540results about "General control strategies" patented technology

An electronic starting switch assembly and control methods for a dryer having a split-phase induction motor. The assembly comprises a microcontroller unit (MCU) configured to execute a control method that dynamically manages the motor's operation by monitoring the forward magnitude current. The MCU determines a stabilized startup forward magnitude current and calculates a crossover condition, allowing for precise control of the motor's transition to single-phase operation by disconnecting the auxiliary winding and connecting the heater element based on real-time forward magnitude current analysis and processing. The system can also monitor for overload conditions indicative of rotor speed drops and can re-engage the auxiliary winding to maintain motor performance. The assembly includes a housing with a heat-sink for efficient thermal management and environmental protection of electronic components. The disclosed method provides a robust solution for efficient dryer operation by ensuring accurate control of motor start-up, running conditions, and overload protection.

The invention discloses a self-adaptive logarithmic terminal sliding mode control method and device based on observation, and relates to the technical field of sliding mode control. According to the method, the terminal attractors are nested into the natural logarithmic function, terminal sliding mode control and logarithmic sliding mode control are effectively combined, rapid convergence can be achieved near and far away from the balance point, the global dynamics of the sliding mode surface is improved, and the sliding mode control efficiency is improved. Meanwhile, a self-adaptive logarithmic terminal sliding mode controller is constructed on the basis of super-spiral sliding mode control and self-adaptive gain, the self-adaptive gain is updated according to a self-adaptive law, the self-adaptive law is constructed on the basis of a preset nonlinear obstacle function, intelligent self-adaption of the super-spiral sliding mode control gain is achieved, and therefore sliding mode variables are restrained within a preset boundary; and the interference estimation error is quickly converged based on the estimation of the observer on the interference, the global quick convergence of the state tracking error is realized under the constraint of the sliding mode variable, the steady-state precision is high, the chattering phenomenon is weakened, and the convergence efficiency and the control precision are improved.

The invention discloses a robot joint motor dynamic load self-adjusting method based on fuzzy entropy optimization. The robot joint motor dynamic load self-adjusting method comprises the following steps: S1, acquiring operation parameter data of a robot joint motor by adopting sensors arranged at key joints of a robot; s2, generating a corresponding adaptive adjustment factor data set; s3, forming a load probability distribution model parameter data set; s4, applying the load probability distribution model parameter data set to real-time load prediction, determining the load trend of a robot joint motor in a future period of time, and outputting predicted load distribution data; and S5, dynamically adjusting control parameters of a robot joint motor according to the predicted load distribution data and the adaptive adjustment factor data set to form a new control strategy data set. According to the method, the control parameters of the robot joint motor are dynamically adjusted in different load states, so that the oscillation effect of the robot in a complex load environment can be effectively reduced, and energy consumption is optimized under the condition that the motion precision is not affected.

The invention relates to the technical field of motor control, in particular to a permanent magnet synchronous motor online parameter identification system and a compensation method thereof, comprising a data acquisition module, a deep transfer learning parameter identification module, a parameter optimization module, a temperature compensation module and a controller parameter integration module. The deep transfer learning parameter identification module establishes mapping and function relations between characteristic factors and motor parameters through a teacher network, a transfer network, a memory network and an output layer, processes time sequence information and outputs a parameter identification result, and the parameter optimization module finely adjusts the parameters based on a particle swarm optimization algorithm. The temperature compensation module carries out temperature compensation on the optimized parameters according to a temperature distribution model, the controller parameter integration module generates control parameters, and the motor control module generates torque control signals according to the control parameters, so that fusion processing of multi-physical field characteristics is realized, and the precision and adaptability of parameter identification are greatly improved; and the d-q axis inductance identification error is reduced by more than 70%, and the millihenry-level precision is achieved.

The invention discloses a servo control system and method based on data analysis, and relates to the technical field of servo control, and the system comprises a data collection unit which achieves the communication between a characteristic analysis system and a real object servo system platform through a storage and display mode based on different data sources, and a data analysis unit which carries out the data analysis of the real object servo system platform. The data analysis unit is used for analyzing time-domain characteristics and frequency-domain characteristics of the system and carrying out historical data analysis and real-time data monitoring on stored data, and the data processing unit is used for carrying out related processing on the received data based on a Mallat algorithm. According to the invention, real-time observation and control of speed and position are realized, time-domain characteristic analysis and frequency-domain characteristic analysis can be carried out on response of the servo system, data processing is realized by adopting a Mallat algorithm, and designed PI controller parameters are sent to a servo system controller to realize real-time control of the servo system.

