211 results about "Fuzzy control algorithm" patented technology

The invention relates to a motor power self-adaptive control method and system based on multi-dimensional sensor data, and the method comprises the steps: collecting multi-dimensional signals, such as ground resistance, motor temperature and battery voltage, in real time, carrying out the self-adaptive filtering and noise reduction, analyzing the correlation of all parameters through a multivariable decoupling algorithm, and determining a power demand weight; when it is detected that the ground resistance is a dominant factor, the system generates a load feature vector through weighted fusion, a database is matched to determine an optimal power target value, and PWM output is dynamically adjusted through a fuzzy control algorithm; and a closed-loop feedback mechanism continuously optimizes control parameters to ensure that the system quickly responds to sudden change of ground resistance. According to the method, intelligent adaptation of the motor power is achieved, the problems that adjustment lags behind and multi-parameter coupling processing is insufficient in the traditional technology are effectively solved, the stability of the sweeping robot under the complex ground working condition is remarkably improved, and the service life of the motor and the service life of a battery are remarkably prolonged.

The invention discloses a robot track online compensation and precision control method and system based on multiple sensors, and belongs to the technical field of robot track control. The method comprises the following steps: acquiring target trajectory data and original data of each sensor, and performing time alignment on the original data of each sensor to generate a fusion data set comprising vibration acceleration data and pose data; performing time-frequency feature extraction based on the vibration acceleration data to obtain a dominant vibration frequency spectrum; constructing a mechanical transfer function model of the joint driving torque and the tail end vibration displacement; based on the mechanical transfer function model, constructing an adaptive notch filter to generate a feed-forward compensation sequence; according to the target trajectory data, the pose data and weight parameters, updated in real time, of the sensors, a trajectory fusion deviation value is obtained through calculation; and after the feedforward compensation sequence and the trajectory fusion deviation value are integrated, a joint driving current instruction is generated based on a fuzzy PID control algorithm. The robot trajectory control precision can be improved.

The invention provides a field emission thruster extraction electrode indium deposition cleaning temperature control method and system, and relates to the technical field of space electric propulsion, and the method comprises the steps: obtaining multi-source temperature data and electric field intensity data of a target region, and carrying out the time-space fusion processing of the two data, and generating target feature information reflecting the deposition state of an indium material; based on the feature information, a fuzzy PID control algorithm is adopted to generate a power control signal, and then the embedded heating unit is adjusted; monitoring electrothermal characteristics to obtain thermal impedance parameters, and further generating heat flow distribution data; analyzing heat flow data by using a state observer to predict an indium deposition growth trend to obtain deposition rate information, finally determining a cleaning control strategy according to the growth rate, and controlling temperature change in a non-uniform heating mode to enable the indium material to reach a phase change state. According to the invention, the reliability and maintenance efficiency of on-orbit long-term operation of the field emission propeller are improved.

The invention discloses a frequency modulation control method and system for a thermal power generating unit, and relates to the technical field of frequency modulation control, and the method comprises the steps: collecting a frequency modulation instruction signal of a power grid, decomposing the frequency modulation instruction signal, and obtaining a plurality of intrinsic mode function components and residual components; performing spectral analysis on each intrinsic mode function component, marking the component of which the main frequency exceeds a high-frequency disturbance frequency threshold as a high-frequency disturbance component, and calculating a fluctuation amplitude and a change rate; a thermal system control instruction is generated through a PID control algorithm, the coal feeding amount and the main steam pressure are adjusted, and an auxiliary compensation control instruction is generated for the high-frequency disturbance component through a fuzzy control algorithm; a thermal system control instruction and an auxiliary compensation control instruction are converted into operation parameters of a thermal power generating unit control mechanism and issued for execution, when the control effect deviation continuously exceeds a deviation threshold value, an optimization process is triggered, and the frequency modulation stability and the equipment safety of a unit in the environment that new energy is accessed to a power grid in a high proportion are remarkably improved.

