An adaptive follow-up control method
By constructing an associated control system model and adopting a three-ring nested architecture and adaptive and self-disturbance rejection algorithms, the problem of high-precision tracking of precision electromechanical equipment under parameter uncertainty and dynamic target mutation was solved, and high-stability and fast-response follow-up control was achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- MIANYANG WUBA ROBOT TECHNOLOGY CO LTD
- Filing Date
- 2026-04-08
- Publication Date
- 2026-07-14
Smart Images
Figure CN122386662A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of precision mechanical control technology, and in particular to an adaptive servo control method based on an association model and a three-ring nested architecture, which can achieve high precision and fast response. Background Technology
[0002] In modern precision electromechanical equipment systems, servo control systems need to achieve high-precision, fast-response tracking of dynamic targets. Their control performance directly determines the positioning accuracy and operational efficiency of the equipment. Typical applications include high-precision positioning platforms, intelligent servo actuators, and automated tracking equipment.
[0003] However, there are two major problems in practical applications: First, the torque jumps of different equipment loads, the uncertainty of rotational inertia parameters, and the fluctuations of inductance and permanent magnet linkage parameters lead to model uncertainty; Second, the sudden changes in the speed and acceleration of dynamic targets exacerbate the degradation of control performance and easily lead to speed steady-state errors, system oscillations, or even instability.
[0004] To address the aforementioned issues, some existing literature employs a single PID algorithm to optimize the parameters of the servo system, but this is insufficient to address the model uncertainty caused by time-varying parameters. Other literature introduces adaptive algorithms to improve robustness, but fails to consider the coupling effect between the main tracking channel and the cooperative execution channel, resulting in limited control performance under multi-channel cooperative tracking conditions.
[0005] Therefore, how to achieve high precision, fast response, and high stability tracking of a servo control system under conditions of parameter uncertainty and dynamic target mutation is a technical problem that urgently needs to be solved by those skilled in the art. Summary of the Invention
[0006] In view of the above problems, the present invention provides an adaptive servo control method for overcoming or at least partially solving the above problems.
[0007] This invention provides the following solution: An adaptive servo control method includes: Construct an associated control system model, which includes a main tracking channel and a collaborative execution channel; Both the main tracking channel and the cooperative execution channel adopt a frequency domain-based three-ring nested architecture of current loop-velocity loop-position loop; wherein, the current loop is used to suppress current ripple and load disturbance, the velocity loop is used to improve dynamic response, and the position loop is used to ensure tracking accuracy; The three-ring nested architecture incorporates an adaptive algorithm and an active disturbance rejection algorithm; the adaptive algorithm is used to correct the rotational inertia and load torque parameters in real time, and the active disturbance rejection algorithm is used to compensate for external disturbances. The associated control system model achieves decoupling control between the main tracking channel and the collaborative execution channel through a channel decoupling algorithm module.
[0008] Preferably, the open-loop transfer function matrix of the associated control system model is: The closed-loop transfer function matrix is The system characteristic equation is ; When the associated control system is completely decoupled, the closed-loop transfer function matrix The system open-loop transfer function matrix is a diagonal matrix. It is a diagonal matrix. The characteristic equation of a three-dimensional correlated control system is expressed as follows: ; When the associated control system cannot be completely decoupled, the closed-loop transfer function ,in It is a diagonal matrix. The transfer function matrix of the system's related parts; if Order correlation transfer function matrix eigenvalues corresponding If all single-variable control systems are stable, then the entire associated system is stable.
[0009] Preferably, the velocity loops of the main tracking channel and the cooperative execution channel are equivalent to inertial elements. and ,in , For the speed loop controller gain; The position loop controller of the main tracking channel is The position loop controller of the collaborative execution channel is ; The channel decoupling algorithm module is equivalent to: ,in It is the inertial constant; The transfer function of each channel encoder is equivalent to: ,in It is a lag period.
