274 results about "Fuzzy reasoning" patented technology

The invention discloses a method and a system for adjusting the internal environment of a mobile laboratory cabin, particularly relates to the technical field of environment control, and aims to solve the problem that the existing environment adjusting method adopts a fixed control target and cannot adapt to differentiated environment requirements in a multi-task scene of a mobile laboratory. The method comprises the following steps: acquiring a current task identifier of a mobile laboratory, identifying a corresponding experiment task execution stage, and dynamically generating an inter-parameter collaborative constraint relation matrix based on a fuzzy inference rule base; a regulation and control demand vector is generated by collecting a multi-dimensional environmental parameter measurement value and combining a pre-stored environmental parameter expected value; calculating a regulation and control conflict risk entropy value based on the matrix and the vector, and performing risk judgment; when the risk tolerance is exceeded, a roundabout regulation and control strategy is generated as an optimization guide parameter; finally, an environment control instruction is generated in a coordinated mode according to the optimized guiding parameters and sent to an executing mechanism; the dynamic adaptation of the environmental parameter regulation and control strategy and the experiment task is realized, and the precision and reliability of multi-parameter cooperative control are improved.

The invention relates to the technical field of robot health physical examination, and discloses a robot noninvasive health physical examination and monitoring platform. A health data acquisition module of the system integrates physiological parameters acquired by a multi-modal sensor to generate a standardized health data set; the physical sign load analysis module calculates parameter fluctuation difference to generate a physical sign load distribution state value; the physical examination parameter optimization module screens optimal physical examination parameters to generate an operation parameter set; the environment adaptability adjusting module generates an environment response physical examination scheme in combination with the environment and body position data; a health threshold value dynamic setting module adjusts an abnormal judgment threshold value to generate a grading early warning threshold value; the health trend prediction module generates a health risk prediction value through fuzzy reasoning; and the physical examination feedback control module adjusts operation parameters and scanning frequency to generate a self-adaptive regulation and control strategy. According to the platform, the accuracy and the intelligent level of health physical examination are improved, and the non-invasive health monitoring requirement of the user can be better met.

The invention discloses a mechanical arm control method and system based on fuzzy self-adaptive PID control, relates to the technical field of mechanical arm control, and solves the problem that mechanical arm control is insufficient in flexibility when facing different working conditions. According to the embodiment of the invention, the universe expansion and contraction factor is adjusted through the error, then the close linkage of the quantization factor and universe expansion and contraction is realized through the self-adaptive quantization factor calculation, the fuzzy reasoning technology is combined, the intelligent mapping from the error information to the PID parameter increment is realized, the real-time updating of the PID parameter and the control output calculation are realized, and the real-time updating of the PID parameter is realized. The flexibility and adaptability of the control system are improved; and then output is controlled through incremental PID, so that a complete control link from parameter increment to actuator driving is realized, a complete closed loop is formed by a cascade control architecture, functional modules are tightly coupled, parameters are coordinated, and the whole-process intelligence from error sensing to execution control is realized.

The invention relates to the technical field of electric energy quality management of an electric power system, and discloses an industrial power grid voltage fluctuation suppression method and system, and the method comprises the steps: firstly building a system-level voltage and current forward transmission model composed of a power unit, a filter circuit and power grid impedance which are cascaded; reversely constructing a feedforward controller based on a voltage and current forward transfer model, and generating a main compensation voltage instruction according to the power grid disturbance quantity detected in real time; state parameters of each power unit are obtained, a differential equation is constructed, and a comprehensive real-time health degree index is obtained through fuzzy reasoning; dynamically correcting an equivalent impedance parameter in the forward transfer model by using the index, and calculating a voltage distribution weight of each unit; and decomposing the total compensation voltage instruction into each unit modulation signal according to the weight. Through systematic modeling, intelligent state evaluation and dynamic fault-tolerant distribution, high-speed, accurate and high-reliability suppression of the voltage fluctuation of the industrial power grid is realized.