Disclosed in the present application are a method and apparatus for regulating the power of an offshore wind farm energy storage system on the basis of the state of charge. The method in the present application comprises: acquiring a power grid frequency and the state of charge of an offshore wind farm energy storage system, and on the basis of the power grid frequency and the state of charge, acquiring a power grid frequency deviation and a state-of-charge recovery demand, respectively; determining whether the power grid frequency deviation is within a preset power grid frequency dead band, if the power grid frequency deviation is within the power grid frequency dead band, in view of the power grid frequency deviation and the state-of-charge recovery demand, acquiring an inertia power regulation and control amount of the energy storage system by means of a fuzzy control algorithm combined with a preset adaptive inertia frequency control model, otherwise, in view of the power grid frequency deviation and the state-of-charge recovery demand, acquiring the inertia power regulation and control amount by means of the adaptive inertia frequency control model; and on the basis of the inertia power regulation and control amount, regulating and controlling the inertia power of the offshore wind farm energy storage system. By means of the present application, the level of refinement and accuracy of a regulation and control process for an energy storage system can be improved.

The invention relates to the technical field of ultrasonic riveting, in particular to a 224G high-speed wire harness assembling method and system based on ultrasonic riveting, and the method comprises the steps: carrying out the pretreatment of a high-speed wire harness raw material, and obtaining a pre-riveted wire harness; aligning the pre-riveted wire harness with a pre-constructed target connector to obtain a to-be-riveted wire harness; riveting the to-be-riveted wire harness by using the ultrasonic parameter value, the environment temperature value and the riveting time, and monitoring the to-be-riveted wire harness during riveting in real time based on the riveting monitoring instruction to obtain a compression deviation value and an energy absorption value; based on the compression deviation value and the energy absorption value, acquiring an updated ultrasonic frequency value by using a fuzzy control algorithm, and acquiring a pre-confirmed high-speed wire harness by using the updated ultrasonic frequency value; and performing quality detection on the pre-confirmed high-speed wire harness to obtain a target high-speed wire harness, and realizing the assembly of the high-speed wire harness based on the target high-speed wire harness. According to the invention, high-precision assembly of the high-speed wire harness can be realized by utilizing ultrasonic riveting.

The invention relates to the technical field of digital health, in particular to a personalized rehabilitation exercise method for rheumatoid arthritis patients based on a BCW theory, which comprises the following steps: acquiring joint angle change and calculating a pain delay response coefficient, detecting fluctuation of supporting force and stabilizing force to obtain a joint load tolerance value, analyzing respiratory coordination to generate a respiratory coordination index, and performing rehabilitation training on the respiratory coordination index. The method comprises the steps that a joint angle sensor and pain intensity data are analyzed, a BCW capacity factor weight value is generated in a weighted mode, a fuzzy control algorithm is input to conduct hierarchical mapping adjustment on action amplitude frequency and rest intervals, and exercise adaptability feedback data are generated through monitoring completion degree and pain feedback. The exercise intensity is dynamically adjusted in real time through a data model, a personalized rehabilitation scheme is automatically optimized, the problems that subjective feedback is relied on, and physiological changes cannot be responded in time are solved, more accurate exercise amount adjustment is provided, the situation that the joint burden is increased due to improper exercise intensity is avoided, and the rehabilitation process is effectively promoted.

The invention relates to the technical field of automobile manufacturing, in particular to a multi-focus dynamic regulation and control method for laser welding of a truck frame, which comprises the following steps of: S1, carrying out panoramic digitalization on a to-be-welded part of the truck frame through a three-dimensional laser scanner, and constructing a three-dimensional digital model; millisecond-level dynamic adjustment of the laser multi-focus number, spatial distribution and energy ratio is achieved through a programmable optical system and a fuzzy control algorithm, welding deviation is corrected in real time according to a multi-source sensor and a closed-loop feedback mechanism, and therefore it is guaranteed that the laser focus is accurately matched with the geometric characteristics of a welding seam and the real-time welding state; and the quality problems of abnormal temperature of a molten pool, geometric deviation of welding seams and the like are effectively avoided, the precision, stability and complex working condition adaptability of laser welding of the truck frame are remarkably improved, and meanwhile the manual intervention cost is reduced.

