27499 results about "Servo" patented technology

The invention relates to the technical field of servo motor control, and discloses an intelligent servo motor control method and device and computer equipment. The method comprises the following steps: carrying out multi-dimensional data acquisition and preprocessing on a position loop, a speed loop and a current loop of the intelligent servo motor to obtain standard structured parameter data; identifying a working condition characteristic parameter set of the intelligent servo motor; establishing a two-stage optimization architecture comprising a motor parameter layer and a control algorithm layer, and generating a dynamic parameter adjustment mapping table; a depth deterministic strategy gradient network is trained based on the characteristic parameter set and the dynamic parameter adjustment mapping table, and an optimal control strategy model for different working conditions is generated; and the optimal control strategy model is utilized, control parameters are automatically switched according to the working condition types recognized in real time, and smooth transition control of the intelligent servo motor among different working conditions is achieved. Smooth switching among different working conditions is achieved, system oscillation caused by sudden change of control parameters is avoided, and the disturbance influence in the working condition switching process is greatly reduced.

The invention relates to the technical field of multi-axis servo systems, and discloses a synchronous control method, device and equipment for a multi-axis servo system, and the method comprises the steps: measuring a mechanical coupling relation parameter, a motor dynamic characteristic parameter and a sampling delay time parameter of the multi-axis servo system, and substituting the parameters into a state equation modeling formula, calculating to obtain a discrete time system state matrix; performing Z transformation processing on the discrete time system state matrix and calculating frequency response characteristics to obtain a transfer function matrix and a target coupling axis pair set; executing hierarchical optimization to obtain a preliminary control instruction; a trajectory tracking error and an inter-axis synchronization error are calculated and substituted into the optimization objective function for sampling delay compensation processing, and a compensation control instruction is obtained; the compensation control instruction is processed in real time, synchronous control signals are output to the servo shafts to achieve multi-shaft coordinated movement, and the synchronous control precision in the multi-shaft servo system is improved by accurately recognizing the key coupling shaft pairs and the sensitive frequency points.

The invention provides a filling control method and system based on online parameter identification. According to the method, the synchronous error data of each servo shaft in the multi-shaft servo system is acquired, the error time sequence matrix is constructed by the synchronous error data according to the time sequence, and the displacement feedback data of each servo shaft in the multi-shaft servo system is acquired in real time through the high-precision rotary encoder; a dynamic compensation signal is generated according to the deviation between the displacement feedback data and a preset track, online estimation is carried out on mechanical vibration disturbance of the multi-axis servo system based on the error time sequence matrix, a disturbance parameter estimation value is obtained, the dynamic compensation signal and the disturbance parameter estimation value are fused, and a servo synchronous compensation amount is generated; according to the technical scheme, through fusion of real-time parameter identification and dynamic compensation, the filling precision and efficiency are remarkably improved, meanwhile, the manual debugging complexity is reduced, and a reliable solution is provided for high-stability production under multiple working conditions.

The invention discloses a wind turbine generator hoisting construction tower drum operation system and a construction method thereof, and relates to the technical field of intelligent control. The problems that in the prior art, a static tension balance mechanism cannot restrain bending moment abrupt change, steel-concrete interface stress concentration causes microcrack propagation, the wave dynamic load compensation capacity is insufficient, and dynamic rigidity attenuation early warning is lacked are solved. Comprising a dynamic load prediction module, a multi-mode vibration suppression module, an offset compensation module and a digital twinborn decision module, a hoisting load is solved in real time through a multi-physics field coupling model and an improved time sequence deep learning algorithm, and interface crack propagation is suppressed in combination with traveling wave offset control and sweep frequency vibration. An improved Morison equation is adopted to drive a two-stage hydraulic servo to compensate a wave dynamic load, and a digital twin closed-loop correction mechanism is constructed based on a 5G URLLC protocol; the tower drum hoisting precision, the structural safety and the operation reliability under the complex working condition are remarkably improved.

