654results about "Speed/accelaration control using electric means" patented technology

The invention provides a tunnel fan group cooperative control dynamic optimization method and system. According to the method, dynamic data of vehicles in a tunnel are tracked through the Leiyu fusion technology, and a multi-dimensional game parameter set is constructed in combination with edge computing node analysis data and environment monitoring indexes. Based on a dynamic game theory model, fan cooperative response intensity is dynamically adjusted, smoke exhaust efficiency and evacuation channel wind speed constraint are balanced, fan control priority is calculated, differential rotating speed and deflection angle control is driven, and game strategy weight is iteratively optimized after environment feedback data is generated. And realizing rolling time domain control until the vehicle movement and the environment index reach a stable interval. According to the technical scheme provided by the invention, dynamic collaborative optimization of tunnel smoke exhaust and evacuation safety is realized, and the ventilation response efficiency and the evacuation channel safety in an emergency scene are improved.

The invention provides an unmanned aerial vehicle motor rotating speed control method based on active disturbance rejection. The method comprises the following steps: 1) measuring the rotating speed of a motor by adopting a high-precision rotating speed sensor based on a quantum effect; 2) designing a tracking differentiator TD to smooth an expected rotating speed, and outputting a rotating speed tracking signal and a rotating speed tracking signal change rate; 3) introducing a dynamic weight matrix to form a dynamic weight expansion state observer DWESO, and taking an output state variable estimation value and a total disturbance estimation value as the input of the NLSEF; 4) automatically searching the optimal combination of the gain parameters of the DWESO by adopting an ALA (artificial Louver Mouse Algorithm), so that the optimal state variable estimation value and the optimal total disturbance estimation value are output to the NLSEF; compared with the prior art, the method for controlling the rotating speed of the unmanned aerial vehicle has the advantages that the dynamic response speed, the anti-jamming capability and the parameter adaptability of the system are remarkably improved, and the flight performance and the robustness of the unmanned aerial vehicle are improved.

The invention discloses a ground wire multi-machine synchronous traction pay-off scheduling method and system, relates to the technical field of high-voltage transmission line construction, and is used for solving the problem of insufficient multi-machine real-time tension synchronization precision in the existing method. A tension sensor and a speed sensor which are arranged on each traction device collect a tension value, a traction speed value and position coordinate data of a ground wire in real time, and transmit the data to a central scheduling controller; establishing a multi-machine unified time synchronization reference and tension reference model, calibrating a timestamp through a GPS module, and initializing a threshold value based on historical parameters; comparing tension values one by one to calculate a deviation vector sequence; activating a compensation algorithm to execute a speed fine adjustment and tension compensation instruction; iteratively calculating the feedback adjustment value until the deviation is stable; and integrating the synchronous data to the overall paying-off scheduling model to dynamically update the path planning and speed curve. According to the method and the system, the problem of insufficient multi-machine real-time tension synchronization precision in the prior art is effectively solved.

The invention relates to the technical field of cutting machine control, in particular to a wire cutting machine feeding speed control system and method.The wire cutting machine feeding speed control method comprises the steps that a multi-mode signal recognition material module extracts current and vibration signal features through the self-adaptive feature selection technology, and the current and vibration signal features are obtained on the basis of an improved random forest model; a processing material is identified by combining dynamic weight voting and a weighted fusion method, and online learning and model updating are supported so as to adapt to processing requirements of different materials. The double-loop self-adaptive control module comprises outer-loop initial compensation and inner-loop fuzzy PID adjustment, real-time fine adjustment parameters are optimized according to historical machining records and double-target error values, machining precision and stability are ensured, and machining quality is improved. And the energy consumption management optimization module intelligently regulates and controls the energy consumption of the system by identifying non-processing and processing periods, so that the overall energy efficiency is improved, and energy-saving production is realized. According to the invention, the efficiency and the accuracy of the wire cutting machine in machining of multi-variety and small-batch dies are improved.

