3308 results about "Control mode" patented technology

The embodiment of the invention provides an excavator handle control system for remote operation, a handle control method based on a Hall sensor is adopted, non-contact rocker data sensing is achieved, the influence of contact and movement abrasion on the service life of a handle is reduced, and the excavator handle control system has the advantages of being high in sensitivity and good in performance; the handle mechanism is more flexible to operate, and the service life of the handle is prolonged; a two-hand cooperative control mode is adopted, and two three-degree-of-freedom handles are used for simulating the driving environment of a real excavator, so that a good remote control effect is achieved, and the feeling of presence of an operator in the remote operation process is improved; the operation habits of a driver are fully considered, the walking and working of the excavator are respectively controlled through combination of different degrees of freedom of the left hand handle and the right hand handle, an operating lever of the real excavator is simulated in the aspects of structure, motion degree of freedom and working range, and the man-machine interaction environment of excavator driving is restored.

The invention relates to the technical field of automatic spraying, and particularly discloses a spraying system based on multi-modal vision and artificial intelligence self-correction, comprising a multi-modal vision acquisition module for acquiring color image information, depth information and infrared feature information; the control module is used for generating a spraying sensing model according to the information of the multi-modal visual acquisition module; the control module carries out spraying area identification, track planning and spraying parameter decision making based on the spraying sensing model; the spraying execution module is used for spraying; and the feedback self-correction module iterates the spraying parameter decision in the control module based on a reinforcement learning algorithm according to the difference between the actual coating state information and the expected state. The control method based on multi-modal vision and artificial intelligence self-correction is applied to a spraying system based on multi-modal vision and artificial intelligence self-correction. The scheme is used for solving the problems that the spraying quality of complex workpieces is not high due to the single sensing dimension of an existing spraying system, and the production flexibility is poor due to the rigid control mode.

The invention relates to the technical field of boiler combustion control, in particular to a boiler combustion multi-target collaborative optimization control method and system. The method comprises the following steps: firstly, acquiring coal quality parameters in real time through a laser-induced breakdown spectrum analyzer, carrying out qualitative and quantitative analysis on spectral data by utilizing a machine learning algorithm, constructing a boiler combustion digital twinborn model fusing a combustion mechanism model and a data driving model, and predicting combustion characteristics, NOx generation trends and coking risks under different blending schemes; and then, dynamically generating an optimization instruction combination according to a prediction result of the digital twinborn model, establishing a safety interlocking mechanism while executing the optimization instruction, and automatically switching to a manual control mode when detecting that the working condition fluctuates severely or the model prediction deviation exceeds a preset threshold value. According to the method, the problems of coal quality information lag and untimely combustion adjustment caused by traditional manual sampling are effectively solved, and the economical efficiency, the safety and the environmental protection property of boiler operation are improved.

The invention discloses a converter collaborative current limiting method based on adaptive virtual impedance and a power loop, and the method comprises the steps: firstly building an equivalent impedance model of a converter and a power grid, analyzing the steady-state and transient characteristics of fault current, and extracting key parameters for current limiting design; when it is detected that the voltage drop of the grid-connected point exceeds a threshold value, a self-adaptive virtual impedance link is automatically put into use, and virtual resistance and reactance values are dynamically calculated according to the variation amplitude of voltage or current, so that the virtual resistance and reactance values are proportionally adjusted along with the fault degree; and when the system voltage returns to normal, the virtual impedance automatically quits, and the control continuity is ensured. Then, the active and reactive power reference values are dynamically corrected according to the voltage drop depth, a power reference signal matched with the voltage amplitude is generated, it is guaranteed that power output does not exceed the limit, and the voltage supporting capacity is improved. Finally, real-time current-limiting control of the converter and stable operation of the system are realized on the premise of not switching the control mode through the synergistic effect of the virtual impedance ring and the power ring. The method has the advantages of being high in response speed, excellent in current limiting effect, good in control continuity and the like, and is suitable for fault current limiting and voltage support control of the grid-forming converter.