[0010] Preferably: by configuring the inertial constant With the hysteresis period This ensures that the roots of the characteristic equations of the associated control system model all have negative real parts, thereby maintaining system stability.
[0011] Preferably: the inertial constant The value ranges from 0.05 seconds to 0.1 seconds.
[0012] Preferably, a low-hysteresis, high-precision encoder and an FPGA real-time processing circuit are used to reduce the hysteresis period. .
[0013] Preferably: the closed-loop transfer functions of the main tracking channel and the cooperative execution channel are respectively:
[0014] Furthermore, the poles of both closed-loop transfer functions have negative real parts.
[0015] Preferably, the parameters corrected in real time by the adaptive algorithm include at least the model uncertainty parameters introduced by load torque jumps, uncertainties in rotational inertia parameters, and fluctuations in inductance and permanent magnet linkage parameters.
[0016] Preferably, the external disturbances compensated by the self-disturbance rejection algorithm include environmental vibrations and non-uniform load changes.
[0017] Preferably, under complex operating conditions, the steady-state tracking error is less than or equal to 0.15 milliradians, and the settling time is less than or equal to 60 milliseconds.
[0018] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects: This application provides an adaptive servo control method that addresses the shortcomings of existing single PID algorithms in handling time-varying parameters and the neglect of inter-channel coupling in traditional adaptive algorithms. The invention constructs a coupled control system model of a main tracking channel and a cooperative execution channel, employing a three-loop nested architecture: a current loop suppresses current ripple and load disturbances, a velocity loop improves dynamic response, and a position loop ensures tracking accuracy. Furthermore, an adaptive algorithm is integrated to correct rotational inertia and load torque parameters in real time, and an active disturbance rejection algorithm compensates for external disturbances such as environmental vibrations and non-uniform load variations. This architecture overcomes the technical bottleneck of high-precision stable tracking under multi-source disturbances. It can be extended to high-precision positioning platforms, intelligent servo actuators, automated tracking equipment, and other similar precision electromechanical equipment, and is suitable for demanding conditions such as sudden load parameter changes, rapid changes in dynamic targets, and multi-channel cooperative tracking, demonstrating significant engineering application value and commercialization prospects.
[0019] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description
[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly described below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.
[0021] Figure 1 This is a block diagram of the control model corresponding to an adaptive servo control method provided in an embodiment of the present invention; Figure 2 This is a simplified block diagram of the orientation axis system control system provided in the embodiments of the present invention; Figure 3 This is a SIMULINK simulation diagram of the system provided in the embodiments of the present invention; Figure 4 This is provided by the embodiments of the present invention. The system's step response curve at time; Figure 5 This is provided by the embodiments of the present invention. The system's step response curve at time; Figure 6 This is provided by the embodiments of the present invention. The system's step response curve at time; Figure 7 This is provided by the embodiments of the present invention. The system's step response curve. Detailed Implementation
[0022] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention are within the scope of protection of the present invention.
[0023] See Figure 1 This invention provides an adaptive servo control method, such as... Figure 1 As shown, the method may include: Construct an associated control system model, which includes a main tracking channel and a collaborative execution channel; Both the main tracking channel and the cooperative execution channel adopt a frequency domain-based three-ring nested architecture of current loop-velocity loop-position loop; wherein, the current loop is used to suppress current ripple and load disturbance, the velocity loop is used to improve dynamic response, and the position loop is used to ensure tracking accuracy; The three-ring nested architecture incorporates an adaptive algorithm and a self-disturbance rejection algorithm. The adaptive algorithm is used to correct the rotational inertia and load torque parameters in real time, while the self-disturbance rejection algorithm is used to compensate for external disturbances. In specific implementations, the parameters corrected in real time by the adaptive algorithm may include at least the model uncertainty parameters introduced by load torque jumps, uncertainties in rotational inertia parameters, and fluctuations in inductance and permanent magnet linkage parameters. The external disturbances compensated by the self-disturbance rejection algorithm include environmental vibrations and non-uniform load variations.