The invention provides a control method of a double-closed-loop direct-current speed regulation system based on an improved parrot algorithm, and relates to the technical field of industrial control. Comprising the steps that weights and thresholds of a BP neural network are optimized through an improved parrot algorithm, an initial optimized BP neural network is obtained, the weights for BP neural network optimization are 36, and the thresholds for BP neural network optimization are 12; according to a gradient descent principle, training the initial optimized BP neural network to obtain a final optimized BP neural network; calculating the parameters of the PID controller by using the final optimized BP neural network to obtain the optimal group parameters of the PID controller; and controlling the double-closed-loop direct-current speed regulation system by using the optimal group parameters of the PID controller. The problems that in the prior art, when PID controller parameters are adjusted on an electric dragging site, consumed time is long, difficulty is large, the workload is large, and a BP neural network falls into a local optimal solution are solved.

The invention discloses a reinforcement learning-based control method for a differential steering driving system of a climbing cleaning vehicle, and belongs to the technical field of hull cleaning vehicle control methods. Comprising the following steps: model establishment: modeling a differential steering driving control process of the wall-climbing cleaning vehicle into a Markov decision process; defining a state space and an action space; constructing a state transition model of the differential steering driving system; acquiring current state data, and generating a steering wheel speed and steering time distribution strategy through the model; executing the steering action strategy, and updating the state data after action execution; rewards are returned according to the actual execution effect to judge whether the action strategy is good or bad; performing model optimization through an experience playback pool; and resetting the scene to continue training until the model converges, and finally obtaining the trained differential steering driving system model. According to the method, the complexity of path planning and control algorithms is reduced, the requirement for maximum cleaning of the coverage area is met, and the difficulty of the path planning and control algorithms is simplified.

The invention provides an intelligent control system and an intelligent control method of a bridge girder erection machine, and relates to the technical field of bridge construction application, the intelligent system comprises a plurality of variable frequency controllers which are respectively installed on a front support and a middle support, a front crown block and a rear crown block, and a rear support, the variable frequency controller controls the rotating speed of the transverse moving motors of the front support and the rear support, the rotating speed of the walking motors of the front crown block and the rear crown block and the rotating speed of the front and rear running motors of the middle support and the rear support according to a control instruction of the PLC control system. The rotating speed of the motor is controlled through the frequency converter, so that the left-right moving synchronism of the front support and the middle support of the bridge girder erection machine is effectively controlled, the walking synchronism of the front crown block and the rear crown block on the left and right wheels on the track is effectively controlled, and derailment caused by inconsistent speeds of the wheels on the two sides of the track is avoided.

The invention relates to a gradient-adaptive abrupt slope slow descent control method and a vehicle, and belongs to the field of vehicle control. According to the current actual rotating speed of the motor and the pre-obtained corresponding relation between the rotating speed of the motor and the torque of the motor, the feed-forward torque is obtained according to the torque of the motor, the feed-forward torque is superposed to a torque output value of vehicle speed closed-loop control, and the vehicle is controlled to reach the HDC target vehicle speed; the corresponding relation is in positive correlation within the peak torque range of the motor, and the motor rotating speed in the corresponding relation is divided into an acceleration interval, a gradient self-adaptive interval and a deceleration interval along with increase of the rotating speed; the gradient adaptive interval corresponds to an HDC target motor rotating speed interval; the minimum value of the motor torque corresponding to the gradient self-adaptive interval is obtained by the full-load mass, the minimum gradient of the HDC and the first-gear target vehicle speed, and the maximum value of the motor torque corresponding to the gradient self-adaptive interval is obtained by the full-load mass, the maximum gradient of the HDC and the highest-gear target vehicle speed; and the vehicle speed is ensured to be stably reduced or increased to the target vehicle speed along with the increase or decrease of the motor torque.

