3931results about "Electronic commutation motor control" patented technology

The invention relates to the field of mine ventilation, in particular to an intelligent adjusting method and system for mine ventilation. The method comprises the following steps: constructing a dynamic topology model taking a roadway as an edge and taking a fan and an air door as nodes based on a mine CAD drawing; acquiring the actual wind pressure and the actual wind volume of each roadway branch in real time, performing inversion to obtain the current wind resistance, and updating the wind resistance attribute of the edge in the dynamic topology model by using the current wind resistance; calculating the optimal air volume of the roadway branch by using the updated dynamic topology model; based on the optimal air volume, target regulation and control parameters of the draught fan and the air door are obtained through solving by means of a particle swarm algorithm; and according to the target regulation and control parameters, the fan and the air door are adjusted through a fuzzy PID algorithm. The problem that in the prior art, mine ventilation adjustment is not intelligent and safe enough is solved, the theoretical optimal air volume is obtained through deep analysis of the mine, then ventilation adjustment is conducted step by step, and the scientificity and efficiency of ventilation adjustment are improved.

The invention discloses a multi-cycle prediction compensation method for a servo motor based on an M3 kernel, and belongs to the technical field of industrial automation control, and the method comprises the steps: obtaining real-time operation parameters of the servo motor, carrying out the compensation for the rapid change of the servo motor, and generating a short-cycle prediction compensation amount; generating a long-period prediction compensation amount by analyzing a long-period operation rule of the servo motor; generating an instantaneous confidence coefficient according to the real-time operation parameters and the short-period prediction compensation amount, and generating a trend confidence coefficient based on historical precision data of the long-period prediction compensation amount; and calculating a dynamic weight according to the instantaneous confidence coefficient and the trend confidence coefficient, carrying out fusion processing on the short-period prediction compensation amount and the long-period prediction compensation amount, generating a final compensation instruction, and superposing the final compensation instruction to an output end of a servo motor control ring. According to the method, disturbance is processed by constructing short-period and long-period prediction with differential precision in parallel, and the dynamic response speed and tracking precision of the servo system can be remarkably improved.

The invention relates to the technical field of motor control, and discloses a permanent magnet synchronous motor control system and method for an electric drive hydraulic source, and the system comprises a data collection module which is used for collecting the state parameters of the electric drive hydraulic source and the operation data of a permanent magnet synchronous motor in real time through multiple sensors; the sensor redundancy and fault-tolerant module is used for performing parallel sampling through hardware dual-redundancy configuration and dual sensors; the self-adaptive fuzzy logic control module is used for dynamically adjusting a rotating speed instruction and a torque instruction of the permanent magnet synchronous motor based on the collected state parameters; a data driving optimization module; and a digital twinning prediction maintenance module. A self-adaptive fuzzy logic control module is used for dynamically generating a motor rotating speed and torque instruction based on parameters such as real-time pressure, flow deviation and change rate, a fuzzy logic algorithm is used for processing a nonlinear time-varying load and quick response, a self-adaptive fuzzy logic control rule weight and a power conversion circuit parameter are optimized through a reinforcement learning algorithm, and the control precision is improved. And dynamic self-optimization of permanent magnet synchronous motor control is realized.

The invention belongs to the technical field of permanent magnet synchronous generator demagnetization fault detection, and particularly discloses a permanent magnet motor fault early warning system based on big data, which comprises a high-frequency injection and grid-connected control module, a fault early warning module and a fault early warning module, actively injecting a high-frequency disturbance signal of which the frequency is higher than the fundamental frequency into a control loop of the permanent magnet synchronous generator; the multi-source synchronous acquisition module is used for synchronously acquiring multi-dimensional operation parameters of the permanent magnet synchronous generator and performing time domain alignment and frequency domain separation on the multi-dimensional operation parameters to obtain synchronous acquisition signals; the composite feature extraction module is used for extracting a multi-dimensional demagnetization criterion of the permanent magnet synchronous generator based on the synchronous acquisition signal; the self-adaptive threshold regression prediction module is used for performing fusion evaluation on the multi-dimensional demagnetization criteria by using the demagnetization health index model to generate a demagnetization judgment result of the demagnetization degree of the permanent magnet synchronous generator; the method has the advantages that the demagnetization recognition accuracy is improved, and early warning is achieved.

