1250 results about "Servo control" patented technology

The invention relates to the technical field of intelligent control, provides a flow regulating valve servo force control method and system based on a force sensor, and aims to solve the technical problems of response delay, weak overshoot suppression capability and poor long-term operation stability. The method comprises the following steps: acquiring a servo driving current data set and a valve displacement track data set of a target regulating valve; performing pressure feature mapping processing on the servo driving current data set to generate a pressure fluctuation feature set corresponding to the driving current waveform data; the pressure fluctuation characteristic set and the valve displacement track data set are input into a preset force control decision model for dynamic matching processing, and a servo control instruction set is generated; executing multi-stage dynamic adjustment operation on a servo driving unit of the target adjusting valve according to the servo control instruction set, and generating real-time pressure balance state data; and iteratively updating the dynamic matching processing parameters of the force control decision model based on the deviation value of the real-time pressure balance state data and the preset pressure reference value.

The invention relates to the technical field of marine monitoring, in particular to a marine target visual servo tracking method, which comprises the steps of multi-modal sensor fusion, a self-adaptive visual tracking algorithm, a servo control and visual collaboration mechanism and a shielding processing and target re-identification strategy. The problem that tracking is unstable under the conditions of illumination change, ship body shaking, target shielding and the like in a traditional method is solved. The IMU, the GNSS and the visual data are fused through extended Kalman filtering, ship body shaking is compensated, and the target state estimation precision is improved; the improved D-Fi ne target detection model is combined with an online feature updating mechanism to dynamically adapt to the appearance change of the target; the prediction and correction control strategy and the double-closed-loop PI D controller cooperate to adjust the camera holder, and the tracking delay is reduced; the multi-clue shielding detection and space-time joint feature matching technology ensures accurate re-identification of the target after shielding is removed. The real-time performance and robustness of the tracking system on an embedded platform are improved, and an efficient and stable target tracking solution is provided.

The invention relates to a multi-product-line-oriented robot welding integration method, device and equipment and a medium, and the method comprises the steps that three-dimensional geometrical characteristics and material attribute data of multiple types of workpieces are collected, and geometric parameters and material mechanical properties of weld joints are extracted; an order demand template is intelligently matched, and initial welding parameters and a clamp configuration scheme are generated; the health state of production equipment is evaluated in real time, and the collision-free movement track of the mechanical arm is planned; dynamically analyzing the joint angle sequence to generate a high-precision servo control signal; the welding process is monitored in real time, and current and molten pool temperature parameters are corrected; and iteratively optimizing the algorithm weight of the process knowledge base to improve the adaptive capacity. Through cooperation of multi-source data fusion and an intelligent algorithm, rapid switching of multiple kinds of workpieces, self-adaptive compensation of the equipment operation state and closed-loop optimization of welding process parameters are achieved, and the equipment utilization rate and the welding quality stability in a flexible production scene are remarkably improved.

The invention discloses a deep foundation pit stability deformation control method and device based on digital twinning. The method comprises the steps that monitoring time sequence data of a deep foundation pit are collected and obtained; constructing a deep foundation pit deformation control digital twin platform; constructing a CNN-LSTM composite neural network based on an Adam optimization algorithm through a foundation pit deformation prediction module, and performing model training / verification on the CNN-LSTM composite neural network through the data training set and the data verification set to obtain an optimized CNN-LSTM composite neural network; based on the optimized CNN-LSTM composite neural network, performing time sequence change prediction on the axial force of the steel support according to the data test set to obtain a prediction result; the steel support servo module realizes servo control on the axial force of the steel support according to a prediction result on the basis of a constructed servo control strategy; and the foundation pit BIM module is used for constructing a deep foundation pit BIM model based on a Revit modeling technology and interacting with the deep foundation pit BIM model in real time through a RevitAPI data interface according to the output of the steel support servo module so as to realize visualization of deformation control of the deep foundation pit. The problems that in the deep foundation pit construction process, due to the fact that complex geological conditions are involved, the surrounding environment and an existing building are affected to a certain degree, and deformation and stability of the deep foundation pit cannot be accurately controlled are solved.

