3595 results about "Time control" patented technology

The invention relates to the technical field of data processing, and discloses a real-time data processing analysis method and system of an industrial PLC. The method comprises the following steps: transmitting temperature, pressure, current, vibration and acoustic parameters acquired by multiple sensors to an industrial PLC (Programmable Logic Controller) in real time to obtain multi-source heterogeneous original data; preprocessing the multi-source heterogeneous original data to obtain standardized fusion data; correlation calculation and anomaly recognition are carried out through the multivariate analysis model, and an abnormal state classification result is obtained; dynamically adjusting data interaction frequency and sampling rate between the edge nodes and the central PLC, and generating a real-time control decision instruction; and matching the real-time control decision instruction with the current motor load fluctuation state, and outputting the optimal frequency conversion control parameter. According to the invention, the response delay of the system is reduced, the control precision and reliability are improved, the dynamic balance between the safety and the energy efficiency is realized, and the system can intelligently adjust the control strategy according to the real-time safety situation.

The invention relates to the technical field of automatic industrial control, and discloses an automatic industrial equipment plc data acquisition monitoring control method and system. The method comprises the following steps: receiving a multi-source PLC data stream, and processing the multi-source PLC data stream through a multi-modal data fusion model to generate an equipment health degree evaluation matrix; constructing a dynamic control strategy generation model, and outputting a multi-target optimization instruction set; simulating the interaction influence of the equipment group by utilizing a process chain collaborative constraint model, and optimizing real-time control parameters of an instruction set; parameters are adjusted in parallel through a distributed edge computing framework, and an equipment cooperative control signal is output to an industrial monitoring center. The system comprises a distributed data acquisition module, a multi-modal fusion calculation module, a dynamic strategy generation module, an edge cooperative control module and an industrial communication gateway. According to the invention, multi-source data can be efficiently processed, equipment health can be accurately evaluated, a control strategy is optimized, equipment collaboration is realized, and industrial production efficiency and energy utilization rate are improved.

The invention relates to a shaft linkage curved surface component machining path real-time control method, system and device, and the method comprises the steps: obtaining geometric data and machining process parameters of a shaft linkage curved surface component, and carrying out the shaft linkage decomposition to obtain a multi-shaft linkage machining path; real-time operation parameters of machining equipment and tool workpiece contact data are obtained, deviation matching is conducted on the multi-axis linkage machining path, and a real-time axis control instruction set and an axis position compensation trend curve are obtained; performing path optimization on the shaft position compensation trend curve according to the real-time shaft control instruction group to obtain an initial shaft linkage adjustment scheme; performing curved surface precision evaluation on the tool workpiece contact data, and performing curved surface prediction in combination with the axis position compensation trend curve to obtain a curved surface quality prediction area; and performing coordinated optimization on the initial axis linkage adjustment scheme according to the curved surface quality prediction area to obtain an axis linkage optimization processing strategy. It can be guaranteed that efficient operation can be achieved in different machining states, and path deviation in the machining process is reduced.

The invention relates to the technical field of construction progress management, in particular to a BIM (Building Information Modeling)-based construction progress analysis and regulation and control system, which comprises a component sequence identification module, a component time acquisition module, a sequence deviation identification module, a node offset analysis module and a plan time regulation and control module. According to the method, the three-dimensional coordinates of the BIM components are extracted to establish a spatial sorting relation, a priority system with spatial constraints is constructed, the sequence recognition precision is improved, time mapping is formed by combining state data and completion time, ordered association from the site progress to the model components is achieved, the completion time of the previous components is compared to recognize abnormal procedures, and quantitative records are formed. The actual offset and the planned floating time are fused to judge the offset type, the influence weight of the component in the progress network is quantified in combination with the offset direction and the sequence offset number, a comprehensive evaluation index is formed, the construction progress management has a clear logic structure, and the construction progress regulation and control precision and response efficiency are improved.