The invention relates to the technical field of equipment operation control, and discloses an operation control system of a spin coating roaster. The system comprises an initialization module used for carrying out parameter initialization on the uniform glue baking machine and generating equipment initial state data; the time sequence control module is used for performing time sequence control on an upper shovel hand servo mechanism and a lower shovel hand servo mechanism of the uniform glue baking machine to obtain wafer position data and adsorption state data; the rotating speed grading control module is used for carrying out five-section type rotating speed grading control on rotating servo equipment of the spin-coating baking machine to obtain rotating speed control data; the gluing control module is used for carrying out gluing control on gluing equipment and generating gluing parameter data; and the compensation control module is used for performing inter-region heat coupling compensation control on the four-region heating units of the spin-coating baking machine and outputting a temperature uniformity control result. According to the invention, the gluing positioning precision control is realized, the consistency of the gluing amount is improved, and the variation between batches of products is reduced.

The invention relates to the technical field of automobile part optimization, in particular to an intelligent self-adaptive screw locking control method for a motor, which can acquire an image of an assembly area in real time and establish a three-dimensional coordinate model of a screw hole pose through a camera integrated at the front end of the motor and a three-dimensional visual recognition algorithm. According to the method, the position and the posture of the screw hole can be determined with high precision, so that the vertical alignment relation between the screwdriver blade and the target screw hole is ensured, and the consistency and the accuracy of locking operation are improved.

The invention belongs to the technical field of power transmission and transformation project construction, and provides an ecological environment protection method and system for a power transmission and transformation project, which can construct a frequency portrait of a bird flapping behavior in real time by fusing multiple technical means such as high-frame-rate visual perception, target tracking, individual flapping frequency extraction and frequency domain behavior modeling. The operation state of the rotating device is adaptively adjusted according to a frequency interference similarity principle, so that high-frequency phase dislocation disturbance with the most interference effect is triggered at the moment when birds enter a key critical area, the flight rhythm and the path recognition capability of the birds are effectively damaged, and the birds are promoted to deviate from a flight path of a power transmission equipment area; birds can be prevented from approaching a lead area in time, and the risks of short-circuit tripping, biological casualties and other events caused by the fact that the birds strike the lead are remarkably reduced.

According to the cleaning brush equipment and the control method thereof, the target surface type of a to-be-cleaned surface is determined, cleaning parameter matching is conducted according to the target surface type, the preset brush head rotating speed is obtained, the reasonable brush head rotating speed is matched according to different surface materials, and resource waste is avoided while the cleaning efficiency and effect are guaranteed. Furthermore, when the cleaning parameters are matched according to the target surface type, preset pressure is obtained, the contact pressure between the brush head and the to-be-cleaned surface can be detected in real time while the brush head of the cleaning brush equipment is controlled to clean the to-be-cleaned surface at the preset brush head rotating speed, and when the contact pressure exceeds the preset pressure, the to-be-cleaned surface can be cleaned. And controlling the rotating speed of the brush head to be reduced based on the contact pressure until cleaning is completed. A dynamic feedback mechanism is added between the brush head and the motor, so that the rotating speed of the brush head is adjusted according to real-time contact pressure, and the cleaning surface cannot be damaged during cleaning.

The invention relates to the technical field of intelligent control, in particular to a cable braiding machine intelligent control system based on feedback adjustment. The system comprises a braiding pitch acquisition module used for acquiring a braiding pitch of a cable by acquiring a cable image in a cable braiding process, the braiding pitch being related to the number of spindles of the cable braiding machine and the distance of each strand of the cable; the rotating speed regulation and control parameter acquisition module is used for acquiring rotating speed regulation and control parameters of the spindle according to the knitting pitch; and the adjusting module is used for adjusting the current rotating speed of the spindle according to the rotating speed regulation and control parameters so as to obtain the target rotating speed of the spindle. According to the embodiment of the invention, the rotating speed of the spindle of the cable braiding machine can be automatically adjusted by analyzing the cable braiding pitch in the cable image, so that the high-precision and intelligent operation of the cable braiding machine is realized, the cable braiding precision is improved, and the material cost and the human resource cost are reduced.