The invention relates to the technical field of automatic workpiece grabbing and visual servo control, and discloses a workpiece grabbing method and system based on visual feedback, and the method comprises the steps: obtaining a real-time image through a front-view camera, a side-view camera and a top-view camera, and extracting surface features through a feature fusion network; inputting the features into a pose estimation model based on a particle filtering framework, and iteratively updating the pose in combination with a multi-dimensional observation likelihood function to generate prediction parameters; constructing a multi-target path planning model based on the parameters, and optimizing the path by adopting a dynamic planning algorithm with the shortest path and the minimum joint movement as targets; a hierarchical control model is established, a strategy layer performs global planning, an adjustment layer corrects a local path, and an execution layer realizes trajectory tracking through visual servo control and outputs a control instruction to complete grabbing. Through multi-view perception, robust pose estimation, global optimization path planning and hierarchical control, the precision, efficiency and stability of workpiece grabbing in a complex environment are improved.

The invention relates to an equipment flexible resistance adjustment servo control method and system, and the method comprises the steps: obtaining resistance torque data and a periodic control instruction of target equipment, carrying out the expansion estimation of disturbance parameters, and obtaining the total disturbance torque data and load equivalent stiffness information of a system; acquiring servo motor data of the target equipment, performing multiple feed-forward compensation on the total disturbance torque data of the system to obtain anti-interference feed-forward compensation data, and performing stiffness reference adjustment in combination with the load equivalent stiffness information to obtain a feed-forward reference coefficient; performing torque parameter coupling on the anti-interference feed-forward compensation data according to the feed-forward reference coefficient to obtain rigidity compensation torque data; and according to the servo motor data, the feedforward reference coefficient and the rigidity compensation torque data, performing instruction construction to obtain a servo control instruction. According to the invention, the dynamic characteristics of the system under complex working conditions can be evaluated more accurately, and the precision of servo control is improved.

The invention discloses a digital twinning-based major engineering construction safety active control method, system and equipment, and belongs to the technical field of construction active control. The problems of low safety risk identification efficiency and inaccurate risk control means in the major engineering construction process are solved, major engineering construction site environment and structural feature data are obtained through space-air-ground-water multi-way intelligent means and equipment, a digital twinborn model of a real-time mapping construction site is established, and the safety risk identification efficiency of the major engineering construction site is improved. Correcting the digital twinborn model by using real-time data; a digital twinborn model is used as a basic model of finite element analysis, mechanical properties of different construction stages are analyzed, dynamic early warning is performed on an analysis result in combination with real-time data, a safety risk derivation model is established to perform real-time analysis on key problems such as a risk point location, a risk influence range and risk derivation prediction in the digital twinborn model, and the safety risk derivation prediction result is obtained. Data support is provided for engineering safety active control, an active control strategy model is established, a control strategy is output to a servo control device according to risk information, strategy dynamic adjustment is performed according to a real-time effect, and high-precision cooperative control of major engineering safety monitoring is realized.

The invention discloses a precision compensation method of a composite numerical control machine tool, and particularly relates to the technical field of precision control of the numerical control machine tool, which comprises the following steps: synchronously acquiring temperature, vibration and force information under the driving of a unified clock through multiple types of sensors deployed at key nodes of the machine tool, and generating a synchronous multi-source sensing data set with aligned timestamps; inputting the data set into a multivariable coupling error model obtained through data driving training, and calculating and generating a comprehensive space volume error predicted value of a tool nose point of the tool; performing inverse calculation based on a machine tool kinematic chain model, and generating a multi-dimensional micro-compensation instruction set containing the compensation amount of each motion axis and the sequential relationship; and finally, dynamically writing the instruction set into a servo control ring of the numerical control system through a real-time data interface, and driving each motion shaft to execute synchronous compensation motion. According to the method, comprehensive compensation of multi-physics field coupling errors such as temperature, vibration and force load is achieved, and the machining precision and stability of the numerical control machine tool under complex working conditions are improved.