The invention discloses a real-time computing system resource coordination and decision engine system based on a large language model. According to the system, a large language model is innovatively used as a central strategic decision engine, and a'decision-coordination-execution 'three-layer architecture is constructed. According to the system, macroscopic strategy generation and microscopic real-time control are decoupled by introducing a hierarchical decision-making mechanism (a strategic layer, a tactical layer and an execution layer), so that the core contradiction between LLM high reasoning delay and the microsecond / millisecond-level real-time requirement of the system is effectively solved, and the method is suitable for local computing equipment and a cloud data center. The system comprises a predictive strategy preloading system, and transient response can be achieved. Meanwhile, the system adopts an asynchronous event-driven decision-making mechanism for continuous intelligent optimization. According to the method, the top-down, semantic understanding-based and global collaborative intelligent management of the computing resources is realized, and the resource utilization efficiency, the system automation degree and the overall energy efficiency in a complex and dynamic computing environment are remarkably improved.

The invention discloses a modular reconfigurable production line control system integration method, which relates to the technical field of industrial automation, and comprises the following steps: establishing virtual mapping based on physical attribute parameters to form a production line digital twin basic model framework; collecting data in real time based on an on-site sensor, and establishing a digital twinborn dynamic mapping mechanism synchronous with a physical production line state; a reconstruction scheme is imported into a virtual environment, and key performance indexes are analyzed through a production line digital twin model rehearsal module combination process. A virtual production line model is constructed through a digital twin technology, a rehearsal and verification reconstruction scheme in a virtual environment is supported, trial and error time and cost required by traditional physical debugging are remarkably reduced, a reconstruction strategy is further optimized through a cloud AI algorithm, closed-loop optimization from virtual verification to physical execution is achieved in combination with edge end real-time control, and the real-time performance of the virtual production line is improved. The production line can quickly complete local or overall reconstruction according to production requirements, and the response speed and flexibility of the production line are greatly improved.

The invention relates to the technical field of force feedback handles, in particular to a remote surgical robot control system based on a force feedback handle and a control method thereof. The method comprises the following steps: carrying out multi-dimensional force data acquisition on an end effector of the surgical robot, and carrying out contact force size, direction and time sequence feature extraction to obtain multi-dimensional force feature data; performing surgical operation safety baseline analysis according to the multi-dimensional force feature data to generate surgical operation safety baseline data; performing dynamic force feedback threshold calculation according to the surgical safety operation baseline data to obtain force feedback threshold range data; and performing adaptive compression processing on different force feedback signals according to the force feedback threshold range data to obtain dynamic force feedback control parameters. Through real-time control instruction optimization and a closed-loop feedback strategy, the system can quickly respond to an operation intention, early warning is carried out on potential risks, and it is ensured that the operation process is safer and more reliable.

The invention belongs to the technical field of industrial control, and discloses a powder mixing processing control method, device and equipment and a storage medium, and the method comprises the steps: collecting target data in a powder mixing processing process in real time; inputting the target data into a prediction model to obtain a probability distribution prediction result of the state of the mixed production line in a plurality of time steps in the future, the prediction model being constructed by adopting a dynamic Bayesian network in advance based on the mixed production line; based on the probability distribution prediction result and the target data, a model prediction control algorithm is adopted to optimize a real-time control strategy, and a control instruction is obtained; and controlling the mixed production line according to the control instruction. The powder is uniformly mixed, and the dynamic adaptability is high.

The invention relates to the technical field of intelligent equipment autonomous control, and discloses an AIGA-driven intelligent equipment autonomous control and feedback adjustment method, which comprises the following steps of S1, collecting equipment body state parameters and external environment data in real time through a multi-mode sensor array; s2, combining the collected data with a preset user instruction and a real-time environment semantic analysis result; s3, disassembling the task target into a continuous action instruction set; s4, executing the action instruction set through the layered real-time control architecture; s5, monitoring an action execution effect based on the multi-modal sensor array; and S6, analyzing the relevance between the evaluation result and the action instruction through a causal inference engine. According to the method, an equipment action execution result is fed back to an intention generation layer in real time, a deviation source is positioned through a causal inference engine, a control strategy is dynamically adjusted, closed-loop iteration from one-way instruction execution to perception-decision-execution-verification is achieved, and the effect of self-adaptability in a dynamic scene is achieved.