The invention relates to the technical field of industrial automation control, and discloses a water-based paint production and processing equipment control system, which comprises the following steps: acquiring stator current and rotor angular velocity, and reconstructing total load torque by using a sliding mode algorithm; extracting an input power low-frequency component to construct a heat dissipation slow manifold, and calculating a thermal drift disturbance component and an orthogonal residual component through orthogonal projection; on the basis of a two-component generation superposition instruction closed-loop adjustment driving mechanism, a double-time-scale orthogonal projection mechanism is utilized, non-structural thermal drift interference is automatically stripped under the condition that heat transfer parameters of equipment do not need to be predicted, the problem of control divergence caused by model parameter mismatch is solved, and decoupling control over the real rheological state of materials is achieved.

The invention discloses a current harmonic disturbance suppression method and suppression system for a permanent magnet synchronous motor. The method comprises the following steps: acquiring voltage and current signals of an electrical loop phasor test in the operation of the motor; an inductance identification algorithm based on high-frequency response is adopted, high-frequency excitation signals are injected, current response is monitored, and stator inductance parameters are calculated; constructing a multi-synchronous rotating coordinate system based on the parameter, and decomposing the current signal to obtain each harmonic current component; building a fuzzy full-order sliding mode observer, inputting an inductance parameter, voltage data and a harmonic current component, and dynamically adjusting a sliding mode surface parameter to observe the position and the rotating speed of a rotor; independently controlling each harmonic current adjusting channel under a multi-coordinate system in combination with observation information, and generating a compensation control signal; and the synthesized master control signal is output to the driving circuit. The system comprises six units, and the method and the system can accurately obtain parameters, efficiently decompose harmonic waves, accurately observe states, realize multi-frequency harmonic disturbance suppression, and improve motor operation stability and efficiency.

The invention relates to the technical field of servo control, in particular to a high-precision current closed-loop control system and method for a servo driver, and the method comprises the steps: collecting three-phase current, rotor position, winding temperature and bus voltage, and constructing a state data set; constructing a parameter identification model fusing physical prior and an attention mechanism, deducing inductance and flux linkage parameters influenced by temperature, saturation and cross coupling, and correcting a motor model in real time; the correction parameters are injected into an FOC decoupling and feedforward link, and a self-adaptive PI regulator is linked to set the gain of a current loop on line; calculating a d-q axis voltage command according to the update model to respectively control excitation and torque components; an extended state observer is introduced to estimate load abrupt change and parameter disturbance, feed-forward compensation is carried out, and three-phase PWM is generated through anti-Parker and SVPWM; and an inverter nonlinear compensation model of a dead zone and switch delay is constructed, PWM is pre-distorted and output to a power device, and robust and low-ripple current closed-loop control of the servo motor is realized.

The invention relates to the technical field of inverter power control, and discloses a given current-based inverter power control method and system, and the method comprises the steps: calculating a fluctuation compensation parameter based on a bus voltage, and carrying out the real-time compensation of a q-axis basic current, and obtaining a first given q-axis current; predicting the bus voltage of the next period and correcting the first given q-axis current in advance to obtain a second given q-axis current; on the basis of the stator voltage saturation state, weak magnetic d-axis current given is generated, low-pass filtering is carried out on the second q-axis current given and the weak magnetic d-axis current given, and a d-axis current instruction and a q-axis current instruction are obtained; a PWM driving signal corresponding to a dq-axis current instruction is generated, an inverter switch is controlled, meanwhile, a power deviation signal is collected to update q-axis basic current, accurate prediction of bus voltage and advanced correction of given current are achieved, compared with traditional lag compensation, the dynamic response is faster, and the power control precision and the operation stability are improved.