The invention discloses an integrated monitoring and sampling method and system for red-bed groundwater, and belongs to the technical field of groundwater monitoring, and the method comprises the steps: deploying and initializing a system, collecting water level and equipment state information, calculating initial water level monitoring reference parameters in combination with a water level monitoring logic model, and obtaining real-time water level data and anti-blocking water pump structure parameters; generating an intelligent water pumping control execution sequence through a fuzzy control algorithm and a fluid dynamic model; a large-flow well washing operation path is obtained through a dynamic pressure adjusting algorithm and a water quality standard judgment model by taking the well washing flow reference parameter as a constraint and combining data of a water quality sensor; obtaining a steady-state sampling execution scheme through a double-pump linkage control algorithm and a bubble suppression model on the basis of the well washing end point parameters in combination with a small-flow sampling pressure reference and pipeline characteristics; summarizing data and generating an integrated monitoring sampling report; according to the invention, intelligentization and standardization of red layer underground water monitoring sampling are realized, and monitoring efficiency and data accuracy are improved.

The invention provides a composite material machine tool machining precision real-time measurement and thermal deformation compensation control method and system, and relates to the technical field of composite material machining. Collecting data through a temperature sensor and a displacement sensor; establishing a multi-dimensional thermal deformation prediction model; measuring the position of the cutter in real time by adopting a laser interferometer; constructing a self-adaptive compensation controller, and generating a compensation instruction by adopting a fuzzy PID control algorithm; and sending the compensation instruction to a numerical control system to realize real-time compensation of the processing track. Closed-loop control over the machining precision of the composite machine tool is achieved, and the machining precision is improved.

The invention relates to the technical field of production management, and particularly discloses a bearing processing productivity optimization and production scheduling system, which comprises a process state sensing module, a dynamic bottleneck identification module, a self-adaptive buffer control module, a collaborative scheduling decision module and a productivity optimization execution module. Through cooperative work of the dynamic bottleneck identification module and the adaptive buffer control module, a static management mode of a traditional fixed buffer area is thoroughly changed. The system can sense the change of a production flow in real time, accurately identify a bottleneck, and dynamically adjust the target inventory level of a buffer area based on a fuzzy control algorithm, so that a buffer strategy can adaptively match a current production state. The problem that upstream and downstream processes wait for each other due to improper arrangement of a buffer area is solved, and passive blockage and material interruption between the processes are converted into active and flexible rhythm cooperation, so that systematic equipment waiting time is remarkably shortened, hidden capacity is released, and the equipment comprehensive utilization rate and output efficiency of a whole production line are improved.

The invention relates to the technical field of data processing, and discloses a hydropower station fish gathering system inlet flow field adaptability optimization method and system. The method comprises the following steps: grading target fishes according to swimming speed and body length, setting a flow velocity adaptation threshold value, monitoring a flow field through an acoustic Doppler current meter, fusing data by using a Kalman filtering algorithm, calculating a fish rheotaxis index, and carrying out matching analysis to evaluate the adaptability of the flow field, according to the evaluation result, the flow guide pier and the microbubble curtain are controlled to conduct multi-stage linkage regulation and control, and a fuzzy PID control algorithm is adopted to achieve self-adaptive flow field control with the fish hydrotaxis index as a feedback signal. The problem that flow field optimization lacks fish behavior response feedback and multi-device coordination control in the prior art is solved, and the biological adaptability and the regulation and control precision of the inlet flow field of the fish gathering system are improved.

According to the method, a fuzzy subset is set according to the required torque, the current SOC value and the difference value between the engine rotating speed and the motor rotating speed, and the torque of an ISG motor is dynamically adjusted through a fuzzy control algorithm. The fuzzy control adopts a fixed fuzzy rule, so that a Q table is established through a Q learning algorithm, the compensation torque of the ISG motor is obtained, the final output torque of the ISG motor is determined to be the sum of the output torque of the fuzzy controller and the compensation torque output by the Q learning algorithm, and the torque output by the ISG motor is determined. According to the method, the advantage of high response speed of the torque of the motor is utilized, the difference value between the required torque and the actual torque is effectively compensated, the rotating speed fluctuation of the engine caused by overlarge change of the torque of the engine is avoided, and the fuel economy and the driving operation stability are improved.