The invention provides a seed disc pay-off speed control method and device for preventing a seed rope from loosening and tensioning, and relates to the technical field of agricultural production.The method specifically comprises the steps that the advancing speed of a rope sowing machine and a seed rope tension signal are collected in real time, and effective data are obtained after filtering and noise reduction processing; calculating an expected tension reference value based on the traveling speed and the seed disc radius data, and comparing the actually measured tension with the expected tension reference value to obtain a tension deviation value; judging whether the seed rope is in a loose, tensioned or normal state according to whether the deviation value exceeds a preset tolerance range; if the state is abnormal and the deviation is in a controllable interval, calculating a speed compensation amount through a feedback control algorithm according to the size and direction of the deviation and the current speed; the basic pay-off speed is calculated according to the advancing speed and the seed rope winding density, the target rotating speed is generated after the compensation amount is overlaid and sent to the speed control executing mechanism, the seed disc is driven to rotate according to the target speed, the tension deviation is made to return to the tolerance range by adjusting the pay-off speed, and therefore the normal stress state of the seed rope is maintained.

The invention discloses a multifunctional silage maize harvester control system, and relates to the technical field of silage maize harvesters, the multifunctional silage maize harvester control system comprises a data acquisition module, the data acquisition module is used for acquiring parameter data of crops, specifically including planting density and row spacing data of the crops and height data of the crops; the control module is used for adjusting all equipment parameters of the silage maize harvester, specifically, according to crop parameter data collected by the data collection unit, adjusting signals for a header of the silage maize harvester are output, and the specific adjusting signals comprise the height and position of the header and the line spacing and cutting speed of the header; the silage maize harvester is adjusted according to the adjusting signal; through the control module, the function of automatically adjusting the height, the position, the line spacing and the cutting speed of the header of the silage maize harvester is achieved, the problem that frequent manual adjustment is needed can be solved, the frequency of manual adjustment is reduced, the working efficiency is improved, meanwhile, the adaptability to crops with different planting densities is improved, and the grain waste phenomenon is reduced.

The invention relates to the technical field of varnished wire production, in particular to an automatic adjustment method and system for a varnished wire production process, and the method comprises the steps: obtaining the real-time linear speed data of a wire rod in a varnishing process of varnished wire production; determining wire motion characteristics according to the real-time linear velocity data; inputting the wire motion characteristics and the wire speed characteristics into a pre-constructed risk prediction model for prediction processing to obtain a wire motion risk coefficient; steepness of all the sequences is determined according to the real-time linear speed data, and an automatic adjustment strategy is generated according to the steepness output of all the sequences to obtain the wire operation complexity; and inputting the maximum steepness and the wire motion characteristics in the extracted sequence into a multi-dimensional learning model to obtain the wire pay-off speed regulation and control proportion. Under the condition that the safety and adjustability are qualified, the linear speed is automatically regulated by considering the change fluctuation, early warning, trend and complex comprehensive degree of the linear speed, so that the wire pay-off speed regulation and control proportion is greatly improved, and the wire pay-off speed regulation and control proportion is improved. And the uniform coating effect of the enameled wire is ensured.

The invention relates to a working method of a cleaning device, the cleaning device comprises a cleaning tank and a supply system for supplying water and air to the cleaning tank, and the supply system comprises an air pump for supplying air; the working method of the cleaning device comprises the steps that the cleaning device comprises multiple different working modes, and a corresponding air pump rotating speed dynamic adjusting strategy is set for each working mode; during working, the selected working mode information is obtained, the air pump is controlled to dynamically adjust the rotating speed of the air pump according to the air pump rotating speed dynamic adjusting strategy corresponding to the current working mode, and then work corresponding to the current working mode is completed. The invention further relates to a storage medium for storing computer instructions corresponding to the working method of the washing device. The invention further relates to a cleaning device applying the working method.