The embodiment of the invention provides a filling production line control method and system based on a virtual reality technology. According to the embodiment of the invention, the method comprises the steps: synchronously collecting a real-time dynamic parameter set of a fluid medium, constructing a dynamic coupling factor, generating a dynamic response coefficient matrix through a fluid coupling identification model, generating a nonlinear control parameter combination according to the dynamic response coefficient matrix, and inputting the nonlinear control parameter combination into a motion trail planner. Generating an optimized motion track instruction, driving an execution mechanism to execute filling operation according to the optimized motion track instruction through a servo controller, monitoring the deviation degree in real time, reconstructing the fluid coupling identification model when the deviation degree exceeds a preset threshold value, and updating a dynamic coupling factor; the nonlinear control parameter combination is corrected through the updated dynamic coupling factor, a closed-loop interlocking control mechanism is generated, and the technical scheme provided by the embodiment of the invention not only improves the intelligent level of a filling production line, but also improves the precision and stability in the filling process.

The invention relates to the technical field of target tracking, in particular to a photoelectric tracking algorithm and system for self-adaptive target tracking, and the system comprises an image collection module, a cross-spectrum self-adaptive sensing module, an image processing and target recognition module, a self-adaptive tracking algorithm module and a servo control module, and constructs a closed-loop feedback link to achieve the synchronous optimization of parameters in a whole link. The algorithm comprises the steps of image acquisition and adjustment, target detection, parameter optimization, servo driving and feedback. The system can accurately estimate a high-speed turning target, is adaptive to complex environments such as low illumination / haze and the like, completes sheltered target recapture within 0.5 s, has servo compensation precision of + / -0.1 degree, is suitable for airport bird monitoring, port unmanned aerial vehicle tracking and highway vehicle monitoring scenes, and significantly improves tracking stability and practical value.

The invention discloses a servo control method and system based on a PLC. The method comprises the steps of track data acquisition, interpolation instruction generation, control instruction output, state information acquisition, synchronous error evaluation, error compensation, track continuity control and the like. Wherein the PLC generates a multi-axis interpolation control instruction according to trajectory data issued by the upper computer, periodically issues the multi-axis interpolation control instruction to each servo driver through a high-speed timed task, collects feedback information in real time, and evaluates multi-axis synchronous deviation. On the basis, the PLC constructs an error vector and dynamically corrects interpolation parameters of the next period to realize synchronous control. Meanwhile, a buffer transition area is arranged at the track section switching position, acceleration and speed changes are adjusted, and it is guaranteed that the motion track is continuous and smooth. The system comprises a PLC, a trajectory data input module, an interpolation generation module, an error evaluation and compensation module and the like, has high real-time performance and high synchronization precision, and can improve motion coordination and system stability in complex trajectory execution.

The invention provides a heat-water-force coupling experimental device and a testing method based on dynamic true triaxial electromagnetic Hopkinson bar system loading. The experimental device comprises an X-axis dynamic loading system, a Y-axis lateral anti-seepage loading system, a Z-axis normal static pressure servo control loading system, a seepage system, a temperature control system and a data monitoring and collecting system. According to the device, on the basis of a dynamic true triaxial electromagnetic Hopkinson bar system, a shear loading module, a temperature regulation and control module and a seepage control module are creatively integrated, so that the true working condition of a deep rock mass under the coupling action of dynamic disturbance, osmotic pressure and temperature is simulated. The device breaks through the limitation that a traditional experiment system is difficult to realize multi-field coupling loading under a high-speed shearing condition, and provides an experiment means for dynamic response research of fractured rock mass under a complex multi-field environment.

