Prepreg Tape Tension Detection Method, Device and Medium Based on Extended State Observer

Abstract

The present invention discloses a method, device and medium for detecting the tension of prepreg tape based on an extended state observer. The method includes: performing dynamic analysis on the unwinding reel of an automatic tape laying machine to construct a tension model; converting the tension model into a state space equation, and constructing a tension state observer according to the state space equation; optimizing the tension state observer through a genetic algorithm based on the error between the tension estimated value output by the tension observer and the tension target value; obtaining the current corresponding to the unwinding torque, the real-time radius of the unwinding reel, and the conveying speed of the unwinding reel, and inputting them into the optimized tension state observer to obtain a tension estimated value; decoupling the tension estimated value by a controller to obtain a control signal, and controlling the unwinding torque through the control signal; inputting the unwinding torque into the tension model to obtain the actual tension value; setting a Lyapunov function, and judging whether the actual tension value is accurate through the Lyapunov function.

Description

Technical Field

[0001] The present invention relates to the field of composite prepreg tape tension detection, and particularly to a prepreg tape tension detection method, device and medium based on an extended state observer. Background Art

[0002] Compared with existing engineering materials, carbon fiber reinforced polymer (CFRP) has a relatively high specific strength and specific modulus, and is one of the commonly used lightweight materials in the fields of aerospace and the like. Carbon fiber composite materials have good fatigue resistance, vibration resistance and corrosion resistance, enabling components to have relatively high reliability and long service life. As the main equipment for forming composite components, the automatic tape laying machine for composite materials has been widely used in the manufacture of aircraft composite components due to its high production efficiency, reliability and stability of component quality. During the laying process of the automatic tape laying machine, the key factors affecting the laying quality include prepreg tape tension, laying speed, temperature, pressure, etc. Among them, the control of prepreg tape tension is particularly important. Tension fluctuations will cause defects such as bubbles, wrinkles and bridging in the laying of prepreg tape, directly affecting the appearance and strength of composite components. During the process of tension control, tension feedback is an important link, and the accuracy and feedback speed of tension detection directly affect the control accuracy and stability of the tension control system. If the tension detection accuracy is not up to standard, it may lead to the control system being unable to perform feedback adjustment according to the actual tension value, resulting in too large or too small prepreg tape tension, or even the breakage of the prepreg tape backing paper. Therefore, during the tension control process of the automatic tape laying machine, the detection of tension is crucial.

[0003] In the existing tape tension detection methods, the commonly used detection devices include spring rollers, strain gauge tension sensors and extended state observers (ESO).

[0004] Among them, when a spring roller is used as the tension detection device, the system has mechanical compliance, and the elastic deformation of its spring and the axial movement of the spring roller can effectively absorb the tension transient impact and reduce the risk of tape breakage. However, this detection method has various technical limitations: under dynamic conditions, the inertial effect and movement parameter fluctuations of the spring roller will introduce measurement errors, and only the accuracy can be guaranteed in the equilibrium state; in the calibration process, it is necessary to pre-calibrate the tension-displacement relationship under steady-state conditions, increasing the system debugging cycle and maintenance cost; in terms of hardware configuration, the purchase cost of a high-precision displacement sensor is similar to that of a traditional tension sensor, and the system design needs to consider the coordinated optimization between the spatial layout and the measurement accuracy. In addition, the installation of the displacement sensor needs to meet strict positioning tolerance requirements, which poses a higher challenge to the equipment structure design.

[0005] Compared with the spring roll detection method, the strain gauge type tension sensor has the advantages of high precision, small size, light weight, wide measurement range, high natural frequency, and fast dynamic response. However, the structure is relatively fixed and lacks a flexible element similar to the spring roll, without a buffering effect when the tension value changes suddenly, requiring the control system to have a higher dynamic response speed; the strain gauge type tension sensor also has problems such as high cost, susceptibility to environmental influence, and complex maintenance. In addition, in some special environments (such as high temperature, high humidity, strong vibration, etc.), it is difficult to guarantee the reliability and accuracy of the strain gauge type tension sensor.

