52 results about "Motor dynamics" patented technology

The invention discloses an early warning method and device for climbing instability of a crawler unmanned vehicle and a medium, and relates to the technical field of unmanned vehicle climbing control. The early warning method comprises the steps that a digital twin model of the tracked unmanned vehicle is constructed, the digital twin model fuses a motor dynamic model and a whole vehicle dynamic model, and virtual scene data is generated; real-time data of a multi-source sensor of the tracked unmanned vehicle are obtained, wherein the real-time data comprise vehicle posture data, environment data and driving system data; and constructing a time convolutional network prediction model based on transfer learning, performing pre-training by using virtual scene data as source domain data, and performing fine tuning by using real-time data as target domain data to form a target domain prediction model. And inputting the current data into the target domain prediction model, and outputting a predicted vehicle state parameter prediction sequence. According to the vehicle state parameter prediction sequence and a preset safety threshold value, the instability risk is evaluated, an early warning signal is sent out, and the generation logic of the early warning signal is evaluated and optimized through an early warning performance loss function.

The invention relates to the technical field of motor fault diagnosis, and discloses a multi-degree-of-freedom resonant excitation motor dynamic vibration test system and a test method, the system injects a specific harmonic current into a motor through closed-loop control and calculation and a high-bandwidth harmonic injection driver, so that the actual vibration of the tested motor tracks a preset target vibration profile in real time. In the testing process, the cross-spectral density of multi-point vibration signals is analyzed, and a transmission path and a collection area of vibration energy in a motor structure are calculated; and meanwhile, the electromagnetic impedance and the mechanical impedance of the motor are identified and decoupled on line by superposing a broadband disturbance signal in the driving current. In combination with energy flow analysis and an impedance decoupling result, the method can accurately position a vibration abnormal position, clearly causes whether a fault source is from mechanical structure characteristic change or electromagnetic part performance change from a physical level, and realizes deep and accurate diagnosis of the dynamic characteristics of the motor.

The invention discloses a real machine deployment method and device for a quasi-direct-drive robot for migration from simulation to reality, and the method comprises the steps: S1, driving each joint motor through a PD controller on a real machine of the robot to follow a plurality of groups of reference tracks, and synchronously collecting the real motion track data of each joint; s2, in a parallel simulation environment, performing initialization based on a random frame in a real motion track, randomly endowing a group of motor kinetic parameters, then driving a simulation robot through a PD controller by using the same group of reference tracks, and generating corresponding simulation motion track data; s3, based on a trajectory error between the two types of trajectory data, iteratively updating motor kinetic parameters by using an optimization algorithm until the error converges, thereby obtaining a calibrated simulator; s4, training a control strategy network of the robot through reinforcement learning in the calibrated simulator; and S5, directly deploying the control strategy network obtained by training to a real machine for performance evaluation and security verification.

The invention relates to the technical field of motor control, and discloses a vector control application of a direct drive motor, which comprises the following steps: S1, collecting stator current, rotor speed and bus voltage signals of the motor, and carrying out filtering preprocessing on the collected signals; and S2, constructing a self-adaptive flux linkage observation model, estimating a stator flux linkage in real time based on stator current and bus voltage signals in combination with rotor rotating speed information, and correcting stator resistance and inductance parameters through a model reference self-adaptive algorithm. According to the method, the motor parameters are corrected in real time through the self-adaptive flux linkage observation model, parameter drift caused by factors such as temperature change and magnetic saturation is effectively counteracted, and the accuracy of flux linkage estimation is improved; the improved PI regulator realizes online self-tuning of control parameters through a fuzzy control algorithm, can quickly adapt to changes of dynamic characteristics of the motor, and shortens the regulation response time of flux linkage and torque; and the resistance of the system to external interferences such as load fluctuation, power supply voltage change and the like is enhanced.

The invention relates to the technical field of motor testing, and discloses a motor dynamic characteristic compensation test method and platform based on multi-modal data, the method collects motor data through a multi-modal synchronous test system, and a processing module executes the following steps: constructing a state observer model to estimate winding temperature and loss torque; in the online test, the accuracy of the model is monitored by calculating the residual error between the model prediction and the measured value; and when the residual dynamic characteristic exceeds a threshold value, generating and applying an adaptive excitation sequence according to the residual characteristic, collecting high-resolution data to update model parameters on line, forming a self-optimization closed loop, after the test is finished, adopting a fixed interval smoothing algorithm to be combined with a final model to obtain a global optimal state track, and calculating a dynamic characteristic compensation result according to the global optimal state track. According to the invention, through adaptive excitation of residual error driving and online model updating, accurate identification and compensation of dynamic characteristics of the motor are realized, and the test automation level and accuracy are improved.