The invention discloses a parameter optimization method for an ADRC controller of a motor rotating speed loop, and relates to the field of swarm intelligence optimization algorithms, a self-adaptive genetic algorithm is applied to the rotating speed loop of the motor for a simulation experiment, a current loop of the motor adopts PI control, and the bandwidth of the current loop is adjusted by adjusting parameters so as to meet the control requirement of the rotating speed. ADRC control is adopted for control of a motor rotating speed ring, and S-function is built and written in Matlab / Simulink to achieve ADRC control simulation; the adaptive genetic algorithm comprises crossover and mutation operations, and individual fitness in the population is used as a reference index of crossover probability and mutation probability, so that excellent individuals can be screened out; according to the method, parameters in the genetic algorithm can be adaptively adjusted, and selection of the crossover probability and the mutation probability plays a great role in accurately searching global optimum by the genetic algorithm.

The present application is applicable to the technical field of autonomous driving. Provided are a velocity control method and apparatus for an autonomous vehicle, and a device and a medium. The method comprises: acquiring the current driving information data of a target vehicle, the current driving information data of surrounding vehicles, and trajectory data of a human-driven vehicle; constructing a simulated driving environment of the target vehicle; on the basis of the driving information data of the target vehicle and the driving information data of the surrounding vehicles, using an SAC algorithm to generate a synthesized trajectory, and running the synthesized trajectory in the simulated driving environment; on the basis of the running result and the trajectory data of the human-driven vehicle, calculating an assistance reward function value, a discriminator calculating a reward function value, and then optimizing the SAC algorithm; using the optimized SAC algorithm to generate a final synthesized trajectory; and on the basis of the final synthesized trajectory, controlling an acceleration and a velocity direction of the target vehicle. The method in the present application can improve the rationality of control over autonomous vehicles.

The invention discloses an aerial work platform ramp rotation action stability control and adjustment method and a rotation device, and relates to the technical field of aerial work, and the method comprises the steps that a first horizontal tilt angle sensor detects a first angle value K; a second horizontal tilt angle sensor detects a second angle value L; when the first angle value K belongs to the interval of (0, 180 degrees), judging whether the second angle value L belongs to the interval of (K, K + 180 degrees), or when the first angle value K belongs to the interval of (180 degrees, 360 degrees), judging whether the second angle value L belongs to the interval of (K, 360 degrees) union (0, K-180 degrees), if so, judging whether the electric signal of the rotary handle is left, and if not, judging whether the electric signal of the rotary handle is right; if yes, the acceleration of the electric rotary motor is controlled to be executed according to a descending section curve W of the climbing driving force curve, and if not, the acceleration of the electric rotary motor is controlled to be executed according to an ascending section curve Q of the climbing driving force curve. The method can improve the problems of platform impact and shaking when the high-altitude platform is operated to rotate on the slope.

The invention provides an industrial servo motor operation control method and system, and the method comprises the steps: collecting the motion image data of load equipment in a preset track parameter, carrying out the preprocessing and positioning of the motion image data, and obtaining the real-time position coordinate data of the load equipment; determining theoretical position coordinate data corresponding to the load equipment at each acquisition moment based on a preset trajectory parameter, and comparing the real-time position coordinate data with the theoretical position coordinate data to obtain trajectory deviation data at each acquisition moment; on the basis of the trajectory deviation data in combination with motion correlation characteristics of the servo motor and a preset control target, candidate control instructions for generating a plurality of future control periods in each control period are determined; and evaluating and screening the candidate control instruction set based on a minimization strategy of the trajectory deviation data to obtain a target control instruction, converting the target control instruction into a signal, and outputting the signal to a servo motor driver. The precision of industrial production and the stability of the production process are guaranteed.