The invention discloses a control method of an electric actuating mechanism. The electric actuating mechanism is used for driving a valve to be opened and closed. The control method comprises the steps that real-time operation state parameters of the electric actuating mechanism are collected; determining a parameter control target value of the electric actuating mechanism according to a preset control mode; extracting historical operation data of the electric actuating mechanism, and outputting a control signal on the basis of a set target value according to a preset adaptive algorithm in combination with the historical operation data and the current operation state parameter; and driving the electric actuating mechanism based on the control signal. According to the technical scheme, the control precision of the electric actuating mechanism on the valve can be effectively improved.

The invention discloses a multi-mode hybrid energy storage cooperative control method and system for a megawatt-level network-building type energy storage power station, and the method comprises the steps: S1, collecting the frequency, voltage amplitude and phase of a power grid, and the charge state and temperature of each energy storage branch, and generating real-time monitoring data; s2, determining an operation mode of the energy storage power station based on a comparison result between the frequency deviation and the voltage deviation in the real-time monitoring data and a preset threshold value; s3, based on the operation mode of the energy storage power station, performing double-layer decomposition on the power instruction through a high-pass filter and a low-pass filter to generate a super-capacitor power instruction and a lithium battery power instruction; s4, generating an internal potential amplitude and a phase angle by adopting a virtual synchronous machine algorithm; and S5, on the basis of the amplitude and the phase angle of the internal potential and the detection result of the power grid connection state, executing switching control of a network construction type control mode or a network following type control mode. The millisecond-second level multi-time scale power optimal distribution is realized; self-adaptive inertia and voltage support is carried out; and island / grid-connected seamless switching is realized.

The invention relates to the technical field of process optimization, in particular to a collaborative optimization analysis method for multi-station tower drum welding. In order to solve the problem that cooperative control of tower drum multi-station welding is difficult, firstly, multi-mode sensing data of welding seam vision, arc sensing, thermal field distribution and welding voiceprint are loaded, a fusion evaluation model is constructed to obtain a welding seam deviation value and a sensor confidence score, and the health state of a sensor is judged according to a threshold value; and a corresponding fault-tolerant reconstruction control mode is triggered to obtain welding tracking control parameters, then a multi-station welding heat source model is loaded, thermal interference is decoupled in combination with the control parameters and thermal field data, multiple stations are cooperatively regulated and controlled, a cooperative control instruction is output and executed, and welding process optimization is achieved.

The invention relates to the technical field of droop control, in particular to a voltage droop control optimization method and system based on parameter self-adaption and a medium, and the method comprises the steps: dynamically recognizing a voltage sensitive interval according to voltage fluctuation characteristics, determining critical voltage distribution data, and determining a switching trigger condition of a current power grid control mode according to the critical voltage distribution data; analyzing the correlation degree between the current power grid control mode switching event and the power grid stability based on the switching trigger condition to obtain a switching behavior risk level; reconstructing voltage droop control parameter adjustment direction logic based on the switching behavior risk level, and generating a stable direction vector; calibrating the original droop control output signal according to the stable direction vector, and generating a self-adaptive droop control output instruction; and distributing the adaptive droop control output instruction to each substation node for voltage regulation. The voltage droop control parameters are adaptively optimized through the real-time running state of the power grid, and parameter adaptive optimization of voltage droop control is achieved.

The invention relates to a multi-type emergency vehicle signal dynamic priority control method based on vehicle-road cloud cooperation, and belongs to the technical field of intelligent traffic control. The method comprises the following steps: acquiring an emergency vehicle state and traffic environment data in real time through cooperation of a vehicle-mounted terminal, roadside equipment and a cloud control platform; the cloud control platform dynamically calculates priority scores based on vehicle types, task emergency degrees, predicted arrival time, real-time traffic influences and path complexity multi-dimensional factors; when multiple vehicles have conflicts, collaborative decision making is carried out based on scores; and finally, an optimized signal control strategy is generated and executed. The system effectively solves the problems that a traditional priority control mode is extensive, and traffic jam and multi-vehicle conflicts are easily caused, achieves the purpose that interference to social traffic is minimized while efficient passing of emergency vehicles is guaranteed, and improves the overall efficiency and safety of an urban traffic system.

