Chain type scraper speed regulation control method of fixed time extended state observer

Abstract

The invention discloses a chain type scraper speed regulation control method of a fixed time extended state observer, and relates to a chain type scraper speed regulation system, comprising the following steps: converting a permanent magnet synchronous motor current model containing a disturbance term into a local model; setting a sampling period, discretizing the local model, and establishing a permanent magnet synchronous motor expansion state space model containing disturbance terms; defining a current error increment and a disturbance error increment, and establishing an expansion increment model of current prediction; designing a fixed-time convergence extension state observer, and discretizing the fixed-time convergence extension state observer; designing a cost function including a current tracking error and a voltage increment error; and designing a composite controller based on the fixed time convergence extension state observer and the cost function. According to the method, the robustness and the response speed of the system can be remarkably improved under the complex load change and disturbance conditions, and the performance loss caused by response lag in a traditional control method is effectively reduced.

Description

Technical Field

[0001] The invention relates to the technical field of chain scraper speed regulation systems, in particular to a chain scraper speed regulation control method of a fixed time extended state observer. Background Art

[0002] With the acceleration of the global industrialization process, automation and intelligent technology are increasingly used in all walks of life, especially in the field of heavy-duty material transportation. As an important link in energy transportation, the railway bulk cargo unloading operation has become a technical problem that needs to be solved urgently in terms of efficiency improvement and automation level. As an efficient material conveying equipment, the chain scraper conveyor system plays a key role in the transportation of bulk materials such as coal and ore. The system drives the scraper along the track through the motor-driven chain, thereby realizing continuous and efficient transportation of materials.

[0003] However, chain scraper conveyor systems face many technical challenges in practical applications. First, the device is usually affected by factors such as load fluctuations, changes in material stacking patterns, and uneven coal compaction during operation. These factors lead to dynamic changes in the load, especially when there are large load fluctuations or sudden changes in the load, the stability and control accuracy of the system are often difficult to guarantee. Secondly, since the equipment often operates in harsh and complex working conditions, traditional control strategies are unable to cope with sudden load changes, external disturbances, and system uncertainties. How to maintain efficient and stable operation of the equipment under load changes, nonlinear disturbances, and uncertainties has become a key problem in improving the performance of chain scraper conveyor systems.

[0004] At present, although traditional control methods such as PID control and conventional model predictive control (MPC) methods can optimize motor speed regulation to a certain extent, they often cannot effectively maintain the stability and accuracy of the system in the face of large load fluctuations, complex disturbances, etc. Traditional control methods fail to fully consider the unforeseen disturbances and nonlinear characteristics in the system, resulting in delayed response during operation and low control accuracy. Summary of the invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a chain scraper speed control method of a fixed-time extended state observer to solve the problem of how to achieve efficient, stable and precise control of a chain scraper conveying system under complex load fluctuations and disturbance environments.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] The present invention provides a chain scraper speed control method of a fixed-time extended state observer, which comprises the following steps: based on a permanent magnet synchronous motor current model containing a disturbance term, converting the model into a local model; setting a sampling period, discretizing the local model, and establishing an extended state space model of the permanent magnet synchronous motor containing a disturbance term; defining a current error increment and a disturbance error increment, and establishing an extended increment model for current prediction; designing a fixed-time convergent extended state observer and discretizing the observer; designing a cost function containing a current tracking error and a voltage increment error; and designing a composite controller based on the fixed-time convergent extended state observer and the cost function to adjust the speed and torque of the motor.

[0009] As a preferred solution of the chain scraper speed control method of the fixed time extended state observer described in the present invention, the permanent magnet synchronous motor current model containing the disturbance term is:

[0010]

[0011] Among them, L d , L q They are the motor d-axis inductance and q-axis inductance respectively; i d 、i q are the motor d-axis current and q-axis current respectively; R is the stator resistance of the motor; P is the number of pole pairs of the motor; ω m is the mechanical angular velocity of the motor; is the permanent magnet link flux of the motor; u d and u q are the d-axis voltage and the q-axis voltage respectively; f d and f q They are d-axis disturbance and q-axis disturbance, respectively, representing the disturbance of the system or the change of external load.