The invention provides a color steel plate coating flatness evaluation method and system based on artificial intelligence. According to the method, the three-dimensional point cloud data is generated by collecting the interference fringe image, and the surface fluctuation characteristics are quantified; capturing a multi-dimensional vibration spectrum of the transmission roller shaft, generating a servo motor compensation control signal, driving a multispectral scanning head to perform reverse displacement compensation, and generating real-time compensation data; inputting the surface topography features in the three-dimensional point cloud and the real-time compensation data into a lightweight convolutional neural network, and outputting fusion features; and dynamically classifying and identifying surface defects and uneven areas based on the fusion result, adjusting a classification threshold in combination with the speed of the production line, outputting a flatness evaluation result, and synchronizing the flatness evaluation result to a speed regulation system of the production line to realize closed-loop optimization. According to the method, laser interference, vibration compensation and lightweight AI technologies are fused, dynamic high-precision evaluation of the surface flatness of the color steel plate of the high-speed production line is achieved, and the problems of defect misjudgment and measurement distortion caused by vibration interference are solved.

The invention relates to the technical field of information, in particular to an error compensation method for multi-axis linkage machining of a mold blank hole system, which comprises the following steps: judging the time range of a tool changing window based on an error accumulation trend, if error accumulation reaches a preset threshold value, triggering a compensation action, otherwise, continuously monitoring error change; aiming at the complexity of a motion track, a nonlinear optimization algorithm is adopted, an execution path of a compensation action is optimized, and conflicts with a processing action are reduced; according to the optimized compensation path, the control parameters of the servo motor are adjusted in real time, and it is ensured that the compensation action is stably executed in the machining process; dynamically updating an error model through data of a main shaft temperature sensor and a tool wear monitoring device, and continuously optimizing a time point and an execution path of a compensation action; in the machining process, the error accumulation condition is monitored in real time, if the error exceeds the preset range, the compensation action is triggered again, and the machining precision is ensured.

The invention relates to the technical field of program control, in particular to a servo position control method and system applied to an engraving and milling machine. The method comprises the following steps that real-time temperature data and real-time load data of lead screws of all shafts in the engraving and milling machine are obtained; collecting multi-node temperature distribution data of the engraving and milling machine; obtaining cutting force data and resonant frequency characteristic values in the engraving and milling machine; constructing a screw rod reverse clearance prediction model based on the real-time temperature data and the real-time load data of the screw rod, and generating a clearance compensation value; performing pre-compensation control before the servo position direction of each axis is changed based on the clearance compensation value to obtain a correction position instruction; and performing thermal deformation simulation on the engraving and milling machine based on the multi-node temperature distribution data to generate thermal deformation compensation amounts of all shafts. Through multi-source data fusion and intelligent control, comprehensive optimization of the servo position system of the engraving and milling machine is achieved, the machining precision, dynamic response and stability are effectively improved, and efficient and reliable operation of high-speed and high-precision machining is guaranteed.

The invention provides a servo system optimization method and system based on algorithm control, and relates to a motor control technology, and the method comprises the steps: firstly obtaining a real-time dynamic response parameter set during the dynamic operation of a servo device, covering inertia delay, torque fluctuation and position deviation parameters, and a corresponding optimization demand set, including optimization demands for each parameter; performing multi-level control signal generation on the real-time dynamic response parameter set according to the optimization demand priority, generating a control signal sequence set matched with a first compensation signal, a second compensation signal, a third compensation signal and the like, inputting the control signal sequence set into an execution mechanism, and driving the execution mechanism to dynamically respond according to an updating track, and finally, the control signal sequence set is optimized according to a feedback signal set generated by an execution mechanism, so that operation parameters of the servo device can be comprehensively considered, control signals are generated in a targeted manner, dynamic adjustment and optimization are realized, and the performance of the servo system is effectively improved.