The invention provides a patient rehabilitation tracking system, a rehabilitation training regulation and control method based on active perception and environment self-adaption, equipment and a medium, and the method comprises the steps: determining a cooperative motion state of a nerve-muscle-bone system according to a multi-modal physiological data flow of rehabilitation training tracking of a target patient; performing intention-muscle force cooperative identification based on the cooperative motion state to obtain motion intention and muscle force contribution distribution of the target patient; determining a dynamic risk map of the target patient during rehabilitation training; variable universe fuzzy reasoning is carried out on the motion intention, the muscle force contribution distribution and the dynamic risk map, and then a rehabilitation adjustment instruction matched with the rehabilitation state of the target patient is obtained; the rehabilitation progress of the target patient is continuously tracked, and the rehabilitation training robot is controlled to execute self-adaptive power-assisted compensation according to the rehabilitation adjustment instruction. By means of the scheme, motion intention decoding and muscle force contribution analysis can be conducted on rehabilitation training of the patient, and rehabilitation training regulation and control are conducted in combination with the dynamic environment risk.

The invention relates to the technical field of power equipment, in particular to an intelligent circuit breaker electric operation mechanism integrating multi-parameter detection and an intelligent monitoring system.The intelligent circuit breaker electric operation mechanism comprises a basic mechanism unit, a detection unit, an intelligent control unit and a communication unit, and the basic mechanism unit comprises a double-layer sliding block compensation system and a transmission mechanism; the double-layer sliding block compensation system is composed of a first sliding block, a second sliding block and a spring set, and a thin film pressure sensor is integrated on the bottom face of the second sliding block. According to the intelligent circuit breaker electric operation mechanism integrated with multi-parameter detection and the intelligent monitoring system, the health state and fault assessment system achieves fault assessment through data receiving, feature fusion, health modeling and fuzzy reasoning, and the intelligent monitoring system comprises a remote monitoring platform. And data display, fault early warning, remote control and reference model optimization are supported, intelligent control and multi-dimensional state monitoring of the circuit breaker are realized, and the fault diagnosis accuracy and the reliability of a power system are improved.

The invention provides an argon flow and micro-positive pressure linkage control method for an electroslag furnace. The method comprises the steps that the oxygen content and micro-positive pressure signals in the furnace are collected; the future furnace condition is predicted through the deep belief network model; optimizing initial parameters of the fuzzy PID controller in an off-line manner by using a particle swarm algorithm; on the basis of the real-time signal and the prediction result, adaptively adjusting controller parameters on line; and finally, an argon flow and dust removal valve opening control instruction is output in a linkage mode. According to the method, future furnace conditions are predicted through the deep belief network model, the control advancement is realized, and the problem of large lag of the system is solved; offline parameter optimization is carried out on the fuzzy PID controller through a particle swarm algorithm, and excellent initial performance adapting to different working conditions is provided for the fuzzy PID controller; the parameters of the controller are adaptively adjusted through online fuzzy reasoning, so that the system has robustness for coping with a dynamic process; finally, accurate and stable linkage control of the oxygen content in the furnace and the micro-positive pressure is achieved through linkage calculation of the argon flow and a dust removal valve opening instruction.

The invention discloses an infant state recognition method and system based on traditional Chinese medicine five-tone monitoring analysis, and the method comprises the steps: synchronously collecting the crying sound, physiological signals and behavior videos of an infant, extracting the Mel-frequency cepstral coefficient of the audio, the heart rate variability, galvanic skin response and respiratory rate of the physiological signals, and the facial expression and limb movement features, and carrying out the recognition of the state of the infant through the Mel-frequency cepstral coefficient of the audio, the heart rate variability, galvanic skin response and respiratory rate. Performing structured integration by using a multi-modal feature fusion model; in combination with the five-tone theory of traditional Chinese medicine, a corresponding relation between audio features and five-organ states is established, and the robustness of five-tone and five-organ mapping is improved through fuzzy reasoning and a Bayesian mechanism; the system dynamically adjusts the weight coefficient of each mode, adapts to the individual and emotion historical trend, achieves more accurate emotion recognition and physiological evaluation, achieves cross-mode and multi-layer information fusion, improves the accuracy and interpretation ability of infant emotion and five-internal-organ state recognition, and provides a scientific basis for clinical evaluation and health management.

