Motor parameter identification method based on nonsingular fast terminal sliding mode disturbance observer

Abstract

The invention discloses a motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer. The method comprises the following steps: designing an initial sliding mode surface and an initial switching control law based on a nonlinear system; according to the motor torque equation, the initial value of the rotational inertia of the motor and the deviation value between the actual value and the initial value of the rotational inertia of the motor are introduced to establish a total disturbance equation needing to be observed, a disturbance observer is designed, a system error state equation is obtained, and the system error state equation comprises a speed estimation error value and a system disturbance estimation error value; readjusting the initial sliding mode surface, the initial switching control law and the disturbance observer to obtain a nonsingular terminal sliding mode disturbance observer model; a deviation value calculation equation of the rotation inertia of the motor is designed when the motor is in a steady-state speed state, and a system disturbance estimated value and a viscous friction coefficient identification value are introduced, so that an identification equation is obtained for calculating the rotational inertia. According to the method, the convergence speed is effectively improved, high-frequency buffeting is reduced, the dynamic performance is improved, and the identification complexity is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of motor control, and particularly relates to a method for identifying motor parameters based on a nonsingular fast terminal sliding mode disturbance observer. Background Art

[0002] The surface-mounted permanent magnet synchronous motor (SPMSM) has the advantages of low moment of inertia, wide speed regulation range, high working efficiency, energy conservation and high efficiency, and is widely used in fields such as artillery and automatic weapons, aerospace, new energy vehicles, and intelligent robots. In the high-performance control system of the permanent magnet synchronous motor, parameter accuracy is an important factor affecting the control performance of the entire system. In particular, mechanical parameters such as the moment of inertia and viscous damping coefficient of the entire system play a key role in achieving high-dynamic-performance vector control of the permanent magnet synchronous motor.

[0003] However, during the operation of the motor, there are not only unknown external disturbances, but also its electrical parameters and mechanical parameters will change due to changes in the operating environment. Therefore, in high-precision vector control, whether accurate moment of inertia and viscous damping coefficient can be obtained is the key issue to ensure the dynamic response performance and robustness of the permanent magnet synchronous motor.

[0004] The mechanical parameter identification technology of the permanent magnet synchronous motor can be divided into two categories according to the different identification processes: the first category is the online parameter identification that can monitor the operating state of the motor in real time and achieve adaptive control by updating the controller parameters in real time; the second category is the offline parameter identification. Although this method can produce relatively accurate identification results, its operation process is relatively cumbersome. Under various constant speed states and different acceleration states, the motor needs to run continuously to collect data and perform detailed data processing. This process not only takes time, but also increases the complexity and operation difficulty of the identification, and cannot reflect the dynamic changes of the motor in the real operating environment in real time.

[0005] To make up for the deficiencies of traditional identification methods, some existing technologies have been improved based on the sliding mode observer. Based on the analysis of the adaptive law of stability and feedback gain coefficient, the adaptive identification of load torque parameters has been realized. There are also some extended sliding mode observers combined with improved radial basis function neural networks, which not only accurately identify the moment of inertia of the motor, improve the performance of the control system, but also provide strong support for the state monitoring and fault diagnosis of the motor, further enhancing the reliability and stability of the system. Although the sliding mode observer is known for its strong robustness, it does not show high-precision advantages in mechanical parameter identification. Especially when the system state value is far from the sliding mode surface, its convergence speed is often slow, and when identifying mechanical parameters, the motor still needs to be placed in different acceleration states. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide a motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer, which can effectively improve the convergence speed, reduce high-frequency chattering, enhance the dynamic performance, and reduce the complexity of identification, and there is no need to place the motor in different acceleration states.

