A carbon fiber winding tension control method and device based on interference observation compensation

Abstract

The present invention belongs to the field of carbon fiber winding equipment control, and aims to solve the problem that various interference signals exist in the composite material winding molding process, and such disturbance signals will have a great impact on the winding tension. A carbon fiber winding tension control method and device based on interference observation compensation is provided, which includes the following steps: obtaining the position deviation signal of the rocker in the tension control system and the tension information at the yarn; controlling the unwinding speed of the servo motor based on the output of the fuzzy fractional-order PID controller to rebalance the rocker, and controlling the tension adjustment rod based on the output of the interference observer to compensate for the unknown interference signal; completing the tension control in the tension control system based on the cooperation of the fuzzy fractional-order PID controller and the interference observer. The present invention significantly enhances the robustness and adaptability of the system in the face of parameter changes and external interference, so that the system can maintain high-precision control effects even in complex and changing environments.

Description

Technical Field

[0001] The present invention belongs to the field of carbon fiber winding equipment control, and in particular relates to a carbon fiber winding tension control method and device based on interference observation compensation. Background Art

[0002] Filament winding, an advanced composite molding process, creates composite products with high strength, stiffness, and excellent structural properties by tightly wrapping continuous fiber material around a core mold or preform along a predetermined path and angle. This technology precisely controls fiber tension, winding angle, and interlayer structure to optimize material properties. Widely used in aerospace, pressure vessels, piping, sports equipment, and other fields, it is a key means of improving product performance and achieving lightweight design.

[0003] However, during the composite winding process, various interference signals often exist. These disturbances can significantly affect winding tension, and in severe cases, can even disrupt the stability of the tension control system, leading to uncontrollable system failure. Winding tension is a critical process parameter in the winding process, and its control accuracy directly impacts fiber orientation, resin impregnation, and the strength and durability of the final product. Summary of the Invention

[0004] In order to solve at least one of the above technical problems existing in the prior art, the present invention provides a carbon fiber winding tension control method and device based on interference observation compensation.

[0005] The present invention is implemented by the following technical solution: a carbon fiber winding tension control method based on interference observation compensation, comprising the following steps:

[0006] Based on the physical characteristics of the controlled system, a fractional-order mathematical model of the tension control system is established;

[0007] A fuzzy fractional-order PID controller is established to adjust the unwinding speed.

[0008] A disturbance observer is established to achieve observation compensation for unknown disturbances. The disturbance observer includes an inverse filter, a second-order auxiliary filter, and an interference compensator. The steps of constructing the disturbance observer are as follows: designing an inverse filter to stimulate the interference characteristics of an error signal and convert the error signal into a measurable signal; constructing a second-order auxiliary filter to establish a relationship between the interference frequency and the input disturbance, expressing the input disturbance as a parameter form with respect to a virtual disturbance, and then inversely calculating the input disturbance by successively reducing the order; and constructing an interference compensator to reconstruct the disturbance signal and perform feedforward compensation on the disturbance signal.

[0009] Obtaining the position deviation signal of the swing rod in the tension control system and the tension information at the yarn;

[0010] The output of the fuzzy fractional-order PID controller is controlled based on the position deviation signal of the pendulum, and the output of the disturbance observer is controlled based on the tension information at the yarn.

[0011] The output of the fuzzy fractional-order PID controller is used to control the unwinding speed of the servo motor to rebalance the pendulum. At the same time, the output of the disturbance observer is used to control the tension adjustment lever to compensate for unknown interference signals. The coordination of the fuzzy fractional-order PID controller and the disturbance observer completes the tension control in the tension control system.

[0012] Among them, the transfer function of the fractional-order mathematical model of the tension control system is The expression is:

[0013]

[0014] Where, is the fractional order mathematical model of permanent magnet synchronous motor, ,in is the torque constant, is the electrical time constant, is the mechanical time constant, is the order of the electromagnetic link, and , is the mechanical link order, and ; is the controller gain parameter; is the motor reducer parameter; is the control system gain parameter; is the sensor gain parameter; is the radius of the yarn ball; is the complex frequency in the Laplace transform domain;

[0015] Transfer Function of Fuzzy Fractional-Order PID Controller for:

[0016]

[0017] Where, is the proportional coefficient of the fractional-order PID controller; is the integral coefficient of the fractional-order PID controller; is the differential coefficient of the fractional-order PID controller; is the integral order of the fractional-order PID controller, and ; is the differential order of the fractional-order PID controller, and ;

[0018] The expression of the inverse filter is:

[0019]

[0020] In the formula is the coefficient matrix The corresponding numerator and denominator polynomials; The order of express; It is composed of first-order inertia links connected in series. is a parameter to be determined;

[0021] The expression of the second-order auxiliary filter is:

[0022]

[0023] Where, , , is the internal signal of the auxiliary filter, , is a parameter to be determined, A detectable signal.