The invention discloses a deep sea underwater integrated electro-hydraulic actuator system adopting pump and valve combination. The deep sea underwater integrated electro-hydraulic actuator system comprises a hydraulic cylinder, a pump control assembly and a valve control assembly. The pump control assembly comprises a metering pump, a first switch valve and a second switch valve; the valve control assembly comprises a large-flow proportional valve, a small-flow proportional valve, a deep sea compensation energy accumulator and a third switch valve. The metering pump, the first switch valve and a rod cavity of the hydraulic cylinder are sequentially connected through a pipeline, the metering pump, the second switch valve and a rodless cavity of the hydraulic cylinder are sequentially connected through a pipeline, the metering pump, the third switch valve and the deep sea compensation energy accumulator are sequentially connected through a pipeline, and the rodless cavity of the hydraulic cylinder is connected with the large-flow proportional valve and the small-flow proportional valve through pipelines. Two control modes of the actuator can be completed, large-flow control is achieved through the pump control assembly, high efficiency and energy conservation are achieved, flow needed by maintenance is supplied to a rodless cavity of the actuator through the valve control assembly via the large-flow proportional valve and the small-flow proportional valve, and posture keeping and emergency action are achieved.

The invention relates to the technical field of transformers, in particular to a transformer with a high-temperature early warning device, which comprises a base and a transformer body fixedly mounted on the base, and further comprises a temperature control system, and the temperature control system is used for monitoring the temperature of the transformer body and dynamically analyzing the transformer body. A plurality of sets of cooling fins are fixedly connected to the outer portion of the transformer body, and a plurality of sets of mounting frames are fixedly connected to the base. In the invention, aiming at the defect of incomplete monitoring of a traditional temperature sensor, the temperature control system can realize comprehensive temperature monitoring and dynamic operation analysis of the transformer body, accurately capture internal complex temperature field distribution, and avoid the problem of insulation aging acceleration caused by local high-temperature leak detection; compared with an existing single threshold value control mode, intelligent early warning is achieved through a dynamic analysis technology, a control strategy can be adjusted according to real-time temperature changes, and the limitation that a traditional method lacks state perception is overcome.

The invention belongs to the technical field of track planning, and particularly relates to a track planning method for a track and non-track mixed region, and the method comprises the steps: dynamically distributing a path point sequence for an automatic guided vehicle, and switching a control mode according to the type of a region where a current target point is located: generating a first control instruction for path tracking in a track region; in the non-orbital area, the pose and curvature of the exit of the previous orbital area are used as initial reference quantities to plan a smooth trajectory, and a second control instruction is generated; constraint shaping is carried out on the first control instruction, the second control instruction is adjusted, it is ensured that the end point state of path tracking and the starting point state of trajectory planning meet the continuity rules of the position, the course and the curvature at the joint point of the two areas, and finally the instructions are sent to corresponding control loops to be executed. According to the invention, smooth and coherent navigation control of the automatic guided vehicle between the fixed track and the free driving area is realized.

The invention discloses a multi-device and multi-mode centralized control system which comprises an interaction control end and a device assembly. The interactive control end is configured according to three different control modes of centralized control, independent control and hybrid control, in the centralized control mode, a set of main control unit is configured for all devices, and the main control unit comprises a main control server which is used for operating a main control program and coordinating and controlling operation of all device components; in the independent control mode, each equipment component is provided with a corresponding embedded controller, and the embedded controller comprises an embedded control server which is used for operating a main control program for controlling the corresponding equipment component; in the hybrid control mode, one or more independent devices are provided with embedded controllers, the embedded controllers communicate with the main control server, the device assembly comprises a device body and a driving unit, and the device body is driven by the driving unit to achieve various operation functions. According to the invention, centralized control of multiple devices in a large-scale manufacturing factory can be realized.