Various embodiments herein provide techniques for uplink control information (UCI) multiplexing in multi—transmission-reception point (TRP) multi-panel operation. For example, the UCI may be multiplexed on a physical uplink shared channel (PUSCH) and / or a physical uplink control channel (PUCCH). Embodiments further include techniques for handling collision between PUSCH and PUCCH with different priorities. Additionally, embodiments include techniques for timing control for multi-TRP multi-panel operation. Other embodiments may be described and claimed.

The invention relates to an injection mold temperature control method and device and computer equipment. The method comprises the following steps: acquiring temperature data of a plurality of temperature measuring points of the injection mold to obtain a temperature data matrix; establishing a heating and cooling input matrix and a temperature response matrix, and solving to obtain a heat transfer path coefficient matrix; taking the temperature data matrix as state input, constructing a depth deterministic strategy gradient control network comprising a gating circulation unit and a full connection layer, and performing linear mapping to obtain a hybrid action space; inputting the heat transfer path coefficient matrix and the mixed action space into a training environment, performing iterative training on a depth deterministic strategy gradient control network based on an experience playback mechanism, and updating network parameters by calculating a reward function to obtain a temperature control model; and deploying the temperature control model to a target control system, and calculating a real-time control parameter set. According to the invention, coordinated control of the heating stage and the stabilizing stage is realized, the injection molding period is shortened, and the energy consumption is reduced.

The invention discloses a video generation system based on a video large model, and belongs to the technical field of video generation. A trajectory control unit; a physical rule constraint unit; the scene generation unit is used for constructing a high-fidelity dynamic environment and enhancing the scene immersion of the video; a timing consistency unit; a multi-modal fusion unit; the user interaction unit is used for realizing man-machine collaborative creation and real-time control and improving the generation efficiency; a quality evaluation unit; the post-processing optimization unit is used for improving the terminal applicability of the output video and adapting to multi-platform requirements; and a distributed deployment unit. Millimeter-level regulation and control of the object motion trail are realized through a multi-dimensional accurate control mechanism, and physical rule constraints are combined to ensure that the generated video conforms to the reality mechanics law, so that the content authenticity is remarkably improved; the multi-modal fusion technology integrates text, voice and image input, accurately restores the intention of the user and realizes lip shape synchronization and emotion migration.

The invention discloses an electric arc dynamic self-adaptive control method and sensing system based on multi-modal sensing, and relates to the technical field of electric arc control. A multi-modal sensor integrated on a welding gun is used for synchronously collecting an electric arc form image, a molten pool area image, a molten pool oscillation sound signal and current and voltage multi-dimensional data; the collected data are preprocessed, and real-time parameters in the welding process are extracted; calculating and outputting an optimal welding control parameter in real time by combining a depth Q model and taking the welding quality as an optimization target; the control parameters are transmitted to a welding actuator, real-time adjustment of the welding process is completed, and real-time control over the welding arc is achieved; the control method can be used for enhancing the real-time self-adaption of a welding control system to complex welding components and the flexible manufacturing capacity of replacing a product line; the technical problems that in an existing automatic electric arc welding control method, electric arc welding information collection is single, control response is delayed, the flexible degree is low, and welding feature extraction errors are large are solved.

