533results about "Modelling/simulations for control" patented technology

The invention is suitable for the technical field of brushless motor control, and provides an intelligent brushless motor and a control method thereof, and the method is applied to a control system of the intelligent brushless motor. The system comprises a data acquisition module, a model construction module, a training tuning module, a model verification module, a parameter setting module, an operation application module, a wireless communication module, a memory, an alarm, a processing center and an intelligent mobile terminal. The data acquisition module, the model construction module, the training optimization module, the model verification module, the parameter setting module, the operation application module, the wireless communication module, the memory and the alarm are respectively connected with the processing center; the invention also provides an intelligent brushless motor. According to the method, the AI model is constructed and trained by collecting the daily motor operation quality data, and the operation control parameters are matched according to the model, so that various operation quality abnormalities are prevented, and accurate control of the motor is ensured.

The invention provides a multi-mode control method and system for a brushless doubly-fed motor, and relates to the technical field of motor control, and the method comprises the steps: extracting torque-rotating speed slopes and dynamic response time constants of two points based on a steady-state working point of a current mode and an expected working point of a target switching mode, and constructing a linear correction function; fusing an output value of the linear correction function with an optimization result to generate a modal transition compensation coefficient, and injecting the compensation coefficient into a rotor side voltage control ring based on a feedforward control channel to generate an anti-disturbance dynamic compensation control strategy; and for a non-smooth adjustment item in the dynamic compensation control strategy, performing smoothing processing on a discontinuous boundary of a control quantity by adopting a subgradient projection algorithm, verifying continuous conductivity of a control curved surface in combination with a Lyapunov stability criterion, and generating a final control instruction. According to the invention, adaptive smooth switching control of the brushless doubly-fed motor can be realized.

The invention relates to the technical field of electric driving system energy-saving control, and discloses a multi-motor driving system torque optimal distribution method and system, and the method comprises the steps: building a single power unit power loss model of a multi-motor driving system; constructing a fitting straight line segment; constructing a torque-current mapping relation curve; a train speed prediction model, a multi-motor driving system power unit motor rotating speed prediction model, a multi-motor driving system total torque reference value prediction model and a multi-motor driving system power unit power loss prediction model are constructed; establishing a multi-motor driving system energy efficiency evaluation function, a multi-motor driving system stability evaluation function, a multi-motor driving system total torque following evaluation function and a system optimization objective function; designing a learning rate of a control vector; and updating the control vector according to the learning rate, and obtaining an optimized torque distribution coefficient and an optimized torque reference value distributed by each power unit. Therefore, the torque optimization distribution of the multi-motor driving system is realized, and the energy utilization efficiency of the system is improved.

The invention provides a brushless motor multi-axis cooperative control method and system for an industrial robot, and relates to the technical field of control, and the method comprises the steps: processing the real-time parameters of a brushless motor of each joint axis through constructing an extended dynamic model, and obtaining a temperature drift coefficient and a load inertia parameter; a self-adaptive pre-compensation model, a neural network compensator and a recurrent neural network prediction model are combined, a torque control instruction is output, a three-phase current prediction value is calculated, a distributed model prediction controller is adopted to generate an optimal switching sequence, multi-axis cooperative control is achieved, and the system stability and the response speed can be effectively improved.

The invention relates to the field of motor control, and particularly discloses a model-free deadbeat predictive speed control method and system for a permanent magnet synchronous motor (PMSM), and the method comprises the steps: building a second-order hyperlocal model of the permanent magnet synchronous motor; according to the second-order hyper-local model of the permanent magnet synchronous motor, establishing a third-order linear expansion state observer; based on the second-order hyper-local model of the permanent magnet synchronous motor, establishing a model-free and dead-beat speed control law; and substituting the speed observed by the third-order linear expansion state observer and the observation value of the total disturbance in the next period into a model-free deadbeat speed control law to obtain a reference current. According to the method, the dynamic and steady-state performance of the PMSM driving system can be improved, the system has high robustness, and high-performance safe operation of speed control of the PMSM driving system is achieved.