The invention discloses an intelligent closed-loop control system for a passivation solution in a hot galvanizing process, particularly relates to the technical field of industrial process automatic control, and is used for solving the problem of large parameter fluctuation caused by the fact that an existing passivation solution control mode lags behind intermittent production takt change. A signal monitoring module identifies a production cycle and calculates an estimated compensation value, an entropy weight generation module generates a weight distribution coefficient based on symbol sequence information entropy, and a data fusion module fuses the estimated compensation value and real-time monitoring data to generate a cooperation instruction. The trajectory prediction module simulates and generates a virtual change trajectory and a dynamic envelope line thereof according to the instruction, the envelope monitoring module monitors the running state of the real trajectory in the envelope line in real time, and the execution early warning module executes the instruction or generates an early warning signal according to the monitoring result. According to the system, prospective prediction and self-adaptive control of parameters of the passivation solution are realized, and the control precision and stability are effectively improved.

The invention belongs to the field of new energy, and particularly discloses a direct-current bus voltage control method and system of a flywheel energy storage system. Comprising the following steps: if DC bus voltage is in a normal range, DC voltage forms a q-axis current reference signal after being adjusted by a PI controller, the q-axis current reference signal generates a q-axis voltage instruction signal after being adjusted by a current control loop PI, and a dq-axis voltage instruction value is generated through decoupling; if the current control loop slightly deviates from the normal range, parameters of a PI controller are adjusted, so that an integration link plays a leading role in control output, a virtual impedance link connected to the current control loop in parallel is adjusted, and a dq-axis voltage instruction value is generated; and if the voltage is seriously deviated from the normal range, a grid-side power signal is fed forward to a machine-side direct-current voltage control loop, virtual resistance in a virtual impedance link is adjusted, and a dq-axis voltage instruction value is generated. According to the invention, the control mode is automatically switched according to different conditions of the DC bus voltage by adopting a threshold-grading regulation and control strategy, and the adaptability to large disturbance is improved while the steady-state precision of the system is maintained.

The invention provides a spindle constant-temperature AI closed-loop heat engine system, and relates to the technical field of numerical control machine tool control and heat management. The invention aims to solve the problems of response lag, uncontrollable thermal stress, single heating strategy and the like of the traditional spindle heat engine method. The system comprises a multi-dimensional thermal state sensing module used for constructing a multi-node discrete temperature field representing the overall thermal distribution of the main shaft; the real-time heat balance feedback module is used for judging the cold / hot starting state of the main shaft according to the initial temperature difference and executing a differentiated feedback control strategy; and an AI prediction forward compensation module that predicts a future cutting thermal load by pre-reading a machining instruction and generates a feedforward thermal compensation instruction. According to the method, the thermal stress is controlled by introducing the radial thermal gradient index as the safety constraint, negative precooling or positive preheating is achieved in combination with the AI predictive capacity, a feedback and feedforward composite control mode is formed, and the dynamic thermal stability and the machining precision of the main shaft under the complex working condition are improved.

The invention discloses an AGV portal motion speed control method and an AGV, and the method comprises the steps: receiving a portal motion speed instruction, and obtaining a needed portal motion speed in the portal motion speed instruction; based on the action speed of the portal frame, a speed-rotating speed formula is used for calculating the required rotating speed of the pump; if the required rotating speed is larger than or equal to the minimum rotating speed of the pump motor, the rotating speed of the pump motor is adjusted to the pump required rotating speed, the current corresponding to the opening degree of a multi-way valve port enabling the output flow allowed by the multi-way valve to be larger than the real-time output flow of the pump is calculated, and the opening degree of the multi-way valve port is controlled based on the current; otherwise, the rotating speed of the pump motor is adjusted to the minimum rotating speed, the current corresponding to the opening degree of the valve port of the multi-way valve enabling the output flow allowed by the multi-way valve to be smaller than the real-time output flow of the pump is calculated, and the opening degree of the valve port of the multi-way valve is controlled based on the current. According to the method, different flow control modes are selected based on the required rotating speed of the pump, the low-speed lifting micro-motion performance is optimized, the pressure loss generated by rapid lifting is reduced, and the energy consumption is reduced.