The invention belongs to the field of industrial automation and mechanical control, and discloses a heavy-load mechanical arm trajectory tracking and control method and system under a dynamic working condition, and the method comprises the steps of kinetic parameter identification, multi-model predictive control and fault-tolerant control, real-time collection of motion state data of a mechanical arm, and real-time control of the mechanical arm. A recursive least square method and a particle swarm optimization algorithm are combined, and dynamic parameters of the mechanical arm are updated and optimized in real time; a dynamic prediction model set under different dynamic load working conditions and motion states is constructed, an optimal model is dynamically selected, and a mechanical arm trajectory tracking strategy is adjusted through a model prediction control algorithm; the motion state of the mechanical arm is monitored in real time, fault detection and diagnosis are synchronously carried out, redundancy control is started once a fault is detected, the control strategy is dynamically adjusted in combination with the redundancy freedom degree of the mechanical arm and the distributed control architecture, normal operation of the system is maintained, the robustness and reliability of the system are improved, and the requirements of complex operation scenes are met.

The invention relates to the technical field of medical care management, in particular to an intelligent mental disease risk assessment system which comprises a physiological rhythm extraction module, a rhythm alignment module, an interference analysis module, a branch recognition module and an assessment output module. According to the method, the sleep duration and the heart rate change are continuously recorded, the corresponding relation between the sleep rhythm and the heart rate fluctuation is constructed, a quantifiable mental rhythm parameter set is formed, dynamic mapping is established between sleep interruption and the heart rate fluctuation, and the stability of the individual physiological rhythm and the time structure of rhythm deviation are effectively revealed. Anchoring is performed based on a maximum offset day, a time contrast section is established around a specific time point, and differential features of variables in the section are finely extracted, so that micro rhythm disturbance is dynamically captured and measured. A coupling factor evaluation mechanism is constructed by using cross decision logic of sleep time history and heart rate amplitude, and the sensitivity and multi-dimensional analysis ability of rhythm change recognition are enhanced.

The invention relates to the technical field of asphalt pavement paving, and discloses an asphalt pavement 3D intelligent paving cooperative control system and method based on BIM + GIS, and the system comprises a data fusion layer, a real-time control layer, a multi-machine cooperation and task distribution layer, and a quality closed-loop layer. The real-time control layer comprises multi-source data acquisition (positioning / temperature / compaction degree and the like) and three types of core decisions carried out by the cloud center, and the three types of core decisions carried out by the cloud center comprise feeding demand prediction (based on paving speed + thickness) of a dumper, thickness / speed adaptive adjustment of a paver and dynamic planning of a rolling path of a road roller. According to the method, real-time correction of transverse deviation and elevation deviation is achieved through combination of PID control and fuzzy control, the expansion amount of a hydraulic cylinder of the ironing plate is dynamically adjusted by associating the paving speed, the multi-source sensing technology of Beidou, IMU, laser ranging and infrared imaging is adopted, time sequence consistency data synchronization is achieved through 5G communication, and the real-time correction of the transverse deviation and the elevation deviation is achieved. And the precision and the closed-loop optimization effect can be controlled in real time.

The invention provides an unmanned ship path tracking control method based on lightweight self-adaptive sight guidance. The method comprises a self-adaptive sight guidance algorithm, a foresight distance is adjusted in real time according to the current position and path deviation of an unmanned ship, ideal course information is obtained, and the path convergence speed and algorithm calculation efficiency are improved. And in the virtual simulation platform, marine environment information is combined, and unmanned ship dynamic model parameters are obtained through experiments. And constructing an objective function taking the path tracking error and the rudder angle change as evaluation indexes, and optimizing PID controller parameters by adopting an improved sparrow search algorithm. According to the algorithm, a dynamic additive updating strategy is introduced, so that the global search capability and the convergence stability are improved, and the optimal PID parameter is ensured to be obtained. The method has the advantages of being high in response speed, small in overshoot and high in path tracking precision in the complex marine environment, the real-time control performance and the environment adaptability of the unmanned ship can be remarkably improved, and the method is suitable for the unmanned ship path tracking control requirements in various task scenes.