[0024] The present invention also provides a carbon fiber winding tension control device based on interference observation compensation, comprising an unwinding roller, a motor reducer, a cylinder, an angle sensor, a swing arm, a dipping tank, a tension adjustment rod, a pressure sensor, a winding core mold, an A / D conversion module, a host computer, a PLC controller, a servo driver, an electric proportional valve, a servo motor and an interference observer;

[0025] The unwinding roller is used to unwind the fiber yarn, and the unwinding speed of the unwinding roller is controlled by a servo motor and a motor reducer. The cylinder, angle sensor and pendulum constitute the detection mechanism of the tension control system. After the winding tension is set, the PLC controller controls the electric proportional valve to make the cylinder apply a constant force to the pendulum. When the tension on the yarn is equal to the constant force applied by the cylinder, the pendulum is in a balanced position. When the tension on the yarn is not equal to the constant force applied by the cylinder, the pendulum deviates from the balanced position. The angle sensor detects the position deviation signal and transmits it to the PLC controller. The PLC controller controls the output through PID control and controls the yarn tension by changing the unwinding speed to restore the balance of the pendulum.

[0026] The dipping tank is used to dip the yarn in glue. The pressure sensor collects tension information in real time. After passing through the A / D conversion module, the real-time tension is transmitted to the host computer. The interference observer reconstructs the interference signal in Matlab. After reconstruction, the interference variable is transmitted to the DB data block of the TIA Portal through the TCP / IP protocol. The PLC controller controls the tension adjustment rod based on the interference variable to compensate for the unknown interference signal.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The present invention successfully applies the tension fluctuation suppression strategy based on feedforward compensation to the field of carbon fiber winding tension control. At the same time, an interference observer consisting of an inverse filter, a second-order auxiliary filter and an interference compensator is designed. The observer can estimate and compensate for interference signals of specific frequencies. Its design method is independent of the controller structure. By establishing a relationship between the interference frequency and the virtual interference, the input interference is inferred using the estimated value of the virtual interference, without the need to estimate the equivalent interference state, which significantly reduces the computational complexity. In addition, the present invention combines conventional PID controllers with fuzzy control principles and fractional-order theory to propose a fuzzy fractional-order PID controller, which not only enhances the robustness and adaptability of the system in the face of parameter changes and external interference, but also improves the control accuracy through the intelligent adjustment mechanism of fuzzy logic, optimizes the dynamic response and static stability of the system, reduces overshoot and shortens the adjustment time. At the same time, the controller exhibits strong anti-interference ability, ensuring stable operation of the system. Finally, the present invention constructs a carbon fiber winding tension control system with Siemens PLC as the core, uses TIA Portal V18 software for software and hardware configuration and PLC program writing, establishes communication with S7-1200PLC through TIA Portal, MATLAB, realizes data interaction function, and completes the tension control of the entire winding process. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 A flow chart illustrating the implementation of tension control in the present invention;

[0031] Figure 2 It is a composition diagram of the tension control system of the present invention;

[0032] Figure 3 is a transfer function block diagram of the entire tension control system of the present invention;

[0033] Figure 4 It is the principle diagram of the fuzzy adaptive fractional-order PID controller of the present invention;

[0034] Figure 5 is a schematic diagram of the interference observer of the present invention;

[0035] Figure 6This is a schematic diagram of the inverse filter structure of the present invention;

[0036] Figure 7 This is a schematic diagram of the structure of the second-order auxiliary filter of the present invention;

[0037] Figure 8 Output curve graph of the tension control system of the present invention;

[0038] Figure 9 This is an interference compensation effect diagram of the present invention;

[0039] Figure 10 This is the interference compensation error diagram of the present invention.

[0040] In the figure: 1-unwinding roller; 2-motor reducer; 3-cylinder; 4-angle sensor; 5-rocker; 6-glue dipping tank; 7-tension adjustment rod; 8-pressure sensor; 9-winding core mold; 10-A / D conversion module; 11-host computer; 12-PLC controller; 13-servo drive; 14-electric proportional valve; 15-servo motor; 16-interference observer. DETAILED DESCRIPTION

[0041] The technical solutions in the embodiments of the present invention are clearly and completely described in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other implementations derived by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts are within the scope of protection of the present invention.