The invention discloses a degradation trend prediction method for a brushless direct current motor, and relates to the technical field of motor control, current, temperature and vibration signals of motor operation are collected, a characteristic signal transmission path model of a winding, a bearing and magnetic steel is constructed, and the degradation trend of the brushless direct current motor is predicted by analyzing the reflection characteristics and attenuation conditions of degradation signals of all parts. Extracting characteristic quantities of mutual influence among current, temperature and vibration; according to the method, a multi-component characteristic signal transmission path model is constructed, degradation signals are regarded as fluctuation quantity transmitted and reflected among different components, mutual influence of current, temperature and vibration signals is comprehensively analyzed, false characteristics are separated in combination with heat transfer lag characteristics and cooperative change critical points, accurate extraction of real degradation characteristics is realized, and the accuracy of the degradation characteristic extraction is improved. The problem that weak degradation signals are covered by interference is solved.

Disclosed are systems and methods for motor control using piecewise affine modelling. An electronic controller may determine current values for a motor in a rotational reference frame. Each current value may be associated with a dimension of a set of dimensions of the rotational reference frame. The electronic controller may further determine, based on the current values, a flux linkage value for each of the set of dimensions of the rotational reference frame using a piecewise affine map. The electronic controller may further determine a target flux linkage value for each of the set of dimensions of the rotational reference frame. The electronic controller may then control a power switching network coupled between a power supply and the motor based on the flux linkage values and the target flux linkage values.

The invention belongs to the technical field of engineering machinery control, and discloses a permanent magnet synchronous motor fault early warning and detection method, which comprises the following steps of: obtaining a system model of a permanent magnet synchronous motor by adopting a mechanism modeling method, and calculating the fault early warning of the permanent magnet synchronous motor through different analysis methods of the system model according to an optimization theory under constraint conditions; different minimum output deviation functions are designed under different external cause conditions, numerical analysis is carried out on the deviation functions to achieve triggering conditions of different faults, and meanwhile the controller transmits control signals to the fault early warning device to achieve detection of different faults. According to the method disclosed by the invention, the defects that a traditional motor fault diagnosis method is not timely, fault point judgment is inaccurate and misjudgment is easily caused by uncertain interference factors are overcome, and the steady-state performance and the transient-state performance of a permanent magnet synchronous motor system are enhanced.

The invention discloses a multi-target robust model predictive control method for a permanent magnet synchronous motor, which is used for a three-level inverter power supply permanent magnet synchronous motor system with a quadruple BOOST booster circuit, and comprises the following steps: firstly, carrying out system modeling and discretization, then carrying out multi-target cost function design, solving a multi-target optimization problem based on compromise programming and a fuzzy decision method, and finally, carrying out multi-target robust model predictive control on a three-level inverter power supply permanent magnet synchronous motor system with a quadruple BOOST booster circuit. And calculating a delay compensation strategy and a robustness enhancement measure, and finally calculating the output voltage of the quadruple Boost circuit and the output voltage of the inverter. The method improves the DC bus voltage, improves the output power and efficiency, enhances the robustness of the system to parameter change and uncertainty, realizes multi-target optimization control, ensures that the system stably and efficiently operates under complex working conditions, and is suitable for the fields of speed regulation of motors with booster circuits and the like.

The invention provides a permanent magnet frequency conversion double-sine modulation swimming pool pump energy-saving control method, and relates to the technical field of motor driving and control, and the method comprises the steps: building a double-sine carrier modulation model of a permanent magnet synchronous motor, and calculating a dynamic harmonic suppression factor and a double-sine modulation depth in real time; feedforward compensation is carried out on the inverter current based on the DHSIF, and a q-axis current reference value is generated by adopting double-closed-loop vector control; dynamically adjusting a carrier frequency range according to the DSMD, generating double sine carriers with a phase difference of pi / 3, and superposing the double sine carriers into a composite modulated wave; the modulation wave amplitude is corrected through a DHSIF, and fifth and seventh harmonics are eliminated in combination with an adaptive filtering algorithm; a carrier wave ratio is dynamically optimized to generate a PWM signal, and a transient compensation mechanism is triggered to correct a voltage instruction when a load suddenly changes; and an energy efficiency optimization database is constructed to call historical optimal parameters, and nonlinear mapping of DHSIF and motor characteristics is established through parameter self-tuning. According to the invention, cooperative control is realized through dynamic harmonic suppression, modulation depth optimization and intelligent thermal protection.