The invention discloses an intelligent control method and system for a motor driver, and the method comprises the steps: building an acoustoelectric incidence matrix through collecting harmonic current and sound pressure fluctuation data in the operation process of a motor, and forming a fault feature library; identifying an available fault mode to determine an energy collection point, and performing phase deviation processing on the collection point to generate an auxiliary driving signal; performing spectrum analysis on the sound pressure fluctuation data to obtain an acoustic characteristic spectrum, extracting an efficiency indication tone through characteristic decomposition, mapping the efficiency indication tone into a torque optimization parameter, and establishing a noise reduction control table; performing spectrum analysis on the enhanced control domain to identify a high-energy frequency band, executing a frequency shift operation to generate a safety frequency band signal, and forming a multi-frequency band management strategy in combination with a noise reduction control table; a management strategy is decomposed into parallel control flows for sequential staggered arrangement, and an energy-saving control matrix is generated; and generating a PWM control signal based on the matrix, carrying out edge reconstruction, and obtaining a softened edge waveform through an anti-resonance injection technology to complete intelligent control of the motor driver.

The invention provides a motor parameter online identification method based on an improved golden section method, and belongs to the technical field of motor parameter identification, and the method comprises the steps: S1, obtaining a residual function of a recursive least square method with a forgetting factor when parameter identification is not carried out on a motor model for the first time; s2, detecting whether the residual function exceeds a preset threshold value or not, and executing a step S3 when the residual function exceeds the preset threshold value; s3, taking the residual function as a target function, and adjusting the forgetting factor by using a golden section method to obtain an optimized forgetting factor; and S4, carrying out motor parameter online identification by using a recursive least square method with the optimized forgetting factor. The method has the advantages that the forgetting factor is dynamically adjusted through the golden section method, the residual function serves as the target function, the optimal solution of the forgetting factor under the corresponding working condition can be found when the system changes rapidly, the tracking speed is increased, the steady-state precision is further improved, and therefore the overall performance of parameter identification is improved.

The invention discloses an open-phase self-fault-tolerant control method for a phase-shift-free dual three-phase permanent magnet synchronous motor. The method can automatically adjust a current distribution relation in the case of an open-phase fault and suppress torque pulsation in combination with neutral point voltage compensation. Comprising the following steps: driving two pairs of three-phase winding modules of the phase-shift-free DTP-PMSM in parallel by adopting two two-level three-phase voltage source inverters, and providing a mathematical model of the motor; current distribution is automatically adjusted; compensating the voltage of the neutral point, and calculating the offset of the fault module; the current is redistributed to suppress the torque ripple after the fault, and the secondary oblique wave component generated by the phase failure fault is eliminated; a current loop controller is improved through dead-beat predictive control; the speed ring controller is optimally designed into an improved sliding mode controller; an improved double-loop controller system is formed by combining improved sliding mode control and dead-beat prediction control, high-gain parameters are set to improve the dynamic response performance of the system, and a new self-fault-tolerant control system is formed.

The invention discloses a frequency conversion vector control method for a digital energy-saving pump station, which belongs to the technical field of vector control and comprises the following steps: constructing a coupling vector model, simulating the running states of a pump unit under different working conditions through a virtual test signal, and automatically correcting the coupling vector model; operating data of a pump set are collected in real time, an operating situation feature set is constructed, predictive vector control is carried out, an optimal voltage vector sequence is generated, and meanwhile load fluctuation of a pipe network is predicted; demand pre-judgment is carried out on the starting and stopping time and the action amplitude of the anti-backflow device, a bidirectional disturbance suppression mechanism is constructed, current vector parameters are pre-adjusted, and calculus correction is carried out based on deviation judgment; when multiple pumps operate in parallel, the instantaneous operation efficiency point of the pump set is calculated in real time, the efficiency change trend is predicted, a load distribution scheme is generated, the comprehensive energy efficiency is evaluated, energy efficiency self-optimization is carried out, the comprehensive energy efficiency of the system is improved, and control experience reuse is achieved.