The invention discloses a component real-time control method and system for vacuum glow coating, and relates to the technical field of vacuum coating, firstly, in a holographic component collection stage, a sensor and monitoring equipment are used for collecting multi-dimensional data in a coating process in real time, and secondly, in a self-adaptive component adjustment stage, a chromium-nitrogen component prediction value in a vacuum cavity is calculated to obtain a chromium-nitrogen component prediction value; the concentration is compared with the target concentration to judge whether component adjustment is needed or not, then in the real-time strategy adjustment stage, when the components deviate from the target value, the nitrogen flow, bias voltage and target current are automatically adjusted through the equipment management platform to ensure the stability of the coating process, and finally, in the real-time film quality correction stage, the film quality is corrected. The film layer quality is quantified through an innovative calculation formula, the stability and consistency of chromium-nitrogen film coating are improved through closed-loop control, and the film coating process can be dynamically optimized so as to ensure that the final film layer quality meets the design requirement.

The invention relates to the technical field of industrial control, and discloses an energy-saving air conditioner intelligent control system which comprises an edge computing node, a dynamic load prediction module, a self-adaptive control module, an energy consumption optimization evaluation module and a fault diagnosis module. A data acquisition module, a real-time control module and a communication interface are integrated; based on the historical environment data and the air conditioner operation log, a long-short-term memory network model is adopted to predict the expected load demand in 2-4 hours in the future; dynamically adjusting the operation number of chilled water units, the frequency conversion frequency of water pumps and the opening degree of fresh air valves according to the expected load requirement; the unit cold energy consumption of a single air conditioner is calculated in real time, and a global optimization instruction is generated in combination with a time-of-use electricity price strategy; motor current harmonic characteristics are collected through the edge calculation nodes, the abnormity of the air conditioner is recognized, graded response is conducted, the intelligent control efficiency of the energy-saving air conditioner is improved, and the overall energy consumption cost of the air conditioner is reduced.

The invention discloses a transmission method and device, Internet of Things equipment and electronic equipment, and belongs to the technical field of communication, and the transmission method comprises the steps that target Internet of Things equipment receives a first downlink message sent by first equipment, and the first downlink message is used for indicating at least one piece of Internet of Things equipment to initiate a random access process; wherein the first downlink message comprises at least one of the following items: identification information of the at least one piece of Internet of Things equipment; a cause is paged; accessing process information; transmitting data information; the access resource configuration information of the target Internet of Things device; time control information; the retransmission resource configuration information of the target Internet of Things device; the security information is used for carrying out authentication on the target Internet of Things equipment and carrying out encryption or decryption on transmission data; and a first indication, wherein the first indication is used for indicating the backoff time of data retransmission of the target Internet of Things equipment.

The invention relates to the technical field of numerical control lathe control, discloses a high-precision numerical control lathe Y-axis dynamic adjustment drilling reamer holder control method, and aims to improve the precision and efficiency of Y-axis motion control. According to the method, Y-axis motion data, machining parameters, tool abrasion and workpiece material information in the historical machining process are collected, and a motion prediction model is constructed. And acquiring current processing state data in real time, and inputting the model to predict a Y-axis movement track. Meanwhile, Y-axis real-time motion data are obtained and compared with a predicted track, and deviation points are marked. And then, a Y-axis dynamic adjustment decision model is constructed, and the adjustment process is modeled as a Markov decision process. And performing real-time control based on the trained decision model, selecting an optimal adjustment action according to the current processing state and strategy, and automatically executing the optimal adjustment action. According to the method, multiple factors are comprehensively considered, the prediction accuracy and the adjustment flexibility are improved, and the machining quality and the production efficiency are guaranteed.