[0024] The associated control system model achieves decoupling control between the main tracking channel and the collaborative execution channel through a channel decoupling algorithm module.
[0025] To address the collaborative tracking requirements of the main tracking channel and the collaborative execution channel in precision electromechanical equipment, and to meet the dynamic and static performance of the control system, the method provided in this application constructs an associated control system model, adopting a frequency domain-based three-loop nested architecture of current loop-velocity loop-position loop: the current loop suppresses current ripple and load disturbances, the velocity loop improves dynamic response, and the position loop ensures tracking accuracy; at the same time, an adaptive algorithm is incorporated to correct parameters such as rotational inertia and load torque in real time, and an active disturbance rejection algorithm compensates for external disturbances (such as environmental vibration and non-uniform load changes).
[0026] Furthermore, the open-loop transfer function matrix of the aforementioned associated control system model is: The closed-loop transfer function matrix is The system characteristic equation is ; When the associated control system is completely decoupled, the closed-loop transfer function matrix The system open-loop transfer function matrix is a diagonal matrix. It is a diagonal matrix. The characteristic equation of a three-dimensional correlated control system is expressed as follows: ; When the associated control system cannot be completely decoupled, the closed-loop transfer function ,in It is a diagonal matrix. The transfer function matrix of the system's related parts; if Order correlation transfer function matrix eigenvalues corresponding If all single-variable control systems are stable, then the entire associated system is stable.
[0027] Furthermore, the velocity loops of the main tracking channel and the cooperative execution channel are equivalent to inertial elements. and ,in , For the speed loop controller gain; The position loop controller of the main tracking channel is The position loop controller of the collaborative execution channel is ; The channel decoupling algorithm module is equivalent to: ,in It is the inertial constant; The transfer function of each channel encoder is equivalent to: s, where It is a lag period.
[0028] By configuring the inertial constant With the hysteresis period This ensures that the roots of the characteristic equations of the associated control system model all have negative real parts, thereby maintaining system stability.
[0029] The inertial constant The value ranges from 0.05 seconds to 0.1 seconds.
[0030] A low-hysteresis, high-precision encoder and an FPGA real-time processing circuit are used to reduce the hysteresis period. .
[0031] The closed-loop transfer functions of the main tracking channel and the cooperative execution channel are respectively:
[0032] Furthermore, the poles of both closed-loop transfer functions have negative real parts.
[0033] Under complex operating conditions, the steady-state tracking error is less than or equal to 0.15 milliradians, and the settling time is less than or equal to 60 milliseconds.
[0034] The adaptive servo control method provided in the embodiments of this application will be described in detail below.
[0035] The adaptive servo control method provided in this application integrates a three-loop control architecture combining PID, adaptive, and active disturbance rejection algorithms. It establishes a related system model and, through a logical chain of "theoretical analysis - quantitative calculation - simulation verification," systematically solves the problems of parameter uncertainty and dynamic tracking, providing support for engineering applications. The control system model block diagram is shown below. Figure 1 As shown.
[0036] in, Transfer function for the main tracking channel position loop controller; The forward channel transfer function of the main tracking channel velocity loop; The transfer function from the speed output of the main tracking channel to the position feedback; Pass functions to the channel decoupling algorithm module; The transfer function of the encoder for each channel detection; Transfer functions for the coordinated execution channel position loop controller; For the coordinated execution of the channel velocity loop forward channel transfer function; The transfer function for coordinating the execution channel speed output to the position feedback; Input signals (such as target trajectory, given commands, etc.) to the coordinated execution channel control system; Output position signal to the main tracking channel; To coordinate the output position signal of the channel.