The invention discloses an electric shovel lifting steel wire rope dynamic control device and method based on bucket lifting lug angle changes. The electric shovel lifting steel wire rope dynamic control device comprises a tilt angle sensor, a lifting motor and a whole vehicle controller. The tilt angle sensor is installed in a lifting lug of a bucket of the electric shovel and used for monitoring the dynamic change conditions of the axial tilt angle and the angular acceleration of the lifting lug in the operation process of the electric shovel in real time. A lifting motor dynamic control model established based on the data of the tilt angle sensor is configured in the vehicle control unit, the lifting motor dynamic control model analyzes the real-time posture information of the lifting lug according to the obtained data of the tilt angle sensor, and the tension state of the lifting steel wire rope is further recognized according to the real-time posture information of the lifting lug. And the lifting motor is dynamically controlled accordingly. The angle change of the lifting lug can be automatically monitored in real time, the lifting motor is dynamically adjusted, the fatigue fracture caused by overload of the lifting steel wire rope and the groove jumping overlying fault caused by looseness are effectively avoided, and the operation safety and reliability of equipment are remarkably improved.

The invention provides a shaftless drilling winch and an intelligent cooperative control and thermal management method thereof, and the method is implemented based on an embedded controller and a sensor network, and comprises the following steps: data real-time acquisition, intelligent lubrication heat dissipation control, dual-motor dynamic cooperative control, predictive maintenance management based on a health state, and fault tolerance and degradation operation. According to the system, efficient cooperative driving, on-demand accurate heat management and state-based predictive health maintenance of the winch are achieved, the problems that a traditional winch control system is poor in collaboration, extensive in heat management, lack of health management and the like are solved, and the safety, economical efficiency and modernization level of drilling operation are remarkably improved. According to the invention, the winch is changed from traditional mechanical equipment to intelligent equipment with self-sensing, intelligent decision making and active health management capabilities.

The invention discloses a cross arm and insulator installation robot motor control method based on a T-S fuzzy model, and the method comprises the following steps: building a permanent magnet synchronous motor nonlinear model according to electromagnetism and motor dynamics; based on a sector nonlinear method, establishing a permanent magnet synchronous motor T-S fuzzy model; designing an observer to obtain a load torque estimated value; designing an L-infinity robust controller to ensure that the angular velocity of the motor can track a reference instruction; and an anti-control gain matrix solving criterion is formulated, and it is ensured that the system meets performance indexes. According to the method, the nonlinear control problem of the permanent magnet synchronous motor system is effectively solved, the influence of continuous interference signals on the system can be effectively suppressed, and the robustness of the system is enhanced.

The application provides a motor dynamic control method, device, equipment and vehicle, which can determine different induced electromotive force voltages according to different operation parameters of a target motor, determine a maximum value of the induced electromotive force voltage allowed to appear in the current relay state, and further determine the maximum allowed speed of the target motor. Since the induced electromotive force voltage is constantly changing, the maximum allowed speed is also changing. The switching of the protection mode is performed according to the maximum allowed speed, the dynamic switching is realized, the safety of the motor is ensured, the maximum allowed speed corresponds to a higher vehicle speed, and the normal driving of the vehicle is not affected by limiting the vehicle speed according to the maximum allowed speed.

This application provides an adaptive control method, device, equipment, and medium for a permanent magnet linear synchronous motor, belonging to the field of permanent magnet linear synchronous motor control technology. The method involves: solving a first control law in real time based on motor dynamic characteristic data, motion characteristic data, error characteristic quantities, and a motion error convergence model. This first control law indicates the basic adjustment amount for controlling the motion error convergence of the mover when there is no disturbance, achieving rapid error convergence. Based on the error characteristic quantities and compensation function, compensation coefficients are generated in real time and smoothed using a saturation function to derive a second control law, which provides smooth and effective compensation when disturbances exist. Unlike existing technologies, this application can decouple multiple different control laws through the calculation of the first and second control laws, accommodating control requirements under different operating conditions and ensuring both motor control accuracy and system stability and robustness.

