heating barrel is provided with a plurality of temperature sensors, a plurality of heaters, and a plurality of cooling sleeves, and the plurality of temperature sensors, a plurality of heaters, and a plurality of cooling sleeves are evenly arranged along the length direction on the section of the heating barrel; The method also includes: Each section of the heating barrel is further divided into multiple sections of sub-heating barrels according to the position of each heater; According to the output power of the heater of each section of the heating barrel and the flow rate of the cooling sleeve, the output power of the heater of each section of the heating barrel and the flow rate of the cooling sleeve are adjusted.

3. The method according to claim 2, characterized in that in: The prediction model is expressed as: Among them, y(k) represents the temperature prediction value corresponding to the k-th heating barrel, and u(k) represents the input control value corresponding to the k-th heating barrel. is a matrix describing the dynamic characteristics of the system; N is a positive integer representing the number of recursive steps; Based on the output corresponding to the current heating barrel and the input control amount corresponding to the historical heating barrel, the output corresponding to the next heating barrel is predicted, and the output represents the temperature prediction value.

4. The method according to claim 3, characterized in that The reference trajectory is expressed as: y c (k+1)=(1-α)y set (k)+αy(k) Among them, y set (k) represents the target temperature value corresponding to the k-th heating barrel, y(k) represents the actual temperature value corresponding to the k-th heating barrel, and y c (k+1) is the reference trajectory, indicating the reference temperature value corresponding to the k+1th heating barrel.

5. The method according to claim 4, characterized in that The objective function is expressed as: Among them, J represents the objective function, Q is the temperature error weight coefficient, and R is the energy consumption weight coefficient.

6. The method according to claim 1 or 5, characterized in that: The objective function is solved according to the set constraints, which include: the power range of the heater of each section of the heating barrel, the flow range of the cooling sleeve, and the speed range of the screw.

7. The method according to claim 1, characterized in that Also includes: The feed amount of each section of the heating barrel is input into the PID controller for feedforward compensation.

8. A heating control system for a rice noodle extruder, characterized in that: The system comprises a rice noodle extruder body and a control unit, wherein the rice noodle extruder body comprises a multi-section heating barrel, each section of the heating barrel is provided with a screw, a temperature sensor, a heater, and a cooling sleeve; The control unit contains: An information acquisition module is electrically connected to each section of the heating barrel to obtain the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw; The main control module is electrically connected to the information acquisition module and is used to start a temperature prediction program, including: The output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw are received as input control quantities of the prediction model, and the actual temperature value of each section of the heating barrel collected by the temperature sensor is used as the state quantity to establish a prediction model, and the prediction model outputs the predicted temperature value of each section of the heating barrel; A reference trajectory is constructed according to the given target temperature value of each section of the heating barrel and the measured temperature value of each section of the heating barrel; Establishing an objective function of rolling optimization according to the prediction model and the reference trajectory, and solving the objective function to obtain an optimal control amount; A PID controller, wherein the input end of the PID controller is electrically connected to the output end of the main control module, and the output end of the PID controller is electrically connected to the information acquisition module, so as to obtain the optimal control quantity, and adjust the output power of the heater of each section of the heating barrel, the flow rate of the cooling sleeve, and the speed of the screw according to the feedback of the optimal control quantity.

9. The system according to claim 8, characterized in that The control unit also includes a feedforward controller, which is electrically connected to the PID controller and is used to receive the feed amount of each section of the heating barrel as input to obtain a feedforward compensation amount, and input the feedforward compensation amount to the PID controller to compensate the output of the PID controller.

10. The system according to claim 8, characterized in that The multi-stage heating barrel comprises: A maturing section barrel, on which a plurality of temperature sensors, a plurality of heaters, and a plurality of cooling sleeves are arranged; The extrusion section barrel is connected to the output end of the maturing section barrel, and a plurality of temperature sensors, a plurality of heaters, and a plurality of cooling sleeves are arranged on the extrusion section barrel.

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