[0006] Compared with the strain gauge type tension sensor, the Extended State Observer (ESO) has significant advantages and certain limitations. Its advantages lie in that it does not require the installation of an expensive tension sensor, reducing the hardware cost, while being able to estimate the tension value in real time, being applicable to dynamically changing scenarios, and having strong robustness to internal uncertainties and external disturbances. However, the performance of the ESO highly depends on the accuracy of the system model. If there are errors in model parameters such as the moment of inertia and damping coefficient, it will directly affect the accuracy of tension estimation. Summary of the Invention

[0007] Aiming at the deficiencies of the prior art, the present invention provides a method, device, and medium for detecting the tension of a prepreg tape based on an Extended State Observer.

[0008] In a first aspect, an embodiment of the present invention provides a method for detecting the tension of a prepreg tape based on an Extended State Observer, the method comprising:

[0009] Conduct a dynamic analysis on the unwind reel of an automatic tape laying machine to construct a tension model;

[0010] Convert the tension model into a state space equation, and construct a tension state observer according to the state space equation;

[0011] Based on the error between the tension estimated value output by the tension observer and the tension target value, optimize the tension state observer through a genetic algorithm;

[0012] Obtain the current corresponding to the unwind torque, the real-time radius of the unwind reel, and the conveying speed of the unwind reel, and input them into the optimized tension state observer to obtain a tension estimated value;

[0013] The tension estimated value is decoupled by a controller to obtain a control signal, and the unwind torque is controlled through the control signal; the unwind torque is input into the tension model to obtain the actual tension value;

[0014] Set a Lyapunov function, and judge whether the actual tension value is accurate through the Lyapunov function.

[0015] In a second aspect, an embodiment of the present invention provides an electronic device, comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein

[0018] The memory stores one or more computer programs executable by the at least one processor, and when the one or more computer programs are executed by the at least one processor, the at least one processor is enabled to execute the pre-impregnated tape tension detection method based on the extended state observer as described above.

[0019] In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the pre-impregnated tape tension detection method based on the extended state observer as described above is implemented.

[0020] In a fourth aspect, an embodiment of the present invention provides a computer program product, including a computer program / instructions, and when the computer program / instructions are executed by a processor, the above-mentioned pre-impregnated tape tension detection method is implemented.

[0021] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0022] The present invention provides a pre-impregnated tape tension detection method based on an extended state observer, which changes the pre-impregnated tape tension detection method from a traditional spring roller or a detection method based on a tension sensor to a measurement based on a tension state observer, constructs an accurate tension model, and optimizes the gain parameters in the tension state observer through a genetic algorithm , improves the global optimization ability of the tension state observer, avoids falling into local optima, realizes the improvement of tension detection accuracy by selecting the optimal solution of the gain parameter combination, and at the same time, the accurate tension model data can also improve the accuracy of tension estimation; this method also reduces the dependence on expensive sensors, avoids the physical limitations of sensors on working environments such as temperature and humidity, and reduces the system hardware cost. Description of the Drawings

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0024] Figure 1 It is a flowchart of the pre-impregnated tape tension detection method provided by an embodiment of the present invention;

[0025] Figure 2 It is a schematic structural diagram of a tape laying machine unwind reel provided by an embodiment of the present invention;

[0026] Figure 3 Schematic structural diagram of the tension state observer provided by an embodiment of the present invention;

[0027] Figure 4 Schematic diagram of an electronic device provided by an embodiment of the present invention. Specific embodiments

[0028] 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.

[0029] It should be noted that, without conflict, the features in the following embodiments and implementation manners can be combined with each other.

[0030] As Figure 1 and Figure 3 shown, a pre-impregnated tape tension detection method based on an extended state observer provided by an embodiment of the present invention includes the following steps:

[0031] Step S1: Perform dynamic analysis on the unwinding reel of the automatic tape laying machine to construct a tension model.

[0032] Specifically, as Figure 2 shown, in this example, the unwinding reel of the automatic tape laying machine is taken as the research object to analyze its force condition. In view of the fact that the unwinding mechanism uses a permanent magnet synchronous servo motor as the direct drive device, the dynamic parameters of the unwinding reel with the pre-impregnated material roll can be converted to the motor shaft end through an equivalent conversion method. Specifically, the moment of inertia, radius, and frictional torque of the unwinding reel can be converted to the motor side through the mechanical equivalent principle, so as to realize the unified modeling and analysis of the unwinding reel and the drive motor.