[0007] To solve the above technical problem, the present invention provides a motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer, which is characterized by including the following steps:

[0008] Design an initial sliding mode surface based on a single-input and single-output nonlinear system, and the initial sliding mode surface adopts the sigmoid(x′) function;

[0009] Design an initial switching control law according to the initial sliding mode surface;

[0010] According to the motor torque equation, introduce the initial value of the motor inertia and the deviation value between the actual value and the initial value of the motor inertia to establish the total disturbance equation to be observed. Based on the total disturbance equation and the initial switching control law, design a disturbance observer, and obtain the system error state equation, which includes the speed estimation error value and the system disturbance estimation error value;

[0011] Introduce the speed estimation error value and the system disturbance estimation error value into the initial sliding mode surface to obtain a nonsingular fast terminal sliding mode surface, and at the same time adjust the initial switching control law and the disturbance observer to obtain a nonsingular terminal sliding mode disturbance observer model;

[0012] When the motor operates at the first steady-state speed and the second steady-state speed, use the nonsingular terminal sliding mode disturbance observer model to output the system disturbance estimation value and calculate the identification value of the viscous friction coefficient;

[0013] Design an equation for calculating the deviation value between the actual value and the initial value of the motor inertia under the steady-state speed state of the motor, introduce the system disturbance estimation value and the calculated identification value of the viscous friction coefficient to obtain an identification equation, and calculate the inertia through the identification equation.

[0014] Further, the single-input and single-output nonlinear system is:

[0015]

[0016] where x and u are the state and control variables of the system respectively, x ∈ R n , u ∈ R; f(x) is a smooth function of x; d(x) is the system disturbance;

[0017] The initial sliding mode surface is designed as:

[0018] where x′ is the unknown in the equation;

[0019] where α, β > 0; 0 < γ < 1; sigmoid(x′) is a function with smooth and continuous characteristics.

[0020] Furthermore, according to the equivalent sliding mode control principle, the equivalent term of the initial switching control law is obtained, and then through the control of the system state on the initial sliding mode surface, the initial switching control law is designed for the switching of the system near the sliding mode surface for robust control of uncertainties and disturbances. The initial switching control law is as follows:

[0021] u = -f(x) - β|x′| γ sigmoid(x′) + u n ;

[0022]

[0023] In the formula, u n (0) = 0; T > 0, k > 0, are all designed parameters, k1, η, r, μ > 0; 0 < δ < 1; 0 < Q < 1.

[0024] Furthermore, the total disturbance to be observed is:

[0025] J is the moment of inertia, J0 is a rough estimate of J, i.e., the initial value of the motor moment of inertia, ΔJ is the deviation value between the actual value and the initial value of the motor moment of inertia, T L is the load torque, is the derivative of the mechanical angular velocity, and B is the friction factor.

[0026] Furthermore, the dynamic equation is expressed as: Based on the dynamic equation, the disturbance observer is designed as: In the formula, is the estimated value of ω r , is the derivative of the mechanical angular velocity; M is the initial switching control law, c is the derivative of the total disturbance value f, and ω r is the mechanical angular velocity in the dq-axis coordinate system.

[0027] Furthermore, according to the dynamic equation and the disturbance observer, the system error state equation is obtained: In the formula, e ω is the speed estimation error value; e d is the system disturbance estimation error value, is the derivative of the equivalent total disturbance value: In the formula, k2 is the parameter for designing the derivative of the disturbance value.

[0028] Furthermore, the non-singular fast terminal sliding mode surface is: The sliding mode control law obtained after adjusting the initial switching control law is as follows:

[0029] M = αe ω + β|e ω | γ sigmoid(e ω ) + M n

[0030] In the formula, M n (0) = 0; p is the parameter designed for the control law.

[0031] Furthermore, the calculation formula for the identified value of the viscous friction coefficient is:

[0032] Furthermore, the identification equation is:

[0033] Advantages of the present invention:

[0034] 1. By utilizing the disturbance observation characteristics of the observer itself, this application can achieve the off-line identification of the viscous friction coefficient and moment of inertia of the motor without the motor running at different accelerations, by means of the smooth disturbance output value of the observer.

