363 results about "Kinematic controller" patented technology

The invention relates to the technical field of large language models, and discloses a voice data interaction feedback control processing method based on a large language model. The method comprises the following steps: acquiring an industrial voice instruction through an AMR main controller, and obtaining a standardized vector through industrial lexicon matching and intention classification; inputting an industrial large language model for reasoning processing, and generating an AMR execution scheme; carrying out distributed coordination and task allocation on the AMR cluster to form a control instruction sequence; and the motion controller executes monitoring, processes exceptions and outputs a feedback strategy. Accurate classification and semantic understanding of complex industrial instructions are achieved, the processing capacity of professional knowledge in the industrial field is improved, and meanwhile high-precision real-time state monitoring is achieved.

The invention discloses a three-dimensional cutting dynamic parameter adjusting system and method based on deep learning, and relates to the technical field of application of three-dimensional five-axis fiber laser cutting machines in the automobile manufacturing industry, and the three-dimensional cutting dynamic parameter adjusting system comprises a multi-mode sensor cluster, an edge calculation unit, a closed-loop control module and an AI model library, the multi-mode sensor cluster collects cutting data, the edge calculation unit receives the multi-mode sensor data and outputs dynamic adjustment parameters, and the closed-loop control module transmits the dynamic parameters to the laser generator and the five-axis motion controller through a high-speed communication bus to form a'sensing-decision-execution 'closed loop. The cutting state and risk are sensed in real time by designing a multi-mode sensor for collaborative decision, the problems that manual experience depends on and dynamic response lags are solved, the reject ratio is reduced, and the response speed is increased.

The invention belongs to the technical field of three-coordinate measurement, and particularly discloses a space parameter measuring system based on a three-coordinate measuring machine, which comprises a measuring platform, a supporting arm, an X-axis driving module, a Y-axis driving module, a Z-axis driving module and a measuring assembly, and is characterized in that a motion controller is arranged at the top of a control box to control each driving module to move. A data acquisition module, a dynamic compensation module, a parameter fusion module and an execution control module are integrated in the box, the data acquisition module acquires multi-source and environmental parameters, the dynamic compensation module outputs a compensation instruction according to the parameters, the parameter fusion module outputs fusion point cloud coordinates, and the execution control module sends the instruction to a motion controller to drive three axes to move according to a preset path. According to the invention, a multi-module collaborative architecture is constructed, contact and non-contact measurement modes are combined, the problem of precision attenuation of a traditional three-coordinate measuring machine is solved, error dynamic correction is realized, and the measurement adaptability to high-precision workpieces is improved.

The invention discloses a three-dimensional jitter compensation method and device for laser cutting and a storage medium, and relates to the technical field of lasers, and the method comprises the steps that fast Fourier transform is carried out based on a vibration signal of a to-be-machined thin plate in the Z-axis direction, and a frequency spectrum feature is obtained; according to the frequency spectrum characteristics, combining a preset jitter filtering parameter set to carry out frequency domain filtering processing, and generating a filtering signal; reconstructing the filtering signal into a time domain compensation amount through inverse Fourier transform; based on the time domain compensation quantity, performing weighted fusion by combining the cutting acceleration and the cutting displacement deviation in the current cutting direction, and generating a three-dimensional compensation vector; and superposing the three-dimensional compensation vector to an original cutting path coordinate through a motion controller so as to correct the following state of the cutting head. The technical problem that the thin plate shakes due to nonlinear cutting force caused by interaction between high-speed movement of the cutting head and laser and materials is solved, and the stability of the thin plate during laser cutting is improved.

The invention discloses a radial forging machine chuck rotation oscillation braking electro-hydraulic control system and method, and the control system comprises a position detection encoder installed on a hammer head of a forging main machine, a hydraulic servo motion controller, a high-frequency servo valve, an oscillation braking oil cylinder with the same area as an A cavity and a B cavity, and an oscillation braking device with a worm gear and a worm. The pressure sensor and the displacement sensor are integrated on the oil cylinder to form a closed-loop control loop; the control method comprises the following steps: activating an oscillation braking function and collecting hammer phase, oil cylinder pressure and displacement signals in real time; a sine control signal synchronous with the forging frequency is generated based on the brake phase of 270-360 degrees; a brake oil cylinder is driven to push the worm to axially move, and the rotating speed of the chuck is modulated through the helix angle characteristic; and the amplitude is dynamically adjusted through a displacement-pressure feedback signal, and 25MPa overrun protection is executed. The purposes of reducing the brake response delay rate, the forge piece distortion rate and the equipment impact load are achieved, and 90-620 times / min wide-frequency-domain forging is supported.