[0033] In this example, through the dynamic analysis of the unwinding reel of the automatic tape laying machine, the moment of inertia, radius, and frictional torque of the unwinding reel are converted to the motor side through the mechanical equivalent principle, thereby constructing a dynamic torque balance equation, and the expression is as follows:

[0034]

[0035] In the formula, represents the unwinding torque generated by the permanent magnet synchronous motor at time t; represents the pre-impregnated tape tension on the unwinding reel side at time t; represents the real-time radius of the unwinding reel; represents the total equivalent moment of inertia of the unwinding mechanism; represents the rotational angular velocity of the unwinding reel; represents the frictional torque of the unwinding mechanism.

[0036] It should be noted that in the unwinding shaft system of the automatic tape laying machine, the torque output by the servo motor acts as a resistance torque, and its acting direction is usually opposite to the rotation direction of the unwinding shaft. Therefore, in the dynamic torque balance equation, the variable should take a negative sign to accurately reflect the relationship between the torque direction and the motion state.

[0037] Further, in the tension model, the tension T is related to the time-varying parameters such as the output torque of the unwinding motor, the unwinding radius, the system moment of inertia, and the laying speed. The dynamic torque balance equation can be simplified accordingly for easy analysis of tension control. In this example, the dynamic torque balance equation is simplified based on the following assumptions:

[0038] (1) The thickness of the prepreg tape is only 0.12 mm, and the layer-by-layer laying method is adopted. The change in the unwinding shaft radius within a short time can be ignored;

[0039] (2) Based on assumption (1), the change in the moment of inertia of the unwinding shaft within the control period can be ignored;

[0040] (3) The unwinding system is driven by a permanent magnet synchronous servo motor, and the influence of the dry friction torque on the tension can be ignored;

[0041] (4) There is no relative sliding between the prepreg tape and the unwinding shaft, the guide wheel, and the pressure roller;

[0042] (5) There is no mass exchange between the prepreg tape and the environment, and volatilization, wear, etc. are ignored;

[0043] (6) The tensile strain of the prepreg tape satisfies the small deformation condition;

[0044] (7) The density, elastic modulus, etc. of the prepreg tape before stretching are constant along the length direction.

[0045] Specifically, the dynamic torque balance equation is simplified to obtain the tension model, and the expression is as follows:

[0046]

[0047] In the formula, represents the friction coefficient of the permanent magnet synchronous motor, represents the laying speed, represents the single-layer thickness of the prepreg tape, represents the density of the prepreg tape, represents the width of the prepreg tape, represents the mass of the unwinding shaft core, represents the radius of the unwinding shaft core. In this example, the tension of the prepreg tape It can be calculated by collecting data such as motor torque and laying speed and combining with a dynamic model. This tension can be used as a comparison quantity with the tension obtained by the tension observer to analyze the accuracy of the observer.

[0048] Step S2: Convert the tension model into a state-space equation, and construct a tension state observer according to the state-space equation.

[0049] Furthermore, convert the tension model into a state-space equation. The expression of the state-space equation is as follows:

[0050]

[0051] In the formula, and both represent the output tension T, represents the change rate of tension, represents the extended state variable, represents the input gain, represents the input variable; As a disturbance , including non-linear terms and external disturbances.

[0052] According to the state-space equation, the control algorithm for the tension state observer can be designed as:

[0053]

[0054] Among them, represents the estimated value of tension; represents the estimated value of the change rate of tension; represents the estimated value of the total disturbance; represents the system input deviation; represents the integration step size; represents the disturbance compensation amount; represents the output error correction gain coefficient; among them, represents the non-linear control function, that is, the output error correction law:

[0055]

[0056] Among them, represents the interval length of the continuous power function segment, which can be used to eliminate the oscillation of the system; is a non-linear exponent, representing the non-linear strength of the control function, where .