The invention discloses an embedded motor torque ripple real-time compensation system based on deep learning, and relates to the technical field of motor control and artificial intelligence crossing, the system comprises a hardware data acquisition module, a signal feature extraction module, a deep learning compensation model module, an embedded real-time compensation module and a compensation effect verification module; a motor position and a current signal are acquired in real time through the hardware data acquisition module, dynamic analysis and multi-dimensional feature construction are performed on torque ripple related features by combining the signal feature extraction module, and the deep learning compensation model module learns a fluctuation rule in historical data by using a space-time sequence model to generate a high-precision compensation current. The model adapts to an embedded environment through lightweight design, real-time deployment and dynamic optimization of a compensation algorithm are achieved, compared with traditional PID control, the scheme can adapt to changes of motor operation conditions, the influence of torque fluctuation on system stability is reduced, and the smoothness and efficiency of motor operation are improved.

The invention provides a dual-motor synchronous coordination control method of an electric helicopter, which comprises the following steps: taking a first controller as a main control motor driving system, and establishing a rotor rotating speed reference by adopting a rotating speed loop control strategy; and the second controller serves as a slave control motor driving system, a torque loop control strategy is adopted, and load disturbance is estimated and compensated in real time through the extended state observer. According to the dual-redundancy motor driving system, mechanical coupling interference is effectively inhibited, the fault tolerance of the system is enhanced, a feasible technical scheme is provided for safe flight of the electric helicopter, and the dual-redundancy motor driving system has important application value.

The invention belongs to the technical field of power electronics, and relates to an energy feedback high-power-factor air conditioner compressor driving system. Comprising a direct-current bus, a direct-current bus electrolytic capacitor, a motor driving circuit, a shutdown energy feedback circuit, a permanent magnet synchronous motor and a motor control module, wherein the two ends of the direct-current bus electrolytic capacitor are connected with the positive electrode and the negative electrode of the direct-current bus respectively; in the energy feedback control module for driving the combined switch device in the shutdown energy feedback circuit, the motor driving circuit and the shutdown energy feedback circuit, the second connecting end I of each phase of bridge arm is connected with the positive electrode of the direct-current bus, and the second connecting end II of each phase of bridge arm is connected with the negative electrode of the direct-current bus; the first connecting end of the phase bridge arm of the shutdown energy feedback circuit is connected with the phase power grid voltage through the phase filter inductor. The method can maintain the stability of the DC bus voltage, and reduces the influence of the power grid voltage fluctuation and the air conditioner compressor load fluctuation.

The invention relates to an FOC control method based on an automobile air conditioner module motor without a Hall sensor, and belongs to the technical field of automobile electronics. The method comprises the following steps: injecting double-frequency voltage pulses into a stator in stages to position a rotor; collecting current through a sampling resistor and filtering to construct a rotor flux linkage distribution model, and presetting rectangular axis current in combination with noise reduction of a miniature acoustic sensor and air speed gear of an air conditioner; an extended Kalman filter observer is adopted to reversely deduce the load torque, and the torque change rate is monitored to trigger instantaneous load impact protection; the voltage space vector amplitude is corrected through voltage feed-forward compensation, a resistor-capacitor series filter circuit is additionally arranged, and phase dislocation pulse width modulation is adopted for resisting interference; and establishing a motor efficiency-rotating speed-load three-dimensional optimization method, starting dynamic flux-weakening control, and estimating the winding temperature through the stator resistance to adjust the flux-weakening depth. Accurate starting and dynamic load adaptation of the Hall-sensor-free motor are achieved, starting out-of-step and noise exceeding are avoided, and stable air volume of an automobile air conditioner and long-term reliable operation of the motor are guaranteed.

The invention relates to the technical field of motor control, and discloses a voltage compensation stable management system for a vortex oscillator motor, and the system comprises a detection unit which is used for collecting a bus current signal; the processing unit is used for performing differential operation on the bus current signal to determine a current change rate, judging that a load sudden change working condition is entered when the current change rate exceeds a preset threshold value, and further querying a load response coefficient according to a preset feature table and calculating a voltage compensation increment; and the driving unit is used for adjusting the phase shift angle of the excitation voltage according to the voltage compensation increment. According to the invention, by identifying the load working condition in real time and executing feedforward compensation, the instantaneous voltage drop caused by load switching is eliminated, the voltage steady-state characteristic of a motor driving link is maintained, the rotation speed fluctuation is effectively inhibited, and the dynamic response capability of the system under the variable load working condition is enhanced.