The invention relates to the technical field of charging switching control, in particular to a dynamic switching system for cooperative work of wireless charging and wired charging, which performs node modeling and edge weight propagation on multiple parameters such as magnetic field intensity, current fluctuation ratio, contact resistance and temperature threshold through a graph neural network. Structured expression and dynamic updating of a nonlinear coupling relation among parameters are achieved, abnormal feature aggregation and channel state characterization are more refined, fuzzy reasoning and weight adjustment are conducted on multiple variables such as power output, the heat growth rate, the voltage drop rate and the energy efficiency ratio through fuzzy logic control, the stability of a channel priority sequence is enhanced, and the stability of the channel priority sequence is improved. Through dynamic detection of power curve intersection points and transition section time sequence calculation, continuous power distribution is converted into a smooth function interval, instantaneous energy abrupt change during switching is reduced, closed-loop correction of multi-period signals is achieved, and the system keeps stable operation and energy efficiency output consistency under high-dimensional parameter disturbance.

The invention relates to the technical field of energy-saving control, and discloses a self-adaptive energy-saving control method and system for building heating and ventilation equipment based on digital twinning. The method comprises the steps of collecting temperature and humidity in a building, heating and ventilation equipment operation, external environment and personnel flow data, extracting energy consumption fluctuation characteristics and performing coupling analysis on the energy consumption fluctuation characteristics and equipment operation data. A distributed lag regression model is constructed in combination with external environment data, the environment influence weight and trend are calculated, and a high-dynamic region is identified through fuzzy reasoning. Energy consumption is predicted based on high-dynamic area data, a waste value is calculated, equipment operation parameters are optimized, and a target power sequence is generated through population iteration. An adjusting instruction is generated through analysis and deployed to a control system, thermal sensation feedback and instantaneous power data are collected, comfort evaluation is conducted, and the adjusting instruction is updated for optimization control. According to the method, dynamic balance of energy conservation and comfort can be realized.

The invention discloses a temperature control system and method based on an electronic cigarette, and belongs to the technical field of electronic cigarette temperature control, and the method comprises the steps: building a temperature difference mapping matrix through obtaining a heating body infrared radiation signal and a cigarette oil liquid level heat conductivity change parameter; establishing a liquid level-heating surface coupling dynamic model by taking the matrix as input, and extracting nonlinear temperature control characteristic factors; constructing a multi-dimensional state recognition vector based on the factors, and performing fuzzy reasoning in combination with a real-time flow signal of a user suction sensor to generate a dynamic target temperature control curve; a heating body voltage is driven through pulse width modulation, a thermal coupling state identification value is updated according to infrared change and an evaporation rate in a sucking process, a temperature control curve is dynamically corrected, and closed-loop self-adaptive temperature control is realized; according to the method, the temperature control precision and responsiveness can be improved, the smoking experience is improved, and the intelligent control level of the electronic cigarette is enhanced.

The invention relates to the technical field of electronic display, and discloses a liquid crystal display screen display control system based on multi-mode driving. The system comprises a content feature analysis module, a mode decision engine, a driving parameter library and a liquid crystal driving signal generation module. Multi-dimensional feature vectors are extracted through the content feature analysis module, a nonlinear decision mechanism combining fuzzy reasoning and hysteresis control is adopted, and single fixed threshold judgment in the prior art is thoroughly abandoned. The system can accurately capture dynamic characteristics of display content, effectively avoids the problem of mode oscillation in a threshold critical region, and realizes smooth and stable switching of driving modes. According to the invention, the hysteresis comparator and the continuous frame decision logic are introduced, so that the anti-interference capability and decision stability of the system are remarkably enhanced. The system does not trigger mode switching due to instantaneous noise or slight jitter of a single-frame image, so that the continuity of display experience is ensured, and extra power consumption caused by frequent switching is reduced.