The invention provides a finite difference-based rapid calculation method and system for an electromagnetic regulation and control roller shape and a rolling condition optimization method and system, and belongs to the field of rolling control. The roller shape rapid calculation method comprises the steps that size parameters, an electromagnetic rod loading form, a regulation mode, regulation parameters and rolling working condition environment parameters of an electromagnetic regulation roller to be regulated are obtained, a geometric model of the electromagnetic regulation roller is established, and the electromagnetic rod loading form, the regulation mode, the regulation parameters and the rolling working condition environment parameters are set in the geometric model; grid division is conducted on the geometric model of the roller, the finite difference theory is introduced, an electromagnetic regulation and control roller shape rapid calculation model is constructed, and temperature field distribution is rapidly solved and calculated through an LU decomposition method; and the roller shape is calculated according to the electromagnetic regulation and control roller shape rapid calculation model and the temperature field distribution. According to the method, online dynamic regulation and control of the electromagnetic regulation and control roller shape under parameter optimization is achieved, and the real-time performance and accuracy of the electromagnetic regulation and control roller shape are improved.

The invention discloses a composite joint control method based on a frequency conversion air source heat pump system, and relates to the technical field of air source heat pump systems, and the method comprises the steps: building an HPF control framework, building a multi-input and single-output control model through machine learning, and coupling a PID feedback signal to generate a composite control basic signal; building load single-step forward prediction is carried out by adopting an LSTM neural network, and a building load prediction value is output through training and calculation of the neural network; the heat pump compressor is subjected to staged joint control; forward control is carried out on the load side circulating water pump; a differential switching mechanism is arranged, and water supply temperature deviation is monitored in real time. According to the variable-frequency air source heat pump composite joint control strategy, an HPF control framework, a compressor staged joint control and differential switching mechanism, load side water pump forward control and equipment cooperative linkage are integrated, model dynamic updating and switching parameter optimization are introduced, and the limitation of a traditional single control mode is broken through.

The application discloses a processing method of gel candies, and belongs to the technical field of gel candies. The method comprises a control unit with multiple independent pouring units, each pouring unit comprising a pouring head and a temperature control module, and the following steps are performed: S1: initial sensing and parameter setting; S2: a staged dynamic pouring step; S201: a starting stage, in which pouring is started at P0 and the F0, and lasts for a predetermined starting time Δt1; S202: a stable stage, in which after Δt1 ends, a control mode based on real-time viscosity feedback is switched to, the heating power is adjusted to maintain the real-time viscosity μ of the material in a target range [μ min , μ max ], and pouring is performed at a basic pump pressure F base . Through the staged dynamic control, the application realizes the precision and high efficiency of the gel candy pouring process.

The invention relates to the technical field of electric energy storage systems, and discloses an electric energy storage system hierarchical cooperative control method based on source-load-storage dynamic matching, and the method comprises the steps: obtaining a common connection point voltage sampling sequence, and calculating a second-order change rate; collecting the first-order change rate of the output current of the energy storage converter and determining a polarization constraint coefficient; switching a control mode according to a second-order change rate magnitude and a polarization constraint coefficient symbol, and utilizing a dynamic damping factor to constrain a duty ratio to adjust a step length; the dynamic damping factor is adjusted and increased when the polarization constraint coefficient exceeds a threshold value under the excitation and transformation state, so that the change rate of the output current is within the charge diffusion safety domain of the storage medium, dynamic damping is guided to implement asymmetric constraint through cooperation of trend pre-judgment and polarization stress identification, the output current is made to adapt to the charge diffusion limit, the switching frequency of the converter is reduced, and the stability of the converter is improved. Active substance precipitation is inhibited; and the total throughput of the equipment in the full life cycle is improved.