The embodiment of the invention provides a dexterous hand control method and device, an intelligent agent and a storage medium, and the method comprises the steps: obtaining sensor data, preprocessing the sensor data, obtaining input information which comprises environment information and state information of a dexterous hand, inputting the input information into a cerebellum model, and obtaining a corresponding control instruction, the cerebellum model comprises a trajectory planning model and a motion controller, the trajectory planning model is used for outputting a corresponding trajectory planning result according to the input information, and the motion controller is used for converting the trajectory planning result into a corresponding control instruction; the motion controller is obtained by combining a cerebellum model neural network and a whole body dynamic model based on a model predictive control algorithm, and performs driving control on an execution mechanism module of the dexterous hand according to a control instruction. According to the dexterous hand control method provided by the embodiment of the invention, the control flexibility and accuracy can be improved.

An adaptive variable-structure duct robot motion control method based on environmental sensing. A duct robot is a dual-swing-arm tracked mechanism, and onboard sensing devices include a depth camera, an IMU, a wheel speed sensor and a TOF module. The method comprises: a depth camera capturing an image of the interior of a duct to perform scenario recognition, segmenting planar and curved surfaces in the image on the basis of scenario recognition results, and extracting edge lines of the duct; using the edge lines to calculate the width of a straight duct, the curvature of a curved duct, the angle of a slope and the height of a step, in order to determine the passability of a robot; designing a path planner and a swing arm planner to generate a reference trajectory and a swing arm angle sequence of the robot, performing smoothing processing, and inputting the smoothed reference trajectory and swing arm angle sequence into an MPC motion controller; using data from the depth camera, an IMU and a wheel speed sensor to estimate the position and state of the robot by means of an ESKF algorithm, and inputting estimation results and a collision warning signal from a TOF module into the MPC motion controller in real time; and finally, outputting control signals for a locomotion electric motor and a swing arm electric motor. Thus, the adaptive variable-structure and autonomous motion of a robot in different scenarios is realized.

A motion control method for an adaptive self-reconfigurable pipeline robot based on environmental perception includes: acquiring internal images of the pipeline for scene recognition, segmenting planar surfaces and curved surfaces in the images according to recognition results, and extracting boundary lines of the pipeline; calculating a straight-pipe width, a bent-pipe curvature, a slope angle, and a step height to analyze passability of the robot; designing a path planner and a swing-arm planner to generate a reference trajectory and a swing-arm angle sequence of the robot, performing smoothing, and inputting the reference trajectory and the swing-arm angle sequence into a model predictive control (MPC) motion controller; estimating a position and state of the robot through an Error State Kalman Filter (ESKF) algorithm, and inputting estimation results and collision warning signals into the MPC motion controller; and finally outputting a signal for control of a motor and a swing-arm motor.

The invention discloses a crane operation parameter self-learning optimization control system oriented to complex working conditions, which is characterized in that a multi-dimensional physical quantity signal is processed through a hierarchical mixed data fusion module, and a working condition feature vector is generated by using a lightweight mode recognition network; the working condition identification and risk assessment module outputs a working condition type identifier and calculates a dynamic safe operation boundary; a physical model enhanced reinforcement learning decision engine is built in the parameter self-learning optimization module, a parameter adjustment instruction is generated through an actor network, and evaluation optimization is carried out through a reviewer network; the optimized parameter adjusting instruction is issued to a self-adaptive fuzzy motion controller to drive an execution mechanism; and after execution, collecting system response data as an empirical sample to be stored and used for periodically updating network parameters. Accurate perception and safety evaluation of complex working conditions are achieved, control parameters can be autonomously optimized through fusion learning and a physical model, and the self-adaptive control capacity, stability and safety of the crane in a changeable environment are improved.