The invention relates to the technical field of heavy-load robot control, in particular to a self-adaptive robust control method of a heavy-load robot fusing differential homeomorphic mapping. According to the method, position information of each joint is collected in real time and accurately compared with an expected trajectory, a ternary input vector is output, differential homeomorphic mapping parameters are updated in real time through a T-S fuzzy inference system, and a joint space state is mapped to a new coordinate space based on the optimized parameters, so that the position information of each joint is accurately compared with the expected trajectory. Neighbor joint information is obtained through distributed communication to generate a cooperative control item, a sliding mode surface is constructed in combination with a local tracking error to generate a robust control item, a compensation item is generated based on adaptive law estimation parameter uncertainty, three-item parallel control output is formed, dynamic weight distribution and fusion are performed on the three control items, a basic control moment is obtained, and the control precision is improved. And then a feed-forward compensation item based on a nominal dynamical model is superposed to generate a final comprehensive control torque, and the comprehensive control torque optimizes energy distribution while ensuring the performance.

The invention discloses a self-adaptive software test case generation optimization method, which comprises the following steps of: carrying out structured analysis on service requirements of a target system, extracting multi-dimensional test requirements of performance, resources, risks and coverage rates, and carrying out tagging and normalization processing to form a quantifiable index system; based on a meta-strategy layer decision engine, fusion reinforcement learning and fuzzy reasoning are carried out to realize multi-target weight distribution and dynamic compromise; generating and optimizing a preferred case set by means of a trade-off adaptive algorithm, performing conflict marking and constraint cooperative adjustment, collecting feedback data through automatic testing, correcting weight distribution and conflict detection rules according to actual results, and continuously iterating case generation strategies; the objective achievement degree is periodically evaluated, the strategy model is reconstructed or switched to adapt to scene changes, the accuracy of test requirement expression and the self-adaptability of the use case generation strategy are improved, and efficient collaborative optimization of multi-objective testing and dynamic adaptation of service scenes are achieved.

The invention discloses a district energy storage three-phase charging and discharging control method based on a fuzzy control strategy, and the method comprises the steps: obtaining the historical load data and related characteristic data of a district, determining an optimal parameter combination of a variational mode decomposition model based on the historical load data through employing a subwolf optimization algorithm, decomposing the historical load data through the combination, and obtaining a district energy storage three-phase charging and discharging control result. And obtaining a plurality of intrinsic mode components. And inputting the IMF components and the feature data into a constructed time convolutional network prediction model, and performing load prediction and reconstruction on each component to obtain a transformer area short-term load prediction value. A predicted operational dataset is obtained based on the predicted load. A double-layer fuzzy controller is constructed based on transformer area historical load data, energy storage charging and discharging power of each phase is obtained through a fuzzy reasoning method, and dynamic power balance and cooperative control of three phases of a transformer area energy storage system are achieved. According to the invention, load randomness, three-phase imbalance and energy storage regulation and control requirements of the transformer area can be effectively met, and the power quality and power supply reliability of the transformer area are improved.

The invention discloses a digital twinborn rehearsal method and system for tower crane collision risks, and relates to the technical field of collision risk analysis, and the method comprises the steps: firstly, generating a unified time mark snapshot through cloud-side double clocks and weight synchronization; secondly, caching snapshots in a layered manner according to survivability and re-collecting failure frames; fusing the time synchronization deviation and the spatial position deviation into a synchronization reliability coefficient through fuzzy reasoning; then driving a physical scheduling model to predict a trajectory based on the reliable coefficient, generating a safety envelope, monitoring a difference value and performing adaptive shrinkage, and adjusting a multi-tower operation window in combination with a time slot insertion algorithm; and finally, tampering prevention is carried out on the archiving key quantity through a fixed-length data packet and a Hash chain, the sampling step length is updated online by utilizing a sliding forgetting model and reinforcement learning, and the weight and the envelope flexibility are weighed. The method realizes second-level prediction, real-time scheduling and self-evolution, can reduce the multi-tower collision risk of the high-rise building, and gives consideration to the construction efficiency.

The invention relates to the technical field of vehicle control, and provides a vehicle chassis drive-by-wire method and device, electronic equipment and a readable storage medium. The method comprises the steps of obtaining current actual state data of a vehicle at a current moment and historical state data of a plurality of continuous historical moments before the current moment; jointly inputting the current actual state data and the historical state data into a pre-trained prediction model to obtain a state change prediction value of the vehicle at the future moment relative to the current moment; calculating a plurality of state error amounts between the state change prediction value and a preset expected state change amount; inputting the plurality of state error amounts into a preset fuzzy controller, and performing fuzzy reasoning based on a preset fuzzy rule base in the fuzzy controller to generate a fuzzy control signal; performing conversion processing on the fuzzy control signal to obtain a control instruction for the vehicle chassis drive-by-wire system; and controlling the action of the vehicle chassis drive-by-wire execution mechanism according to the control instruction.