The invention discloses a sewage treatment dosing method and system based on machine learning, electronic equipment, a storage medium and a product. The method comprises the following steps: constructing a multi-parameter time sequence data set between historical operation data about a sewage treatment system and historical dosing amount data of time lag duration t corresponding to each group of historical operation data; a dosing prediction model is constructed based on a random forest network, and a multi-parameter time sequence data set is used for training; dynamically updating the lagging duration t; operating parameters of the sewage treatment system are collected in real time, and the trained dosing prediction model is used for predicting the dosing amount of the optimal dosing lagging duration. According to the method, the hysteresis of an existing dosing control mode is effectively compensated, meanwhile, the delay time is dynamically regulated and controlled, accurate prediction of the dosing amount is achieved, the fluctuation risk of the effluent quality is reduced, and the working condition generalization ability of a dosing system is improved.

The invention provides a smooth switching method of a converter network construction type control mode and a network following type control mode, and relates to the technical field of grid-connected control, and the method comprises the steps: obtaining a short-circuit ratio of a new energy grid-connected system; determining a current power grid type according to the short-circuit ratio of the new energy grid-connected system; under the condition that the current power grid type is determined to be a strong power grid and the converter operates in a network-building type control mode, a converter phase angle, a converter current reference value, an active power reference instruction value and a reactive power reference instruction value are respectively controlled to be switched into corresponding parameters in the network-building type control mode, and integral zero clearing operation is carried out on a converter current loop PI; and the converter is controlled to be switched to a network following type control mode. By means of the method, smooth switching between the network construction type control mode and the network following type control mode of the converter can be achieved.

The invention discloses a motor coil press fitting process parameter self-adaptive regulation and control method and device, and relates to the technical field of motor vehicle motor manufacturing. The method comprises the steps that press fitting target parameters including a target termination position and target pressing force are obtained, press fitting is started, actual pressure and displacement values are collected in real time, a process state deduction model is constructed, whether double targets can be met at the same time when press fitting is finished in a current control mode or not is predicted, and an analysis result is output. If the conditions cannot be met at the same time, the predicted pressure deviation value and the displacement deviation value are taken as optimization targets, a process state compensation value is introduced, a multi-target optimization function is constructed to solve a control target weighting coefficient, a press fitting tail-section hybrid controller is reconstructed, output instructions of a position ring and a force ring are fused, and press fitting is executed. According to the invention, synchronous high-precision control of the pressing force and the termination position under material fluctuation and environmental interference is realized, and the adaptability and stability of coil press-fitting processes of various motors such as a new energy automobile driving motor and a household appliance motor are improved.

The invention discloses an electronic license technology for special operation examination and approval through material object scanning and face recognition, and particularly relates to an electronic operation license for examining and approving dangerous operation for special operation in a production field in an information acquisition and online management mode. Comprising a special operation management and control system, a face / appliance recognition system, a gas detection system and a movable monitor. According to the special operation management and control system, an informatization platform is mainly built, the original paper version approval process is converted into online approval, whole-process supervision is achieved, and meanwhile a mobile phone end APP and a computer end webpage are built. The face / appliance recognition system is mainly used for a face recognition system and an equipment and facility recognition system; the gas detection system comprises a portable gas concentration detection alarm instrument, a data storage device, a data transmission device and a recording device; the movable monitoring system can construct all processes for monitoring, remote supervision is facilitated, and archiving and reviewing are achieved at the same time. An informatization centralized management and control mode is adopted, the original tedious processes of paper version approval, archiving, regular detection of toxic and harmful gases and recording are broken through, online approval and process full recording are realized through system construction, a tamper-proof function is set, the record traceability is ensured, real field confirmation of personnel at all levels is ensured, and the system is safe and reliable. And meanwhile, the whole process can be remotely and comprehensively monitored.

The invention discloses an unmanned aerial vehicle formation flight control method and device, an unmanned aerial vehicle and a storage medium. The method comprises the steps that formation parameters, flight task instruction data and flight state data of other unmanned aerial vehicles in a formation are acquired or updated; judging a control mode according to the flight task instruction data, wherein the control mode comprises at least one of the following modes: a normal control enabling and conventional flight mode, a calculation mode, a suspended hovering mode or a disintegration mode; according to the judgment result of the control mode, based on an L1 guide algorithm of self-adaptive track tracking, fusing unmanned aerial vehicle spacing control logic and / or formation control logic of formation dynamic adjustment to obtain a control instruction of an expected track and / or attitude, and executing the control instruction; and circularly executing the steps to ensure the continuity and dynamic adaptability of the unmanned aerial vehicle and the formation flight thereof. According to the scheme, a completely decentralized distributed control architecture is adopted, and a fault-tolerant mechanism is matched, so that the reliability and survivability of the formation system are remarkably improved.