The invention discloses a mechanical arm visual servo control method and equipment based on target condition reinforcement learning, and belongs to the technical field of mechanical arm control. A mechanical arm environment is built, a camera is additionally arranged at the tail end of a mechanical arm, a computer is used for designing a safety reinforcement learning model, then online learning is carried out according to a depth deterministic strategy gradient algorithm and a post-experience playback algorithm, and the mechanical arm environment is matched. The position of the feature point in the camera picture serves as input to control the mechanical arm to move and lock the two-dimensional code attached to the surface of the object, and finally the visual servo task is completed. The method is simple in step, low in environment requirement and rapid in response of the mechanical arm, and compared with a traditional control method based on pseudo-inverse, the method has remarkable effect improvement in the aspects of the number of iterations and robustness.

A power door actuation system for a door of a vehicle is provided. The system includes a housing mounted to the door and an actuator mounted within the housing that includes an electric motor configured to output a motor force. The actuator also includes a geartrain with a geartrain input coupled to an output of the electric motor for receiving the motor force and a geartrain output for applying an output force to the door. An extendible member is configured for extension and retraction in response to actuation by the geartrain output for moving the door. The system determines the output force to compensate for external forces affecting the motion of the door, adjusts the output force determined to an adjusted output force to compensate for internal forces affecting the operation of the actuator, and controls the electric motor to move the door at the adjusted output force.

The invention provides a group target-oriented turntable tracking control method, which belongs to the technical field of high-precision turntable control, is realized based on a turntable tracking system, and comprises a servo control module, a turntable and a configuration identification module, the configuration recognition module is used for calculating the miss distance of the main node unmanned aerial vehicle and transmitting an error between the miss distance and a tracking point expected value to the servo control module; and the servo control module calculates the motion speed of the rotary table and controls the rotary table to rotate by using a PI control algorithm according to the error, and the PI control algorithm comprises the following steps: according to the error value, performing segmented adjustment on a proportional parameter and an integral parameter of a rotary table speed ring PI controller. According to the invention, the segmented PI control algorithm is used for segmented adjustment, and the improved particle swarm optimization algorithm is used for optimizing and setting the proportional parameter and the integral parameter, so that the complexity of a manual trial and error method is eliminated, and the unmanned aerial vehicle at the main node of the group target can be stably tracked with the optimal performance under the condition of ensuring that the target is not lost.

The invention discloses an intelligent anti-counterfeiting color box printing positioning control method, and relates to the technical field of printing positioning control, and the method comprises the steps: dividing a color box layout into a plurality of detection regions, setting a cross-shaped and circular combined positioning mark in each region, and collecting positioning information in real time through a high-resolution image sensor to establish a feature database; extracting regional deformation and position features by using a multilayer convolutional neural network, calculating actual deviation by combining a residual network, constructing a mapping model of process parameters and position deviation, and establishing a differential compensation model by using a deep reinforcement learning algorithm; and the compensation parameters are distributed to a servo control unit, a motion control instruction is generated, a compensation effect evaluation index is adopted to carry out real-time evaluation on position deviation, a decision model is established to realize compensation parameter adaptive optimization, and regional compensation adaptive adjustment is realized. According to the method, intelligent monitoring and optimization of the anti-counterfeiting printing process are achieved, and the printing quality stability and the production efficiency of the anti-counterfeiting color box in batch production are greatly improved.

The invention relates to a mechanical arm visual servo control method and system based on deep reinforcement learning. Firstly, real-time state observation and collision detection are conducted on the mechanical arm, and an observation result is obtained; then, a deep reinforcement learning controller is built by means of a maximum entropy deep reinforcement learning SAC algorithm network architecture, and an action space, a state space and a reward function are built according to an observation result and a target position; and then, outputting a first action representation based on the construction content, optimizing a controller according to a calculation result of the first action representation and the reward function, smoothly optimizing the first action representation by using a real-time track interpolation strategy to obtain a second action representation, and controlling the mechanical arm joint according to the second action representation. And the process is continuously repeated until the mechanical arm successfully arrives at the target position. Compared with the prior art, the method has the advantages of high control real-time performance, large application range and the like.