The invention discloses a natural gas pipeline intelligent pressure regulation and flow dynamic optimization system based on a PLC optimization system. The system comprises a data acquisition and monitoring module, a PLC core control module, an intelligent optimization algorithm module, a man-machine interaction module and a safety protection module. According to the method, the defects in the aspects of pressure regulation, flow distribution and safety risk in the prior art are overcome, a deep learning optimization layer is innovatively overlaid on the basis of a traditional PLC control layer through a PLC and AI fusion framework, and organic cooperation of hard real-time control and intelligent decision making is achieved. The PLC is responsible for rapidly and accurately controlling the equipment, the AI is used for analyzing complex data, predicting the trend and optimizing the control strategy, the intelligent level of the system is remarkably improved, and the safety coefficient can be automatically adjusted according to the pipeline aging degree. For example, the safety coefficient alpha of a new pipeline is set to be 1.0, and the safety coefficient alpha of the pipeline running for 10 years is adjusted to be 1.3, so that the safety and the reliability of the system are ensured under different pipeline states.

The invention relates to the technical field of mechanical arm control, in particular to a self-adaptive fuzzy fixed time control method based on an output-limited mechanical arm, and the method comprises the following steps: S1, constructing a mechanical arm dynamic model; s2, setting constraint conditions of an output state of the mechanical arm dynamic model; s3, defining a tracking error and a virtual control law of the mechanical arm dynamic model; s4, on the basis of output state limitation and fixed time control, an actual control law is designed to serve as input of the mechanical arm dynamic model, and an adaptive law is constructed; and S5, a three-level logarithmic obstacle Lyapunov function is constructed, the three-level logarithmic obstacle Lyapunov function is combined with the virtual control law, the actual control law and the self-adaptive law step by step and substituted into the virtual control law, the actual control law and the self-adaptive law, and then it is guaranteed that the output state of the mechanical arm dynamic model does not exceed the preset safety boundary according to the actual fixed time control lemma. According to the invention, high-precision trajectory tracking can be realized on the premise of ensuring safe operation of the mechanical arm.

The invention provides a circuit board processing control method and system applied to an industrial internet of things, and the method comprises the steps: collecting the real-time equipment state data of a plurality of processing equipment in the processing process of a target circuit board, and calling a path generation model to generate an initial processing path based on the historical processing path data in a processing parameter set; inputting the path node data and a physical sensing data set into a parameter adjustment model for matching, and generating a path node adjustment instruction; performing parameter optimization on the processing nodes in the initial processing path based on the path node adjustment instruction through a parameter adjustment model, generating a target processing path, extracting a process constraint condition of each processing node in the target processing path, performing real-time control instruction distribution on the plurality of processing devices, and generating a target processing path; and performing joint iterative updating on the path generation model and the parameter adjustment model based on the feedback signal until the processing error rate of the target processing path is lower than a preset threshold value. The circuit board machining precision and the overall production efficiency can be improved.

The invention relates to the technical field of unmanned aerial vehicle control, in particular to a speed synchronization control method of an unmanned aerial vehicle and a mobile platform, a flight control system and the unmanned aerial vehicle, and the speed synchronization control method comprises the steps: obtaining GNSS information, visual beacon information or mobile visual positioning information according to the relative distance between the unmanned aerial vehicle and the mobile platform, and performing real-time control on the unmanned aerial vehicle by using the acquired GNSS information, the visual beacon information or the mobile visual positioning information so as to realize speed synchronization between the unmanned aerial vehicle and the mobile platform. According to the invention, through mutual complementation and assistance of multiple speed synchronization modes, the optimal speed synchronization mode can be automatically selected for different distance ranges, accurate speed synchronization between the unmanned aerial vehicle and the mobile platform in a complex environment is realized, and accurate following or accurate landing between the unmanned aerial vehicle and the mobile platform can be realized.

The invention relates to a buoyancy tank wharf real-time assembly quality control method, and belongs to the technical field of port engineering automatic construction. According to the method, aiming at the problems of large geometric positioning deviation, uneven contact surface stress and difficulty in real-time control of attitude instability in buoyancy tank assembly, laser range finders are mounted at four corners of a buoyancy tank through a geometric positioning layer to monitor horizontal deviation, and pressure sensors are arranged on a butt joint surface through a mechanical sensing layer to generate a pre-tightening force curve; the attitude monitoring layer adopts a bottom inclination angle sensor to detect inclination; according to the horizontal deviation, the curve similarity deviation and the inclination angle deviation, the real-time management and control platform triggers a hydraulic adjusting mechanism, a torque wrench and a balance weight drive to conduct adjustment; meanwhile, data are stored through a buoyancy tank number, a timestamp and a sensor type three-dimensional index, and a rechecking instruction is generated based on the difference between the current adjusting quantity and the first three mean values. According to the invention, real-time control and dynamic adjustment of the assembly process are realized, and the modular assembly precision and safety of the floating wharf are improved.