[0035] 2. This application proposes a new sliding mode surface. On the basis of this sliding mode surface, the enhanced fractional reaching law and the exponential reaching law are innovatively combined, enabling the sliding mode controller to have a faster convergence speed when facing system disturbances. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is the block diagram of the nonsingular terminal sliding mode disturbance observer model of the present invention;

[0037] Figure 2 is the motor speed acquisition diagram in the analysis of the present invention;

[0038] Figure 3 is of the present invention Figure 2 system disturbance data diagram when the motor rotates in the present invention;

[0039] Figure 4 is the viscous friction coefficient data acquisition diagram of the present invention;

[0040] Figure 5 is the identification result diagram of the traditional sliding mode disturbance observer;

[0041] Figure 6 is the identification result diagram of the traditional nonsingular terminal sliding mode disturbance observer;

[0042] Figure 7 is the identification result diagram of the improved nonsingular terminal sliding mode disturbance observer of the present invention;

[0043] Figure 8 It is the identification result diagram under the initial value of the first motor moment of inertia of the present invention;

[0044] Figure 9 It is the identification result diagram under the initial value of the second motor moment of inertia of the present invention;

[0045] Figure 10 It is the identification result diagram under the initial value of the third motor moment of inertia of the present invention. Specific Embodiment

[0046] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments, so that those skilled in the art can better understand the present invention and be able to implement it, but the embodiments cited do not limit the present invention.

[0047] Refer to Figure 1 As shown, in an embodiment of the motor parameter identification method based on a non-singular fast terminal sliding mode disturbance observer of the present invention, an initial sliding mode surface is first designed based on a single-input and single-output nonlinear system, and the sigmoid(x) function is used for the initial sliding mode surface; an initial switching control law is designed according to the initial sliding mode surface; subsequently, according to the motor torque equation, the initial value of the motor moment of inertia and the deviation value between the actual value and the initial value of the motor moment of inertia are introduced to establish the total disturbance equation to be observed, and a disturbance observer is designed based on the total disturbance equation and the initial switching control law, and the system error state equation is obtained, and the system error state equation includes the speed estimation error value and the system disturbance estimation error value; the speed estimation error value and the system disturbance estimation error value are introduced into the initial sliding mode surface to obtain a non-singular fast terminal sliding mode surface, and at the same time, the initial switching control law and the disturbance observer are adjusted to obtain a non-singular terminal sliding mode disturbance observer model; when the motor operates at the first steady-state speed and the second steady-state speed, the non-singular terminal sliding mode disturbance observer model is used to output the system disturbance estimation value and calculate the viscous friction coefficient identification value; finally, an equation for calculating the deviation value between the actual value and the initial value of the motor moment of inertia is designed under a motor acceleration state, and the system disturbance estimation value and the calculated viscous friction coefficient identification value are introduced to obtain an identification equation, and the moment of inertia is calculated through the identification equation.

[0048] This application deeply analyzes the novel nonsingular fast terminal sliding mode perturbation observer (NFTSMPO). By adopting a novel nonsingular fast terminal sliding mode surface, the perturbation error converges to zero in a short time. Meanwhile, the fractional reaching law is improved, and the sliding mode perturbation control law passes through an equivalent low-pass filter to output a smooth system perturbation quantity, so that the viscous friction coefficient and moment of inertia of the motor can be accurately identified. Specifically, by using the perturbation observation characteristics of the observer itself, only the surface-mounted permanent magnet synchronous motor (SPMSM) needs to maintain a constant speed operation. Without the motor running at different accelerations, the smooth perturbation output value of the observer can be used to realize the off-line identification of the motor.

[0049] The above method is elaborated in a more detailed way as follows:

[0050] To simplify the analysis and model the surface-mounted permanent magnet synchronous motor system, the following assumptions are made: the rotor has no damping winding; the spatial magnetic field is sinusoidally distributed, and the induced electromotive force in the stator armature winding is also a sine wave; the core eddy current and hysteresis losses are not considered; the saturation of the stator core is ignored, and the magnetic circuit is defaulted to be linear with unchanged inductance parameters.