The application belongs to the technical field of motor thermal management and computer simulation, and is a motor dynamic thermal network parameter identification and modeling method for full working conditions, comprising the following steps: S1, constructing an equivalent thermal network model of a motor lumped parameter thermal network structure considering key heat dissipation interfaces; S2, establishing a nonlinear thermal resistance and thermal capacity mathematical model that dynamically changes with temperature; S3, based on virtual and real combination, constructing a combined dataset covering the full working condition domain; S4, using a double-layer hybrid optimization mechanism of sparrow search algorithm combined with a local optimization algorithm to jointly identify unknown parameters to be identified, finally determining the polynomial coefficients of multiple dynamic thermal network parameters, and completing the establishment of the dynamic thermal network model. The application significantly improves the motor full-temperature-zone prediction accuracy, conforms to the physical nature of the motor material and fluid heat dissipation changing with temperature, eliminates the prediction deviation of the traditional constant model in a wide temperature range, and ensures high calculation efficiency by using a simplified model.

This invention relates to a hub-driven electric wheel structure with an integrated disc brake, comprising an electric wheel housing. Within the housing are an outer rotor of a motor, a motor stator, a ventilated brake disc, and an aluminum alloy inner brake caliper. A heat insulation device is provided between the outer circumference of the ventilated brake disc and the electric wheel housing, and a heat insulation baffle is provided between the ventilated brake disc and the motor dynamic seal. The aluminum alloy inner brake caliper is disposed within the inner circumference of the ventilated brake disc, forming a brake assembly. Compared with existing technologies, this invention effectively solves the problem of brake thermal management through structural integration and material innovation, improves motor reliability and system power density, and enables a lightweight, high-thermal-isolation hub-driven electric wheel.

The invention relates to a preset space repeated learning control method for aperiodic speed tracking of a rotating motor, and provides the preset space repeated learning control method for aperiodic speed tracking for the complex and changeable characteristics of speed tracking of the rotating motor, and the method comprises the following steps: introducing a space differential operator to establish a spatial domain rotating motor dynamic model; a speed tracking task is converted into an error tracking task by constructing an expected error trajectory related to a rotor position, and a preset space control law is designed, so that a speed tracking error is converged to an original point neighborhood at a preset position; and further designing a full-amplitude-limiting space repeated learning law, effectively compensating periodic uncertainty caused by the angular position, and realizing rapid and high-precision tracking control on the non-periodic expected angular velocity.

The invention discloses a DC motor dynamic event trigger iteration interval generation method based on ellipsoid set membership estimation. According to the method, firstly, a coding-decoding scheme based on an event dynamic event trigger mechanism is designed to meet the limited bit rate limitation during network transmission, and then, an iteration interval generation method based on a trigger sampling signal is designed to estimate the state of the direct current motor and external interference and generate an interval. When the method is applied to the direct current motor, the interference estimation effect is good, the state interval generation is tight, and the limited bit rate limitation during transmission is met.

The utility model provides a step motor dynamic torque measurement frock relates to electrode measurement equipment technical field, including bearing base and motor main part, bearing base top surface is equipped with L type support frame and telescopic guide frame respectively, and the top surface of L type support frame is equipped with positioning assembly, and the top end side of telescopic guide frame is connected and is equipped with monitoring disc, and the surface of monitoring disc is equipped with torque sensor, and the surface of monitoring disc is embedded and is equipped with guide ball, and the surface of monitoring disc is movably connected and is equipped with transmission torus, and the end of transmission torus away from monitoring disc is hinged and is equipped with flexible coupling, and the end of flexible coupling away from transmission torus is hinged and is equipped with the surface of motor's output shaft, and the multi -point torque sensor on monitoring disc is arranged flexibly through damping telescopic axle, can capture the torque change of different angle, overcomes the limitation of single point measurement, improves precision and data comprehensiveness greatly, provides convenient, efficient technical support for the performance analysis and quality detection of step motor, is especially suitable for research and development and production scene.

The invention provides a motor-oriented dynamic balance deviation adaptive compensation method and system, and relates to the technical field of motors, and the method comprises the steps: collecting a real-time radial vibration time domain signal and a real-time rotating speed signal after a target motor is started and enters a steady-state operation mode; calling a vibration fundamental frequency amplitude reference value and a vibration fundamental frequency phase reference value; amplitude-phase combined comparison is carried out, and the real-time dynamic balance deviation value is quantified; performing deviation time sequence backtracking analysis to obtain a dynamic balance deviation sequence; an intervention compensation decision is made, and a compensation current harmonic component sequence is output; and in the real-time compensation current harmonic injection process of the target motor, tracking closed-loop feedback characteristic parameters to perform dynamic correction. The motor dynamic balance compensation method solves the technical problems that a motor dynamic balance compensation method in the prior art mainly depends on physical static adjustment and cannot respond to dynamic changes of the running state of the motor in real time, vibration of the motor under different working conditions cannot be effectively controlled, and the fault occurrence risk is increased.