The invention provides an intelligent motion control system based on multi-level expansion and multi-type motor compatibility, and aims to solve the technical problems that an existing motion control system is poor in expansibility and weak in motor type compatibility. The system comprises a main controller, a configuration memory and at least one detachable motor control module, the motor control module comprises a motion controller and a motor driver. The core of the method is that when a main controller is initialized, motor type parameters preset for all motor shafts are read from a configuration memory, and differential configuration is executed according to the motor type parameters: when a motor is of a first preset type, a motion controller and a motor driver are cooperatively configured; and when the motor is of the second preset type, only the motion controller is configured to output pulse / direction signals, and the motor driver is disabled. Through software and hardware decoupling, the number of shafts can be flexibly increased or decreased without changing hardware, various motors and encoders are compatible, the expansibility and deployment efficiency of the system are remarkably improved, and the development and maintenance cost is reduced.

The invention discloses a robust trajectory tracking control method for a wheeled mobile robot in finite time, belongs to the technical field of robots, and aims to solve the problems that the wheeled mobile robot is inevitably influenced by model uncertainty and external disturbance in a task execution process due to a complex working environment, and the robot is difficult to track. The design difficulty of a wheeled mobile robot control system is greatly increased due to the factors. The method comprises the following steps: 1, establishing kinematics and dynamics models of a wheeled mobile robot; the invention discloses a wheeled mobile robot finite time robust trajectory tracking control method based on a nonlinear extended state observer, and the method consists of a kinematics controller and a dynamics controller, the kinematics controller can guarantee that the position and attitude tracking error of a wheeled mobile robot is gradually converged to zero, and the kinematics controller can guarantee that the position and attitude tracking error of the wheeled mobile robot is gradually converged to zero. The dynamic controller can ensure that the speed and angular speed tracking errors of the wheeled mobile robot converge to zero within finite time.

A multimodal wheelchair configured to be securely mounted to an aircraft is disclosed. The multimodal wheelchair may include: a first section, including: a processing system contained within a housing of the first section; a movement controller component positioned on a portion of the first section that is connected to the processing system; a plurality of wheels that are controllable by the movement controller; and a set of tracks recessed within a first side of the first section; and a second section, including: a seat portion located on a first side of the second section, the seat portion having an integrated harness; and a connection component, coupled to a second side of the second section, that attaches the second section to the first section via coupling with the set of tracks of the first section. Other aspects are described and claimed.

The invention relates to a control system and method for a seeding and fertilizing integrated seeder, and belongs to the technical field of agricultural machineries, the control system comprises a driving assembly which comprises a seeding motor driver, a seeding motor, a fertilizing motor driver and a fertilizing motor; the seeding motor driver and the seeding motor are mounted on the seeding disc; the fertilization motor driver and the fertilization motor are mounted on the fertilization disc; a sensing assembly; the controller is mounted on the seeder rack; and the Internet of Things cloud platform realizes cooperative control of fertilization operation and seeding operation. The control method comprises the steps that the vehicle-mounted power supply supplies power to the motion controller, and the motion controller determines a speed value; the motion controller adjusts the rotating speeds of the fertilizing motor and the seeding motor according to the speed values, and the two motors are cooperatively controlled; the motion controller sends the data to the Internet of Things cloud platform; the seeder completes seeding. According to the invention, the seeder has intelligent decision-making and remote monitoring capabilities, the seeding precision and efficiency of the seeder in the whole process are improved, and the intelligent degree is improved.

The invention discloses an intelligent vehicle elastic planning and control method based on large language model guidance under network attack, and belongs to the field of vehicle information safety and control, and the method specifically comprises the steps: firstly, building an intelligent vehicle auxiliary decision making and control system, and installing the system on a to-be-detected vehicle; the automatic driving decision-making unit generates an expected driving intention of the current to-be-detected period; the path planning unit generates a corresponding reference trajectory sequence. A vehicle reachable set estimator calculates a maximum allowable motion reachable range. The scene text editor completes scene description of the driving environment in combination with the perception information and converts the scene description into a structured text; the large language model performs comprehensive judgment on an expected driving intention and a planned reference trajectory sequence based on a maximum allowable motion reachable range and structured text description, and gives a final auxiliary decision variable. And based on the reachable set estimation value, constructing a vehicle motion controller based on data driving, and obtaining a control instruction to complete execution. According to the invention, the adaptability and robustness of the real vehicle operation environment are improved.