[0051] Based on the above assumptions, the mathematical model of the SPMSM motor in the rotating dq coordinate system is established as:

[0052]

[0053] where: u d , u q are the stator voltages in the rotating dq coordinate system respectively; i d , i q are the stator currents in the rotating dq coordinate system respectively; R s is the stator resistance; L d , L q are the inductance components of the stator winding in the dq axes; ψ f is the permanent magnet flux linkage; ω is the electrical angular velocity; ω r is the mechanical angular velocity of the dq axis coordinate system; p is the number of pole pairs of the motor; J is the moment of inertia; B is the friction factor; T e is the electromagnetic torque; T L is the load torque. The speed operation is crucial for the dynamic and steady-state performance of the motor. The current loop controls the current of the motor to ensure that the motor outputs the required torque. Then, through the coordinate transformation part, the three-phase alternating current is transformed into the current in a specific dq coordinate system to facilitate vector control. Then, the real-time state information of the motor during operation, including current, voltage, speed, and position, etc., is obtained through feedback detection. The space vector pulse width modulation part adjusts the output voltage generated by the inverter according to the control signal output by the controller, controls the phase current of the motor, and realizes the required position, speed, and torque control.

[0054] For the above-mentioned SPMSM, the non-singular fast terminal sliding mode disturbance observer of this application is designed as follows:

[0055] To accurately obtain the disturbance output value, a non-singular terminal sliding mode surface is proposed. On the basis of this sliding mode surface, the enhanced fractional reaching law and the exponential reaching law are innovatively combined, enabling the sliding mode controller to have a faster convergence speed when facing system disturbances.

[0056] Considering a general single-input and single-output nonlinear system as:

[0057]

[0058] In the formula: x and u are the state and control variables of the system respectively, x ∈ R n , u ∈ R; f(x) is a smooth function of x; d(x) is the system disturbance; R represents the set of real numbers.

[0059] Design a non-singular fast terminal sliding mode surface, that is, the initial sliding mode surface is:

[0060]

[0061] In the formula, x′ is the unknown in the equation;

[0062] In the formula: α, β > 0; 0 < γ < 1; the sigmoid(x′) function with smooth and continuous characteristics, and its expression is:

[0063]

[0064] In the formula: d is an adjustable parameter.

[0065] When the state variable of the sliding mode observer enters the sliding mode, it satisfies That is

[0066]

[0067] It can be seen from formula (5) that: when the error state is far from the equilibrium point, the linear term dominates the state convergence rate, and when the error state approaches the equilibrium point, the non-linear term dominates the state convergence rate. Therefore, in the sliding stage, the non-singular fast terminal sliding mode surface (3) can achieve global fast convergence, and its convergence speed is comparable to that of the traditional non-singular fast terminal sliding mode surface, does not contain negative exponential states, preventing singular phenomena, and compared with the traditional non-singular terminal sliding mode surface, it does not require differential states.

[0068] According to the principle of equivalent sliding mode control, the equivalent term of the sliding mode control law is obtained. Then, by controlling the system state on the sliding mode surface, a switching control law is designed to achieve the switching of the system near the sliding mode surface, realizing the robust control of uncertainties and disturbances. The initial switching control law is as follows:

[0069] u = -f(x) - β|x'|γsigmoid(x') + u n (6)

[0070]

[0071] where: u n (0) = 0; T > 0, k > 0, are all designed parameters, k1, η, r, μ > 0; 0 < δ < 1; 0 < Q < 1. In equation (7), by setting the scaling function, the observer gain adaptively changes according to the magnitude of the stator current error, which is used to ensure the approaching rate when the stator current error system state is close to the sliding mode surface; ηPs is used to ensure the approaching rate when the stator current error system state is far from the sliding mode surface. Through the selection of parameters, the nonsingular fast terminal sliding mode disturbance observer has strong robustness to the disturbances of the system.