[0057] Linearize the tension state observer. Assume that the non-linear control function degenerates into linear feedback under small errors. Then the expression of the simplified tension state observer is as follows:

[0058]

[0059] wherein, represents the input deviation, represents the estimated value of the tension, represents the estimated value of the tension change rate, represents the estimated value of the total disturbance, represents the disturbance compensation amount, represents the output error correction gain coefficient.

[0060] Step S3: Based on the error between the estimated value of the tension output by the tension observer and the tension target value, optimize the tension state observer through the genetic algorithm.

[0061] Furthermore, construct an objective function, and the expression is as follows:

[0062]

[0063] wherein, represents the objective function, represents the weight coefficient, represents the input deviation, represents the output, represents the overshoot;

[0064] Construct a fitness function; the fitness function is an important index function for screening suitable individuals in the population and determines the quality of the solution. Usually, the fitness function is the reciprocal of the objective function, and the expression is as follows:

[0065]

[0066] wherein, represents the fitness function, represents the coefficient (in this example, is a very small real number to ensure that the denominator is not zero);

[0067] Encode the parameters to be optimized in the tension state observer;

[0068] Generate an initial population and calculate the fitness value of each individual according to the fitness function;

[0069] Perform crossover and / or mutation operations according to the fitness value of each individual, re-evaluate the fitness of each individual, and obtain the optimized output error correction gain coefficient .

[0070] It should be noted that for the tension state observer, based on the non-linear feedback effect of the tension state observer, if there is a constant , such that , it can be deduced that:

[0071]

[0072] The above formula shows that the state variables introduced by using ESO as the tension state observer can effectively estimate the tension and disturbance in the system. Further analysis shows that the parameter is the key parameter to be tuned, and its value directly affects the control performance of the active disturbance rejection controller and the accuracy of the tension state observer in estimating the disturbance and tension value.

[0073] Step S4, obtain the current corresponding to the unwinding torque, the real-time radius of the unwinding shaft, and the conveying speed of the unwinding shaft, and input them into the optimized tension state observer to obtain the tension estimation value.

[0074] Specifically, the torque of the unwinding motor Obtain the torque data through the permanent magnet synchronous motor model, build the servo motor model, and select the surface-mounted permanent magnet synchronous motor working in the torque mode. Its , build the motor model in the synchronous rotating coordinate system d-q, and adopt current vector control method. At this time, the stator voltage equation is:

[0075]

[0076] Among them, respectively represent the voltage components of the direct axis and the quadrature axis in the rotating coordinate system, represents the resistance of the stator winding, are the direct axis and quadrature axis components of the stator winding inductance respectively, is the electrical angular velocity of the motor rotor, is the rotor magnetic flux of the permanent magnet.

[0077] The current differential equation in the d-q coordinate is:

[0078]

[0079] The stator flux linkage equation is:

[0080]

[0081] Combining the above formulas, the relationship between the motor current and the motor output torque can be expressed as the electromagnetic torque equation, and the expression is as follows:

[0082]

[0083] Among them, is the torque constant of the servo motor, usually a fixed value. By measuring the quadrature axis current of the motor , and combined with the torque constant of the motor , the output torque of the motor can be calculated .

[0084] For servo motor control, the relationship between its speed and torque can be expressed by the motor motion equation, and the expression is as follows:

[0085]

[0086] Among them, is the mechanical angular velocity of the motor rotor, is the electromagnetic torque of the motor, is the load torque of the motor output shaft, is the moment of inertia of the motor output shaft, is the viscous friction coefficient of the motor output shaft.

[0087] The real-time radius of the unwinding reel is measured by a laser distance sensor. This sensor can dynamically collect the distance data between the surface of the coil on the unwinding reel and the sensor and transmit it to the control system. By combining the fixed distance from the distance sensor to the empty reel and the radius value of the unwinding reel core, a geometric model is constructed to accurately convert it into the instantaneous outer diameter value of the prepreg tape coil .

[0088] At this time, the conveying speed of the prepreg tape can be calculated according to the angular velocity of the motor shaft combined with the measured data of the unwinding radius through the formula .

[0089] Based on the tension model and the tension state observer, the input of the tension state observer is mainly the current signal that generates the unwinding torque, the real-time radius signal fed back by the laser sensor, and the conveying speed signal calculated by the controller. By collecting the above data, the input of the tension state observer can be realized, and the output tension can be obtained according to the tension observer model.