The invention belongs to the field of material cracking, and particularly relates to a microwave bipolar heating-based in-situ graded cracking method for a carbon fiber composite material, which comprises the following steps of: initializing a feeding speed, and combining a preset three-dimensional model of a to-be-cracked material with a graded inversion function space; a multi-stage cracking control sequence containing parameters such as the feeding rate, the preheating temperature and the dual-frequency microwave radiation power is obtained through inversion, wherein a hierarchical inversion function space comprises a hierarchical hierarchical cracking feedback control node chain constructed through an associated fuzzy control algorithm. And generating a control instruction based on the control sequence and the hierarchical linkage control model, monitoring the splitting efficiency and the energy consumption conversion efficiency in real time, and feeding back to the node chain to adjust the control sequence. The node chain construction relates to flow splitting, parameter node set establishment, correlation analysis, feedback factor construction and the like, and finally, through simulation training optimization, splitting efficiency maximization and energy consumption and pollution minimization are realized.

The invention relates to the technical field of heat exchangers, and discloses a control method and system for a spiral wound tube type heat exchanger based on the Internet of Things. The method comprises the following steps: acquiring flow velocity distribution data in a pipe in real time through a multi-point sensor to form a first data set, performing regional analysis to obtain a flow velocity deviation value, evaluating heat exchange abnormality, positioning an abnormal position, and generating an abnormal region distribution map; a dynamic parameter adjustment scheme is calculated in combination with a heat exchange efficiency target, a first adjustment instruction set is generated, a second flow rate data set is obtained after execution, and the matching degree is evaluated through a fuzzy control algorithm; if the preset standard is not met, a second adjusting instruction set is generated in combination with working condition requirements, and finally an operation state report is output. The method has the following effects that the flow velocity distribution in the spiral wound tube type heat exchanger is accurately controlled, the problems of local overheating and uneven heat exchange are effectively solved, the heat exchange efficiency is improved, the purpose of balancing energy consumption is achieved, and stable operation of the system is guaranteed.

The invention discloses a vacuum furnace hearth structure and a simulation optimization method, and relates to the technical field of vacuum furnace control. Pressure values of all cavities in different process stages are collected in real time through a distributed sensor array, a sliding window method is used for calculating pressure gradients, and abnormal points are recognized; based on the vacuum degree deviation sequence, a PID control algorithm is adopted to generate a target air exhaust rate, and the opening degree of a valve is adjusted through a servo motor to optimize the vacuum degree; the pressure difference between the chambers is optimized by combining a computational fluid mechanics model and a fuzzy control algorithm, the change trend of the pressure gradient is analyzed and predicted by using a time sequence, and the air exhaust rate of each chamber is dynamically distributed. The invention can effectively solve the technical problems that in the existing tandem multi-chamber vacuum furnace, the traditional air exhaust system is difficult to adapt to the dynamic requirements of the vacuum degree and the gas flow in different process stages of each chamber, and the process stability, the efficiency and the product quality are influenced due to poor regulation and control of the pressure gradient and the gas flow characteristic.

The invention relates to the technical field of motor control, and discloses a vector control application of a direct drive motor, which comprises the following steps: S1, collecting stator current, rotor speed and bus voltage signals of the motor, and carrying out filtering preprocessing on the collected signals; and S2, constructing a self-adaptive flux linkage observation model, estimating a stator flux linkage in real time based on stator current and bus voltage signals in combination with rotor rotating speed information, and correcting stator resistance and inductance parameters through a model reference self-adaptive algorithm. According to the method, the motor parameters are corrected in real time through the self-adaptive flux linkage observation model, parameter drift caused by factors such as temperature change and magnetic saturation is effectively counteracted, and the accuracy of flux linkage estimation is improved; the improved PI regulator realizes online self-tuning of control parameters through a fuzzy control algorithm, can quickly adapt to changes of dynamic characteristics of the motor, and shortens the regulation response time of flux linkage and torque; and the resistance of the system to external interferences such as load fluctuation, power supply voltage change and the like is enhanced.