The invention relates to the technical field of photovoltaic power generation system control, and provides an MPPT control method and system based on an adaptive fuzzy neural network, and the method comprises the steps: synchronously collecting voltage, current, illumination and temperature signals, and generating original sensing data; transmitting the generated original sensing data to a memory mapping area through a hardware channel; sensing data is obtained from the memory mapping area, calculation is executed, a power variation and an illumination variation are predicted, a fuzzy reasoning algorithm is operated based on the power variation and the illumination variation, and a power point decision scheme is obtained; a fuzzy rule is updated based on the predicted power variation and illumination variation, the updated fuzzy rule is fed back to the dual-core heterogeneous processor in real time, and fuzzy reasoning logic is optimized; and driving the four-phase interlaced power topological structure to work in an interlaced manner according to the power point decision scheme so as to realize maximum power point tracking. According to the invention, rapid tracking and high-precision stable control of the maximum power point of the photovoltaic array in a complex environment can be realized.

The invention relates to the technical field of hydrogen energy preparation and process control, and discloses a fuzzy PID (Proportion Integration Differentiation)-based pressure control method for an alkaline electrolytic water hydrogen production system, which comprises the following steps of: firstly, acquiring current, pressure and separator liquid level data of the system in real time, and calculating a source-load gradient synergistic factor for representing the hysteresis degree of source end disturbance and load end response according to the current, pressure and separator liquid level data; and then pump valve heterogeneous cooperative control is executed, the rotating speed of a circulating pump is actively adjusted through the factor so as to change the flow speed of electrolyte, and feed-forward regulation and control of the gas holdup are achieved. Meanwhile, a gas phase rigidity coefficient is solved according to liquid level changes, a virtual damping domain is constructed, and PID integral and differential parameters are corrected in a self-adaptive mode; and finally, asymmetric variable universe fuzzy reasoning is executed, a hydrogen side universe is compressed through a source load gradient, an oxygen side driven dead zone threshold value is dynamically set, and a double-side valve instruction is output. According to the method, the problems of pressure lag and rigidity time varying under wide power fluctuation are effectively solved through flow velocity auxiliary adjustment and rigidity self-adaption strategies, and efficient and stable operation of the system is achieved.

The invention discloses a meteorological early warning information fusion method and system based on a road network, and the method comprises the steps: obtaining the topology and meteorological characteristics of the road network, carrying out the clustering to form an aggregation unit, and setting a sharing threshold value; obtaining multi-source early warning data according to units and standardizing the data; a comprehensive result is obtained through duplicate removal, sorting and conflict resolution of a scheduling mechanism; a weather system movement parameter is extracted to calculate a differentiated early warning advance; determining a risk level and a confidence interval by combining real-time traffic state fuzzy reasoning; inquiring emergency resources and linking the traffic control system to push early warning; historical data closed-loop feedback optimization model parameters are collected; and applying the optimization model to realize road network meteorological early warning. According to the invention, the space-time accuracy and response efficiency of meteorological early warning are significantly improved, and the road network traffic risk in severe weather is reduced.

The invention discloses a multi-dimensional data fusion analysis method and system for fine chemical production, and belongs to the technical field of industrial process control, and the method comprises the steps: obtaining multi-source production data, and generating a unified time sequence data set through timestamp alignment and redundant data filtering; extracting multi-scale features and fusing the multi-scale features and the process knowledge parameters into a joint feature vector; calculating a production state score and grade through weighted fuzzy reasoning; predicting a deviation trend of the key parameters based on the score and historical optimal production data; actual sampling data are obtained, deviation comparison is carried out on the actual sampling data and the deviation trend data, and optimization calculation is triggered to generate optimization control parameters; the reaction condition is adjusted through the distributed actuator, and the new data is used for updating the unified time sequence data set. According to the method, state evaluation is carried out by fusing process knowledge and multi-scale features, and deviation trend prediction and closed-loop optimization control are carried out in combination with the state transition probability, so that predictability, stability and adaptive optimization capability of the production process can be improved.