[0037] Stability analysis: Suppose a class of associated control systems has Input and Output Then we have: (1) in This is the closed-loop transfer function matrix of the system; assuming the system has unity negative feedback, the transfer function matrix is... And the forward channel transfer function matrix is Then we have: The system error transfer function matrix is: The system characteristic equation is: (2) Case 1, when the associated control system is completely decoupled, is determined by the following conditions: It must be a diagonal matrix. Derive the system's open-loop transfer function. Diagonal matrix. The characteristic equation of a three-dimensional correlated control system can be expressed as: (3) If the system is stable, then all roots of the characteristic equation (3) lie in the left half of the complex plane and all roots have negative real parts.
[0038] Case 2: When the interconnected control system cannot be completely decoupled, the closed-loop transfer function can be written as: In the formula, the system's positive diagonal matrix is: B =
[0039] System-related transfer function: L =
[0040] Assumption Order correlation transfer function matrix Eigenvalues And taking the open-loop transfer function as of If all single-variable control systems are stable, then the entire interconnected system is stable.
[0041] Proof: The characteristic equation of the system is According to the principle of matrix similarity, we can obtain: Based on the assumptions: Open-loop transfer function Both are stable, so the characteristic equation is known. The roots all have negative real parts; then the characteristic equation All roots have negative real parts and lie in the left half of the complex plane. Therefore, the correlated control system is stable.
[0042] Simplified control model: Without considering external disturbances, the control system model of the main tracking channel and the cooperative execution channel is simplified as follows: Figure 2 As shown.
[0043] in, Based on the properties of a two-dimensional correlated control system, its open-loop transfer function matrix is: (4) in: W 11 = ; W 12 = ; W 21 = ; W 22 = .
[0044] Depend on The closed-loop transfer function matrix is known to be: (5) in: Φ 11 = ; Φ 12 = ; Φ 21 = ; Φ 22 = .
[0045] From the condition for complete decoupling of the associated control system, we know that: (6) Assuming condition (6) is satisfied, the system is completely decoupled, and the characteristic equation is: (7) If all the roots of the characteristic equation (7) are located in the left half of the complex plane, then the system is stable.
[0046] because G 1≠0、 G 2≠0、 A 1≠0、 A 2≠0、 K 1≠0、 K 2≠0 and A 1+ K 2≠0; therefore, condition (6) is not satisfied, and the system cannot be completely decoupled. The closed-loop transfer function matrix Φ of the system is rewritten as: Φ = ( I+LB ) -1 LB The positive diagonal matrix B = The transfer function matrix of the system's related components: L = , Q = ≠0.
[0047] use = 0 The eigenvalues are: λ 1,2 = .
[0048] equation: (8) If all roots of equation (8) satisfy Then the diagonal matrix is B The transfer function matrix associated with the system is as follows The associated control system is stable.
[0049] Quantitative analysis: The transfer function in the simplified control model is obtained from the transfer function of the actual control system as follows: (9) Substituting equation (9) into equations (4) and (5) respectively yields the full system models of the main tracking channel and the cooperative execution channel control systems, including the open-loop transfer function W and the closed-loop transfer function. .
[0050] From equation (9), the eigenvalues of the system's correlated transfer function matrix L can be obtained: (10) in: N λ = ; D λ = .
[0051] Substituting (10) into (8) yields the equation: (11) The main tracking channel in the known control system and collaborative execution channels Design a speed loop controller, where the open-loop transfer function of the speed loop is equivalent to... The speed loops of the main tracking channel and the cooperative execution channel can be equivalently represented as: and The inertial link, among which To ensure dynamic response performance, a controller is used. and These serve as position loop controllers for the main tracking channel and the cooperative execution channel, respectively. The decoupling algorithm module projects the target's coordinates from the main tracking channel coordinate system to the cooperative execution channel coordinate system. When analyzing the impact of filtering on stability performance, this is equivalent to... ， The constant is the inertia constant; when analyzing the impact of the required data lag on stability performance, without considering dynamic characteristics, it is simply assumed that the feedback data from the rotary transformer or encoder only has a short time lag, and the transfer function is equivalent to... ,in It is a lag period.