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

An actuator assembly of an actuation system for a closure member of a vehicle is provided. The actuator assembly includes an actuator housing including a sensor housing. The actuator assembly also includes an electric motor disposed in the actuator housing and configured to rotate a driven shaft operably coupled to an extensible member that is coupled to one of a body or the closure member for opening or closing the closure member. The actuator assembly also includes an actuator controller disposed in the sensor housing of the actuator housing and coupled to electric motor and an accelerometer configured to sense movement of the closure member. The actuator controller is configured to detect the movement of the closure member using the accelerometer. The actuator controller then controls the opening or closing of the closure member based on the movement of the closure member using the electric motor.

The invention discloses a high-compliance impedance training method and system based on self-adaptive visual servo control and application of the high-compliance impedance training method and system. The training method comprises the steps that historical pose data and historical contact stress data are collected; performing feature processing to obtain stress pose information and generate a corresponding pose mapping relation; constructing a dynamic mapping model associated with the muscle force, the contact stress, the training track and the impedance parameters in combination with the stress pose information and the pose mapping relation; acquiring rehabilitation training information of a current patient, and generating and optimizing a preliminary expected trajectory; calculating deviation data of the real-time trajectory and the expected training trajectory; and an impedance adjusting model is constructed, the input of the impedance adjusting model comprises the deviation data and the real-time contact stress data, and the output of the impedance adjusting model is the impedance adjusting quantity. According to the invention, through visual real-time feedback, fuzzy PID adaptive adjustment and multi-feature fusion modeling, impedance adjustment training with better dynamic adaptability, higher safety, higher flexibility and high personalized precision can be realized.

The airborne photoelectric confrontation pod comprises a pod body, a U-shaped frame is fixedly arranged at the top of the pod body, side cover plates are arranged on the two sides of the U-shaped frame respectively, a servo control module and an orientation assembly which are used for controlling an image stabilization system are installed in the side cover plates, and the top of the U-shaped frame and an unmanned joint are assembled together through a damping assembly; a front cover for sealing and protecting is arranged at the front end of the cabin body; a power supply module, a power supply system connecting frame and a subsystem connecting frame are sequentially arranged in the cabin body from top to bottom, the power supply module is fixed on the power supply system connecting frame, the power supply system connecting frame is fixedly connected with the subsystem connecting frame, and the subsystem connecting frame is fixedly connected with the inner side of the cabin body. Through control of the upper computer system, stable observation, distance measurement and automatic tracking of ground and low-altitude targets can be realized, and a laser suppression system of the unmanned aerial vehicle is guided to emit strong laser to perform interference blinding and disposal on the unmanned aerial vehicle target.

The invention discloses a dual-redundancy servo controller and a main-standby autonomous switching method thereof, and belongs to the technical field of electric servo control. The controller comprises a host machine and a standby machine; each of the host and the standby machine comprises a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), a hardware ID (Identity) identification module, a motor power driving IPM (Intelligent Power Module) and a generator tripping instruction module which are in signal connection; the DSP and the FPGA are respectively connected with an LDO (Low Dropout Regulator) power module; the FPGA is in communication connection with the control system; the motor power driving IPM is connected with the execution mechanism; the DSP processors of the host and the standby machine are in signal connection; and the switching instruction modules of the host and the standby are in signal connection. The invention discloses a main / standby autonomous switching method for a dual-redundancy servo controller, which adopts a DSP and an FPGA to cooperatively detect and process faults, improves the fault detection rate by 5%, and reduces the possibility that the output of an IPM module is not turned off by 20% when a fault occurs; three heterogeneous redundant generator tripping modes of hardware generator tripping, serial port generator tripping and heartbeat generator tripping are adopted, and the reliability of main and standby independent generator tripping is improved by 20%.