[0072] Subsequently, the system disturbance model is designed:

[0073] According to the motor torque equation (1), and considering the uncertainties of the moment of inertia and viscous friction coefficient, the formula is transformed into:

[0074]

[0075] where: J0 is the rough estimate of J, that is, the initial value of the motor moment of inertia, and ΔJ is the deviation value between the actual value and the initial value of the motor moment of inertia. f is the total disturbance to be observed.

[0076] The dynamic equation of the motor can be expressed as:

[0077]

[0078] Based on this, the nonsingular fast terminal sliding mode disturbance observer is designed as

[0079] where: is the estimated value of ω r ; M is the designed control law, which represents the above initial switching control law or the adjusted control law here; c is the derivative of the disturbance value f.

[0080] The system error state equation can be obtained according to equations (9) and (10)

[0081]

[0082] where: e ω is the speed estimation error value; e d is the system disturbance estimation error value.

[0083] In order to enable the sliding mode controller to have a faster convergence speed in the face of system disturbances, the initial sliding mode surface is improved, and the designed nonsingular fast terminal sliding mode surface is:

[0084]

[0085] According to Equations (6) and (7), the control law is designed as:

[0086] M = αe ω + β|e ω | γ sigmoid(e ω ) + M n (13)

[0087]

[0088] where: M n (0) = 0; P is the parameter designed for the control law.

[0089] The derivative of the equivalent disturbance value can be designed as:

[0090] where: k2 is the parameter for designing the derivative of the disturbance value.

[0091] To verify the effectiveness of the novel nonsingular terminal sliding mode disturbance observer proposed in this application, it is necessary to conduct a stability analysis. Based on the Lyapunov stability criterion, the Lyapunov function is defined as:

[0092]

[0093] Differentiate Equation (17) and make it satisfy the stability condition, that is Then there is

[0094]

[0095] Select When s ≠ 0, we get:

[0096] and When {|s| ≤ min((2PM n |e| / k1) 1 / δ , PM n |e| / ηP)}, is negative definite. For it starts from within {V ≤ c} because It is negative on the boundary V = c, so the solution is uniformly bounded. By choosing the parameters of k, η, δ, and P, the chattering of the system is effectively reduced, a high-precision dynamic error value is obtained, and the stability of the system is ensured.

[0097] The above non-singular terminal sliding mode disturbance observer is used to identify the viscous friction coefficient B:

[0098] When identifying the viscous friction coefficient B, the SPMSM can be operated at two different constant speeds so that ω m (t0) ≠ ω m (t0 + τ0) and When the motor is operating at the first steady-state speed and the second steady-state speed, according to the non-singular terminal sliding mode disturbance observer, the system disturbance estimation value is expressed as

[0099] When the motor is stable and reaches the stable speed, assume is zero, the external load torque is constant, and J0 takes a non-zero constant. Subtracting the formulas in Equation (18) can obtain:

[0100]

[0101] Therefore, the identified value of the viscous friction coefficient is:

[0102]

[0103] Finally, the moment of inertia J is identified:

[0104] Conventionally, the moment of inertia in mechanical parameter identification is generally obtained by making the motor in different acceleration states, and identifying the parameters by measuring the motor acceleration, speed, and system disturbance values in two states. This application can achieve parameter identification without making the motor in different accelerations. By re-deforming Equation (8) into:

[0105]

[0106] In the formula: the denominator The DC component is zero. To avoid the denominator being zero, integrate Equation (21) to get:

[0107]

[0108] According to Equation (22), the disturbance value containing the complete moment of inertia information can be obtained Its calculation formula is:

[0109]

[0110] Substitute and into Equation (23) simultaneously, and the identification formula for the moment of inertia J can be obtained:

[0111]

[0112] According to the above identification formula, the moment of inertia can be effectively calculated.