The invention discloses an AC excitation system rotor initial position on-line identification method and system, and the method comprises the steps: collecting a stator three-phase voltage signal when a stator is no-load, carrying out the Clarke conversion of the signal, obtaining a voltage component under a static coordinate system, and carrying out the low-pass filtering processing; calculating a stator flux linkage based on the stator current and the processed voltage component, and calculating a rotor flux linkage based on the rotor current; the rotor initial position offset is continuously accumulated through closed-loop adjustment by calculating the stator and rotor flux linkage angle and the phase difference until the phase difference approaches zero, and the accumulated rotor initial position offset is output; and combining the mechanical angle output by the encoder with the accumulated rotor initial position offset to obtain a corrected rotor position angle, and updating the corrected rotor position angle to an excitation system. According to the method, the in-phase characteristics of stator and rotor flux linkages are utilized, and the optimally designed low-pass filter is combined, so that the identification precision of the initial position of the rotor is remarkably improved, and the zero offset of the encoder is effectively compensated.

The invention discloses a neural network enhanced active-disturbance-rejection current control method for a flux-adjustable permanent magnet synchronous motor, belongs to the technical field of motor control, and aims to solve the problem of current loop performance deterioration caused by dramatic change of motor parameters in the flux adjusting process of the flux-adjustable permanent magnet synchronous motor. The method comprises the following steps: acquiring the current magnetization state and direct-axis current of the motor; based on the magnetization state and the direct-axis current, time-varying parameters of the motor are predicted online in real time through a neural network, and the predicted time-varying parameters comprise direct-axis inductance, quadrature-axis inductance and permanent magnet flux linkage; calculating a feed-forward compensation voltage based on the predicted time-varying parameter; generating a current instruction value by using the predicted time-varying parameter and the feed-forward compensation voltage; generating an active-disturbance-rejection feedback control voltage based on the predicted time-varying parameter and the current command value; and superposing the feed-forward compensation voltage and the active-disturbance-rejection feedback control voltage to obtain a final voltage given value for driving the motor.

The invention discloses a multi-motor parallel control system and method based on an FPGA, and belongs to the technical field of multi-motor parallel control. The FPGA module is in communication connection with the control processing unit, and the FPGA module is internally provided with a global synchronous triggering unit used for generating a periodic synchronous triggering signal; the number of the position acquisition sub-modules corresponds to that of the motors, and each position acquisition sub-module comprises a position counter and a hardware latch register, wherein the position counter is used for carrying out counting and direction decoding on encoder pulses in real time; wherein the global synchronous triggering unit is connected with all the position acquisition sub-modules. According to the multi-motor synchronous control system, the position and other state signals of the multiple motors are collected at the same time through the parallel processing capacity of FPGA hardware, real-time control is achieved in combination with the control processing unit, and therefore the multi-motor synchronous control precision is improved, and the response speed is increased.

The invention discloses a weight coefficient-free model prediction control system and method for a permanent magnet synchronous motor, and particularly belongs to the field of permanent magnet synchronous motor control. The control system comprises a direct current voltage source, a three-phase converter, a permanent magnet synchronous motor, a rotating speed outer ring PI control module, an MTPA flux linkage calculation module and a model prediction control module. The control method comprises the following implementation steps: firstly, establishing a torque and flux linkage prediction model of the permanent magnet synchronous motor; then, a reference torque amplitude value and a reference flux linkage amplitude value are obtained through a rotating speed outer ring PI controller and a maximum torque per ampere (MTPA) calculation module respectively; secondly, constructing an independent torque cost function and a flux linkage cost function according to the torque error and the flux linkage error, and forming a cascade form; evaluating the switching states by using a cost function, selecting two vectors from the eight switching states of the converter by using the independent cost function of the torque (or flux linkage), and selecting an optimal vector from the two vectors by using the independent cost function of the flux linkage (or torque); and finally, the execution sequence of the torque and flux linkage cost function is alternated in each subsequent period. Compared with the prior art, the method avoids complex weight coefficient design through a cost function cascading mode, alternates the execution sequence of the cost functions in each period, dynamically balances the weights of the two control targets, and reduces the number of calculation times.