The invention discloses a motor dynamic filtering method based on wavelet transform, and relates to the technical field of motor control and signal processing, and the method comprises the following steps: S1, collecting an original angular velocity signal of a motor encoder, and dynamically storing the original angular velocity signal as a data curve; s2, performing frequency analysis on the data curve, and determining a maximum frequency and a target frequency; and S3, selecting a wavelet function, constructing a binary tree-shaped frequency division structure based on the maximum frequency and the target frequency, and performing logarithm and rounding down through the ratio of the maximum frequency to the target frequency. According to the motor dynamic filtering method based on the wavelet transformation, data frequency domain decomposition and reconstruction are achieved through the wavelet transformation, the real-time processing requirement and the data fidelity are effectively balanced, the problems of lagging and data distortion of a traditional filtering method in the aspect of real-time performance are solved, the binary tree-shaped frequency division structure is used for accurately controlling components of all frequency bands, and the filtering efficiency is improved. And the target frequency band is enhanced or weakened by adjusting the wavelet coefficient, so that the frequency domain processing accuracy is improved.

A kind of electromechanical coupling dynamics modeling method of electric vertical take-off and landing aircraft based on differential algebraic equation belongs to electric vertical take-off and landing aircraft technical field.First, the motor dynamics equation in eVTOL electric propulsion system is established according to motor parameters;Second, according to the geometric configuration and inertia parameters of eVTOL, the dynamics equation of fuselage multibody system is established, and the aerodynamic model is applied;Third, the motion driving equation is used to couple based on the general mechanical load calculation scheme of Lagrange multiplier;Finally, the electromechanical coupling dynamics model of eVTOL is established, which is discretized by trapezoidal-Newmark hybrid discrete format, and efficient solution is realized based on Newton iteration method, and it is verified by eVTOL vertical take-off.The invention avoids the defects of traditional simplified model ignoring motor transient characteristics and non-coupling modeling without real-time load feedback, improves the motion response and energy consumption calculation accuracy, and provides reliable dynamics modeling basis for eVTOL energy consumption optimization and commercial design.

The invention relates to the technical field of industrial robot control, in particular to an industrial robot-oriented motor dynamic steering anti-out-of-step control system, which is characterized in that motor operation characteristics are self-learned through an LSTM (Long Short Term Memory) neural network, and rotational inertia is identified in real time by adopting a recursive least square method in combination with multi-sensor data such as vibration, temperature and the like; and the noise covariance is dynamically adjusted in cooperation with improved Kalman filtering. The newly added multi-sensor fusion diagnosis module realizes out-of-step risk pre-judgment based on the D-S evidence theory, and the energy recovery unit improves the braking energy efficiency.

This invention relates to the field of motor dynamic performance technology, specifically disclosing a method for optimizing excitation control parameters based on a high-voltage direct-connected synchronous condenser, comprising: Step S1, defining the excitation control parameters of the high-voltage direct-connected synchronous condenser excitation system; the excitation control parameters include: the gain of the thyristor, the time constant of the integral element of the excitation regulator, the time constant of the differential element of the excitation system, and the coefficient of the thyristor regulation element; Step S2, performing sensitivity analysis based on simulation examples to obtain the influence law of each excitation control parameter on the overvoltage value; Step S3, based on the influence law, constructing a nonlinear coupled mapping model with the excitation control parameters as input and the overvoltage value as output using a neural network; Step S4, using the LMSSA sparrow search algorithm with a leader mechanism, with the minimum overvoltage value output by the mapping model as the optimization objective function, searching and optimizing the combination of excitation control parameters, and outputting the optimized combination of excitation control parameters.

The application belongs to the technical field of motor system control, and discloses a motor feasible task design method based on motor performance parameters and controller structure, which comprises the following steps: first, determining two types of motor performance parameters of the maximum torque and the peak power of the selected motor; second, based on Euler-Lagrange equation, establishing motor dynamics differential equation containing unknown rotational inertia, unknown friction resistance, and describing the characteristics of motor generalized speed; third, designing an adaptive controller to realize speed tracking control and online estimation of unknown rotational inertia, unknown friction resistance and unknown external disturbance; fourth, based on motor performance parameters and adaptive controller structure, establishing task feasibility constraint inequality, and determining motor feasible task in combination with the task load condition. The application can realize the analysis and determination of motor feasible task based on the control strategy and the maximum speed and the maximum torque of the motor without experimental test.