The invention relates to the technical field of body-equipped intelligent robots, in particular to a multi-mode body-equipped intelligent robot control method and device, and the method comprises the steps: synchronously collecting visual, auditory, tactile, force sense and body perception information, and unifying the information to the same time-space reference through a cross-mode time-space stamp alignment mechanism; hierarchical feature extraction and fusion are carried out on the multi-modal information, and unified multi-modal scene state representation is generated; reasoning a decision based on the representation by using a body agent framework, and outputting a control instruction; motion planning and control, visual servo tracking in a non-contact stage and dynamic parameter correction in a contact stage are executed according to instructions; optimizing the multi-modal strategy network through an incremental strategy distillation mechanism based on the interactive data flow; the problem of space-time asynchronization of multi-modal sensing information is solved through a cross-modal space-time stamp alignment mechanism.

The invention relates to a full-automatic injection molding optimization method, device and equipment based on digital twinning, and belongs to the technical field of intelligent manufacturing equipment. Inputting the sensor data into a digital twin model to construct equipment dynamic response simulation, and synchronously comparing the actual mode locking force with the offset of a preset pressure threshold; generating compensation data of mold locking pressure according to the offset, and dynamically correcting an acceleration curve of a servo motor in a glue injection stage on the basis of the displacement of a screw rod; in hot runner control, a thermal interference compensation coefficient is calculated according to a temperature difference value of adjacent temperature zones, and an output power gradient signal of each heating ring is adjusted; the corrected parameter information is transmitted to an equipment PLC through an industrial bus to execute control, and a compensation coefficient threshold value is iteratively updated according to a product weight fluctuation value in the next forming period; closed-loop data interaction of an equipment control system is achieved, and the injection molding process is optimized.

The invention discloses a numerical control machining path control system based on artificial intelligence, particularly relates to the field of numerical control machining, is used for solving the problems of continuity and stability of a curvature mutation area in cutter path planning, and accurately captures global and local geometric characteristics of a curved surface through a curvature constraint feature matrix and a curvature adaptive convolutional network. A machining track meeting the differential geometric continuity is generated, and the problem of path breakage of a curvature sudden change area is effectively avoided; meanwhile, energy scale criteria and curvature manifold constraints are introduced, the machining track is dynamically repaired, geometric repair and physical stability are balanced, cutting force sudden change and stress concentration are reduced, and therefore the machining reliability is enhanced; in addition, through finite element simulation of the digital twin platform and synchronous updating of servo system parameters, dynamic closed-loop matching of a control instruction and a machining state is achieved, and the control efficiency and the surface quality are further optimized. And therefore, high-precision, high-stability and high-efficiency collaborative optimization is realized in complex curved surface processing.

The invention provides a servo motor real-time adaptive control method and system based on artificial intelligence, and the method comprises the steps: injecting a tiny excitation signal into a servo motor, collecting temperature and electromagnetic response data under different working conditions, and constructing a multi-dimensional information data set; performing real-time reasoning on the relationship between the temperature gradient and the magnetic path characteristics by using deep transfer learning to obtain multi-dimensional parameter deviation vectors such as stator flux linkage unbalance degree, permanent magnet flux weakening degree and torque coefficient change; generating a multi-scale compensation strategy through a physical enhancement reinforcement learning method and the multi-dimensional parameter deviation vector; and carrying out Lie group transformation processing on the control law under a differential geometric framework, and realizing accurate compensation on the temperature gradient effect through a dual-channel-dual-time scale framework. According to the method, heterogeneous sensing and multi-dimensional compensation strategies are adopted, the problem that the control precision of a traditional method is insufficient under the complex temperature gradient condition is solved, and the high-precision motion control performance is maintained under the dynamic working condition that the temperature distribution of the motor is rapidly changed.

The invention relates to the technical field of industrial automation control, and discloses a change gear assembly processing technological parameter intelligent optimization system, which comprises a multi-dimensional data synchronous acquisition unit, an angular domain static map construction unit, a phase lead constraint control unit and an angle trigger execution unit, according to the method, a static angle-load topological graph with a main shaft angle as an index is established, a phase lead angle is calculated by combining inherent physical response lag time of a servo system, and a parameter adjustment instruction sequence is directly injected into a servo current loop at a preset angle window before physical load impact occurs; according to the feed-forward control mechanism based on angular domain reconstruction and phase lead constraint, the problem of physical lag of traditional time domain feedback control in response to high-frequency intermittent cutting is avoided, and zero time difference of periodic load impact and even pre-judgment torque compensation are achieved.