The invention discloses a mechanical arm tail end dual-light fusion detection data management system and method, and belongs to the technical field of industrial automatic detection. A visible light camera and an infrared camera are integrated at the tail end of a mechanical arm, discrete monitoring points are set according to the motion path of the mechanical arm, and the mechanical arm is based on pose data output by a motion controller; when moving to a preset monitoring point, synchronously triggering dual-light image acquisition, and carrying out space-time alignment on the acquired data; performing semantic segmentation processing on the visible light image, screening out a cable image from the visible light image to construct a cable identification model, obtaining boundary coordinates of a cable, performing feature matching with an infrared image, mapping a cable region to the infrared image, extracting a corresponding temperature data matrix, and calculating a maximum temperature difference value of the surface of the cable; judging an abnormal region in combination with a preset temperature gradient threshold value; and according to the anomaly detection result, the mechanical arm is triggered to dynamically adjust the detection path, the abnormal point is focused for reinspection, and anomaly early warning prompt is carried out according to the reinspection result.

The invention relates to the technical field of robot obstacle avoidance, in particular to a wafer transfer robot-oriented multi-modal real-time obstacle avoidance method and system, and the method comprises the steps: collecting environment data in real time through a multi-modal data collection device, and obtaining multi-modal environment data; performing space-time alignment on the multi-modal environment data, and establishing a workspace map; collecting operation data of the dynamic obstacle, and inputting the operation data into the constructed trajectory prediction model for trajectory prediction to obtain a trajectory prediction result; performing path planning on the wafer transmission robot to generate an optimal obstacle avoidance path; and verifying the optimal obstacle avoidance path, and outputting the optimal obstacle avoidance path to a motion controller for execution. According to the wafer carrying robot, the problem that the obstacle avoidance capability of the wafer carrying robot is insufficient in a dynamic environment is effectively solved, damage caused by collision in the wafer carrying process is effectively avoided, and the operation accuracy and safety of the wafer carrying robot in a complex production environment are improved.

A series-parallel flexible humanoid double-arm robot comprises an arm connecting piece, two mechanical arm modules, a motion control module and a power module. Two arm joint connecting ends are formed on the arm connecting piece. The two mechanical arm modules are connected to the two arm joint connecting ends in parallel, and each mechanical arm module comprises a plurality of flexible joint mechanisms and a dexterous hand module which are sequentially connected in series. The motion control module is installed on the arm connecting piece, and the motion controller is electrically connected with the two mechanical arm modules so as to control the two mechanical arm modules to bend and stretch in multiple directions; the power module is electrically connected with the two mechanical arm modules and the motion control module so as to achieve equipment power supply. The robot accords with the human arm muscle cooperative work rule, the overall performance and reliability of the equipment are high, and the movement process is natural and smooth; each flexible joint mechanism can be independently driven and tested, in addition, the flexible joint mechanism modules of the double-arm robot can be rapidly assembled and replaced, and the maintenance cost is low.

The invention discloses an intelligent asymptotic motion control method and system for a hydraulic mechanical arm. The method comprises the following steps: firstly, establishing a nonlinear mathematical model of a multi-degree-of-freedom series hydraulic mechanical arm system; secondly, estimating an endogenous uncertain item suffered by the system based on a multi-layer feedforward neural network; then, a robust control law for other uncertain items of the system is constructed, and an intelligent asymptotic motion controller of the hydraulic mechanical arm system is designed; designing a multilayer feedforward neural network updating law; and finally, parameters of the intelligent asymptotic motion controller of the hydraulic mechanical arm system are selected. According to the method, asymptotic tracking control of all the joints can be achieved on the premise that rotational inertia information of the hydraulic mechanical arm is not needed, and the tracking performance, adaptability and reliability of the system under complex working conditions are improved.

Motion is coordinated between a robot and a mover in an independent cart system. Positions for a mover along a track for the independent cart system and for each axis of motion of the robot mounted on the mover are received at the motion controller. The axis position corresponds to either an angular position of the motor or a mechanical position of a corresponding axis on which the motor is mounted. The motion controller receives a robot motion command corresponding to a desired operation of the robot and generates a mover motion command for the mover and an axis motion command for each axis of the robot. The mover motion command and the axis motion commands are generated as a function of the robot motion command, the position of the mover along the track, and the position of the motor or of the axis for each axis of the robot.