The invention belongs to the technical field of clamping, and discloses a large thin-wall shell self-adaptive floating shape follow-up clamp and a force feedback clamping method. The large thin-wall shell self-adaptive floating shape follow-up clamp has certain flexibility and can clamp a large thin-wall shell workpiece in a self-adaptive floating shape follow-up mode. The large thin-wall shell self-adaptive floating shape follow-up clamp can achieve the full-surface clamping force feedback function of a large thin-wall shell workpiece. Force sensors are arranged below the circumferential floating supporting module and the top supporting module, the clamping force can be monitored and displayed in real time through a PLC control system, the purposes of quantitatively applying the clamping force and conducting self-adaptive feedback adjustment on the clamping force are achieved, and the clamping precision is improved. The large thin-wall shell self-adaptive floating shape follow-up clamp can achieve automatic clamping and releasing of a large thin-wall shell workpiece. Based on a PLC control system, the top supporting module and the circumferential floating supporting module are controlled through air pressure and servo, the end face positioning device is driven through oil pressure, automatic clamping and releasing are achieved, manual participation is reduced, and the clamping efficiency is improved.

The invention provides a servo press control system and method based on a time-sensitive network, and relates to the technical field of intelligent manufacturing and industrial automation control, and the system comprises a time-sensitive network TSN which is used for providing global time synchronization and deterministic data transmission; a main controller of the multi-axis servo control unit is used for issuing a motion control instruction and a feeding and discharging control instruction through a TSN. A robot controller in the robot feeding and discharging unit is used for driving an industrial robot to execute plate taking and placing operation under the action of the feeding and discharging control instruction. The visual monitoring unit comprises an industrial camera accessed to the TSN and is used for collecting images and transmitting image data to the edge computing node through the TSN; the edge computing node is used for processing the image data to generate a compensation instruction and feeding back the compensation instruction through the TSN; and the upper monitoring system is used for subscribing real-time data published by the edge computing nodes, so that the control range of the servo pressure control system is expanded, and the convenience of data transmission and interaction is improved.

The invention discloses a method and device for controlling grabbing of dynamic strips based on visual servo guidance and a test platform. According to the method for grabbing the dynamic strip-shaped object based on visual servo guidance control, the mechanical arm is guided and controlled to grab the dynamic strip-shaped object by adopting an image-based visual servo method, and real-time tracking of the dynamic pose of the strip-shaped object and immediate response of the action of the mechanical arm are realized through continuous sensing, processing and tight coupling of execution links; therefore, a more accurate, stable and efficient grabbing effect can be achieved in a highly dynamic and uncertain working environment; a test platform capable of simulating dynamic swing of a real strip-shaped object is also built, and a prediction control method and a visual servo control method are combined, so that effective verification and optimization of the high-precision and real-time grabbing process of the dynamic strip-shaped object are realized; the platform can be used for systematically researching the grabbing capability under various disturbance conditions in a laboratory environment, and a solid technical foundation is laid for automatic and intelligent operation in practical application.

The utility model provides a fuse end cap automatic installation mechanism. The fuse end cap automatic installation mechanism comprises an end cap feeding module, an end cap primary positioning tray, an end cap installation module, a pipe body transmission module and a servo controller. The pipe body conveying module is arranged on one side of the end cap mounting module; the end cap feeding module and the end cap primary positioning tray are arranged on the other side of the end cap mounting module, and an end cap primary positioning structure matched with an end cap is arranged on the upper end face of the end cap primary positioning tray; the end cap mounting module comprises a moving sub-module and a secondary positioning sub-module, and the moving sub-module is located on one side of the secondary positioning sub-module; the secondary positioning sub-module comprises an end cap secondary positioning structure, a pipe body positioning base and a clamping and overturning structure. According to the scheme, by arranging the two-time positioning structure of the end cap, accurate positioning of end cap installation can be achieved, the accuracy of the installation angle and position of the end cap is ensured, meanwhile, automatic production is adopted, and the production efficiency and the product percent of pass are improved.