The invention discloses a servo motor dynamic overload detection and protection method based on a heat accumulation model, which relates to the technical field of servo system fault protection application, and comprises the steps of constructing a heat accumulation equivalent model, dynamically detecting an overload state, executing a heat dissipation recovery strategy, implementing a multi-stage protection mechanism, self-adaptive environment compensation and a historical data learning function. Through discretization processing of overload curve data and a nonlinear acceleration calculation strategy, the problems of protection lag and false triggering caused by traditional single-parameter detection are avoided, it is ensured that the motor can respond in time in light load, heavy load and load fluctuation scenes, the burn-out risk of the motor is reduced, and through integration of an environment temperature sensor and a heat dissipation condition evaluation unit, the reliability of the motor is improved. The heat accumulation coefficient and the heat dissipation attenuation parameter are dynamically adjusted, the problem of model deviation caused by environment interference is solved, when heat dissipation deterioration and temperature feedback abnormity are detected, the heat dissipation recovery period is automatically prolonged, calculation logic is corrected, and the continuous operation reliability of the system is improved.

The invention relates to the technical field of servo motor fault diagnosis, in particular to a servo motor fault diagnosis method and system based on a neural network. The method comprises four steps of data acquisition and preprocessing, feature analysis and mode construction, real-time monitoring and anomaly detection, and fault diagnosis and feedback optimization. Servo motor operation data are synchronously collected through multiple sensors, features are extracted through a neural network model, and a fault diagnosis model is constructed. The state of the servo motor is monitored in real time, abnormity is recognized, the diagnosis result is optimized based on historical data, and the fault prediction accuracy is improved. The system comprises a data acquisition module, a mode training module, a monitoring and diagnosis module and a feedback optimization module which work cooperatively to realize intelligent fault diagnosis. The fault detection precision can be improved, the downtime of equipment is reduced, and the industrial production efficiency is improved.

The invention relates to the technical field of low-temperature storage tank installation, in particular to a low-temperature storage tank heat insulation module installation construction method which comprises the steps that expansion bolts are implanted into preset point positions of the inner wall of a low-temperature storage tank, inner wall morphology data are obtained through three-dimensional laser scanning, and a point cloud model is generated. A BIM system is used for constructing a three-dimensional model of the installation datum plane, the theoretical leveling height of each expansion bolt point position is calculated, and a leveling parameter instruction set is generated. And a servo motor of the bolt tightening equipment is driven to rotate the ball nut, so that the leveling gasket moves to the target height. And a press-fitting path is generated, a press-fitting mechanical arm is controlled to align the preformed hole of the heat insulation module to the screw part of the expansion bolt and press-fit, and the surface of the heat insulation module is fully attached to the surface of the leveling gasket. And a fastening nut is installed on the screw part of the expansion bolt, three-dimensional deviation analysis is carried out, and iterative correction is carried out. Compared with the prior art, the effects of shortening the construction period, improving the leveling precision, reducing stress concentration, ensuring long-term stability and the like are achieved.

The present invention relates to the technical field of pipeline control valves, and provides a fixed cone valve having automatic pressure adjustment and locking functions. The fixed cone valve having automatic pressure adjustment and locking functions comprises external fixed pipes; a supporting pipe is fixedly connected to the interiors of the external fixed pipes; a fixed frame is fixedly connected to the interior of the supporting pipe; a flow dividing cover is fixedly connected to one side of the fixed frame; and a fixed disc is fixedly connected to one side of the flow dividing cover. According to the fixed cone valve having automatic pressure adjustment and locking functions, a servo motor is started, an output end of the servo motor drives a third gear to rotate, the third gear drives a second gear in meshed connection with the third gear to rotate, and the second gear drives an inner ring gear and an outer ring gear which are in meshed connection with the second gear to rotate; and when the inner ring gear and the outer ring gear rotate to drive two first gears to rotate, and the first gears rotate to drive first lead screws to rotate, connecting plates located on the outer side and connected by means of a ball nut pair drive a sealing blocking pipe to horizontally move, so as to control the water outflow amount, achieving the accurate adjustment effect.