The invention is suitable for the technical field of cleaning equipment, and provides a control method and device of cleaning equipment, a main control board and the cleaning equipment. The method comprises the following steps: acquiring motion data aiming at a motion state of the cleaning equipment, and acquiring an expected speed; wherein the expected speed is used for representing the speed of the cleaning equipment after the wiping strip is switched between the first state and the second state of the wiping strip, the first state is that the wiping strip makes contact with the to-be-cleaned face, and the second state is that a preset gap exists between the wiping strip and the to-be-cleaned face; based on the motion data and the expected speed, determining predicted time when the cleaning equipment reaches the expected speed; and based on the predicted time and the preset scraping strip moving time, the scraping strip is controlled to be switched between the first state and the second state. According to the embodiment of the invention, the scraping strip can be accurately controlled to be switched between the first state and the second state, so that the scraping strip is accurately controlled to be in contact with or separated from the ground at proper time, and the cleaning effect is improved.

The invention provides a traveling wave rotating ultrasonic motor speed control method and system based on deep reinforcement learning. Firstly, a virtual dynamic model based on a long short-term memory (LSTM) network is constructed, the time-varying behavior of TRUM can be accurately captured, and the average prediction error is within 0.5%. Secondly, designing an intelligent controller based on a near-end strategy optimization PPO algorithm, and optimizing a reward function and structure to enhance the adaptability of a control strategy; simulation and experiment results show that the method realizes the quick response of 0.034 seconds and the tracking error of less than 0.21 rpm, and the error is maximally reduced by 0.42 rpm compared with the traditional controller. According to the method, the problems of insufficient modeling precision, low control precision, slow response speed, poor adaptive capacity to dynamic characteristics and the like in the prior art are effectively solved, and a new path is provided for application of the TRUM in high-precision complex tasks.

The invention discloses a response speed optimization method applied to an actuator of a ship electric control valve, particularly relates to the field of response regulation of the ship electric control valve, and aims to solve the problems of response delay and unstable speed regulation of the actuator under complex working conditions. Performing linkage analysis on the actuator signal behavior and the deviation trend, and accurately separating a distortion wave band in an inertia compensation threshold domain; a double-parameter mechanism based on a frequency domain energy level and a time domain return difference is introduced, a distortion identification coefficient is generated by means of machine learning, and whether correction operation is introduced or not is accurately determined, so that the speed regulation process has pertinence and controllability; a speed transition curve is formed by driving of a correction factor, and it is guaranteed that the regulation and control signal has the flexible adaptation capacity; a path numbering mechanism realizes traceability of a regulation track, a posterior deviation curve is iteratively combined with a feature set, a strategy is driven to evolve continuously, and the response speed and process stability of an actuator are integrally improved.

The invention discloses a control method for controlling the follow-up speed change of a drip irrigation disc of a seeder based on Beidou speed measurement. The control method comprises the following steps: S1, collecting and preprocessing position information and speed information of a tractor; s2, inputting the preprocessed data into a fusion calculation unit, and executing space-time weight calibration; s3, inputting the fusion speed sequence into a speed prediction network, extracting multi-scale features, and generating a speed guide feature map; s4, generating a target rotating speed instruction according to the mapping function and operation parameter modulation; s5, inputting a target rotating speed instruction to a motor control unit, and generating a current signal through dual-channel torque regulation and control; s6, a motor is driven to rotate the drip irrigation disc, the actual rotating speed is collected, and an error sequence is constructed; and S7, inputting the error sequence into a calibration module, generating a correction parameter to update a current signal, and realizing synchronous control. According to the invention, high-precision synchronous control of the drip irrigation disc on the speed of the tractor is realized, and the drip irrigation consistency, the response speed and the operation stability are improved.

The invention relates to the technical field of intelligent control, and discloses an intelligent hammer crusher control method and system based on artificial intelligence. The method comprises the steps that material characteristics are analyzed through near-infrared scanning, and vibration and acoustic signals are collected to obtain crushing state data; analyzing the energy conversion efficiency and the particle size distribution condition according to the data, and evaluating the crushing efficiency and the product quality; calculating the ratio of the optimal hammerhead linear speed to the feeding rate based on the evaluation result; and the optimization parameters are converted into equipment control signals to realize self-adaptive adjustment. The technical problems that traditional vibrating screen fixed parameter control cannot adapt to multi-coal-type changes, the multi-target constraint problems that screening efficiency and energy consumption are difficult to balance in the parameter optimization process, and a precise matching mechanism is lacked for control parameters and material characteristics are solved.