[0042] It should be noted that the structures, proportions, sizes, etc. illustrated in the drawings of this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the conditions under which the present invention can be implemented. Therefore, they have no substantive technical significance. Any structural modification, change in proportional relationship or adjustment of size should fall within the scope of the technical content disclosed in the present invention without affecting the efficacy and purpose that can be achieved by the present invention. It should be noted that in this specification, relational terms such as first and second are only used to distinguish one entity from several other entities, and do not necessarily require or imply any actual relationship or order between these entities.

[0043] The present invention provides an embodiment:

[0044] like Figures 1 to 10 As shown, a carbon fiber winding tension control method based on interference observation compensation includes the following steps:

[0045] Obtaining the position deviation signal of the swing rod in the tension control system and the tension information at the yarn;

[0046] The output of the fuzzy fractional-order PID controller is controlled based on the position deviation signal of the pendulum, and the output of the disturbance observer is controlled based on the tension information at the yarn.

[0047] The unwinding speed of the servo motor is controlled based on the output of the fuzzy fractional-order PID controller to rebalance the pendulum. At the same time, the tension adjustment rod is controlled based on the output of the disturbance observer to compensate for the unknown disturbance signal. The tension control in the tension control system is completed based on the cooperation of the fuzzy fractional-order PID controller and the disturbance observer.

[0048] Before obtaining the position deviation signal of the swing rod and the tension information at the yarn in the tension control system, the following steps are required:

[0049] Based on the physical characteristics of the controlled system, a fractional-order mathematical model of the tension control system is established;

[0050] A fuzzy fractional-order PID controller (FZFOPID controller) is established to adjust the unwinding speed.

[0051] A disturbance observer is established to realize observation compensation for unknown disturbances. The disturbance observer includes an inverse filter, a second-order auxiliary filter and an disturbance compensator.

[0052] In this embodiment, the core components of the tension control system, such as the unwinding roller 1, motor reducer 2, cylinder 3, angle sensor 4, rocker arm 5, and servo motor 15, are dynamically analyzed, and the fractional-order characteristics of the permanent magnet synchronous servo motor are studied. On this basis, the fractional-order mathematical model of the tension control system is established.

[0053] Specifically, the motion model of the actuator unwinding roller is expressed as:

[0054] (1)

[0055] Where, is the yarn tension, is the real-time radius of the yarn ball, is the motor braking torque, is the motor moment of inertia, is the spindle moment of inertia, is the angular velocity of the yarn ball, is the core radius, and the yarn density is , the yarn width is , the yarn thickness is , is the acceleration due to gravity.

[0056] The simplified motion model of the actuator rocker is expressed as:

[0057] (2)

[0058] Where, is the moment of inertia of the pendulum, is the first derivative of the pendulum’s angular velocity, is the cylinder output force, is the cylinder force arm, is the angle between the cylinder force and the rocker arm, is the force arm of the fiber tension, is the yarn tension, is the angle between the fiber extension direction and the pendulum, is the angle between the pendulum and the horizontal.

[0059] The mathematical model of permanent magnet synchronous motor is basically the same as that of ordinary motor. The fractional order mathematical model of permanent magnet synchronous motor can be Expressed as:

[0060] (3)

[0061] is the electromagnetic link order, The order of the mechanical link. They are torque constant, mechanical time constant, and electrical time constant, respectively, which can be obtained from the model nameplate parameters of the permanent magnet synchronous motor. The permanent magnet synchronous motor model used in this embodiment is: 1FL6034-2AF21-1AA1, and the motor reducer model is: PRF60-L2-20.

[0062] Through the above analysis of the dynamic relationship of the tension control system in the fiber winding process and the establishment of the fractional-order mathematical model of the servo motor, the transfer function framework of the entire tension control system can be obtained. Figure 3 , based on the transfer function of the fractional order mathematical model of the tension control system The expression is:

[0063] (4)

[0064] Where, is the controller gain parameter; is the motor reducer parameter; is the control system gain parameter; is the sensor gain parameter; is the radius of the yarn ball;

[0065] In this embodiment, Siemens S7-1200 PLC and V90 servo drive are used, and the parameter values are as shown in the following table.