The invention provides a bus voltage adjusting method of a compressor, the compressor and electronic equipment. The bus voltage adjusting method of the compressor comprises the steps that the current current of the quadrature axis of a motor corresponding to the compressor and the current rotating speed corresponding to the compressor are collected; determining whether the current meets a first preset condition or not, and determining whether the current rotating speed meets a second preset condition or not; and when one of the first preset condition and the second preset condition is met, increasing the bus voltage of the compressor. According to the bus voltage adjusting method of the compressor, one of the current current of the quadrature axis of the electrode corresponding to the compressor and the current rotating speed of the compressor serves as a reference, so that the bus voltage is increased, the rotating speed of the compressor can be guaranteed, and the overall efficiency and performance are improved.

The invention discloses a surface-mounted permanent magnet synchronous motor sensorless high-performance sliding-mode control method, and the method comprises the steps: designing an improved self-adaptive terminal sliding-mode switching function for the problem of high-frequency buffeting of a sliding-mode observer caused by the fixed gain design of the switching function; and dynamically adjusting the gain of the switching function according to the sum of the stator current error and the integral thereof under the two-phase static coordinate system so as to suppress high-frequency buffeting and improve the estimation precision. In order to further improve the performance of the position sensorless control system, a reaching law in a sliding mode controller is optimized, a novel composite gain self-adaptive sliding mode reaching law is designed, the reaching law combines a self-adaptive gain term, a nonlinear exponential term and a linear term, the system state is accelerated to approach when being far away from a sliding mode surface, buffeting is reduced when the system state approaches, and the control precision of the position sensorless control system is improved. Therefore, the dynamic response speed and buffeting suppression capability of the control system are balanced.

The invention relates to the technical field of maglev motor dynamics and control, and discloses a bearingless asynchronous motor multi-frequency harmonic vibration cooperative suppression method, which comprises the following steps: acquiring radial displacement signals and mechanical angular velocity of a rotor in an x axis and a y axis under a stator fixed coordinate system, and stacking double-axis displacement signals into an observation vector; calculating a weighting coefficient of the normalized residual error through a Huber robust cost function, and outputting the amplitude, the phase and the confidence of each order of harmonic wave; estimating the total disturbance of the system by using a linear extended state observer with harmonic energy injection, wherein the total disturbance is obtained by weighted summation according to the confidence, order and mechanical angular velocity of each order of harmonic; calculating a feedback control force according to the total disturbance estimated value, and superposing the feedforward compensation force and the feedback control force to generate a total suspension force instruction; and according to the total suspension force instruction, inversely calculating a suspension winding current reference value and outputting a control instruction. According to the invention, a mutually complementary cooperative suppression mechanism is formed, and the suppression precision of multi-frequency vibration is improved.

The invention discloses a self-adaptive multi-mode operation control method for a direct-drive motor, and belongs to the technical field of motor control. According to the method, motor operation state data are acquired through a physical sensor network, and after synchronous acquisition through an FPGA, data preprocessing and feature extraction are sequentially performed to obtain and store mode features of the direct-drive motor. And constructing a direct-drive motor mode recognition model based on the decision gradient lifting decision tree, recognizing the motor working mode of the direct-drive motor according to the mode characteristics of the direct-drive motor, automatically switching the corresponding control strategy, monitoring the operation performance index of the direct-drive motor under the control strategy, and judging whether to optimize the internal parameters of the control strategy. According to the method, adaptive control of multi-mode operation of the direct-drive motor is realized, the control precision and the system stability are improved, and the method has relatively high engineering application value.

The invention relates to the technical field of motor control, and discloses a motor single closed-loop control method and system based on D-axis current, and the method comprises the steps: inputting a D-axis current feedback signal of a permanent magnet synchronous motor into a first harmonic band-pass filter and a second harmonic band-pass filter for filtering, obtaining a first harmonic current component and a second harmonic current component; carrying out weight coefficient calculation to obtain a first harmonic weight coefficient and a second harmonic weight coefficient; performing zero steady-state error tracking control through a first harmonic quasi-resonance controller to obtain a first harmonic compensation voltage, and performing zero steady-state error tracking control through a second harmonic quasi-resonance controller to obtain a second harmonic compensation voltage; and performing weighted synthesis and amplitude limiting processing on the first harmonic compensation voltage and the second harmonic compensation voltage to obtain a D-axis compensation voltage, thereby ensuring a harmonic suppression effect in a wide rotating speed range, and solving the problem that a fixed frequency controller fails during variable-speed operation.