The invention discloses an unmanned ship distributed cooperative dynamic target surrounding control method under multiple constraints, and relates to the field of unmanned ship cooperative control. In order to solve the problems that multiple constraint coupling is not fully considered in cooperative surrounding of multiple unmanned ships, target state estimation is insufficient in an intermittent communication environment and the like, the following technical scheme is provided: firstly, a motion model of the unmanned ships and a target is established; a distributed internal model observer is arranged for each unmanned ship, and the internal motion state of the target is estimated; then designing a distributed type progressive average surrounding guidance algorithm, and performing distributed scheduling on the expected speed and heading of the unmanned ship, so that the unmanned ship can still keep safe surrounding when the speed or direction of the target is changed; the input saturation constraint of a propeller or a steering engine is considered, so that each unmanned ship can be autonomously controlled according to an expected trajectory and speed; and finally, stable and collision-free surrounding of the dynamic target is realized under multiple constraint conditions. The method can be applied to scenes such as ocean escort and maritime search and rescue which need to perform collaborative operation around a dynamic target.

A genetic algorithm optimization-based fuzzy PID control method and apparatus, and a device. The method comprises: S1, acquiring a preset standard electrode plate quality, a measured electrode plate quality and a system default ray intensity, acquiring an ambient temperature parameter, retrieving a monitoring index, and monitoring the stability of a surface density measurement system according to the monitoring index; S2, on the basis of a preset system parameter of the surface density measurement system, setting a data sampling interval; S3, on the basis of the data sampling interval, continuously sampling a number N of pieces of data using a median average filtering algorithm, removing extreme values, calculating the arithmetic mean value of the N-2 pieces of data, and eliminating sampling value deviation of the arithmetic mean value, to obtain surface density sampling data; S4, performing fuzzification processing on the surface density sampling data, determining a fuzzy rule, and performing optimization in real time according to the fuzzy rule and by means of fuzzy reasoning, to obtain applicable PID parameters; S5, on the basis of the applicable PID parameters, using a genetic algorithm to control a servo motor of the surface density measurement system. Thus, the technical problems of parameter tuning being difficult and the robustness of closed-loop control being low are solved.

The invention relates to a dynamic cooperative path planning and autonomous landing control method for an unmanned aerial vehicle and an unmanned ship, and the method comprises the following steps: collecting the state data of the unmanned ship and the unmanned aerial vehicle and the high sea condition environment data, and carrying out the data fusion processing; an improved fast extended random tree algorithm is adopted to plan a safe navigation path for the unmanned ship, the generated path of the unmanned ship is optimized based on an unmanned ship motion model considering environmental interference, and a model prediction control algorithm is adopted to plan a path for the unmanned ship to fly to a predicted landing point of the unmanned ship. Dynamic cooperation between the unmanned ship and the unmanned aerial vehicle is realized through information interaction between the unmanned ship and the unmanned aerial vehicle; the unmanned aerial vehicle recognizes an unmanned ship landing identifier through a visual servo guide system, calculates the position and attitude deviation relative to a landing point, adjusts flight control parameters according to interference conditions by using an adaptive control algorithm, and performs trajectory prediction compensation in combination with an unmanned ship motion model to realize autonomous landing. Compared with the prior art, safe landing of the unmanned aerial vehicle on the unmanned ship under the high sea condition is achieved.

The invention relates to a winding tension control method and system. The method is applied to a winding tension control device, the device comprises a tension control part and a linear speed control part, and the method comprises the following steps: acquiring a real-time tension detection value and a tension set value of the tension control part, calculating a tension error and a tension error change rate, and performing fuzzy reasoning according to a fuzzy control algorithm to obtain a linear speed control value; pID output parameters are obtained through integral separation PID and used for indicating and controlling a first servo motor of a tension control part; and acquiring a real-time linear speed value and a linear speed set value of the linear speed control part, calculating a linear speed error and a linear speed error change rate, and inputting the linear speed error and the linear speed error change rate into the PID compensation model based on a fuzzy control algorithm to obtain a PID compensation parameter for indicating and controlling a second servo motor of the linear speed control part. According to the method, the tension and the linear speed are subjected to fuzzy control and PID control respectively, the control precision can be improved, and the stability, the response speed and the production efficiency of the winding process are effectively improved.