[0012] As a preferred solution of the chain scraper speed control method of the fixed time extended state observer of the present invention, wherein: the local model is,

[0013]

[0014] Among them, F d 、F q is the total disturbance set generated by the motor parameter changes and disturbance terms; ΔR, ΔL d , ΔL q , are the increments of stator resistance, d-axis inductance, q-axis inductance and permanent magnet flux respectively.

[0015] As a preferred solution of the chain scraper speed control method of the fixed time extended state observer described in the present invention, the sampling period is set to T s, the local model is discretized as,

[0016]

[0017] Set in the forecast period T s Internal disturbance F d 、F q Keep unchanged, select i d (k), i q (k), F d 、F q is the system state variable, then the permanent magnet synchronous motor extended state space model containing disturbance terms is:

[0018] x(k+1)=Ax(k)+Bu(k)

[0019] y(k)=Cx(k)

[0020] In the formula, i d (k+1) and i q (k+1) represents the motor d-axis current and the motor q-axis current at time k+1 respectively, x(k+1) represents the state vector of the system at time k+1, y(k) represents the control input vector at time k, A represents the state transfer matrix, B is the control input matrix, and C is the output matrix.

[0021] As a preferred solution of the chain scraper speed control method of the fixed time extended state observer of the present invention, wherein: the d-axis current error increment is set to d(k), the q-axis current error increment is set to q(k), and the d-axis disturbance error increment is set to ΔF d (k), the q-axis disturbance error increment is set to ΔF q (k), the extended incremental model of current prediction is expressed as,

[0022]

[0023] As a preferred solution of the chain scraper speed control method of the fixed time extended state observer of the present invention, wherein: the fixed time convergence extended state observer includes d-axis and q-axis current fixed time convergence extended state observers, and the d-axis current fixed time convergence extended state observer is expressed as:

[0024]

[0025] The fixed-time convergent extended state observer of the q-axis current is expressed as,

[0026]

[0027] in, id 、i q The estimated value of 1d 、e 1q are the d-axis and q-axis current observation errors respectively; φ 1d ,φ 1q are the disturbance F d 、F q ; F 0d 、F 0q are the estimated values ​​of disturbances on the d-axis and q-axis respectively; e 2d 、e 2q are the disturbance observation errors of d-axis and q-axis respectively; k 1d , k 2d , k 1q , k 2q are adjustable parameters; b and θ are adjustable parameters.

[0028] As a preferred solution of the chain scraper speed control method of the fixed time extended state observer of the present invention, after the fixed time convergence extended state observer is discretized, the d-axis current discretized fixed time convergence extended state observer is expressed as:

[0029]

[0030] The q-axis current discretization fixed-time convergence extended state observer is expressed as:

[0031]

[0032] As a preferred solution of the chain scraper speed control method of the fixed time extended state observer of the present invention, wherein: the cost function is expressed as,

[0033]

[0034]

[0035] Among them, the current sampling period is k and the prediction period is N p , the control period is N c , k+j is the jth prediction period starting from time k, is the d-axis and q-axis current value of the observer at time k+j, i ref (k+j) is the d and q axis current reference value at time k+j, Δu(k+j) is the d and q axis voltage increment at time k+j, Q is the current error weight, R is the input voltage increment weight, is the expression of the Laguerre function obtained by Z transform in the time domain, is the Laguerre correlation coefficient.

[0036] As a preferred solution of the chain scraper speed control method of the fixed time extended state observer described in the present invention, the composite controller is expressed as u(k+1)=u(k)+Δu(k+1).

[0037] The beneficial effects of the present invention are as follows: by combining the fixed-time extended state observer with the model predictive control method, the present invention significantly improves the robustness and response speed of the system under complex load changes and disturbance conditions. The fixed-time convergence feature enables the system to quickly converge to a steady state within a set time, thereby effectively reducing the performance loss caused by response lag in traditional control methods. Especially in the face of sudden load changes or external disturbances, the system can recover and work stably in a relatively short time, which provides a reliable guarantee for the application of chain scraper conveyor systems in dynamic load environments. The control method of the present invention can accurately adjust the speed and torque of the motor by estimating and compensating for disturbances in real time, ensuring that the system can maintain high operating efficiency and stability under various working conditions. The advantage of fixed-time convergence enables the system to adapt to load fluctuations more quickly and reduce unnecessary energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0039] Figure 1 It is a flow chart of a chain scraper speed control method of a fixed time extended state observer according to an embodiment of the present invention;