The application discloses a pinch detection method and system based on a motor dynamics model, which comprises the following steps: acquiring the current angular velocity and armature current of a seat motor in real time; based on the motor dynamics equation and the motor electrical model, combining the speed component generated by the current angular velocity and the armature current load component after stripping the inertia component, obtaining the comprehensive pinch force including the speed pinch force and the torque pinch force; judging whether the comprehensive pinch force meets the preset trigger condition; if the trigger condition is met, the corresponding pinch response is executed. The application can accurately eliminate the inertia interference generated by the system acceleration and deceleration without accurate calibration of the rotational inertia, which eliminates the large-scale artificial calibration cost, significantly improves the sensitivity and robustness of the pinch detection in mechanical aging and complex environment, is suitable for the pinch protection of movable parts driven by the motor such as automobile seats, electric doors and windows, and has the advantages of strong self-adaptation, high precision and good robustness.

The present application relates to the field of air compressor variable frequency drive and intelligent control, specifically to a double-motor variable frequency drive method for gearless two-stage air compressor, comprising: collecting double-motor stator high-frequency electrical parameters and pneumatic load state parameters in real time; constructing ideal motor dynamics model based on magnetic field orientation control and torque balance, reconstructing double-motor ideal dq-axis current reference trajectory; extracting pneumatic stiffness perturbation coefficient and inter-stage dynamic flow resistance operator, converting into virtual load torque and injecting into the model, generating theoretical disturbed predicted current trajectory; calculating actual residual vector and theoretical residual vector; adopting dynamic time warping and manifold similarity fusion for waveform form matching, generating coupling state judgment result; when matching succeeds, increasing primary motor stator frequency and weakening secondary motor stator flux linkage, when matching fails, maintaining steady-state proportional integral adjustment; and performing closed-loop online calibration on model parameters, so as to distinguish power grid noise and pneumatic instability and reduce excessive compensation risk.

The invention discloses an extreme fault fault-tolerant control method for a bionic underwater robot, the bionic underwater robot is provided with a buoyancy control device and at least one bionic execution part for providing propulsive force, and the extreme fault fault-tolerant control method comprises the following steps: controlling the bionic underwater robot to float to the water surface through the buoyancy control device; acquiring a motion law of the bionic underwater robot under the extreme fault, controlling the bionic underwater robot to execute a first type of action and a second type of action based on a model prediction control strategy, and driving the bionic underwater robot to perform plane position motion on the water surface so as to reach a target recovery point; according to the model prediction control strategy, an optimization problem is constructed based on current state information, target state information and a motion dynamics model of the bionic underwater robot, and the optimization problem is solved through rolling optimization to generate an optimal control input sequence in a future time domain. The purpose of recycling the bionic underwater robot under the extreme fault condition is achieved.

The invention discloses a dynamic installation detection tool and method for a speed reducer motor, relates to a detection tool and method for installation of a speed reducer motor component, and aims to provide a dynamic installation detection tool and method for a speed reducer motor, which can quickly detect the assembly qualification rate, is convenient to use and is low in cost. The speed reducer motor dynamic installation detection tool comprises a mechanical overturning tool, a power mechanism and a wireless vibration sensor, the mechanical overturning tool comprises an overturning support, an overturning platform and a speed reducer sealing cover, and a plurality of overturning screw holes are formed in panels on the two sides of the overturning support; the turnover platform is provided with threaded holes with the same hole diameter as the turnover screw holes, the turnover platform is provided with a positioning shaft, the positioning shaft is movably arranged in one set of turnover screw holes in the turnover platform and can lock the turnover platform and the turnover support through locking screws, and the speed reducer sealing cover is located above the turnover platform. And the wireless vibration sensor is fixed on the mechanical overturning tool.