The invention discloses a model prediction control method of a high-speed permanent magnet synchronous motor and a related device, and relates to the field of control, and the method comprises the steps: building a stator current equation capable of simulating the behavior of the high-speed permanent magnet synchronous motor based on the position change of a rotor in the same control period, a high control input basic voltage value is obtained by fixing motor parameters and combining a total disturbance parameter of a current loop system and a set stator current tracking target at the next moment at the same time; on the basis of the control input basic voltage value, current loop harmonic voltage compensation is carried out through the control input harmonic compensation voltage value to obtain a control input voltage value, and voltage modulation is carried out according to the control input voltage value to control the high-speed permanent magnet synchronous motor. According to the method, when the stator current equation is constructed, rotor position change parameters in the same control period are innovatively introduced, so that the motor behavior simulation precision is remarkably improved; the defect that the switching frequency is not fixed in a traditional finite set model predictive control algorithm is effectively overcome through the voltage modulation technology.

The invention discloses an intelligent control method and system for a brushless direct current motor and a storage medium, and the method comprises the steps: constructing a mathematical model of a rotating speed and current double-closed-loop speed regulation system of the brushless direct current motor and a simulation model of a control system of the brushless direct current motor, and controlling a rotating speed PID (Proportion Integration Differentiation) controller by using an improved Sabot swarm optimization algorithm; when a set termination condition is met, outputting the global optimal position of the salmons individual corresponding to the population position of the current salmons population, and obtaining a target value of the to-be-optimized parameter according to a solution corresponding to the global optimal position of the salmons individual; controlling the brushless direct current motor based on the target value of the to-be-optimized parameter; according to the method, an improved saloat swarm optimization algorithm is fused with a Gaussian random walk strategy and a warning mechanism of a sparrow algorithm, and a chaotic mapping optimization initial population is introduced and is used for optimizing a fuzzy rule, so that the convergence speed and precision of searching the fuzzy rule are improved, and the problem that parameters of a PID controller are difficult to set is more effectively solved.

The invention relates to the technical field of motor control, and discloses an axial magnetic flux hybrid excitation synchronous motor field weakening control system based on multi-source feedback. According to the system, a motor digital twinborn model is constructed, and real-time operation data are collected by using a multi-source sensor and synchronized to the model; establishing a three-dimensional electromagnetic field state space based on the model, extracting features through a manifold neural operator, and generating a multi-dimensional excitation state feature set; determining an excitation anomaly feature index set according to the feature set distribution density; collecting data in real time, extracting current excitation characteristic parameters, mapping the current excitation characteristic parameters to a three-dimensional electromagnetic field state space, calculating spatial correlation with the abnormal index set, and outputting weak magnetic demand correlation factors; and finally, according to the correlation factor, the feature set and real-time data iteration updating operator parameters, a control instruction is generated to dynamically adjust the coupling proportion of the electrical excitation component and the permanent magnet excitation component. According to the system, comprehensive perception and accurate regulation and control of the motor operation state are realized, and the adaptability and reliability of field weakening control are improved.

The invention relates to the technical field of motor control, discloses a direct current brushless motor control method and system based on current prediction, and aims to solve the problems of large torque ripple, low efficiency and poor stability caused by current loop lag in the prior art. The method comprises the following steps: acquiring a motor operation state signal in real time; determining a sector and an electrical angular velocity based on the rotor position and the rotational speed; inputting related parameters into the mixed current prediction model to obtain a three-phase current prediction value of the next period; a prediction error is calculated in combination with a current instruction, and an optimal voltage vector enabling a cost function to be minimum is solved through a model prediction control algorithm; and finally, a space vector pulse width modulation signal is generated to drive an inverter. According to the method, advanced control is realized by fusing a physical model and a data-driven prediction mechanism, the torque ripple is remarkably reduced, and the energy efficiency and robustness are improved.