[0040] Figure 2 A speed tracking comparison diagram of a chain scraper speed control method of a fixed time extended state observer according to an embodiment of the present invention;

[0041] Figure 3 A d-axis current comparison diagram of a chain scraper speed control method of a fixed-time extended state observer according to an embodiment of the present invention;

[0042] Figure 4 A q-axis current comparison diagram of a chain scraper speed control method of a fixed-time extended state observer according to an embodiment of the present invention;

[0043] Figure 5 A speed tracking comparison diagram under variable load of a chain scraper speed control method of a fixed time extended state observer according to an embodiment of the present invention;

[0044] Figure 6A comparison diagram of d-axis current under variable load of a chain scraper speed control method of a fixed time extended state observer according to an embodiment of the present invention;

[0045] Figure 7 A comparison diagram of q-axis current under variable load of a chain scraper speed control method of a fixed time extended state observer according to an embodiment of the present invention;

[0046] Figure 8 A speed tracking comparison diagram under parameter mismatch of a chain scraper speed control method of a fixed time extended state observer according to an embodiment of the present invention;

[0047] Fig. 9 A d-axis current comparison diagram under parameter mismatch of a chain scraper speed control method of a fixed time extended state observer according to an embodiment of the present invention;

[0048] Fig.10 This is a comparison diagram of q-axis current under parameter mismatch of the chain scraper speed control method of the fixed-time extended state observer described in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0050] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0051] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0052] Example 1, reference Figure 1 , which is the first embodiment of the present invention, provides a chain scraper speed control method of a fixed time extended state observer, comprising the following steps:

[0053] Based on the permanent magnet synchronous motor current model containing disturbance terms, it is changed into a local model;

[0054] Set the sampling period, discretize the local model, and establish the permanent magnet synchronous motor extended state space model containing disturbance terms;

[0055] Define the current error increment and disturbance error increment, and establish an extended increment model for current prediction;

[0056] In order to improve the anti-disturbance capability, a fixed-time convergent extended state observer is designed to estimate the system disturbance, and its discretization is used as the system extended variable to participate in predictive control.

[0057] In order to avoid excessive current shock caused by oscillation of control voltage due to power device switching and meet the speed regulation requirements, a cost function containing current tracking error and voltage increment error is designed, so as to design a composite controller to adjust the speed and torque of the motor.

[0058] Specifically, the permanent magnet synchronous motor current model containing the disturbance term is:

[0059]

[0060] Among them, L d , L q They are the motor d-axis inductance and q-axis inductance respectively; i d 、i q are the motor d-axis current and q-axis current respectively; R is the stator resistance of the motor; P is the number of pole pairs of the motor; ω m is the mechanical angular velocity of the motor; is the permanent magnet link flux of the motor; u d and u q are the d-axis voltage and the q-axis voltage respectively; f d and f q They are d-axis disturbance and q-axis disturbance respectively, which usually represent system disturbance or external load change.

[0061] The local model is:

[0062]

[0063] Among them, F d 、F q is the total disturbance set generated by the motor parameter changes and disturbance terms; ΔR, ΔL d , ΔL q , are the increments of stator resistance, d-axis inductance, q-axis inductance and permanent magnet flux respectively.

[0064] Set the sampling period T s , the local model is discretized as:

[0065]

[0066] Assume that in the forecast period T s Internal disturbance F d 、F qKeep unchanged, select i d (k), i q (k), F d 、F q is the system state variable, then the permanent magnet synchronous motor extended state space model containing the disturbance term is:

[0067] x(k+1)=Ax(k)+Bu(k)

[0068] y(k)=Cx(k)

[0069] in,

[0070]

[0071] Define the d-axis current error increment as d(k), the q-axis current error increment as q(k), and the d-axis disturbance error increment as ΔF d (k), the q-axis disturbance error increment is ΔF q (k), the extended incremental model of current prediction is:

[0072] x e (k+1)=A e x e (k)+B e Δu(k)

[0073] y(k)=C e x e (k)