The invention relates to a flexible regulation and control load remote control terminal and method, and belongs to the technical field of power system automation and demand side management.The control terminal comprises an intelligent communication adaptation module, a coupling modeling module, a multi-scene self-adaption regulation and control module and a user interaction feedback module which are interconnected through an internal data bus; real-time interaction and cooperative work of data are realized; according to the invention, the breakthrough of the regulation and control mode from static presetting to dynamic optimization is realized, full-protocol compatibility and high-reliability transmission are realized, the real-time performance and interaction depth of user side response are improved, and the refinement and precision of control are improved.

The invention discloses a distributed power supply-containing power distribution network coordinated scheduling method, which relates to the field of power distribution network coordination, and comprises the steps of S1, multi-flexibility resource refined modeling and interaction characteristic analysis, S2, power distribution network linear load flow calculation and sensitivity analysis, and after the power distribution network linear load flow calculation and sensitivity analysis in S2 are completed, carrying out power distribution network coordinated scheduling. And S3, generating an uncertainty scene based on the generative adversarial network. According to the coordinated dispatching method for the power distribution network containing the distributed power supply, differences of various resources in control modes, response speeds and adjusting capabilities are analyzed through refined modeling, complementary characteristics of the resources are fully utilized by a collaborative optimization model, an overall optimization effect is achieved, a single type of resources are not optimized in an isolated mode, and the method is suitable for large-scale popularization and application. All adjustable resources such as a distributed power supply, an energy storage system, a reactive power compensation device, a flexible load and an intelligent soft switch are incorporated into a unified modeling and optimizing framework, and deep fusion and collaborative interaction of flexible resources can be realized.

The invention discloses a control system and method for a full-automatic probe platform, and relates to the technical field of semiconductor manufacturing and testing equipment, and the system comprises a contact event sensing and processing module which is connected with a signal output interface of a testing machine, applies a DC bias voltage to a selected testing channel, continuously monitors a loop current at a high sampling rate, and transmits the current to the testing machine; generating an electrical feedback signal, calculating the current change rate of the electrical feedback signal in real time, and calibrating a preset threshold value based on background noise for comparison and analysis; a contact starting event is judged by capturing current in real time, the control mode is switched immediately, the system can actively respond but not passively bear the change of the contact state, intelligent and self-adaptive control of the contact process is achieved, the control mode switching adopts a direct force control mode as a main control strategy of the contact process, and the control mode switching speed is high. The overall contact pressure is ensured not to exceed a safety threshold value, and overpressure damage and poor contact are effectively prevented.

The invention belongs to the crossing field of artificial intelligence and industrial automation, particularly relates to an aeration fan frequency conversion group control energy-saving method based on an intelligent optimization algorithm, and aims to solve the problems of high energy consumption, response lag and large equipment loss of a traditional control mode. According to the method, parameters such as dissolved oxygen, flow and pressure are collected in real time, a nonlinear optimization model with minimum energy consumption, accurate oxygen supply and minimum start and stop as multiple targets is constructed, an optimal rotating speed distribution scheme is solved online by adopting an improved particle swarm algorithm, and a smooth slope instruction output and closed-loop feedback correction mechanism is combined, so that the optimal rotating speed distribution scheme is obtained. And dynamic self-adaptive adjustment of fan group control is realized. The energy-saving efficiency is remarkably improved by 18%-25%, the annual electricity is saved by more than 800000 kilowatt-hour, meanwhile, the load unevenness is reduced to below 8%, fan start and stop is reduced by 60%, the service life of equipment is prolonged by 2-3 years, hardware does not need to be newly added, the deployment period is short, investment recovery is fast, and the method is successfully applied to multiple sewage plants.