The invention relates to a self-adaptive laryngeal mask intubation system and method based on anesthesia depth monitoring feedback. The method comprises the following steps: acquiring flow velocity data of gas in a laryngeal mask microfluid channel in real time and denoising to obtain smooth flow velocity data; detecting the deviation between each data point in the smooth flow velocity data and the target flow velocity in real time, and determining the data point of which the deviation is greater than a preset threshold value as an abnormal point; calculating the adjustment amount of the gas parameter according to the abnormal type of the abnormal point and a preset adjustment logic; generating an adjusted flow velocity control signal in combination with safety constraints; and then calculating a comprehensive trend index of the physiological data of the patient fused with the adjusted flow rate control signal, determining a drug delivery amount by adopting a fuzzy control algorithm, and adjusting the flow rate of the drug in the microfluid channel according to the drug delivery amount. By adopting the method, real-time deviation detection and dynamic adjustment can be performed in combination with the anesthesia depth in a complex physiological environment, and accurate mapping of the flow velocity value and the anesthesia depth state of a patient is ensured.

The invention discloses an electrostatic dust collector high-voltage power supply dynamic adjustment method based on fuzzy control, and the method comprises the steps: extracting the impedance change and dust concentration based on real-time operation parameters, judging the tripping risk through fuzzy reasoning, and adjusting the output voltage. And in combination with dust distribution characteristics, pulse parameters are optimized through a fuzzy control algorithm, and waveforms matched with particle motion are generated. Environment parameters are collected to construct a working condition model, and a control mode is switched after scene recognition. And predicting a load change trend, and calculating a millisecond-level response strategy. And fusing the dust removal efficiency and the energy consumption target, dynamically distributing weights, calculating a comprehensive control strategy, verifying a balance state, iteratively adjusting a weight coefficient, and realizing dynamic adjustment of the high-voltage power supply. According to the invention, the stability, the dust removal efficiency and the energy consumption balance of the high-voltage power supply are remarkably improved, and intelligent control of multi-objective optimization is realized.

The invention discloses a depth-controlling and distance-changing seeding device suitable for hills and mountains. The depth-controlling and distance-changing seeding device comprises a rack, three crank plow bodies, a distance-changing mechanism, a depth-controlling mechanism, a sensor, a controller and a plurality of functional systems. The variable pitch mechanism realizes dynamic adjustment of line spacing through a left-handed screw rod, a right-handed screw rod, a nut seat and a servo motor; the depth control mechanism adjusts the seeding depth through a sliding groove, a sliding rod and a servo motor. The inclination angle and humidity sensor collects environmental data, and the controller dynamically regulates and controls the line spacing and depth based on a fuzzy control algorithm in combination with crop type parameters. The device can adapt to complex terrains of hills and mountains, the seeding precision and efficiency are improved, and green agriculture requirements are met.

The invention discloses an intelligent control system and method for preventing a deep-cone thickener from pressing a rake, and the system comprises a multi-parameter real-time monitoring module which is used for collecting various sensor data in real time, and the various sensor data comprise torque, underflow concentration, material level height and mud layer pressure parameters; the control unit is used for receiving the various sensor data, performing comparative analysis on the various sensor data and a set threshold value by utilizing a fuzzy control algorithm or a neural network model algorithm, determining a current rake pressing risk grade, determining control parameters of the deep-cone thickener based on the current rake pressing risk grade, and outputting the control parameters of the deep-cone thickener. And the operation state of the deep-cone thickener is changed through the execution mechanism. According to the invention, real-time high-precision acquisition, analysis and intelligent judgment are carried out on the operation parameters of the deep-cone thickener, and corresponding measures are taken, so that the underflow concentration of the thickener is quickly and accurately regulated and controlled, and the risk of rake pressing is reduced.