[0074] in,

[0075]

[0076] The fixed-time convergent extended state observer is:

[0077] The d-axis current fixed-time convergence extended state observer:

[0078]

[0079] The q-axis current fixed-time convergence extended state observer:

[0080]

[0081] in, i d 、i q The estimated value of 1d 、e 1q are the d-axis and q-axis current observation errors respectively; φ 1d ,φ 1q are the disturbance F d 、Fq ; F 0d 、F 0q are the estimated values ​​of disturbances on the d-axis and q-axis respectively; e 2d 、e 2q are the disturbance observation errors of d-axis and q-axis respectively; k 1d , k 2d , k 1q , k 2q are adjustable parameters; b and θ are adjustable parameters.

[0082] The observer is further discretized as:

[0083] The d-axis current discretization fixed-time convergence extended state observer:

[0084]

[0085] The q-axis current discretization fixed-time convergence extended state observer:

[0086]

[0087] The cost function including current tracking error and voltage increment error is:

[0088]

[0089] Among them, the current sampling period is k and the prediction period is N p , the control period is N c , k+j is the jth prediction period starting from time k. is the d-axis and q-axis current value of the observer at time k+j, It is the reference value of d-axis and q-axis current at time k+j. is the d and q axis voltage increment at time k+j, Q is the current error weight, and R is the input voltage increment weight. is the expression of the Laguerre function obtained by Z transform in the time domain, is the Laguerre correlation coefficient.

[0090] The composite controller is: u(k+1)=u(k)+Δu(k+1).

[0091] Fixed time convergence stability proof:

[0092] Let the Lyapunov function be V(s)=s 2 ≥0. Differentiating V with respect to time yields:

[0093]

[0094] Since θ>0, b-θ>0, we have Thus we can get At the same time, since 0<β<1, 0<1+β<2, we have Therefore, the nonlinear function converges in finite time.

[0095] When V≠0, then:

[0096]

[0097] Further calculation yields:

[0098]

[0099] make but:

[0100]

[0101] Further integration gives:

[0102]

[0103] Case 1:

[0104] Given any initial value s0, the time it takes for s to converge to the origin is:

[0105]

[0106] Case 2:

[0107] Given any initial value s0, the time it takes for s to converge to a specific value ρ is:

[0108]

[0109] Among them, the smaller the β value, the faster the convergence speed.

[0110] Case 3:

[0111] From the above two cases, the convergence time is a monotonically increasing function given any initial value s0, so the convergence time T max is bounded:

[0112]

[0113] Further calculation:

[0114]

[0115] Let e 3d =φ 1d -F d ,have to:

[0116]

[0117] From the above, we can see that e 1d 、e 3d For fixed time convergence, when the system reaches a steady state, there is Established.

[0118] Further calculation:

[0119]

[0120] From this we can get:

[0121]

[0122] Subcase 1:

[0123] if but:

[0124]

[0125] Subcase 2:

[0126] if but:

[0127]

[0128] It is proved that by choosing appropriate values ​​of θ and b, the observer's estimate is sufficiently close to the true value of the system, and the estimation error is arbitrarily small.

[0129] Example 2

[0130] Reference Figures 2 to 10 , which is the second embodiment of the present invention, is based on the previous embodiment, and is different from the previous embodiment in that:

[0131] A simulation test verification of a chain scraper speed control method with a fixed-time extended state observer is provided, including:

[0132] In order to verify and illustrate the technical effects adopted in the present invention, a surface-mounted three-phase permanent magnet synchronous motor is selected as the test target in this embodiment, and the control method proposed in the present invention is tested. The test results are compared by means of scientific demonstration to verify the real effect of the control method.

[0133] Test environment and parameter description: The surface-mounted three-phase permanent magnet synchronous motor theoretical model is run on the simulation platform. The speed loop adopts the general sliding mode control, and the current loop adopts the control method proposed by the present invention (method 1) and the traditional extended state observer model predictive control method (method 2) for comparison experiment. The parameters are as follows: T s =1e-05s, L d=8.5e-3H,L q =8.5e-3H, R = 2.875Ω, P = 4, J = 0.003 kg·m 2 , B = 0.008N·m·s.