[0052] Substituting the above transfer functions into equation (11) yields the following about The equation, whose coefficients explicitly contain and Since the other parameters are determined, the root of equation (11) is... and OK. If a suitable one exists. and Make all roots of equation (11) satisfy If so, the system is stable.
[0053] To ensure the dynamic response performance and stability of each system, select The closed-loop transfer functions for the main tracking channel and the cooperative execution channel are as follows: (12) Since the poles of the closed-loop transfer functions of both systems have negative real parts, both systems are stable.
[0054] inertia constant Impact on system stability: In analysis When it affects system stability, Since the inertia constant of the filtering algorithm is a real number and can be set, we can take... and The roots obtained by substituting into equation (11) are shown in Tables 1 and 2.
[0055] Table 1 Roots of the equation
[0056] Because it is necessary to make Q ≠0, then Remove, have If a root has a real part greater than zero, the system is unstable.
[0057] Table 2 Roots of the equation
[0058] Because it is necessary to make Q ≠0, then If we remove it, then the real parts of all roots of the equation will be less than zero, and the system is stable.
[0059] Lag cycle Impact on system stability: In analysis When it affects system stability, When using data from a rotary transformer or encoder, take... and They can be equivalently represented as: and The roots obtained by substituting into equation (12) are shown in Tables 3 and 4, respectively.
[0060] Table 3 Roots of the equation
[0061] Because it is necessary to make Q ≠0, then Remove, have If the real parts of all five roots are greater than zero, the system is unstable.
[0062] Table 4 Roots of the equation
[0063] Because it is necessary to make Q ≠0, then Remove, have The system is unstable when the real parts of all six roots are greater than zero.
[0064] Simulation verification: Basic simulation model construction: Based on the mathematical model and simulation model of the control system given above, a SIMULINK simulation model is established as follows: Figure 3 As shown. A step signal with an amplitude of 1 rad is input to the system to simulate a sudden change in the target position. The parameters are consistent with the quantization analysis, verifying... and Impact on stability. Selection .
[0065] Impact on system stability: Select each and A step signal with an amplitude of 1 rad is input to the system, and the position output curves of the main tracking channel and the cooperative execution channel are as follows: Figure 4 and 5 As shown; the dashed line is the main tracking channel position output curve, and the solid line is the cooperative execution channel position output curve.
[0066] from Figure 4 It can be seen that when At that time, the system was unstable, with the amplitude of the oscillation reaching 1088 rad within 1500 ms, completely diverging. From Figure 5 It can be seen that when The system moves smoothly with zero oscillations and a settling time of Ts = 50ms.
[0067] Impact on system stability: Select each and A step signal with an amplitude of 1 rad is input to the system, and the position output curves of the main tracking channel and the cooperative execution channel are as follows: Figure 6 and 7 As shown; the dashed line is the main tracking channel position output curve, and the solid line is the cooperative execution channel position output curve.
[0068] when When the value is less than 0.02s, the system is unstable. When the system runs for 3000ms, the amplitude of the oscillation reaches 1031rad.
[0069] As can be seen, the method provided in this application addresses the parameter mismatch and model uncertainty problems of the servo control system for precision electromechanical equipment by designing a three-loop control architecture that integrates PID, adaptive, and active disturbance rejection. Stability theory analysis and simulation verification were conducted, and the proposed theory and method can achieve high-precision, fast-response tracking under reasonable parameter configuration. Furthermore, it addresses the issue that system stability is easily affected by the filtering inertia constant. and feedback lag period The impact of this is discussed, and the filter inertia constant is considered in engineering applications. A balance needs to be struck between "increasing inertia to improve stability" and "decreasing inertia to accelerate response," with a suggested range of 0.05-0.1s; and to eliminate feedback lag. To mitigate the impact on system stability, measures such as using low-hysteresis, high-precision encoders and fast-response FPGA real-time processing circuits for signal processing can be employed to reduce feedback delay.