[0090] Step S5, the tension estimated value is decoupled by the controller to obtain a control signal, and the unwinding torque is controlled by the control signal; the unwinding torque is input into the tension model to obtain the actual tension value.

[0091] The expression of the controller is as follows:

[0092]

[0093] In the formula, , are control gains, is the tension tracking error, is the tension target value, is the estimated value of the tension output by the tension state observer, is the tracking error of the tension change rate, is the change rate of the tension target value, is the change rate of the estimated value of the tension output by the tension state observer, is the non - linear exponent, represents the interval length of the continuous power function segment, represents the disturbance compensation term, represents the estimated value of the total disturbance, represents the input gain.

[0094] Step S6: Set the Lyapunov function and determine whether the actual value of the tension is accurate through the Lyapunov function.

[0095] Set the Lyapunov function, and its expression is as follows:

[0096]

[0097] In the formula, represents the tension error, represents the tension change rate error, represents the disturbance error; the Lyapunov function represents the "energy" of the system, and the smaller its value, the smaller the observation error.

[0098] Judge the negative definiteness of the derivative of the Lyapunov function and optimize the output error correction gain coefficient in the tension state observer , so that the estimated value of the tension converges to the true value of the tension (that is, by optimizing to make ), thus ensuring the accuracy of the estimated value of the tension obtained by the tension observer.

[0099] In summary, the present invention provides a method for detecting the tension of a prepreg tape based on an extended state observer, which changes the prepreg tape tension detection method from the traditional spring roller or tension sensor - based detection method to measurement based on a tension state observer, constructs an accurate tension model, and optimizes the gain parameters in the tension state observer through a genetic algorithm , improves the global optimization ability of the tension state observer, avoids falling into local optima, realizes the improvement of the tension detection accuracy by selecting the optimal solution of the gain parameter combination, and at the same time, the accurate tension model data can also improve the accuracy of the tension estimation; this method also reduces the dependence on expensive sensors, avoids the physical limitations of sensors on working environments such as temperature and humidity, and reduces the system hardware cost.

[0100] Correspondingly, the present application further provides an electronic device, including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the pre-impregnated tape tension detection method based on the extended state observer as described above. As Figure 4 shown, it is a hardware structure diagram of any device with data processing capabilities where the pre-impregnated tape tension detection method based on the extended state observer provided by the embodiment of the present invention is located. In addition to Figure 4 the processors, memory, and network interfaces shown, any device with data processing capabilities where the device in the embodiment is located usually includes other hardware according to the actual functions of the device with data processing capabilities, which will not be elaborated here.

[0101] Correspondingly, the present application further provides a computer-readable storage medium, on which computer instructions are stored, and when the instructions are executed by a processor, the pre-impregnated tape tension detection method based on the extended state observer as described above is implemented. The computer-readable storage medium may be an internal storage unit of any device with data processing capabilities described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium may also be an external storage device, such as a plug-in hard disk, a smart media card (SMC), an SD card, a flash card, etc. equipped on the device. Further, the computer-readable storage medium may also include both the internal storage unit of any device with data processing capabilities and the external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capabilities, and may also be used to temporarily store the data that has been output or will be output.

[0102] Those skilled in the art will readily think of other implementation schemes of the present application after considering the specification and practicing the content disclosed herein. The present application is intended to cover any variations, uses, or adaptations of the present application, and these variations, uses, or adaptations follow the general principles of the present application and include the common general knowledge or conventional technical means in the technical field not disclosed in the present application. The specification and the embodiments are only regarded as exemplary.

[0103] It should be understood that the present application is not limited to the exact structure described above and shown in the drawings, and various modifications and changes can be made without departing from its scope.