The current profile of excitation current provided to the electrical coils of a switched reluctance machine is controlled to reduce acoustic noise. A plurality of potential current waveforms can be evaluated to select a desired waveform that reduces the acoustic noise level of the switched reluctance machine. A cumulative sound pressure level of the switched reluctance machine can be determined for each potential current waveform. The cumulative sound pressure level can be determined based on a plurality of harmonic sound pressure levels expected to result from the potential current waveform. A desired current waveform can be identified as the potential current waveform associated with an optimal cumulative sound pressure level. The desired current waveform can then be applied to the corresponding phase coil of the switched reluctance machine in order to operate the switched reluctance machine while reducing acoustic noise without sacrificing other motor performance metrics.

The invention discloses a coaxial double-switch reluctance motor torque ripple minimization control method, which comprises the following steps: establishing a unified model for two switch reluctance motors, obtaining a reference torque through a proportional integral controller after making a difference between a reference rotating speed and an actual rotating speed, and establishing a phase current prediction model according to a phase voltage equation of the switch reluctance motors, based on the predicted current and the predicted angle, establishing a torque prediction model in a positive voltage excitation and zero voltage follow current mode in the conduction interval of each phase winding, and establishing a torque prediction model in a negative voltage demagnetization mode in the turn-off interval of each phase winding to obtain predicted torques of each phase winding in the conduction interval and the turn-off interval; and establishing a unified evaluation function by using the predicted torque and the reference torque of each phase winding of the two switched reluctance motors, and selecting an optimal switching state which enables the evaluation function to be minimum, thereby realizing the torque pulsation minimization control of the coaxial double-switched reluctance motor. The torque ripple minimization control method of the coaxial double-switch reluctance motor is not influenced by the phase difference of the double motors and the conduction range of each phase winding, can be easily expanded to a double-switch reluctance motor driving system with any phase number, and has good application prospect and engineering value.

The invention discloses a deep-cone thickener rake frame driving method and system based on a permanent magnet motor, and belongs to the technical field of mine solid waste disposal and filling, and the method comprises the following steps: collecting real-time operation parameters of the permanent magnet motor, the real-time operation parameters including stator current, voltage, rotating speed and output torque; based on the output torque, whether the deep-cone thickener is in a rake pressing state or not is recognized, and when the deep-cone thickener is in the rake pressing state, the reference rotating speed of the permanent magnet motor is controlled to be reduced; the real-time temperature of a stator winding and a rotor permanent magnet area in the permanent magnet motor is obtained, and when the real-time temperature is higher than a preset threshold value, the output power of the permanent magnet motor is controlled; acquiring historical load data of the deep-cone thickener, and modeling the historical load data and the output torque to obtain a historical load-torque model; and constructing a torque change prediction model based on the historical load-torque model, predicting future torque data by using the torque change prediction model, and identifying an impending rake pressing risk.

The invention provides an efficiency optimization control method of a permanent magnet synchronous motor and related equipment. The method comprises the following steps: acquiring an output current of an inverter; constructing an inverter loss model based on the output current of the inverter and the inverter loss coefficient; constructing a total loss model based on the electromagnetic loss model, the inverter loss model and an equivalent conversion method; constructing a current population by taking the plurality of d-axis current values as individuals; and performing optimization solution based on the total loss model, the current population, a PID search algorithm and an artemisinin optimization algorithm to obtain a global optimal solution and control the permanent magnet synchronous motor. According to the scheme, the driver loss is added into the total loss model, and efficiency optimization can be carried out on the whole motor driving system; in order to solve the problem that a traditional method is not suitable for an IPMSM, a PID search algorithm and an artemisinin optimization algorithm are combined, parameter search is carried out on a motor efficiency optimal point by simulating an incremental PID controller adjusting mechanism, a global optimal solution is obtained, and therefore optimal control over the click efficiency is achieved.