[0070] This method provides a theoretical basis for parameter optimization and engineering applications of servo control systems for precision electromechanical equipment, and offers optimization directions for engineering applications under complex working conditions. Verified through actual tests on precision electromechanical equipment, this control technology achieves a steady-state tracking error ≤0.15 milliradians (mrad) and a settling time ≤60 milliseconds (ms) under complex working conditions. Compared to traditional control methods, it effectively improves stability and dynamic response speed. It has been successfully applied to the digital transformation project of a certain type of automated tracking equipment and can be extended to similar precision electromechanical equipment such as high-precision positioning platforms and intelligent servo actuators, demonstrating significant engineering application value and promising transformation prospects.
[0071] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0072] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.
[0073] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.
[0074] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of protection of the present invention.
Claims
1. An adaptive servo control method, characterized in that, The method includes: Construct an associated control system model, which includes a main tracking channel and a collaborative execution channel; Both the main tracking channel and the cooperative execution channel adopt a frequency domain-based three-ring nested architecture of current loop-velocity loop-position loop; wherein, the current loop is used to suppress current ripple and load disturbance, the velocity loop is used to improve dynamic response, and the position loop is used to ensure tracking accuracy; The three-ring nested architecture incorporates an adaptive algorithm and an active disturbance rejection algorithm; the adaptive algorithm is used to correct the rotational inertia and load torque parameters in real time, and the active disturbance rejection algorithm is used to compensate for external disturbances. The associated control system model achieves decoupling control between the main tracking channel and the collaborative execution channel through a channel decoupling algorithm module.
2. The adaptive servo control method according to claim 1, characterized in that, The open-loop transfer function matrix of the associated control system model is: The closed-loop transfer function matrix is The system characteristic equation is ; When the associated control system is completely decoupled, the closed-loop transfer function matrix The system open-loop transfer function matrix is a diagonal matrix. It is a diagonal matrix. The characteristic equation of a three-dimensional correlated control system is expressed as follows: ; When the associated control system cannot be completely decoupled, the closed-loop transfer function ,in It is a diagonal matrix. The transfer function matrix of the system's related parts; if Order correlation transfer function matrix eigenvalues corresponding If all single-variable control systems are stable, then the entire associated system is stable.
3. The adaptive servo control method according to claim 2, characterized in that, The velocity loops of the main tracking channel and the cooperative execution channel are equivalent to inertial elements. and ,in , For the speed loop controller gain; The position loop controller of the main tracking channel is The position loop controller of the collaborative execution channel is ; The channel decoupling algorithm module is equivalent to: ,in It is the inertial constant; The transfer function of each channel's encoder is equivalent to: ,in It is a lag period.
4. The adaptive servo control method according to claim 3, characterized in that, By configuring the inertial constant With the hysteresis period This ensures that the roots of the characteristic equations of the associated control system model all have negative real parts, thereby maintaining system stability.
5. The adaptive servo control method according to claim 4, characterized in that, The inertial constant The value ranges from 0.05 seconds to 0.1 seconds.
6. The adaptive servo control method according to claim 4, characterized in that, A low-hysteresis, high-precision encoder and an FPGA real-time processing circuit are used to reduce the hysteresis period. .
7. The adaptive servo control method according to claim 1, characterized in that, The closed-loop transfer functions of the main tracking channel and the cooperative execution channel are respectively: Furthermore, the poles of both closed-loop transfer functions have negative real parts.
8. The adaptive servo control method according to claim 1, characterized in that, The parameters that the adaptive algorithm corrects in real time include at least the model uncertainty parameters introduced by load torque jumps, uncertainties in rotational inertia parameters, and fluctuations in inductance and permanent magnet linkage parameters.
9. The adaptive servo control method according to claim 1, characterized in that, The external disturbances compensated by the self-disturbance rejection algorithm include environmental vibrations and non-uniform load changes.
10. The adaptive servo control method according to claim 1, characterized in that, Under complex operating conditions, the steady-state tracking error is less than or equal to 0.15 milliradians, and the settling time is less than or equal to 60 milliseconds.