The invention relates to the technical field of industrial equipment control, and discloses a dynamic maintenance management method and system based on the full life cycle of test equipment, and the method comprises the steps: obtaining a time domain vibration signal and torque current data during the operation of the equipment through a high-frequency vibration sensor and a current loop feedback interface; calculating an accumulated damage gradient parameter representing the physical recession degree of the mechanical transmission chain; the parameters are input into a preset damage stress coupling model to solve the maximum radial impact force allowed to be borne by the damaged part, and the impact force is mapped into a dynamic capability boundary for carrying out logic constraint on the motion planning instruction; and the motion controller reconstructs an ideal speed curve by using the boundary in an interpolation period, and reshapes a torque load spectrum output to a servo motor by reducing the jump of acceleration and deceleration sections. The problem that an existing static control strategy is mismatched with the dynamic aging characteristic of equipment is solved.

The present invention discloses a deep Gaussian vehicle dynamics model, a training method, an intelligent automobile trajectory tracking control method and a terminal device. The present invention uses a physical model to obtain the mean required in the deep Gaussian model, and uses a feedforward neural network to obtain the covariance matrix required in the deep Gaussian model. Compared with the data-driven model, the established model integrates the prior knowledge of the physical model on the basis of accurately identifying various complex dynamic behaviors during vehicle operation, thereby increasing the robustness of the model and avoiding unknown errors in the data-driven model in areas not covered by the training data. The designed trajectory tracking control algorithm has higher interpretability than the end-to-end control algorithm. In addition, the tracking control of the desired trajectory can be achieved under different road conditions and driving conditions. While ensuring the path tracking accuracy, the lateral and longitudinal stability are also taken into account, laying a good foundation for the development of high-performance motion controllers for intelligent vehicles.

The invention belongs to the technical field of display panel manufacturing equipment, and discloses a large-size substrate lifting device, a control method of the large-size substrate lifting device and a carrying device.The lifting device comprises a substrate carrying table, a lifting mechanism, a flexible bearing array, an air pressure adjusting system and a motion controller; the flexible bearing array comprises a plurality of pneumatic bearing units arranged on the lifting mechanism, the pneumatic bearing units penetrate through the substrate carrying table, and the lifting mechanism can drive the flexible bearing array to move upwards so that the upper ends of the pneumatic bearing units can stretch out of the top face of the substrate carrying table to bear a to-be-carried substrate. The pneumatic bearing unit moves downwards to enable the upper end of the pneumatic bearing unit not to extend out of the top surface of the substrate carrying table so as to place the to-be-carried substrate on the substrate carrying table; the motion controller is used for controlling the lifting mechanism to ascend and descend and controlling the air pressure adjusting system to adjust the air pressure of each pneumatic bearing unit, so that the uniformity of the supporting force of the flexible bearing array on the to-be-carried substrate is ensured; therefore, the stability and the safety in the lifting process are improved, and the damage risk of the base plate is reduced.

The invention provides a path planning method and system and a cleaning robot, and belongs to the technical field of path planning. The method comprises the following steps: rasterizing an obtained swimming pool environment image to obtain a raster map; based on the attribute information of each grid in the grid map, identifying a to-be-cleaned uncleaned area set; taking the current position of the cleaning robot as a starting point, covering all the uncleaned areas and taking the shortest path total length as targets, searching in the grid map by utilizing a heuristic search method, and determining a target planning path of the cleaning robot to the uncleaned area set; based on the target planned path and a preset differential driving model in the cleaning robot, generating a walking control instruction for driving the driving wheels by the motion controller; and controlling the cleaning robot to move based on the walking control instruction. The cleaning time can be remarkably shortened, the coverage rate can be increased, the method can adapt to various complex swimming pool environments, and repeated cleaning and missing sweeping of the swimming pool are effectively avoided.

The invention discloses an immersive cinema dynamic content adaptation control method based on multi-modal fusion, and the method comprises the steps: collecting at least one non-contact physiological signal of a target audience seat area in real time, the physiological signal comprising a respiratory wave signal collected by a millimeter wave radar or a photoplethysmography signal collected by a near-infrared photoelectric sensor; performing time-frequency analysis on the physiological signal, and extracting a physiological wake-up characterization value in a current time window; the physiological wake-up characterization value comprises a heart rate variability change rate and a heart rate deviation value; constructing a dynamic damping adjustment model, and calculating a virtual damping coefficient of the seat movement system at the current moment based on the physiological wake-up characterization value; and the virtual damping coefficient is converted into an execution instruction of a seat motion controller, and damping force output of the motion platform is adjusted in real time. The technical problem that the pre-programmed motion feedback is disjointed with the real-time physiological and psychological state of the audience can be solved, the experience adaptability and comfort of the cinema seat are improved, and the system safety is improved.