[0066] Table 1 Parameter values

[0067]

[0068] Finally determine the transfer function of the fractional order mathematical model of the tension control system The expression is:

[0069] (5)

[0070] The state space expression of the tension control system with disturbance is:

[0071]

[0072] in: , , , , , are system state, control input, output signal, equivalent bounded disturbance, and unknown disturbance, respectively. R is the set of real numbers, R n for n -dimensional real vector; is the coefficient matrix, given by the transfer function It can be directly decomposed into dynamic equations and obtained.

[0073] Establish a fuzzy fractional-order PID controller. By combining the fuzzy control principle with the fractional-order theory, a new fuzzy adaptive fractional-order PID controller is designed. Its basic structure is as follows: Figure 4 The controller consists of two parts, one is the fuzzy controller, which adopts a two-input five-output control structure. and deviation rate As input, Controller parameters As output, its value is based on and Real-time adjustment of changes, is the initial setting value of the controller parameters. The actual fractional-order controller parameters can be calculated as:

[0074] (6)

[0075] Input variables , and output variables The fuzzy subsets are all set to [NB NM NSZE PS PM PB], and the input domain is selected , The output domain is [-3, 3] is [-3, 3], The input variable is [0, 1]. , The membership function adopts Gaussian membership function, and the output variable The membership function adopts triangular membership function.

[0076] Transfer Function of Fuzzy Fractional-Order PID Controller for:

[0077]

[0078] Where, is the proportional coefficient of the fractional-order PID controller; is the integral coefficient of the fractional-order PID controller; is the differential coefficient of the fractional-order PID controller; is the integral order of the fractional-order PID controller, and ; is the differential order of the fractional-order PID controller, and .

[0079] The steps to construct a disturbance observer are as follows:

[0080] Design an inverse filter to stimulate the interference characteristics of the error signal and convert it into a measurable signal;

[0081] Construct a second-order auxiliary filter, establish the relationship between the interference frequency and the input interference, express the input interference as a parameter form of virtual disturbance, and then reversely infer the input interference by successively reducing the order;

[0082] The interference compensator reconstructs the interference signal and performs feed-forward compensation on the interference signal.

[0083] In this embodiment, the disturbance observer consists of three parts: an inverse filter, a second-order auxiliary filter, and a disturbance compensator. The control input is defined as , is the output of the fractional-order PID controller; is the interference estimation signal; the error signal is ,in is the output signal of the system reference model, Output signal to the controlled object.

[0084] Closed-loop system from arrive The error transfer function Expressed as:

[0085] (7)

[0086] in, is the integer-order open-loop transfer function of the controlled system; is the gain matrix of the system reference model; design To satisfy is the Hurwitz matrix; is the coefficient matrix The corresponding numerator and denominator polynomials; The order of express;

[0087] The inverse filter is designed to stimulate the interference characteristics of the error signal and convert it into a measurable signal. The reverse dynamics It is connected in series with the first-order inertia link and can be used Figure 6 The inverse filter is described as:

[0088] (8)

[0089] In the formula It is composed of first-order inertia links connected in series. To be determined parameters.

[0090] Combine Figure 6 , It can be defined as:

[0091] (9)

[0092] In the formula is a measurable signal;

[0093] From this we can get the following relationship:

[0094] (10)

[0095] In the formula for The time domain form after Laplace transform.

[0096] Further, Described as:

[0097] (11)

[0098] in: is an unknown interfering virtual signal, is the attenuation term, is an equivalent bounded interference signal, Assumptions:

[0099] (12)

[0100] for The first-order derivative of , combined with formula (11) and Figure 6 Available and The following relationship is satisfied:

[0101] (13)

[0102] They are The complex frequency domain form after Laplace transform.

[0103] From the above analysis, we can see that the inverse filter can stimulate the error signal The interference characteristics of Decomposed into unknown interfering virtual signal, equivalent bounded interference and attenuation term.

[0104] like Figure 7 Shown: Output signal using inverse filter , reverse Second, an estimate of the unknown interference can be obtained.

[0105] To facilitate analysis, define Figure 7 middle is the virtual interference estimate, , is a parameter to be determined, , , It is about the undetermined parameters , function, , , is the internal signal of the auxiliary filter, which can be described as:

[0106] (14)

[0107] Where, , , is the internal signal of the auxiliary filter, , To be determined parameters.