The invention discloses a permanent magnet synchronous motor rotating speed control method based on composite sliding mode control. The method comprises the steps that a mathematical model of a permanent magnet synchronous motor in a d-q axis synchronous rotating coordinate system is built; designing a layered sliding mode surface according to the mathematical model of the permanent magnet synchronous motor; designing a mixed reaching law containing a barrier function in combination with a sliding mode surface; and estimating periodic and non-periodic disturbances existing in the rotating speed of the permanent magnet synchronous motor and carrying out feed-forward compensation on sliding mode control by adopting a cascaded extended state observer combined with quasi-resonance control. According to the method, the rotating speed precision of the permanent magnet synchronous motor can be effectively improved, the dynamic response is improved, and a better inhibition effect on periodic and non-periodic disturbance is achieved.

The invention relates to the technical field of servo motor control, and particularly discloses an intelligent control system and method for a servo motor, and the method comprises the steps: collecting the position, speed, current and acceleration data of the servo motor, and constructing a state vector; constructing a reference disturbance observer based on the theoretical parameters, and outputting an observation state, a disturbance value and an observation residual error; a multi-scale time sequence feature tensor is constructed by using the observation residual error and the state vector, and future disturbance is predicted through a CNN-Transform network; carrying out adaptive fusion on the neural network prediction result and the output of the reference observer; performing security constraint on disturbance compensation through a constraint filter and an amplitude limiter; and injecting the constrained compensation signal into a control system, and continuously optimizing the network performance through online incremental learning. According to the method, a traditional observer and a deep learning technology are fused, precise prediction and effective suppression of complex nonlinear disturbance are realized, and the control stability of the servo motor is remarkably improved.

The invention discloses a motor control method and device, a motor, an air compressor, a storage medium and a computer program product, and the method comprises the steps: carrying out the processing of the components of the stator voltage of the motor on the alpha and beta axes and the components of the stator current of the motor on the alpha and beta axes through a preset sliding mode observer module, and carrying out the control of the motor; the components of the counter electromotive force estimated value of the motor on the alpha and beta axes are obtained; based on the components of the back electromotive force estimation value of the motor on the alpha axis and the beta axis, after a preset phase-locked loop module and a preset staged angle compensation module are used for processing, a rotor electrical angular speed estimation value of the motor and a rotor electrical angular position estimation value of the motor are obtained, and control over the motor is achieved. According to the scheme, by combining the sliding mode observer module, the phase-locked loop module and the staged angle compensation module, the rotor electrical angular velocity estimation value and the rotor electrical angular position estimation value of the motor are determined, sensorless control over the motor is achieved, and the control performance of the motor is improved.

The invention discloses a permanent magnet synchronous motor joint simulation method, which comprises the following steps of: firstly, establishing a permanent magnet synchronous motor finite element model in Maxwell, and defining material nonlinear characteristics and motion boundary conditions; a motor drive control circuit is constructed in Simplorer, the finite element model is imported through a Twinbuild tool, and an electromagnetic-circuit joint simulation environment is established; creating a motor multi-body dynamic model and an external load model in Adams, and respectively exporting the motor multi-body dynamic model and the external load model into an FMU format and an Adamssub format; and finally, establishing an electromagnetic-circuit-mechanism joint simulation platform in the Simulink, and executing joint simulation. Compared with traditional joint simulation, according to the method, through electromagnetic-circuit-mechanism three-field real-time interaction, the motor can sense the load sudden change working condition, then the torque and current of the motor are rapidly adjusted through the PI controller, the problems that in engineering practice, the external load of the motor is not real, and the abnormal load is detected are solved, and the reliability of the motor is improved. And the crossing from an ideal load to an actual load is realized.