The invention relates to the field of servo control, and particularly discloses a servo control method and system based on a programmable logic controller. The method comprises the following steps: the main control module and the shaft control module complete communication initialization through a high-speed bus, and load a standardized instruction library to generate an adaptive program segment; the digital twin engine collects data in real time to construct a virtual model, and when the deviation exceeds a threshold value, early warning is triggered; when a fault occurs, the feature parameters are matched with the fault gene pool to judge the type, and a maintenance work order is generated; and hot plug maintenance is supported, and parameters are quickly synchronized to recover operation after a new module is inserted. According to the technology, through modularization and intelligent integration, multi-axis flexible expansion is achieved, frequent hardware change is not needed, the maintenance process is optimized, faults are rapidly positioned, a main system is not interrupted, the whole process is traceable, meanwhile, system stability and control precision are guaranteed, and the flexible requirement of industrial multi-axis cooperation is met.

The invention provides a motor control PID parameter setting method and a motor control system. The method comprises the following steps: calculating a theoretical current loop PID parameter value according to a parameter when a motor is static and a discrete current loop model; performing actual control by using a theoretical current loop PID parameter value, and inputting a given current to a q axis during the actual control so as to obtain a feedback current; a comparison result of the feedback current and the given current is obtained based on multi-point FFT calculation; and based on the comparison result, adjusting the PID parameter value of the current loop until a new comparison result meets a predetermined condition. Theoretical PID parameters are obtained through calculation based on a discrete model, phase and amplitude changes of actual feedback current compared with given current are calculated through FFT, a current loop is adjusted in a self-adaptive mode according to the phase and amplitude changes, and PID parameters of a speed loop and a position loop can be further adjusted. According to the invention, the anti-noise capability of the FFT algorithm is utilized to improve the control precision, and the method is especially suitable for three-closed-loop servo control.

The invention relates to a servo driver parameter self-tuning oscillation suppression compensation method and related equipment, and the method comprises the following steps: carrying out the multi-channel synchronous collection of an operation state signal of a servo motor, and obtaining a real-time dynamic response data flow; performing time-frequency domain conjoint analysis on the servo motor based on the real-time dynamic response data flow to obtain an oscillation characteristic parameter matrix; performing oscillation source identification on the servo motor based on the oscillation characteristic parameter matrix to obtain an oscillation excitation source classification matrix; performing compensation parameter calculation on the oscillation excitation source classification matrix to obtain a multi-dimensional compensation coefficient set; and performing real-time parameter updating adjustment on the servo driver based on the multi-dimensional compensation coefficient set to obtain a servo control output signal after oscillation suppression, thereby solving the technical problem that a traditional servo driver depends on a fixed parameter setting method, is difficult to adapt to a complex and changeable working condition environment, and cannot effectively suppress an oscillation phenomenon.

This invention provides a thermal-hydraulic-mechanical coupling experimental apparatus and testing method based on a dynamic true triaxial electromagnetic Hopkinson bar system. The experimental apparatus includes an X-axis dynamic loading system, a Y-axis lateral anti-seepage loading system, a Z-axis normal static pressure servo-controlled loading system, a seepage system, a temperature control system, and a data monitoring and acquisition system. Relying on a dynamic true triaxial electromagnetic Hopkinson bar system, the apparatus innovatively integrates shear loading, temperature regulation, and seepage control modules to simulate the real-world conditions of deep rock masses subjected to dynamic perturbations, osmotic pressure, and temperature coupling. This apparatus overcomes the limitations of traditional experimental systems in achieving multi-field coupled loading under high-speed shear conditions, providing an experimental approach for studying the dynamic response of fractured rock masses under complex multi-field environments.