The invention discloses an automatic air cylinder clamping system and method, and belongs to the technical field of air cylinder clamping, and the system comprises a map drawing module which is used for drawing a three-dimensional clamping force distribution map; the risk prediction module is used for synchronously predicting a deformation deviation risk value in the clamping process; the model calculation module is used for generating a dynamic attenuation coefficient; and the air cylinder adjusting module is used for dynamically adjusting the opening degree of a multi-stage cushion valve and the servo pressurization rate of the automatic air cylinder set through a self-adaptive control strategy till the clamping force error is stabilized within a preset threshold value. The technical problems that in the automatic air cylinder clamping process, due to environment interference and system errors, the clamping force is unstable, and the workpiece clamping precision is low are solved, and the technical effects that the clamping force stability is improved through dynamic compensation and self-adaptive adjustment, the deformation risk is reduced, and the clamping precision is improved are achieved.

Disclosed in the present invention is an output feedback control method for a pilot-operated electro-hydraulic proportional servo valve considering disturbance suppression. According to the control method, a nonlinear active disturbance rejection controller with both disturbance suppression and unknown state estimation is designed on the basis of a constructed disturbance observer in combination with an extended state observer. To address the problem of a valve core position control system of the pilot-operated electro-hydraulic proportional servo valve, the present invention not only ensures suppression of matched interference in the system, but also compensates for mismatched interference in the system, and utilizes a state observer to estimate unmeasurable state variables, so as to construct full-state feedback control, thereby ultimately achieving high-precision tracking control of the valve core position.

The invention relates to the technical field of arc discharge control, in particular to an arc discharge machine control method based on multi-parameter collaborative optimization, which comprises the following steps of: generating a first regulation and control instruction by adopting a fuzzy PID (Proportion Integration Differentiation) algorithm based on a deviation value between a dynamic parameter feedback signal and a preset threshold value, the axial feeding speed of the servo motor, the power output curve of the arc generator and the coolant spraying time sequence are synchronously adjusted, so that the arc energy density gradient and the workpiece heat conduction rate form dynamic balance, the mechanical resonance frequency in the machining process is monitored through the vibration spectrum analysis unit, and when it is detected that the resonance intensity exceeds a safety threshold value, the coolant spraying time sequence is started. And a second regulation and control instruction is generated by triggering a frequency compensation algorithm, and the driving frequency of the servo motor is corrected in real time, so that the control precision is improved, the arc discharge process is more stable, the response speed is increased, the arc discharge time is shortened, the adaptability is enhanced, the requirements of different materials and processes can be met, the energy consumption is reduced, and the production efficiency is improved.

The invention relates to a control system for stabilizing an equipment foundation embedded part mounting device. Comprising the following steps that a dynamic sensing network is arranged on an embedded part mounting device, comprises a tilt angle sensor, a pressure sensor and a displacement sensor and is used for monitoring the dynamic balance state of the embedded part in real time and obtaining monitoring data; the monitoring data are integrated through the central processing unit to form real-time three-dimensional attitude and gravity center position feedback of the equipment foundation; constructing a posture adjustment algorithm based on real-time monitoring data, simulating mechanical changes in the installation process of the embedded part by utilizing a finite element dynamic analysis model, and calculating an adjustment angle and a position deviation; the inclination angle and height of the mounting platform are finely adjusted through an electric servo device, and self-adaptive posture regulation and control of the embedded part are controlled; a partition pressure control technology is adopted, the bottom of the mounting device is divided into a plurality of mechanical unit areas, and the supporting force of each area is adjusted in real time through a distributed pressure regulator; and dynamic balance monitoring data is combined.