[0113] An effective analysis is carried out with a specific parameter case:

[0114] This application adopts i d =0 control, and the system can obtain the maximum torque / current ratio. The SPMSM adopts a double-loop cascade control method composed of a speed loop and a current loop in the dq coordinate system for simulation analysis. A system simulation model based on MATLAB / Simulink is established. The parameters designed for the nonsingular terminal sliding mode disturbance observer are: α = 1, β = 2, γ = 0.6, Q = 0.001, k1 = 0.65, r = 0.5, μ = 4, δ = 0.6.

[0115] Table 1 Simulation Experiment Parameters of Permanent Magnet Synchronous Motor

[0116]

[0117] By measuring the motor speed and system disturbance under two different constant-speed operations, Figure 2 the motor speed, Figure 3 the derivative value of the system disturbance f can be obtained. When the motor speed increases from 500 r / min to 1000 r / min, the external load can be regarded as a constant value. Given J0 = 0.002 kg·m 2 , and the running time τ of the system is 2 s, the system disturbance changes accordingly. The viscous friction coefficient B is obtained through Equation (18), and the identification result is as Figure 4 shown.

[0118] It can be seen from Figures 2 to 4 that after the motor speed starts to change, the system disturbance value changes accordingly. The required identified viscous friction coefficient B converges to the actual viscous friction coefficient of the motor, and the chattering is small. Therefore, this method can accurately identify the viscous friction coefficient B.

[0119] After identifying the viscous friction coefficient B of the motor, the motor is maintained at a speed of 1000 r / min, and the moment of inertia J of the motor can be obtained according to Equation (24).

[0120] When J0 = 0.002 kg·m 2 is given, Figure 5To identify the moment of inertia using a traditional Sliding Mode Perturbation Observer (SMPO), the waveform stabilizes at 0.7 s, and the maximum overshoot reaches 0.0027 kg·m 2 , Figure 6 The identification result of the Non-singular Terminal Sliding Mode Perturbation Observer (NTSMPO) shows that its maximum overshoot is 0.002566 kg·m 2 , but it stabilizes at 0.9 s, Figure 7 For the improved non-singular fast terminal sliding mode perturbation observer, it can reach stability at 0.02 s, and the maximum overshoot is only 3.5×10 -6 kg·m 2 . By comparison, it can be concluded that for the moment of inertia identified by the improved perturbation observer, both the convergence time and the overshoot are better than those of the traditional identification method, and only the motor needs to run at a constant speed, without the need to run at different accelerations.

[0121] When the system operation time τ = 0.3 s, after giving three different J0 values, the waveforms of the moment of inertia parameter identification shown in Figures 8 - 10 are obtained. In Figure 8 , J0 = 0.0015 kg·m 2 , Figure 9 in J0 = 0.002 kg·m 2 , Figure 10 in J0 = 0.003 kg·m 2 . It can be seen that under different J0 values, the identified parameter values can quickly converge to the actual moment of inertia value of the motor. Therefore, this method can accurately identify the moment of inertia J. In summary, this application proposes a mechanical parameter identification method for a permanent magnet synchronous motor drive system based on a non-singular fast terminal sliding mode perturbation observer. Utilizing the disturbance observation characteristics of the observer itself, only the SPMSM needs to maintain a constant speed operation, and without the need for the motor to run at different accelerations (and without the need to run at an acceleration), the smooth disturbance output value of the observer can be used to achieve the offline identification of the motor. The simulation results show that the proposed parameter identification method can effectively and quickly identify the mechanical parameters.