The embodiment of the invention provides a rotor operation control method and device, electronic equipment and a storage medium, and the method comprises the steps: firstly, obtaining initial planning operation data of a target rotor, and the initial planning operation data comprises acceleration stage operation data and uniform speed stage operation data; then, acquiring a speed adjustment coefficient, and generating deceleration stage operation data based on the speed adjustment coefficient and the acceleration stage operation data; and finally, planning operation data is generated based on the deceleration stage operation data and the initial planning operation data, and operation control is performed on the target rotor based on the planning operation data, so that the operation control flexibility of the rotor is improved. And the generated operation control data can meet the operation requirements of different workpieces by utilizing an adjustable speed adjustment coefficient, so that the reliability of rotor operation control is improved.

The invention discloses a horizontal rotary coating control method and system based on a neural network, and relates to the technical field of data processing, and the method comprises the following steps: obtaining surface point cloud data of a part at a spraying station inlet; obtaining the current curvature of the part according to the surface point cloud data; paint viscosity and environment temperature are obtained; inputting the current curvature, the coating viscosity and the environment temperature into a rotating speed prediction model, and outputting a predicted rotating speed; acquiring the current curvature, the coating viscosity and the environment temperature at a preset time interval, and updating the predicted rotating speed; and controlling the rotation speed of the part according to the predicted rotation speed. According to the method, the part data and the environment data on the horizontal rotary coating line are obtained in real time, the rotating speed of the part is dynamically adjusted through the rotating speed prediction model, paint film forming of the part at the proper rotating speed is facilitated, and the quality of the paint film is improved.

The invention belongs to the technical field of stirrer control, and discloses a stirrer rotating speed control model, method, device, equipment and medium, and the model comprises a Transform variant module, a multi-mode cross attention module and a full connection module. The Transform variant module is constructed on the basis of a local time window self-attention mechanism, and the local time window self-attention mechanism is used for capturing a short-term local dependency relationship of material characteristic data on different time steps; the multi-modal cross attention module is constructed on the basis of a cross attention mechanism, and the cross attention mechanism is used for performing multi-modal fusion on the feature data output by the Transform variant module so as to capture relevance among different material characteristics; and the full connection module is used for obtaining the rotating speed of the stirrer according to the characteristic data output by the multi-mode cross attention module and outputting the rotating speed of the stirrer. The stirring speed can be flexibly adjusted, and the uniformity of materials and the process stability are ensured.

The invention relates to an express balance wheel sorting machine control method and device and a sorting machine, and aims to improve the cargo posture stability and transmission efficiency in the logistics sorting process. The method comprises the following steps: receiving goods sorting path information, and generating a synchronous control instruction including swing wheel disc angle deflection, goods linear speed and a four-wheel belt transmission mechanism; the deflection angle of each swing wheel disc is calculated in real time, and on the premise of ensuring stable conveying of goods and balanced stress of each roller, the optimal rotating speed of a driving wheel is dynamically solved by adopting a multi-target dynamic optimization model on the basis of transmission balance among the driving wheel, a tensioning wheel and a driven wheel, so that the vibration torque of each belt is minimum, and the transmission efficiency is maximized. The control device is composed of a path information receiving module, a control instruction generating module, a swing wheel disc angle control module, a linear speed control module and a shearing vibration control module, efficient, low-energy-consumption, cooperative and intelligent control and stable transmission of the multi-swing-wheel disc sorting mechanism in the sorting process are achieved, and the multi-swing-wheel disc sorting mechanism is suitable for a logistics automatic sorting system.