[0108] Laplace transform this formula and combine it have to:

[0109] (15)

[0110] Where, for The second derivative of for The first-order derivative of ; further we can get:

[0111] (16)

[0112] Given the theorem: If there exists a vector function If the above formula is satisfied, then the unknown virtual interference signal It can be described as:

[0113] (17)

[0114] in: is transposed; is the attenuation term; satisfy:

[0115] (18)

[0116] (19)

[0117] (20)

[0118] Proof: In There is a vector satisfy:

[0119] (twenty one)

[0120] in: It can be described as:

[0121] (twenty two)

[0122] in: ; is the attenuation term and satisfies:

[0123] (twenty three)

[0124] therefore, It can be further expressed as:

[0125] (twenty four)

[0126] Then, combining equations (11), (15) and (21), we can obtain:

[0127] (25)

[0128] According to formula (25), let , and bring it into (24), it can be simplified to the form of (17).

[0129] Combining (17) and Figure 7 , the interference estimation signal can be Described as:

[0130] (26)

[0131] in satisfy:

[0132] (27)

[0133] when Pick When , combining (26) and (27), we can see that there is make Described as:

[0134] (28)

[0135] Unknown interference estimation error Convergence analysis:

[0136] Combining equations (17) and (26), we can obtain:

[0137] (29)

[0138] Estimation error of unknown interference Establishing Lyapunov function :

[0139] (30)

[0140] Combining equations (12) and (18), we can obtain:

[0141] (31)

[0142] in:

[0143] (32)

[0144] in is a real symmetric matrix, because is a Hurwitz matrix, and , according to the Hurwitz matrix properties, we can get It is not difficult to conclude ( for ). Therefore is asymptotically convergent. And because is bounded, so Asymptotically converges; similarly, when Pick When Asymptotically convergent.

[0145] The designed FZFOPID controller and disturbance observer are simulated and verified using SIMULINK and S-function editor on MATLAB platform. The unit step signal is used as the reference tension input, and the system is considered to be disturbed by multiple sources. A standard sinusoidal interference signal is added to the system input channel. The parameters of the disturbance observer to be determined are: ; , , , , , , , . Initial parameters of fuzzy fractional-order PID controller , , , , The output curve of the tension control system is as follows: Figure 8 shown.

[0146] There are unknown disturbances in the system When, such as Figure 9 、 10 As shown by the dotted line, when the target tension is set to 20N, the PID controller can suppress the disturbance to a certain extent, making the tension output stable at 3N range, but after adding the designed disturbance observer compensation, the unknown disturbance can be greatly reduced, making the tension output stable at In the 0.2N range, the effect of unknown interference is almost offset.

[0147] The present invention also provides a carbon fiber winding tension control device based on interference observation compensation, comprising an unwinding roller 1, a motor reducer 2, a cylinder 3, an angle sensor 4, a swing arm 5, a dipping tank 6, a tension adjustment rod 7, a pressure sensor 8, a winding core mold 9, an A / D conversion module 10, a host computer 11, a PLC controller 12, a servo driver 13, an electric proportional valve 14, a servo motor 15 and an interference observer 16;

[0148] The unwinding roller 1 is used for unwinding the fiber yarn, and the unwinding speed of the unwinding roller 1 is controlled by the servo motor 15 and the motor reducer 2; the cylinder 3, the angle sensor 4 and the rocker 5 constitute the detection mechanism of the tension control system. After the winding tension is set, the PLC controller 12 controls the electric proportional valve 14 to make the cylinder 3 apply a constant force to the rocker 5. When the tension on the yarn is equal to the constant force applied by the cylinder 3, the rocker 5 is in a balanced position. When the tension on the yarn is not equal to the constant force applied by the cylinder 3, the rocker 5 deviates from the balanced position. The angle sensor 4 detects the position deviation signal and transmits it to the PLC controller 12. The controller controls the output through PID control and controls the yarn tension by changing the unwinding speed to restore the balance of the rocker 5.

[0149] The dipping tank 6 is used to dip the yarn in glue. The pressure sensor 8 collects tension information in real time. After passing through the A / D conversion module 10, the real-time tension is transmitted to the host computer 11. The interference observer 16 reconstructs the interference signal in MATLAB. After reconstruction, the interference variable is transmitted to the DB data block of the TIA Portal through the TCP / IP protocol. The PLC controller 12 controls the tension adjustment rod 7 based on the interference variable to compensate for the unknown interference signal.