The invention relates to the field of waterproof sockets, and discloses a multi-scene adaptive intelligent waterproof socket remote regulation and control system and method, and the method comprises the steps: obtaining multi-source sensing data of a socket deployment environment, and constructing a multi-scene adaptive input data set in combination with a parameter fusion strategy and a signal interference compensation mechanism; environment feature recognition is carried out on the multi-scene adaptive input data set, and typical application modes in different scenes are extracted by using a socket state tag extraction algorithm; based on the state mapping relation model, a remote regulation and control strategy optimization algorithm is adopted to dynamically analyze the operation state of the socket, and the matching degree of the current operation mode and the environment scene is identified; an intelligent judgment mechanism is introduced, pre-execution verification is carried out on the multi-scene regulation and control suggestion set, and potential control conflicts are recognized in combination with historical operation data and real-time control instructions; and performing instruction issuing management on the remote control behavior of the socket based on the optimized execution strategy. The invention has the advantage of improving the universality of the intelligent waterproof socket.

The invention discloses a fault simulation method and equipment in a complex flight scene, belongs to the technical field of flight fault simulation, and aims to improve the fault-tolerant capability of a system and realize full-coverage simulation of the complex flight scene through state injection and fault simulation. The problems of insufficient fault scene coverage, real-time control and data reproducibility in the prior art can be solved; moreover, the method can inject the fault states of a plurality of devices in parallel in the same simulation process, and compared with a traditional method which only supports a single-device single-fault simulation mode, the method has the advantages that the capability of restoring a composite fault scene is greatly enhanced, and the method is suitable for limiting condition verification of a high-reliability aircraft system.

The invention relates to the field of numerical control machining center control, in particular to a control system and method suitable for a five-axis machining center, and the system comprises a data input module, a path planning module, a data processing module, a data processing module and a control module, the motion path generating module is used for generating a motion path of a cutter according to the geometrical shape and process requirements of a machined part, the motion control module is used for controlling motion of all axes in real time, the interference detection module is used for adjusting the path or posture of the cutter according to a detection result, and the feedback control module is used for collecting state data in the machining process through all sensors. And real-time adjustment and error compensation are carried out on the machining process according to the data, so that the problems of poor machining precision and relatively low working efficiency due to the fact that a machining tool path needs to be manually demonstrated during operation of the five-axis machining center at the present stage and parameters such as tool compensation, feeding amount and cutting speed need to be manually input according to a tool model are solved.

The invention discloses a programmable logic controller programming system with an internet of things function, which relates to the technical field of industrial automation control and comprises a main control module based on a heterogeneous multi-core processor architecture and used for executing user program logic and coordinating operation of a communication module, a task distribution module, a dynamic loading module and a safety verification unit; according to the programmable logic controller (PLC) programming system of the internet of things, the real-time performance and the resource efficiency of an industrial control system are remarkably improved through heterogeneous multi-core collaboration, dynamic resource scheduling and multi-protocol compatibility technologies; on the basis of differential division of labor of the ARM and the FPGA, master core global scheduling and slave core high-real-time control are combined, and millisecond-level response of key tasks is guaranteed; compared with a traditional PLC, the system breaks through the limits of protocol closure, resource rigid distribution, shutdown dependence and the like, provides a flexible, stable and safe intelligent control core for the industrial Internet of Things, and promotes industrial automation to evolve towards high efficiency, networking and high availability.