This invention relates to the field of motor dynamic performance technology, specifically disclosing a method for jointly optimizing the excitation control structure and parameters of a high-voltage direct-connected synchronous condenser. The method includes: Step S1, establishing an excitation control system for the high-voltage direct-connected synchronous condenser; Step S2, optimizing the fixed parameter module by using the controlled variable method to determine the thyristor amplification factor that improves the system's voltage support performance, i.e., the optimal fixed parameters; Step S3, constructing a mapping model of an artificial neural network for searching and optimizing the dynamic parameter module; Step S4, using an improved artificial fish swarm algorithm to search and optimize the parameter combination of the dynamic parameter module, with minimizing the overvoltage prediction value as the optimization objective, to obtain the optimal dynamic parameter combination; Step S5, applying the optimal fixed parameters and the optimal dynamic parameter combination as the optimized excitation control parameters to the excitation control of the high-voltage direct-connected synchronous condenser. This invention can improve the dynamic response characteristics and voltage support effect of the high-voltage direct-connected synchronous condenser.

The application relates to a method and device for early warning of climbing instability of a tracked unmanned vehicle, and a medium, and relates to the technical field of climbing control of unmanned vehicles. The early warning method comprises the following steps: a digital twin model of the tracked unmanned vehicle is constructed, the digital twin model is fused with a motor dynamic model and a whole-vehicle dynamics model, and virtual scene data is generated. Real-time data of a plurality of sources of the tracked unmanned vehicle is acquired, the real-time data comprises vehicle attitude data, environment data and driving system data. A time convolution network prediction model based on transfer learning is constructed, the virtual scene data is used as source domain data for pre-training, the real-time data is used as target domain data for fine-tuning, and a target domain prediction model is formed. Current data is input into the target domain prediction model, and a predicted vehicle state parameter prediction sequence is output. According to the vehicle state parameter prediction sequence and a preset safety threshold, the instability risk is evaluated, and a warning signal is sent out, wherein the generation logic of the warning signal is evaluated and optimized through a warning performance loss function.

This invention discloses a load balancing scheduling optimization method for multi-motor cooperative drive, relating to the field of multi-motor cooperative control technology. The invention includes the following steps: Step S1, initialization of multi-motor drive system parameters and dynamic load perception; Step S2, forward static load balancing allocation based on an improved equal-increase rate method; Step S3, verification of multi-motor dynamic response constraints and identification of infeasible periods; Step S4, dynamic margin release and load redistribution through finite-depth backward backtracking; Step S5, multi-motor cooperative execution and real-time data feedback; Step S6, iterative optimization and adaptive parameter update. This invention constructs a scheduling framework of "forward calculation - dynamic verification - backward correction - closed-loop iteration," balancing load balancing, dynamic feasibility, and operational economy, significantly reducing the number of dynamic response failures and improving the stability of multi-motor cooperative drive systems. It is applicable to multi-motor cooperative scenarios such as industrial robots and new energy vehicle drives.

The invention relates to the technical field of locomotive modeling, in particular to an urban rail transit locomotive modeling method considering direct current network voltage and mechanical rotating speed, which comprises the following steps: constructing an initial locomotive model of a target locomotive traction system comprising a control system model, a three-phase alternating current asynchronous motor dynamic model and a frequency converter dynamic model; constructing an AC / DC side instantaneous power equivalent model to replace a rotor flux linkage tracking dynamic process of an initial locomotive model, realizing accurate description of a motor transient initial stage at a motor frequency converter DC port, and further ignoring a current inner loop dynamic process of the initial locomotive model; and keeping the rotating speed outer ring control model and the active damping feedforward control model of the initial locomotive model to obtain a locomotive model considering the influence of the direct current network voltage and the mechanical rotating speed. Therefore, the defects that a traditional detailed dynamic model is difficult to carry out mechanism analysis and low in simulation efficiency are overcome, and the problems that a common current equivalent power source model cannot reflect a large-disturbance transient mechanism and the like are solved.

The application discloses a kind of multi-motor dynamic synchronous regulation and control methods based on virtual total shaft state feedback, comprising: constructing multi-motor virtual total shaft control model, through virtual main shaft output setting expected traction torque value and setting each physical motor as follow motor;According to the state data of each motor collected, the state and disturbance of each motor are jointly probabilistically modeled using a pre-set modeling method, to generate the estimated mean and covariance of each motor state;Design a nonsingular terminal sliding surface and calculate the control signal;Set the soft saturation buffer range and construct a soft switching function, buffer the control signal and output the modified control signal;According to the modified control signal, the synchronization control of multi-motor traction output is realized.The multi-motor dynamic synchronous regulation and control method of the application can improve the synchronization stability, anti-interference ability and output smoothness in complex dynamic environment.