To enable an operator to easily confirm the operation of a working machine and a turning body in the automatic turning control of a working machine.SOLUTION: A system according to one aspect of the present disclosure is a system for controlling a work machine. The work machine includes a swing body and a work implement. The turning body is turnable. The work implement is operably attached to the revolving unit. The system comprises an input device and a controller. The input device is operable by an operator to acquire teaching of an operation of automatic turning control of the work machine. The controller executes the automatic turning control in a normal mode in which an operation of the work implement and a turning operation of the turning body are controlled such that the work implement moves based on the teaching. The controller is configured to execute the automatic turning control in a rehearsal mode in which an operation of the work implement and a turning operation of the turning body are controlled such that the work implement moves based on the teaching at a speed different from a speed in the normal mode.SELECTED DRAWING: Figure 8

Various implementations are provided which include receiving an instance of natural language (NL) text input indicating a task for a multi-legged robot to perform in an environment. In many implementations, the system can process the NL text input using a large language model (LLM) to generate a foot contact pattern, indicating a sequence of leg positions of the robot relative to the surface, where one or more of the legs of the robot are in contact with the surface. Additionally or alternatively, the system can generate low-level robot control output by processing the foot contact pattern using a locomotion controller.

The invention discloses a multi-robot model-free adaptive cooperative control method and system based on neurodynamics. The method comprises the following steps: establishing a kinematic model containing a to-be-estimated Jacobian matrix and an unknown interference term for each robot; synchronously estimating the matrix and the interference term in real time by using an online learning algorithm based on the measurable speed; a comprehensive error model coupling individual tracking errors (actual and expected trajectory deviation of a single robot) and collaborative errors (tracking error difference of adjacent robots) is constructed, and a closed-loop error transmission structure is formed; then designing a distributed motion controller, and calculating a joint control speed enabling a comprehensive error to be converged to zero by using a neurodynamics method in combination with an online learning result and a synchronization error; and finally, discretizing a related formula, generating an iterative update formula, and outputting instructions in each control period to drive the robot to move according to the iterative update formula. The method does not need an accurate model, is high in robustness, can ensure that multiple robots accurately track the trajectory and maintain a stable formation, and is good in system expandability.

The invention relates to a multi-axis cooperative scanning motion control method and system for high-precision scanning imaging, and relates to the technical field of scanning imaging process.The method comprises the steps that in the scanning imaging process, an imaging mechanism model of light tube-sample-flat plate imaging is constructed based on a ray expected track of a ray source, and a light tube-sample-flat plate imaging model is constructed; and analyzing the expected position of the flat panel detector. Then, according to an expected position and a ray expected trajectory, analyzing a motion error and a coupling relationship between the expected position and the ray expected trajectory, and establishing a coupling influence; and according to the coupling influence, a high-precision synchronous motion controller is constructed. Then, kinematics capability limitation and coupling characteristics of each axis are analyzed, coupling mapping and speed constraint are introduced, and a control instruction of synchronous control is updated through speed correction; and finally, performing high-precision synchronous scanning control on each axis motion controller by using the control instruction. Therefore, the full-coverage detection and high-precision imaging of the detected sample are realized by limiting the motion and constraining a zooming synchronous control mechanism.

The invention discloses a multi-IP motion controller, industrial equipment and a control method, and relates to the technical field of virtual controllers. A plurality of virtual controls; a multi-IP binding module; an IP mapping module; wherein the virtual controller receives a data packet to generate a control instruction, and sends the control instruction to the corresponding execution terminal through the physical network interface, so as to control the operation of the execution terminal. According to the multi-IP motion controller provided by the invention, the independent IP address is allocated to each internal virtual controller and bound to the same physical network interface, and accurate data addressing and distribution based on the target IP address are realized in combination with an IP mapping mechanism, so that the problems of resource coupling and communication mixing of a traditional single IP architecture are effectively solved, the system integration and use process is simplified, and the system reliability is improved. And a high-performance, high-reliability and flexible solution is provided for complex multi-station cooperative control.