[0150] The foregoing description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be readily conceived by a person skilled in the art within the technical scope disclosed herein should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A carbon fiber winding tension control method based on interference observation compensation, characterized in that: The following steps are involved: Based on the physical characteristics of the controlled system, a fractional-order mathematical model of the tension control system is established; A fuzzy fractional-order PID controller is established to adjust the unwinding speed. A disturbance observer is established to achieve observation compensation for unknown disturbances. The disturbance observer includes an inverse filter, a second-order auxiliary filter, and an interference compensator. The steps of constructing the disturbance observer are as follows: designing an inverse filter to stimulate the interference characteristics of an error signal and convert the error signal into a measurable signal; constructing a second-order auxiliary filter to establish a relationship between the interference frequency and the input disturbance, expressing the input disturbance as a parameter form with respect to a virtual disturbance, and then inversely calculating the input disturbance by successively reducing the order; Construct an interference compensator, reconstruct the interference signal, and perform feedforward compensation on the interference signal; Obtaining the position deviation signal of the swing rod in the tension control system and the tension information at the yarn; The output of the fuzzy fractional-order PID controller is controlled based on the position deviation signal of the pendulum, and the output of the disturbance observer is controlled based on the tension information at the yarn. The output of the fuzzy fractional-order PID controller is used to control the unwinding speed of the servo motor to rebalance the pendulum. At the same time, the output of the disturbance observer is used to control the tension adjustment lever to compensate for unknown interference signals. The coordination of the fuzzy fractional-order PID controller and the disturbance observer completes the tension control in the tension control system. Among them, the transfer function of the fractional-order mathematical model of the tension control system is The expression is: Where, is the fractional order mathematical model of permanent magnet synchronous motor, ,in is the torque constant, is the electrical time constant, is the mechanical time constant, is the order of the electromagnetic link, and , is the mechanical link order, and ; is the controller gain parameter; is the motor reducer parameter; is the control system gain parameter; is the sensor gain parameter; is the radius of the yarn ball; is the complex frequency in the Laplace transform domain; Transfer Function of Fuzzy Fractional-Order PID Controller for: Where, is the proportional coefficient of the fractional-order PID controller; is the integral coefficient of the fractional-order PID controller; is the differential coefficient of the fractional-order PID controller; is the integral order of the fractional-order PID controller, and ; is the differential order of the fractional-order PID controller, and ; The expression of the inverse filter is: In the formula is the coefficient matrix The corresponding numerator and denominator polynomials; The order of express; It is composed of first-order inertia links connected in series. is a parameter to be determined; The expression of the second-order auxiliary filter is: Where, , , is the internal signal of the auxiliary filter, , is a parameter to be determined, A detectable signal.

2. A carbon fiber winding tension control device based on interference observation compensation, used to implement the carbon fiber winding tension control method based on interference observation compensation as claimed in claim 1, characterized in that: It includes an unwinding roller (1), a motor reducer (2), a cylinder (3), an angle sensor (4), a swing arm (5), a dipping tank (6), a tension adjustment rod (7), a pressure sensor (8), a winding core mold (9), an A / D conversion module (10), a host computer (11), a PLC controller (12), a servo driver (13), an electric proportional valve (14), a servo motor (15) and a disturbance observer (16); The unwinding roller (1) is used for unwinding the fiber yarn, and the unwinding speed of the unwinding roller (1) is controlled by a servo motor (15) and a motor reducer (2); the cylinder (3), the angle sensor (4) and the swing rod (5) constitute a detection mechanism of the tension control system. After the winding tension is set, the PLC controller (12) controls the electric proportional valve (14) to make the cylinder (3) apply a constant force to the swing rod (5). When the tension on the yarn is equal to the constant force applied by the cylinder (3), the swing rod (5) is in a balanced position. When the tension on the yarn is not equal to the constant force applied by the cylinder (3), the swing rod (5) deviates from the balanced position. The angle sensor (4) detects the position deviation signal and transmits it to the PLC controller (12). The PLC controller (12) controls the output through PID control and controls the yarn tension by changing the unwinding speed, so that the swing rod (5) is rebalanced. The dipping tank (6) is used for dipping the yarn in glue. The pressure sensor (8) collects tension information in real time. After passing through the A / D conversion module (10), the real-time tension is transmitted to the host computer (11). The interference observer (16) reconstructs the interference signal in MATLAB. After reconstruction, the interference variable is transmitted to the DB data block of the TIA Portal through the TCP / IP protocol. The PLC controller (12) controls the tension adjustment rod (7) based on the interference variable to compensate for the unknown interference signal.

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