The invention discloses a liquid cooling energy storage system thermal management optimization method based on thermal diffusion modeling. The method is used for solving the problems that thermal runaway risk assessment of a liquid cooling energy storage system is inaccurate and energy consumption and cost are difficult to balance. The method comprises the following steps: firstly, collecting battery temperature, spacing, charging and discharging current, SOC, SOH, environment temperature and cooling liquid flow velocity data, dynamically adjusting sampling frequency based on a temperature change rate, and obtaining a fusion vector through filtering fusion denoising; inputting the three-dimensional unsteady-state heat conduction model into COMSOL to construct a multi-physical-field coupling model, and obtaining an initial heat diffusion probability through a three-dimensional unsteady-state heat conduction equation; then optimizing the probability by using an adaptive neural fuzzy inference system; and finally, constructing a multi-objective function by taking the optimized probability as a constraint, and outputting an optimal cooling liquid flow rate and an optimal battery spacing parameter through iteration of an iDBO algorithm, so that the system safety, the energy consumption efficiency and the economical efficiency are improved.

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 relates to the technical field of sewage treatment, and discloses an environment-friendly aeration device and method for chemical sewage treatment. The device comprises a conveying module used for detecting chemical oxygen demand and sludge concentration and calculating target dissolved oxygen concentration and initial aeration control parameters; the driving module is used for calculating the aeration depth and driving the aeration bracket to lift and rotate to perform sweeping type aeration; the control module is used for processing the dissolved oxygen deviation and the deviation change rate through a fuzzy reasoning algorithm to obtain a controller parameter adjustment amount; the blowing module is used for updating controller parameters and adjusting the rotating speed of a blower to output total air supply; and the adjusting module is used for calculating a gas distribution coefficient and adjusting the opening degree of each branch pipe valve to distribute the total gas supply. The adaptive capacity of the aeration device to water quality fluctuation and the dissolved oxygen concentration control precision are improved, the energy consumption of the air blower is reduced, and the aeration uniformity of each area is improved.

The invention relates to the technical field of power load regulation and control, in particular to an electric vehicle charging and discharging load aggregation potential assessment method, system and device and a medium, and the method comprises the steps: obtaining a traffic network topology and a power distribution network topology, considering a travel demand in the traffic network topology, considering charging and discharging load distribution in the power distribution network topology, and calculating the aggregation potential of the charging and discharging load; identifying space-time distribution of charging and discharging loads of the electric vehicle; based on the time-space distribution of the charging and discharging load and the time-domain fluctuation of the bus load in the power distribution network topology, evaluating the influence of the bus load fluctuation on the power flow distribution; the method comprises the following steps: constructing an electric vehicle response quantity model based on time-space distribution of charge and discharge loads, obtaining an electric vehicle intraday response capability condition based on fuzzy reasoning, and evaluating the electric vehicle aggregation response potential based on an evaluation result of influence of bus load fluctuation on power flow distribution and the electric vehicle intraday response capability condition. The problem of insufficient regulation potential mining caused by insufficient consideration of the global influence of the local charging and discharging behavior in the existing evaluation technology is effectively solved.

The invention relates to the field of numerical control machining and computer-aided manufacturing software, and particularly discloses a honeycomb core six-axis ultrasonic cutting track digital control and interpolation optimization system which comprises a track preprocessing module, a parameterized spline interpolation module, a six-axis linkage inverse solution module, a dynamic feed-forward compensation module, an ultrasonic energy adaptive control module and a multi-source information fusion and decision module. By the adoption of the technical scheme, smooth and efficient interpolation of a track, dynamic feed-forward compensation of motion errors and self-adaptive adjustment of cutting energy can be achieved, and therefore the machining precision, the surface quality and the system stability are improved. According to the invention, ultrasonic energy control is originally incorporated into an overall trajectory control closed loop, and real-time accurate regulation and control of cutting energy are realized through the ultrasonic energy adaptive control module. The module is based on force, amplitude, temperature and other multi-sensor information, adopts fuzzy reasoning to intelligently decide output power, and ensures that cutting energy is constant and optimal under different processing conditions.