The invention discloses a large-diameter steel pipe sectional type galvanizing speed cooperative control method and a production system, and relates to the technical field of steel pipe hot galvanizing process control. The method is used for solving the problems of uneven coating thickness and deformation risk control of multiple sections of steel pipes under the complex heat flow variable working condition. The method comprises the following steps: firstly, constructing a dynamic coupling model of zinc liquid flow-steel pipe deformation-coating phase change, identifying a high-voltage sensitive section and triggering a speed coordination mechanism; afterwards, in combination with a historical process and a real-time purging state, a multi-dimensional speed-purging cooperative control instruction is generated by utilizing a fuzzy control algorithm, and a segmented control baseline is formed; and then, based on a cross-section cooperative constraint model and a feed-forward-feedback double-loop control strategy, speed transition of adjacent sections is dynamically adjusted, and flow impact and stress concentration are inhibited. And finally, collecting online detection feedback data to perform reverse correction on the boundary condition and the control weight of the model, thereby realizing closed-loop optimization control, and improving the consistency of the plating layer and the robustness of the system.

The invention relates to the technical field of sewage treatment, in particular to a sewage treatment partition aeration control method based on LSTM feedforward prediction and feedback, which comprises the following steps: S1, collecting real-time key data of a sewage treatment tank, the real-time key data comprising a dissolved oxygen measured value, an ammonia nitrogen measured value, a mixed liquid suspended solid concentration measured value and a flow measured value; s2, acquiring historical key data, inputting the historical key data into the long-short-term memory neural network model, and outputting an aeration prediction amount required by aeration; s3, calculating a deviation value between a dissolved oxygen measured value and a dissolved oxygen set value and a change rate of the dissolved oxygen measured value, and carrying out primary adjustment on the aeration prediction quantity based on the deviation value, the change rate and a fuzzy control algorithm; calculating a correction parameter K according to the sludge concentration, and adjusting the aeration prediction amount again based on the correction parameter K to obtain a target aeration amount; s4, determining the number and the opening degree of air blowers based on the target aeration rate; and S5, determining the opening degree of the valve based on the target aeration rate. The energy consumption can be reduced, and the sewage treatment efficiency can be improved.

The invention discloses a device and a method for intelligently regulating and controlling liquid-liquid continuous separation of plant extracts, and belongs to the field of plant extract separation. The device comprises a mixing and concentrating device, a gravity type liquid-liquid separator and a data processing unit; the mixing and concentrating device is provided with a mixer, a film evaporator and a first near-infrared spectrometer; the gravity type liquid-liquid separator is provided with a plurality of flowmeters and a second near-infrared spectrometer; the method comprises the following steps: constructing a concentrated solution prediction model, monitoring parameters such as spectral data, temperature, stirring speed, flow and the like of the concentrated solution in real time, analyzing data through a data processing unit, optimizing a separation process by adopting a fuzzy PID control algorithm, regulating parameters such as interface height, temperature, stirring speed and the like in real time, and realizing accurate control on separation efficiency and separation effect. According to the invention, precise monitoring and regulation of liquid-liquid continuous separation of the plant extract are realized, and the separation efficiency and the separation effect are improved.

The invention relates to the field of air purification control, in particular to a mobile air purifier operation control method, system and equipment and a medium. The method comprises the following steps: acquiring environmental parameters through a multi-source sensor, generating a multi-dimensional operation parameter matrix by using a fuzzy control algorithm, planning an optimal moving path by using an improved AI algorithm according to spatial topology sensing data, and cooperatively adjusting related components through a PID controller. A night low-noise operation strategy, a specific algorithm calculation parameter, sleep stage identification, corresponding control and the like are provided, and a look-ahead control instruction set can be generated; the invention further comprises a corresponding operation control system, electronic equipment and a computer readable storage medium. The technical effects that the ambient air quality and the user state are accurately perceived, global coverage purification and multi-system parameter joint debugging of the air purifier are achieved, low-noise operation at night is achieved, the function is dynamically adjusted according to the sleep stage, and the air purification effect and the user use experience are improved are achieved.

The invention discloses a signal processing method and system of an aviation intelligent flow sensor. The method comprises the following steps: collecting real-time signal data and generating a flow characteristic data set; determining an initial measurement parameter based on a preset flow signal model; the real-time deviation between the initial parameter and the actual operation state is obtained, the initial parameter is subjected to self-adaptive optimization through a normalized weighted deviation correction formula, and an optimized measurement parameter is obtained; and performing dynamic intelligent processing on the sensor based on the optimized parameters, evaluating a measurement error variance and a precision fluctuation rate through working condition segmentation and a fuzzy control algorithm, and generating measurement stability information. According to the method, through non-dimensionalized deviation correction and dynamic working condition segmentation processing, the flow metering precision and the signal stability in the aviation complex environment are effectively improved.