[0134] Table 1 Comparison test table

[0135]

[0136]

[0137] Reference Figure 2 , is a speed tracking comparison diagram of the chain scraper speed control method with a fixed time extended state observer. Figure 2 As shown in the figure, the motor reference speed is set to 100r / s, the load is 5N·m, and the motor is started with load. When t=0.2s, the motor reference speed is set to 120r / s. It can be seen from the figure that the control method proposed by the present invention has a faster speed response, and can still maintain good tracking performance when the reference speed changes.

[0138] Reference Figure 3 and Figure 4 , is a comparison diagram of the d-axis and q-axis currents of the chain scraper speed control method with a fixed-time extended state observer. Figure 3 It can be seen that the current energy required by method 1 on the d-axis is significantly smaller than that of method 2.

[0139] Reference Figure 5 , is a speed tracking comparison chart of the chain scraper speed control method under variable load using a fixed time extended state observer. To test the algorithm's ability to resist external interference, the motor reference speed is set to 100r / s, and it is started without load. At t=0.2s, the load is increased by 5N·m. Figure 5 As shown in the figure, when the motor is started without load, the speed and stability of method 1 are obviously better than those of method 2. In addition, when the load changes, method 1 has stronger anti-interference ability than method 2 and can return to a stable state (speed 100r / s) in a shorter time.

[0140] Reference Figure 6 and Figure 7 , is a comparison diagram of the d-axis and q-axis currents under variable loads for the chain scraper speed control method with a fixed-time extended state observer. Figure 6 It can be seen that the required d-axis current of method 1 under variable load conditions is smaller than that of method 2.

[0141] Reference Figure 8 , is a speed tracking comparison diagram of the chain scraper speed control method under parameter mismatch of the fixed time extended state observer. When t = 0.2s, the inductance parameter of the motor changes from the initial Ld Change to 2L d , other parameters remain unchanged. Figure 8 As shown in the figure, in the initial stage of motor startup, the rapidity of method 2 is poor; when the parameters are mismatched, the overshoot of method 2 is significantly greater than that of method 1, and the stability of method 2 is poor.

[0142] Reference Fig. 9 and Fig.10 , is a comparison diagram of the d-axis and q-axis currents under parameter mismatch of the chain scraper speed control method with a fixed-time extended state observer. Fig. 9 and Fig.10 It can be seen that at the initial stage of motor startup, the d-axis current required by method 2 is greater than that of method 1, which means that method 2 requires more energy and consumes more energy.

[0143] According to the above test environment and parameter settings, the simulation results show that compared with the prior art, the present invention discloses a chain scraper speed control method of a fixed-time extended state observer, which is demonstrated from three aspects: speed tracking, load change, and parameter mismatch. The fixed-time convergence proposed by the method of the present invention can effectively reduce the d-axis current control amount. In terms of stability control, the method of the present invention has good stability and can limit the error to a smaller range.

[0144] It should be appreciated that embodiments of the present invention may be implemented or enforced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The method may be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and drawings described in the specific embodiments. Each program may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, if desired, the program may be implemented in an assembly or machine language. In any case, the language may be a compiled or interpreted language. In addition, the program may be run on a programmed ASIC for this purpose.

[0145] Furthermore, the operations of the processes described herein may be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The processes described herein (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) that is executed collectively on one or more processors, by hardware, or a combination thereof. The computer program includes a plurality of instructions that may be executed by one or more processors.

[0146] Further, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, etc. Aspects of the present invention can be implemented in machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, a RAM, a ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or part thereof, can be transmitted via a wired or wireless network. When such media includes instructions or programs that implement the steps described above in conjunction with a microprocessor or other data processor, the invention described herein includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques described in the present invention, the present invention also includes the computer itself. The computer program can be applied to input data to perform the functions described herein, thereby converting the input data to generate output data stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on a display.

[0147] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A chain scraper speed control method with a fixed time extended state observer, characterized in that: include, Based on the permanent magnet synchronous motor current model containing disturbance terms, it is converted into a local model; Setting a sampling period, discretizing the local model, and establishing an extended state space model of a permanent magnet synchronous motor containing a disturbance term; Define the current error increment and disturbance error increment, and establish an extended increment model for current prediction; Design a fixed-time convergent extended state observer and discretize it; Design a cost function that includes current tracking error and voltage increment error; Based on the fixed-time convergence extended state observer and the cost function, a composite controller is designed to adjust the speed and torque of the motor.