Disclosed is a low-precision incremental encoder-based method for ultra-low speed control of a servo system. According to the present invention, a fast speed observer in an ultra-low-speed working state is achieved, only a sampling speed and load torque in an M / T method need to be observed, and position information of an electric motor does not need to be observed, such that the structure of the observer is simplified, and calculation is simple and fast; moreover, the influence of a friction force and cogging torque on a speed change is considered, such that the speed observation precision is further improved. The fast speed observer can reduce hysteresis and measurement dead zones, such that the speed response and the speed control precision in a low-speed working state are greatly improved, the problem in a traditional observer of a large position deviation caused by nonlinear factors such as an external load is avoided, improving the stability and robustness of the system. According to the present invention, the processing of sampling measurement time at a medium-high speed and the processing of switching the observer at a low speed in the M / T method can optimize the speed measurement precision at both the medium-high speed and the ultra-low speed, and can better satisfy the requirements of apparatuses such as a radar on rotating speed control.

The invention provides an intelligent control method and system based on electro-hydraulic linkage. The method comprises the steps that multi-mode environment parameters are collected, a digital twin environment model is constructed, and data are synchronized with an electro-hydraulic servo system in real time. And establishing a nonlinear model, identifying parameters by using a least square method and a recursive least square method, verifying the precision through a step response test, and updating. And constructing an adaptive LSTM neural network inverse model to output a control voltage signal. And the signal is subjected to weighted fusion with the output of a PID controller, and the PID controller dynamically adjusts a gain parameter according to an error integral term to generate a control instruction to drive the system. According to the invention, the LSTM inverse model provides feed-forward compensation, the PID controller realizes feedback correction, and the LSTM inverse model and the PID controller are complementary. Meanwhile, based on a related nonlinear model and a parameter self-adaptive updating mechanism, the influence of working condition change is accurately described, and high-precision control of the electro-hydraulic servo system under the complex working condition is achieved.

The invention provides a fault determination method and device of a servo motor and a fault detection system of the servo motor. The method comprises the following steps: acquiring feature data; fusing the plurality of feature data to obtain comprehensive feature data; a fault analysis model is constructed, the fault analysis model is obtained through training of multiple sets of training data, and each set of training data in the multiple sets of training data comprises historical comprehensive feature data obtained in a historical time period and historical analysis results corresponding to the historical comprehensive feature data, the historical analysis result is used for representing whether the servo motor has a fault or not in a historical time period; and inputting the comprehensive feature data into a fault analysis model to obtain an analysis result corresponding to the comprehensive feature data. According to the scheme, the problem of poor fault detection accuracy of the servo motor in the prior art is solved.

The invention relates to the technical field of robot control, in particular to a robot motion control method, a robot and a system. The method comprises the following steps: acquiring depth information and color information of a current scene and visual textures and geometric features of a target object through an RGB-D camera, and generating a local environment map; introducing a motor current sampling value, correcting the material category of the target object, and determining an initial set value of the clamping force; the corrected joint torque estimated value is converted into a tail end force corrected value through a mechanical arm jacobian matrix; and on the basis of the force control weight and the position control weight, position control output and impedance force control output are calculated respectively, and a final control instruction is generated in combination with the clamping force initial set value and the tooth space compensation item. A harmonic compensation function based on the joint position, the speed and the current is constructed, periodic torque disturbance caused by the cogging effect of the servo motor is effectively restrained, the tail end force estimation is closer to the real acting force, and the clamping control stability is improved.

The invention discloses a centrifugal separation device for kelp processing and a use method of the centrifugal separation device, and belongs to the technical field of kelp centrifugal separation devices. Comprising a first cavity cylinder, a second cavity cylinder, a second servo motor and a separation disc, a plurality of sets of dynamic adjusting mechanisms are sequentially arranged and installed at the outer edge of the upper surface of the separation disc in a circumferential mode, a dehydration cylinder is formed through the dynamic adjusting mechanisms, and gas is injected in a reciprocating mode in the centrifugal separation process through dynamic adjustment; compared with a passive scheme depending on a flexible lining or rotating speed adjustment in the background technology, the active intervention mechanism can adjust the kelp distribution state in real time, and a moisture discharge channel is prevented from being blocked.