The invention relates to the technical field of molten salt conveying, and discloses a molten salt spherical tank heat storage and heat exchange gas pressure conveying regulation and control system and method.The method comprises the following steps that multi-source parameters are read in real time, the current pressure difference is calculated to be combined with the temperature to fit the real-time viscosity value, the pressure difference, the viscosity and the valve opening degree are used for dynamically updating the theoretical calculation value of viscosity time lag, and the viscosity time lag is calculated. Historical data of time lag, pressure difference and valve opening are stored, a time window sample is formed, a time lag change rule is learned through an LSTM network, model weight parameters are updated online, a current working condition sequence is input, and a predicted value of future time lag is output. According to the method, the influence of fluid transmission time lag on pressure control is reduced, valve actions are synchronized with actual requirements through dynamic prediction and a fuzzy compensation mechanism, overshoot or undershoot of pressure is avoided, the anti-interference capability and robustness are enhanced by combining an online learning prediction model and a fuzzy inference rule base, and the pressure control precision is improved. And a scheme integrating dynamic response quality and long-term stable operation is realized.

The invention discloses a pressure self-adaptive regulation and control system and method for a motor pump set, and particularly relates to the field of general control regulation and control, and the method comprises the steps: collecting multi-dimensional data step by step, synchronously collecting basic data such as a pressure time domain sequence, temperature, vibration and the like and derivative parameters, and carrying out the time sequence synchronization processing to form a unified data matrix; extracting multi-dimensional features, extracting dimensionless core features according to four dimensions such as pressure features, and constructing standardized feature vectors; multi-dimensional feature function construction: respectively constructing four types of functions including pressure characteristics and pump body states based on the features of each dimension, and quantifying the performance of each dimension; deep fusion and decision making are carried out, a comprehensive pressure control index is constructed through dynamic weight and kernel function mapping, a swash plate angle adjusting amount is generated in combination with fuzzy reasoning and converted into a control current, and a pump body is driven to adjust the displacement; meanwhile, a three-level quality judgment standard and an exception handling mechanism are established, and pressure control quality monitoring and fault early warning are achieved; the method improves the voltage control precision and stability, and guarantees the safety of equipment.

The invention relates to a multi-motor cooperative control method, system and device based on position and speed double feedback and a self-adaptive sliding mode and a medium, and relates to the technical field of multi-motor cooperative control. The multi-motor cooperative control method comprises the following steps: acquiring an actual position signal and an actual speed signal of each motor, and converting and calculating a position synchronization error and a speed synchronization error between the motors; calculating a position tracking error and a speed tracking error of each motor according to a preset reference position signal and a reference speed signal; fusing the weighted operation position synchronization error, the speed synchronization error, the position tracking error and the speed tracking error to construct a sliding mode surface function; iteratively optimizing the sliding mode surface function according to a preset fuzzy reasoning mechanism, outputting a self-adaptive adjustment amount, updating the original switching gain, and calculating a new switching gain; and calculating the final control quantity of each motor according to the new switching gain, the sliding mode surface function and the saturation constraint function, and outputting the final control quantity to a corresponding motor driver to drive the motor to move.

The invention relates to the technical field of electronic cigarette control, and particularly discloses an electronic cigarette self-adaptive precise temperature control system based on fuzzy PID control, which comprises a temperature acquisition module, a disturbance quantization module, a fuzzy reasoning module, a parameter self-adaptive PID control module and a power driving module. By quantizing the disturbance intensity and adjusting PID parameters in real time based on a fuzzy rule, the system can adaptively enhance the anti-interference capability and the steady-state precision. The system has quick response to sudden disturbance, control oscillation possibly caused by frequent parameter adjustment is avoided, optimal balance between response speed and control stability is achieved, and the system is particularly suitable for portable equipment such as electronic cigarettes with complex and changeable working conditions. According to the scheme, rapid, stable and overshoot-free accurate control over the atomization temperature is achieved, and the use experience and consistency of the electronic cigarette are improved.