The invention provides a permanent magnet synchronous motor sliding mode control method and system based on disturbance compensation, and the method comprises the steps: constructing a first motor state equation based on a permanent magnet synchronous motor mathematical model containing disturbance; secondly, on the basis of a sliding mode control theory, a novel adaptive reaching law and a non-singular fast terminal sliding mode surface are constructed, stability proving is completed, and the fast convergence capability is analyzed; designing a novel speed ring controller through the state equation, the reaching law and the sliding mode surface; designing a sliding mode disturbance observer for a disturbance part in the speed loop controller; and finally, carrying out FOC speed regulation control on the permanent magnet synchronous motor by using the designed speed ring controller and the disturbance observer. Compared with an existing well-known sliding mode control scheme, the hybrid control method of the speed loop controller and the sliding mode disturbance observer is adopted, system buffeting is effectively weakened, meanwhile, the dynamic response speed is considered, and the system robustness is improved.

The invention discloses a BLDC (brushless direct current) driving parameter self-tuning embedded system and method for multiple equipment types, and the method comprises the steps: constructing a BLDC unified mathematical model containing an electromagnetic torque equation, a back electromotive force equation and a mechanical motion equation, and building a nonlinear mapping relation library of motor type identification codes and a key electrical parameter set; a predefined multi-mode excitation signal sequence is injected into the to-be-driven BLDC motor, dynamic response data are synchronously collected, and the dynamic response data are used for representing the characteristics of the key electrical parameter set; based on collected dynamic response data, equivalent inductance and equivalent resistance in a key electrical parameter set are decoupled and extracted through a frequency domain impedance analysis method, and meanwhile, a counter electromotive force coefficient and rotational inertia in the key electrical parameter set are identified by combining time domain counter electromotive force zero crossing point detection with rotating speed differential operation. Based on a motor fingerprint feature library and a fuzzy adaptive architecture, multi-model debugging-free plug-and-play is realized, and stable control performance is maintained under a dynamic working condition.

The invention discloses an EMC simulation modeling and optimization prediction method based on a permanent magnet brushless direct current motor driver. The method comprises the steps of obtaining first interference source data based on a driver real object; performing near-field electric field simulation based on the primary driver PCB and the first interference source data to obtain a primary near-field electric field radiation simulation cloud picture; obtaining an optimized driver PCB based on the initial edition of the near-field electric field radiation simulation cloud picture, and performing near-field electric field simulation based on the optimized driver PCB and the first interference source data to obtain an optimized near-field electric field radiation simulation cloud picture; judging whether optimization design is needed or not according to the near-field electric field radiation simulation nephograms obtained twice; and if the optimization design is not needed, acquiring second interference source data corresponding to the optimized driver PCB and judging whether the second interference source data reaches a preset target, and if the second interference source data does not reach the preset target, continuing optimization based on the optimized near-field electric field radiation simulation cloud picture. The method is low in complexity, rapid and accurate in simulation and lower in cost.

The invention provides a multi-permanent magnet synchronous motor rotating speed tracking consistency control method based on local information interaction, and relates to the technical field of multi-permanent magnet synchronous motor rotating speed cooperative control. A vector control subsystem of a single motor in a multi-permanent magnet synchronous motor rotating speed cooperative control system is regarded as an intelligent agent, the intelligent agent interacts rotating speed information with a neighbor intelligent agent according to a designed communication topology, and expected q-axis current is updated in real time through a rotating speed tracking consistency protocol; therefore, the rotating speed tracking consistency is realized based on the local rotating speed information, and a rotating speed tracking controller does not need to be independently designed, so that mutual restriction of rotating speed tracking performance and synchronization performance can be avoided; in addition, distributed control has the advantages of simple structure, high flexibility, high expansibility and the like; the disturbance observer designed by the invention has continuous observation output values, and the system buffeting can be further weakened and the system robustness can be enhanced by utilizing the observer to estimate unknown disturbance and carry out feedforward compensation.