This invention discloses a method for constant temperature and humidity control of a cigar cabinet based on a fuzzy control algorithm, comprising the following steps: setting a target temperature and humidity range; collecting environmental data of each layer through a distributed sensor array and comparing it with the target range to obtain the temperature and humidity deviation of each layer; inputting the deviation into a temperature and humidity decoupling control module and outputting a weight adjustment signal; inputting the weight adjustment signal into a fuzzy controller to construct a multi-objective fitness function, optimizing it with the WFPSO algorithm, and outputting hierarchical fuzzy controller parameters; inputting the hierarchical fuzzy controller parameters into a hierarchical temperature and humidity model to monitor the status of each layer in real time, and outputting a drive command when the limit is exceeded; inputting the drive command and hierarchical parameters into an actuator, adjusting it, and outputting new environmental data; and using a feedforward control module to adjust in advance when a door opening / closing disturbance warning is issued, dynamically adjusting the status of the affected space layer. This invention improves the temperature and humidity control accuracy and disturbance adaptability of the cigar cabinet through hierarchical optimization and feedforward intervention control mechanisms.

The invention discloses an anti-collision early warning system for remote control operation of engineering machinery, and relates to the technical field of anti-collision early warning. A laser radar, a millimeter wave radar and a binocular camera are deployed to form a 360-degree sensing network, and data are synchronized through a GPS timestamp; an improved YOLOv5 algorithm and a density adaptive DBSCAN algorithm are adopted to identify engineering machinery, personnel and obstacles and extract parameters; calculating a collision risk index based on trajectory prediction, and dividing mild, moderate and high risk levels; the early warning decision module adopts a fuzzy control algorithm to generate three-level early warning from visual prompt to automatic deceleration; a 5G and WiFi (Wireless Fidelity) double-link redundancy framework is constructed, and data transmission is guaranteed; developing a console and a tactile feedback handle, presenting risks and providing tactile prompts. According to the method, blind areas are eliminated through source sensing fusion, and targets are accurately recognized; false alarm and missing alarm are reduced through dynamic risk assessment; the safety is improved through three-level early warning and automatic intervention; operation experience is optimized through tactile feedback, and scene adaptability is enhanced through self-learning.

The invention discloses an outdoor heavy-load AGV navigation control system and a control method thereof, and aims to solve the problems of low navigation precision and poor control stability of an existing outdoor heavy-load AGV in a complex environment. The system comprises a hardware system and a control method. The hardware system comprises a navigation box, a domain controller, a sensor assembly, an execution and interface assembly, a power supply assembly, a communication assembly, a man-machine interaction and monitoring assembly and an electrical control assembly; the control method comprises the following steps: 1) the environment sensing module based on multi-sensor fusion adopts a Kalman filtering algorithm to construct a high-precision map and detect obstacles; the path planning module is used for generating and optimizing a safe path in real time in combination with an improved A * algorithm; 3) the motion control module integrates a PID control algorithm and a fuzzy control algorithm to realize accurate tracking; 4) the system monitoring module monitors the state of the AGV in real time; and the navigation precision, the operation stability and the safety of the outdoor heavy-load AGV in a complex dynamic environment are remarkably improved.

This invention relates to the field of intelligent commerce technology, and more particularly to an electromagnetic linkage-based vehicle cruise control system based on adaptive fuzzy control. The system includes: a control switch for receiving input commands from the driver, including commands to activate / deactivate cruise control, accelerate / decelerate, cancel, and resume cruise control; a central controller connected to both a vehicle speed sensor and the control switch, the central controller incorporating an adaptive fuzzy control algorithm to generate throttle control commands based on the deviation between the current vehicle speed and a set speed; a servo actuator electrically connected to the central controller; and a motor that receives commands from the central controller to drive a synchronous belt. This invention achieves automatic and precise throttle adjustment and stable cruise control in motor vehicles, solving the problems of driver fatigue and poor driving comfort caused by the need for continuous manual throttle control during long-distance driving.