[0122] The above-described embodiments are only preferred embodiments given to fully illustrate the present invention, and the protection scope of the present invention is not limited thereto. Equivalent substitutions or transformations made by those skilled in the art based on the present invention are all within the protection scope of the present invention.​

Claims

1. A motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer, characterized in that Including the following steps: Design an initial sliding mode surface based on a single-input and single-output non-linear system. The initial sliding mode surface uses the sigmoid(x′) function; Design an initial switching control law according to the initial sliding mode surface; According to the motor torque equation, introduce the initial value of the motor inertia and the deviation value between the actual value and the initial value of the motor inertia to establish the total disturbance equation to be observed. Design a disturbance observer based on the total disturbance equation and the initial switching control law, and obtain the system error state equation. The system error state equation includes the speed estimation error value and the system disturbance estimation error value; Introduce the speed estimation error value and the system disturbance estimation error value into the initial sliding mode surface to obtain a non-singular fast terminal sliding mode surface, and at the same time adjust the initial switching control law and the disturbance observer to obtain a non-singular terminal sliding mode disturbance observer model; When the motor operates at the first steady-state speed and the second steady-state speed, use the non-singular terminal sliding mode disturbance observer model to output the system disturbance estimation value and calculate the viscous friction coefficient identification value; Design an equation for calculating the deviation value between the actual value and the initial value of the motor inertia when the motor is in the steady-state speed state, and introduce the system disturbance estimation value and the calculated viscous friction coefficient identification value to obtain an identification equation. Calculate the inertia through the identification equation.

2. The motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer according to claim 1, wherein, The single-input and single-output non-linear system is: where \(x\) and \(u\) are the state and control variables of the system respectively, \(x\in\mathbb{R}\) n , \(u\in\mathbb{R}\); \(f(x)\) is a smooth function; \(d(x)\) is the system disturbance; The initial sliding mode surface is designed as: where x′ is the unknown in the equation; Where α, β > 0; 0 < γ < 1; sigmoid(x′) is a function with smooth and continuous characteristics.

3. The motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer according to claim 1, characterized in that According to the equivalent sliding mode control principle, obtain the equivalent term of the initial switching control law, and then through the control of the system state on the initial sliding mode surface, design the initial switching control law for the system to switch near the sliding mode surface for robust control of uncertainties and disturbances. The initial switching control law is as follows: u = -f(x) - β|x'| γ sigmoid(x') + u n ; where u n (0) = 0; T > 0, k > 0, are all design parameters, k1, η, r, μ > 0; 0 < δ < 1; 0＜Q＜1。 4. The method for identifying motor parameters based on a nonsingular fast terminal sliding mode disturbance observer according to claim 1, characterized in that, The total disturbance to be observed is: J is the moment of inertia, J0 is a rough estimate of J, i.e., the initial value of the motor moment of inertia, and ΔJ is the deviation between the actual value and the initial value of the motor moment of inertia, T L is the load torque, is the derivative of the mechanical angular velocity, and B is the friction factor.

5. The motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer according to claim 4, characterized in that The dynamic equation is expressed as: Based on the dynamic equation, the disturbance observer is designed as: In the formula, is the estimated value of ω r , and is the derivative of the estimated value of the mechanical angular velocity; M is the initial switching control law, c is the derivative of the total disturbance value f, and ω r is the mechanical angular velocity in the dq-axis coordinate system.

6. The motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer according to claim 5, characterized in that, The system error state equation is obtained based on the dynamic equation and the disturbance observer: where e ω is the velocity estimation error value; e d is the system disturbance estimation error value, and is the derivative of the equivalent total disturbance value: where k2 is the parameter for designing the derivative of the disturbance value.

7. The motor parameter identification method based on the nonsingular fast terminal sliding mode disturbance observer according to claim 6, characterized in that, The non-singular fast terminal sliding mode surface is as follows: The sliding mode control law obtained after adjusting the initial switching control law is as follows: M = αe ω + β|e ω | γ sigmoid(e ω ) + M n where M n (0) = 0; p is a parameter for control law design.

8. The motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer according to claim 1, wherein The calculation formula for the identification value of the viscous friction coefficient is as follows:

9. The motor parameter identification method based on a nonsingular fast terminal sliding mode disturbance observer according to claim 1, characterized in that The identification equation is: In the formula,

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