The invention discloses a permanent magnet synchronous motor cogging torque suppression method and device based on coordinate analysis, and belongs to the technical field of permanent magnet synchronous motors, and the method comprises the steps: effectively suppressing the cogging torque of a permanent magnet synchronous motor through collaborative optimization of the geometric parameters of stator and rotor auxiliary slots, reducing the torque pulsation, and improving the vibration noise, thereby improving the cogging torque of the permanent magnet synchronous motor. The comprehensive performance of the motor is improved. Wherein the stator auxiliary slots weaken periodic components related to stator tooth slots in air gap magnetic conductance harmonic waves by adjusting slot widths and depths, and excitation of the periodic components to tooth slot torque is reduced; the rotor auxiliary grooves optimize the pole-arc coefficient by adjusting the opening angle, and remanence harmonic waves of the permanent magnets are inhibited from being periodically matched and coupled with the stator tooth grooves. The collaborative design of the two enables the amplitudes and phases of air-gap magnetic conductance harmonic waves and permanent magnet residual magnetic harmonic waves to be mismatched, the amplitude of cogging torque is remarkably reduced, meanwhile, periodic disturbance of an air-gap magnetic field is reduced, the output torque is more stable, and mechanical vibration and noise caused by electromagnetic force fluctuation are synchronously weakened.

According to an aspect of the invention, there is provided a method of controlling a discontinuous linear motor system comprising a mover and a motor, the method comprising: obtaining a set of current values representing current flowing through coils of the motor, wherein a reaction plate of the mover is in a position relative to the coils; obtaining a set of voltage values representing voltage present over the coils; predicting a velocity, acceleration and / or position of the mover from the set of current values and the set of voltage values; and, calculating input parameters for control of the motor to move the mover to a desired velocity, based on the prediction.

The invention discloses a rapid calculation method for electromagnetic vibration of a permanent magnet synchronous motor, and belongs to the technical field of electromagnetic field calculation. According to the method, a magnetic potential and magnetic conductance method is innovatively combined with an improved sub-domain method, the problem of complexity of electromagnetic field distribution of a nonlinear material is effectively solved through the magnetic potential and magnetic conductance method, and the capture precision of electromagnetic field changes is remarkably improved by dividing a computational domain into a plurality of sub-domains through the improved sub-domain method. According to the method, the influence of the tangential electromagnetic force wave and the harmonic current is fully considered, and high-precision calculation of the electromagnetic force can be realized. On the basis, a stator core shell equivalent theoretical model is established, the inherent frequency of the stator is calculated by adopting an energy method, and the accuracy of the model is verified through a modal experiment. Furthermore, by determining the frequency response function of the stator in the low-order mode, the acceleration spectrum and electromagnetic force wave distribution of the prototype stator in each mode are obtained based on the linear superposition principle. Compared with a traditional electromagnetic-structure coupling finite element model, the method has the advantages that the calculation efficiency is remarkably improved while the calculation precision is guaranteed, the calculation time is shortened by 59.3%, and efficient and reliable technical support is provided for optimization design of electromagnetic equipment.

The invention discloses an improved multi-vector combined model predictive control method and device for a permanent magnet synchronous motor. The method comprises the following steps: acquiring a three-phase current of each sampling period, and converting the three-phase current into a d-axis current and a q-axis current; performing one-beat delay compensation on the current, predicting a reference voltage of a next beat, and judging a sector where the reference voltage is located; selecting a corresponding voltage vector output combination in the reconstructed voltage vector selection table by combining the sector and the previous period zero vector; solving a cost function only containing voltage vectors and action time by using the KKT theorem, and calculating the action time of each voltage vector; and generating a pulse signal according to the action time for driving the output of an inverter of the permanent magnet synchronous motor. According to the method, the advantages of fast dynamic response, easy processing of multiple constraints and the like of model prediction control are maintained, and meanwhile, lower calculation complexity, fixed switching frequency and higher reliability are realized, so that the comprehensive performance of a permanent magnet synchronous motor control system is improved.