2. The chain scraper speed control method of the fixed time extended state observer according to claim 1 is characterized in that: The permanent magnet synchronous motor current model containing the disturbance term is: Among them, L d , L q They are the motor d-axis inductance and q-axis inductance respectively; i d 、i q are the motor d-axis current and q-axis current respectively; R is the stator resistance of the motor; P is the number of pole pairs of the motor; ω m is the mechanical angular velocity of the motor; is the permanent magnet link flux of the motor; u d and u q are the d-axis voltage and the q-axis voltage respectively; f d and f q They are d-axis disturbance and q-axis disturbance, respectively, representing the disturbance of the system or the change of external load.

3. The chain scraper speed control method of the fixed time extended state observer according to claim 2, characterized in that: The local model is: Among them, F d 、F q is the total disturbance set generated by the motor parameter changes and disturbance terms; ΔR, ΔL d , ΔL q , are the increments of stator resistance, d-axis inductance, q-axis inductance and permanent magnet flux respectively.

4. The chain scraper speed control method of the fixed time extended state observer according to claim 3 is characterized in that: Set the sampling period to T s , the local model is discretized as, Set in the forecast period T s Internal disturbance F d 、F q Keep unchanged, select i d (k), i q (k), F d 、F q is the system state variable, then the permanent magnet synchronous motor extended state space model containing disturbance terms is: x(k+1)=Ax(k)+Bu(k) y(k)=Cx(k) In the formula, i d (k+1) and i q (k+1) represents the motor d-axis current and the motor q-axis current at time k+1 respectively, x(k+1) represents the state vector of the system at time k+1, y(k) represents the control input vector at time k, A represents the state transfer matrix, B is the control input matrix, and C is the output matrix.

5. The chain scraper speed control method of the fixed time extended state observer according to claim 4 is characterized in that: The d-axis current error increment is set to d(k), the q-axis current error increment is set to q(k), and the d-axis disturbance error increment is set to ΔF d (k), the q-axis disturbance error increment is set to ΔF q (k), the extended incremental model of current prediction is expressed as, x e (k+1)=A e x e (k)+B e Δu(k) y(k)=C e x e (k)。 6. The chain scraper speed control method of the fixed time extended state observer according to claim 5, characterized in that: The fixed-time convergence extended state observer includes d-axis and q-axis current fixed-time convergence extended state observers, and the d-axis current fixed-time convergence extended state observer is expressed as: The fixed-time convergent extended state observer of the q-axis current is expressed as, in, i d 、i q The estimated value of 1d 、e 1q are the d-axis and q-axis current observation errors respectively; φ 1d ,φ 1q are the disturbance F d 、F q ; F 0d 、F 0q are the estimated values ​​of disturbances on the d-axis and q-axis respectively; e 2d 、e 2q are the disturbance observation errors of d-axis and q-axis respectively; k 1d , k 2d , k 1q , k 2q are adjustable parameters; b and θ are adjustable parameters.

7. The chain scraper speed control method of the fixed time extended state observer according to claim 6 is characterized in that: After the fixed-time convergence extended state observer is discretized, the d-axis current discretized fixed-time convergence extended state observer is expressed as: The q-axis current discretization fixed-time convergence extended state observer is expressed as:

8. The chain scraper speed control method of the fixed time extended state observer according to claim 7, characterized in that: The cost function is expressed as, Among them, the current sampling period is k and the prediction period is N p , the control period is N c , k+j is the jth prediction period starting from time k, is the d-axis and q-axis current value of the observer at time k+j, i ref (k+j) is the d and q axis current reference value at time k+j, Δu(k+j) is the d and q axis voltage increment at time k+j, Q is the current error weight, R is the input voltage increment weight, is the expression of the Laguerre function obtained by Z transform in the time domain, is the Laguerre correlation coefficient.

9. The chain scraper speed control method of the fixed time extended state observer according to claim 8, characterized in that: The composite controller is expressed as u(k+1)=u(k)+Δu(k+1).

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