A shock absorption mechanism includes connectors, supporting components, and shock absorption components capable of driving the supporting components to swing back and forth or left and right. The connectors are clamped in the middle of the shock absorption components and are operatively connected to the shock absorption components on both sides. The supporting components are movably connected to the shock absorption components, and the lower end of the connectors is operatively connected to the supporting components. A notable feature of this invention, distinct from existing technologies, is the shock absorption components' capacity to induce front-back or left-right oscillations in the supporting components through their inherent rotation when detecting a tendency for swinging. This proactive response effectively mitigates the centrifugal force resulting from camera swinging, preventing detachment between the camera and the damping arm and averting camera jitter. Consequently, the stability of the recorded footage is assured.

The invention discloses an electronic switch assembly and a control method of a split-phase starting single-phase induction motor for a household clothes dryer. The assembly comprises an MCU, the MCU is loaded with a real-time algorithm software control program, and the starting speed state of the motor can be detected by analyzing and processing the change of steady-state positive sequence amplitude current in the starting process. Based on real-time positive sequence amplitude current analysis processing, the MCU calculates and detects an overspeed condition in real time, disconnects an auxiliary winding and connects a heater element so as to accurately control the transition of the motor to single-phase operation until a rated rotating speed is reached. Based on real-time positive sequence amplitude voltage and current analysis and processing, the overload condition of rated rotor speed reduction can be detected, and the auxiliary winding can be switched on again to maintain the operation performance of the motor. The assembly includes a housing having a heat sink for efficient thermal management and overheating protection of electronic devices. And an effective, reliable and low-cost solution is provided for the operation of the efficient clothes dryer by ensuring the accurate control on the starting and operating conditions of the motor and the overload protection.

The invention discloses a PMSM (permanent magnet synchronous motor) AC servo system speed control method based on improved particle swarm optimization optimization RBF (radial basis function) fuzzy neural network PID control, the system is composed of a speed outer ring and a current inner ring, and the current ring adopts a PI regulator. A speed loop is designed to be an RBF fuzzy neural network PID speed controller, an RBF fuzzy neural network is optimized by improving a particle swarm optimization algorithm, and optimal parameters kp, ki and kd suitable for the PID controller are output. Simulation analysis and experiment results show that compared with a common PID control strategy, a BP algorithm optimization fuzzy neural network PID control strategy and a particle swarm algorithm optimization RBF fuzzy neural network PID control strategy, the particle swarm algorithm optimization RBF fuzzy neural network PID control strategy based on the improved particle swarm algorithm has optimal control performance; the method has the advantages of being high in dynamic response speed, good in control stability, resistant to load disturbance and high in robustness, and the excellent speed control effect of the PMSM alternating current servo system can be achieved.

A motor control system includes a measurement interface designed to measure a mechanical angle of a shaft driven by a motor and a rotational speed of the shaft, and to generate a speed feedback signal representative of the rotational speed, a speed controller, and a current controller.The speed controller comprises an error component configured to generate a speed error signal based on the difference between a speed reference signal and the speed feedback signal; a proportional-integral controller configured to regulate a torque reference value based on the speed error signal and to maintain a speed reference value; and a load torque ripple compensator configured to apply a torque feedforward function to reduce load torque ripple in the torque reference value. The current controller is configured to drive motor currents to generate a torque equal to the torque reference value.

The invention discloses a feedforward torque compensation control method and system for a photoelectric pod. The method belongs to the technical field of photoelectric pod real-time control. The technical problem that the requirement for high dynamic performance of the photoelectric pod is difficult to meet in photoelectric pod control is solved. The method comprises the following steps: sensor arrangement: arranging accelerometers at each motion axis of the photoelectric pod; signal acquisition and calculation: calculating the angular acceleration of each motion axis through acceleration data output by an accelerometer; calculating the disturbance torque: calculating the disturbance torque of each motion axis through the angular acceleration of each motion axis; calculating a current value of a feed-forward path: calculating a current value required by a motor of each motion shaft to resist the disturbance torque through the disturbance torque of each motion shaft; feed-forward path current and feedback path integration: injecting the current value as a feed-forward signal into a current loop given link in the servo control system, and resisting disturbance of each motion axis by controlling motor current of each motion axis.