Claims

1. A method for detecting the tension of a prepreg tape based on an expansion state observer, characterized in that: The method comprises: Conduct dynamic analysis on the unwinding shaft of the automatic tape laying machine and construct a tension model; The tension model is converted into a state space equation, and a tension state observer is constructed according to the state space equation; including: converting the tension model into a state space equation; the state space equation is used to express the relationship between the tension and its change rate and the expansion state variable, the input variable and the disturbance; constructing a tension state observer according to the state space equation, wherein the tension state observer is provided with an error correction gain coefficient and is used to estimate the tension and its change rate and compensate for the disturbance; Based on the error between the tension estimate output by the tension observer and the tension target value, the tension state observer is optimized by genetic algorithm. The current corresponding to the unwinding torque, the real-time radius of the unwinding shaft, and the conveying speed of the unwinding shaft are obtained, and input into the optimized tension state observer to obtain the tension estimation value; The tension estimation value is decoupled by the controller to obtain a control signal, and the unwinding torque is controlled by the control signal; the unwinding torque is input into the tension model to obtain the actual tension value; Set the Lyapunov function and use it to determine whether the actual tension value is accurate.

2. A method for detecting the tension of a prepreg tape based on an expansion state observer according to claim 1, characterized in that: The process of conducting dynamic analysis on the unwinding shaft of the automatic tape laying machine and constructing the tension model includes: The unwinding shaft of the automatic tape laying machine is subjected to dynamic analysis. The moment of inertia, radius and friction torque of the unwinding shaft are converted to the motor side through the mechanical equivalent principle, so as to construct the dynamic torque balance equation. The dynamic torque balance equation includes: the unwinding torque at time t is equal to the product of the prepreg tape tension on the unwinding shaft side at time t and the radius of the unwinding shaft, the product of the rate of change of the unwinding shaft moment of inertia and the angular velocity, the product of the unwinding shaft moment of inertia and the angular acceleration, and the sum of the friction torque of the unwinding shaft.

3. A method for detecting the tension of a prepreg tape based on an expansion state observer according to claim 1 or 2, characterized in that: The process of simplifying the dynamic moment balance equation to obtain the tension model includes: The prepreg tension on the unwinding shaft side is the unwinding torque divided by the real-time radius of the unwinding shaft, minus the product of the motor friction coefficient and the laying speed divided by the square of the real-time radius of the unwinding shaft, minus the nonlinear term determined by the single layer thickness, density, width, speed square and unwinding shaft core radius of the prepreg, and the additional term determined by the unwinding shaft core mass, speed square and real-time radius of the unwinding shaft.

4. The method for detecting the tension of a prepreg tape based on an expansion state observer according to claim 1, characterized in that: Based on the error between the tension estimate output by the tension observer and the tension target value, the process of optimizing the tension state observer by genetic algorithm includes: Construct the objective function; Construct a fitness function; Encoding the error correction gain coefficient to be optimized in the tension state observer; Generate the initial population and calculate the fitness value of each individual according to the fitness function; A crossover and / or mutation operation is performed according to the fitness value of each individual, the fitness of each individual is re-evaluated, and the optimized output error correction gain coefficient in the tension state observer is obtained.

5. The method for detecting the tension of a prepreg tape based on an expansion state observer according to claim 1, characterized in that: The process of decoupling the tension estimate value through the controller to obtain the control signal includes: The controller is used to generate a control signal according to an error between an estimated tension value and an actual tension value, an error in a tension change rate, and a disturbance compensation term; The control signal is used to adjust the unwinding torque so that the actual tension value approaches the estimated tension value.

6. The method for detecting the tension of a prepreg tape based on an expansion state observer according to claim 1, characterized in that: The process of setting the Lyapunov function and judging whether the actual tension value is accurate by the Lyapunov function includes: Set up the Lyapunov function; The negative definiteness of the derivative of the Lyapunov function is determined, and the output error correction gain coefficient in the tension state observer is optimized to make the tension estimate converge to the true value of the tension, thereby ensuring the accuracy of the tension estimate obtained by the tension observer.

7. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores one or more computer programs executable by the at least one processor, and the one or more computer programs are executed by the at least one processor to enable the at least one processor to perform the prepreg tape tension detection method based on an expansion state observer as described in any one of claims 1 to 6.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the computer program implements the prepreg tape tension detection method based on an expansion state observer according to any one of claims 1 to 6.

9. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the prepreg tape tension detection method based on an expansion state observer as described in any one of claims 1 to 6 is implemented.

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