The invention belongs to the technical field of parameter estimation of machines, and particularly relates to a permanent magnet synchronous motor parameter identification method based on an improved eel-grouper algorithm. The method comprises the following steps: establishing a full-rank discrete voltage equation set of a mathematical model of a PMSM under a dq coordinate system; constructing a fitness function reflecting an error between an actual parameter output value and a theoretical output value of the motor; performing parameter identification on the permanent magnet synchronous motor by using an improved eel-grouper optimization algorithm, and initializing a population by using an elite reverse learning mechanism; a Levy flight strategy is introduced in the algorithm development stage; introducing a reconnaissance alert strategy of a sparrow search algorithm; a chaotic Tent search strategy is introduced, a fitness function is calculated, parameter optimization is carried out through algorithm iteration, iteration is stopped after the maximum number of iterations is reached, and optimal identification parameters are output. By improving a search strategy and a parameter adjustment mechanism of the algorithm, the precision and robustness of parameter identification are further improved, and more reliable parameter support is provided for high-performance control of the permanent magnet synchronous motor.

The invention discloses a motor multi-parameter identification method based on sampling noise excitation and bias compensation, and the method comprises the steps: firstly obtaining the voltage and sampling current of a motor, and enabling the sampling current to comprise sampling noise; then constructing an information evaluation index, and adjusting a proportional parameter of a current controller to improve the identification information amount; then, shaft voltage feed-forward compensation is constructed to suppress electromagnetic torque pulsation; recursion is carried out by adopting a least square method based on the discrete linear parameterization model to obtain a parameter initial value and a covariance matrix; secondly, estimating offset-containing parameters on line, and calculating a sampling noise variance by using an estimated residual error; and finally, obtaining unbiased parameter estimation according to bias compensation iteration updating so as to output online estimation values of stator resistance, direct-axis inductance Ld, quadrature-axis inductance Lq and permanent magnet flux linkage.

The invention discloses a discrete modeling and position-free control method for a low-carrier-ratio long-cable permanent magnet motor, and belongs to the field of motors. In order to solve the problem that the precision of a conventional mean voltage model is reduced due to the remarkable resistance characteristic of a low-carrier-ratio long-cable permanent magnet synchronous motor, a switching period is decomposed into a plurality of zero-order holding voltage excitation sections according to the discrete characteristic of the output pulse width modulation voltage of a converter; a motor accurate discrete model considering resistance characteristics is established by solving accurate current response of the permanent magnet motor segment by segment, a dead-beat current controller and a motor back electromotive force observer are further established based on the discrete model, and sensorless operation of the low-carrier-ratio long-cable permanent magnet synchronous motor system is realized. The discrete modeling precision of the low-carrier-ratio long-cable permanent magnet synchronous motor is improved, and the position-free control performance of the permanent magnet synchronous motor system under the working condition is improved.

The invention belongs to the technical field of permanent magnet synchronous motor control, and particularly discloses a permanent magnet synchronous motor finite time switching active-disturbance-rejection rotating speed control method, which comprises the following steps: acquiring a reference rotating speed and an actual rotating speed of a permanent magnet synchronous motor; the absolute value of the error between the reference rotating speed and the actual rotating speed is calculated and compared with a preset first threshold value and a preset second threshold value, and the stage of the permanent magnet synchronous motor is judged; constructing a finite time cascade expansion state observer comprising a first-stage finite time ESO and a second-stage linear ESO to observe the state and lumped disturbance of the permanent magnet synchronous motor; and based on the stage of the permanent magnet synchronous motor, selecting a composite state of the observation value of the first-stage finite time ESO, the observation value of the second-stage linear ESO or the observation value of the first-stage observer and the observation value of the second-stage observer generated based on the Bezier curve to generate the rotating speed loop control law of the permanent magnet synchronous motor. According to the invention, the problems that the transient anti-interference capability is weak and the current performance is reduced due to the fact that transient control and steady-state control are not distinguished in the prior art are solved.