The invention relates to the technical field of servo drivers, in particular to a servo driver control method, and the technical scheme comprises the steps: carrying out the online identification of load inertia and external disturbance through a self-adaptive observer, generating a dynamic compensation parameter, constructing a multi-model parallel self-adaptive observer group, and carrying out the online identification of the load inertia and external disturbance through the self-adaptive observer group, a dynamic confidence evaluation mechanism is designed, disturbance dynamic compensation is realized, parameter sudden change and slow change scenes can be taken into consideration, the real-time performance of dynamic response can be ensured, compensation parameters are input into a fuzzy neural network controller, an optimal control quantity is generated in combination with a preset control target, a multi-source compensation parameter input channel is constructed, and the optimal control quantity is generated. A dynamic input weighting module is designed, fuzzy rule confidence is updated through an online strategy gradient algorithm to generate an optimized control quantity, the working condition adaptability can be enhanced, a dynamic target can be dealt with, finally, a sliding mode variable structure algorithm is adopted to carry out high-frequency buffeting suppression on the control quantity, and a final driving signal is output to a power module. And the control precision of the servo driver is improved.

An electric drive system includes an electric machine having a stator assembly and a rotor assembly. The stator assembly has a plurality of multi-phase stator windings, including a first stator winding and a second stator winding. A first inverter is adapted to feed the first stator winding. A second inverter is adapted to feed the second stator winding. The rotor assembly includes rotor windings having a single phase. A controller is configured to selectively command excitation of the rotor windings with a pulsed field current such that a direct-axis (d-axis) stator flux linkage is generated. A d-axis stator voltage is induced in the first stator winding and the second stator winding by the d-axis stator flux linkage. Pulsed power transfer is enabled through interaction of the d-axis stator voltage and respective d-axis winding currents in the first stator winding and the second stator winding.

The invention discloses a load prediction-based regenerative braking electric hoist control method for hot-line work, and relates to the technical field of electric hoist control. The method comprises the following steps: collecting parameters of the electric hoist, and obtaining a predicted load weight according to an LSTM model; adjusting parameters of a PID controller according to the load weight, recording the parameters as initial PID parameters, generating a control signal according to the initial PID parameters, and driving the electric elevator to operate; setting a regenerative braking triggering standard, and judging whether the electric hoist reaches the regenerative braking triggering standard or not; if the electric hoist reaches the regenerative brake triggering standard, monitoring the recovered energy and generating an expected cumulative reward Q; and updating the optimized PID parameter according to the expected cumulative reward Q to obtain an updated PID parameter, and generating a control signal according to the updated PID parameter to control the electric hoist. According to the invention, the reliability of control of the regenerative braking electric hoist based on load prediction for hot-line work is improved.

The embodiment of the invention provides a motor control method and device, electronic equipment and a storage medium, and the method comprises the steps: firstly, obtaining a current speed error corresponding to a current iteration period of a motor, and a preorder speed error and a preorder output compensation parameter corresponding to a previous iteration period; the current speed error is obtained based on a preset speed instruction corresponding to the current iteration period and a corresponding speed feedback parameter; then, based on the iteration control parameter, the current speed error, the preorder speed error and the preorder output compensation parameter, calculating to obtain a current output compensation parameter corresponding to the current iteration period of the motor; and finally, performing compensation control on the motor based on the current output compensation parameter, thereby effectively reducing the speed fluctuation of the motor, remarkably improving the stability and positioning precision of the system during low-speed operation, and meanwhile, ensuring high stability and high robustness of the whole control system.

The invention relates to the technical field of automobile electronic mechanical braking system control, in particular to an electronic mechanical braking system motor control method based on error compensation, which comprises the following steps of: analyzing the difference of each kind of motor data between all adjacent moments within a preset duration before each moment and the amplitude distribution of each kind of motor data in a frequency domain; determining the disturbed degree; determining a coupling correlation index by analyzing the correlation of the disturbances between each type of motor data and all other types of motor data within the preset duration and the interdependence relationship between each type of motor data and all other types of motor data; and the current of the automobile motor at the current moment is controlled. The problem of distortion caused by noise and non-linear interference of a single data source in an electronic mechanical braking system is solved, control deviation and errors caused by multi-physical field coupling are solved, and the accuracy and reliability of motor control are improved.

Methods, controllers and electric machine systems are described that facilitate pulsed control of electric machines (e.g., electric motors and generators) to improve the machine's energy conversion efficiency. Under selected operating conditions, the electric machine is intermittently driven (pulsed). The pulsed operation causes the output of the electric machine to alternate between a first output level and an off state. The output levels are selected such that the electric machine has a higher energy conversion efficiency during the pulsed operation than the electric machine would have when operated at a third output level that would be required to drive the electric machine in a continuous manner to deliver the desired output. In some embodiments, the power converter it turned off during at least portions of the time that the electric machine is pulsed off.

The invention discloses a method, a system and a related device for controlling a motor based on an adaptive algorithm, which are used for improving the accuracy of motor control. The method comprises the following steps: acquiring initial data of a motor; decomposing the initial data into intrinsic mode function components, and performing time-frequency transformation on the intrinsic mode function components; dynamic time-frequency features of the intrinsic mode function component are extracted, cross-band weighted fusion is carried out on the dynamic time-frequency features through a preset attention weighting mechanism, and a multi-dimensional feature vector is generated; inputting the multi-dimensional feature vector into a preset deep learning model, and constructing a target prediction model in combination with a loss function and an adaptive momentum optimization algorithm; transmitting the target prediction model to an analysis module of the motor to obtain a load change trend and a confidence coefficient; dynamically adjusting the proportion of the weight of the PID controller according to the load change trend and the confidence coefficient, and optimizing the parameters of the unit of which the proportion is adjusted through a gradient descent method; and dynamically regulating and controlling the motor based on the PID controller.

The invention discloses a suspension flux linkage repetitive control method for a single-winding bearingless flux switching motor. A rotor dynamic eccentric suspension flux linkage model is established according to a magnetic suspension rotor system of the single-winding bearingless flux switching motor; a model compensation repetitive controller with an integral element, a model compensator and a same-frequency phase shift notch filter is arranged in the magnetic suspension rotor system; the integration element is used for eliminating steady-state errors, the model compensator is used for obtaining inverse system output signals so as to obtain accurate displacement control signals, and the notch filter is used for reducing same-frequency pulsation of rotor radial displacement; an expected suspension flux linkage is obtained through calculation of the model compensation repetitive controller, the expected suspension flux linkage is compared with an actual flux linkage obtained by the flux linkage observer to obtain a flux linkage error, expected voltage is obtained through calculation of the flux linkage error, and therefore an inverter switching signal is obtained. According to the method, the radial displacement pulsation of the rotor under the steady-state working condition and the displacement sudden change phenomenon under the dynamic working condition are effectively treated, and good control is achieved.

The invention discloses a control device and a control method for suppressing circumferential torque pulsation and radial vibration of a motor. The compensation current data table, the proportion setting part and the voltage conversion part are used for providing a torque ripple compensation current iqnh * for circumferential torque ripple suppression of the synchronous motor and providing a radial vibration compensation current idnh * for radial vibration suppression caused by increase of radial electromagnetic force harmonic waves of a stator for hybrid injection control, q-axis compensation current is injected, circumferential torque ripple is suppressed, and the torque ripple is suppressed. Meanwhile, d-axis compensation current is injected to suppress circumferential torque pulsation, reduce the radial vibration influence generated by q-axis compensation current and eliminate the increasing part of radial electromagnetic force; and a good circumferential torque ripple suppression effect is kept and radial electromagnetic force is prevented from being increased when the motor is at a low rotating speed and a high rotating speed, so that the risk of increasing stator vibration is avoided.

An electric apparatus includes a rotary electric machine, an electric power control unit, and an AC electric power source connection portion. The rotary electric machine includes a stator core on which a slot shared by a β-phase first coil and a β-phase second coil is formed. The electric power control unit includes: a third full-bridge circuit and a fourth full-bridge circuit that are connected to each of both ends of each β-phase coil; and a third connection-disconnection device and a fourth connection-disconnection device that are connected between each of one end of each β-phase coil and each full-bridge circuit. The AC electric power source connection member is connected to both ends of each connection-disconnection device such that magnetic fluxes are cancelled each other when a current supplied from an external AC electric power source to the β-phase coils that are magnetically coupled flows.

The invention provides a multi-motor cooperative control system based on an open-source real-time operating system, and relates to the technical field of multi-motor control, the system calculates a target rotating speed through an upper computer controller, and ensures that a rotating speed instruction can be simultaneously sent to a plurality of dynamometers by using a real-time controller. By means of the EtherCAT high-speed communication protocol, the system can synchronously transmit instructions with extremely low delay, and it is guaranteed that all the drivers receive and execute the same operation instructions at the same moment. In addition, by setting consistent acceleration and deceleration time and PI control parameters of a speed loop and a current loop in the driver, the synchronism and response performance of the system are further optimized. The invention aims to realize high-precision synchronous operation.

The invention relates to the technical field of motor control, in particular to a coating machine die head motor control method and system based on a neural network model. The method comprises the following steps: acquiring real-time position data, rotation direction identification data and angular velocity change data of each section of motor of the die head of the coating machine and torque feedback data of each section of gap adjusting mechanism, and forming a multidimensional motor state data set containing time sequence marks; constructing a direction sensitive activation function according to the rotation direction identification data and the angular velocity change data; and setting a forward weight coefficient and a reverse weight coefficient based on a direction sensitive activation function to carry out dynamic switching mechanism simulation on the direction dependence characteristic of the mechanical gap. According to the method, inter-segment torque propagation and stress waves are analyzed in combination with the neural network model, multi-segment coordination compensation is achieved, and the problem of inter-segment coupling interference is solved.

The invention discloses a permanent magnet motor state monitoring control system based on petroleum drilling machine driving, and relates to the technical field of permanent magnet motor state monitoring. Comprising a data acquisition and construction module, a data preprocessing and feature extraction module, a dynamic monitoring and trend analysis module, a deep learning evaluation module and a fuzzy control and real-time compensation module, the collected real-time data are stored in a time sequence mode, a data set is established, and complete and accurate basic data are provided for subsequent analysis and model evaluation. Through real-time data acquisition, deep learning evaluation, fuzzy control optimization and error compensation, and adaptive regulation and control of dead zone time, the stability, reliability and energy efficiency of the petroleum drilling machine driving permanent magnet motor are improved, the short circuit risk, energy loss and harmonic damage are reduced, the system performance is optimized, and the operation efficiency is improved.

The invention relates to the technical field of PWM (Pulse Width Modulation), and discloses a method for optimizing double random PWM, which comprises the following steps: randomizing a carrier frequency fc and a pulse position to obtain double random PWM, performing parameter setting on random distribution of the carrier frequency and the pulse position by adopting a Sigmoid function, improving a genetic algorithm by utilizing a particle swarm algorithm, and optimizing the double random PWM. Optimizing a minimum value fmin of a random number of a carrier frequency or a pulse position, a maximum value fmax of the random number of the carrier frequency or the pulse position and a curve transverse adjustment parameter sigma of random number Sigmoid distribution in the double random PWM by adopting an improved genetic particle swarm algorithm; according to the method, harmonic energy is dispersed from frequency and phase dimensions to a wider range through double random PWM, the switching frequency and the harmonic amplitude at the integral multiple of the switching frequency are reduced, random numbers are distributed in a Sigmoid mode, and the carrier frequency and the pulse position can more easily avoid a sensitive area by means of the nonlinear probability density characteristic that samples are more on the two sides and less in the middle, so that the switching efficiency is improved. And EMI peaks caused by extreme parameters in traditional uniform distribution are reduced.

The embodiment of the invention discloses an air compressor control system, a control method and an air compressor. The control system comprises a data acquisition module, a control module and a power module, the data acquisition module is used for acquiring air pressure parameters of a target air compressor at set time intervals; the control module optimizes PID control parameters by using a radial basis function network and a particle swarm optimization algorithm on the basis of the air pressure parameters, adjusts the optimized PID control parameters in real time by using a fuzzy control method, determines PID output quantity by using the adjusted PID control parameters, and controls the power module to act on the basis of the PID output quantity; and the power module is used for driving the target air compressor to act under the control of the control module. The technical problems that in the prior art, due to the fact that an air compressor adopts traditional PID control, the control precision is insufficient, the dynamic response is poor, and the anti-interference capacity is poor are solved.

The invention relates to a calibration device for determining a phase current correction coefficient of a motor. The calibration device comprises a current source; at least one sampling resistor, wherein each sampling resistor is connected in series between a corresponding bridge arm in the inverter bridge and the current source; at least one switch element, wherein each switch element is connected in series with a corresponding sampling resistor, a corresponding bridge arm and the current source to form a current detection loop; and the control unit is configured to selectively switch on the corresponding current detection loop by controlling the on-off of the at least one switch element in a calibration program and collect the actual current value flowing through the corresponding current detection loop, and the control unit is further configured to read the current value of each phase in the motor and determine the current value of each phase in the motor. And calculating a current correction coefficient of each phase winding of the motor based on the read current value and the actual current value. The invention also relates to a motor inverter comprising the calibration device and an electric drive system comprising the motor inverter.

The invention relates to a multi-motor load balance control method based on a normalized current average value, and the method comprises the following steps: S1, collecting an actual torque current feedback value and a corresponding rated current value of each loop motor, S2, carrying out the normalization processing of the current feedback values according to the rated value, and calculating a normalized current average value, s4, an extreme value search control algorithm framework is established, and a gain coefficient is optimized by using the framework; S5, gain adjustment is carried out on a deviation value; and S6, respective speed compensation is superposed to an original speed instruction to form a new target speed instruction, and the new target speed instruction is sent to a frequency converter, so that real-time closed-loop adjustment of the multi-motor load is realized. According to the scheme, real-time closed-loop coordination of the power of each motor in the multi-motor driving system is realized, and the operation consistency and robustness of the system are enhanced.

The invention discloses an emulsion pump loading valve speed regulation control system and a working method thereof. The emulsion pump loading valve speed regulation control system comprises a servo motor, a servo driver and an upper computer. The working method comprises the following steps: S1, inputting a pressure set value of the loading valve of the emulsion pump; s2, the upper computer calculates the input pressure set value of the loading valve of the emulsion pump through a PID (Proportion Integration Differentiation) controller to obtain a required rotating state and a required rotating speed of a servo motor and transmits the required rotating state and the required rotating speed to a servo driver; s3, controlling a servo motor by a servo driver, and enabling the servo motor to drive an emulsion pump loading valve to work; s4, the pressure sensor feeds back the pressure acquisition value to the upper computer; s5, the upper computer carries out comparison calculation on the pressure parameters of the loading valve of the emulsion pump through a PID (Proportion Integration Differentiation) controller; and S6, the servo driver adjusts and controls the servo motor according to the comparison calculation result, and precise pressure control over the loading valve of the emulsion pump is achieved.

An electric apparatus includes: an electricity storage device; a rotary electric machine including an α-phase first coil and an α-phase second coil; and an electric power control unit that controls electric power transfer of each of the electricity storage device and the rotary electric machine. The electric power control unit includes: a first full-bridge circuit connected to both ends of the α-phase first coil; and a second full-bridge circuit connected to both ends of the α-phase second coil. When electric power is transmitted via the α-phase first coil and the α-phase second coil between the first full-bridge circuit and the second full-bridge circuit, the electric power control unit controls a phase difference between the first full-bridge circuit and the second full-bridge circuit in a range that includes 90° to 180°.

The invention provides a motor control method and device, equipment and a medium, and the method comprises the steps: obtaining at least two groups of sampling signals of a motor, verifying the validity of the sampling signals, determining the rotation angle of the motor based on effective signals if at least one group of sampling signals is effective signals, and collecting the electrical parameters of the motor if the sampling signals are invalid, calculating a rotation angle of the motor according to the electrical parameters, calculating the rotation angle and a preset motor zero angle to obtain a current angular position of the motor, and further controlling the motor based on the current angular position; the method does not independently depend on sensor signals for recognition, and for various conditions that the sensor signals are valid or invalid, the angular position of the motor can be calculated by adopting an angular position calculation mode corresponding to the sensor signals, so that the calculation flexibility of the angular position of the motor is improved, and the fault tolerance and adaptability of motor control are enhanced.