34 results about "Fuzzy subset" patented technology

The invention provides a hybrid model fault early warning method and system based on time sequence prediction and fuzzy logic, and the method comprises the steps: collecting operation and maintenance data of equipment in a continuous operation period, constructing an equipment state feature set, carrying out the feature correlation analysis of the equipment state feature set, generating an equipment state potential vector which reflects a dynamic coupling relation between parameters, and carrying out the fault early warning of a hybrid model. Calling a pre-trained fuzzy logic reasoning model to carry out fuzzy rule matching, and generating a fuzzy state set containing a multi-dimensional fuzzy subset; performing space-time correlation processing on the fuzzy state set to generate a multi-dimensional decision cloud picture, and performing spatial reconstruction on the multi-dimensional decision cloud picture through a quantization weight distribution mechanism to obtain an optimized decision matrix; and generating a fault early warning signal containing a fault early warning level and fault position positioning information based on the confidence distribution characteristics corresponding to the fault types. According to the invention, the accuracy and timeliness of fault early warning can be improved, and reliable decision support is provided for equipment operation and maintenance management.

The invention provides a pump station water level dynamic boundary adjusting method based on a fuzzy firefly algorithm, which comprises the following steps of: presetting a target water level in an intelligent water level monitoring system, calculating water level deviation and a water level change rate, and determining a sensitive parameter; presetting a linguistic variable of a fuzzy variable to obtain a fuzzy subset about a high-sensitivity parameter, a fuzzy subset about a low-sensitivity parameter, a fuzzy subset about a dynamic boundary adjustment value and a fuzzy subset about a flow adjustment value; determining a corresponding triangular membership function according to the input variables and the output variables of the different sensitive parameters; setting a fuzzy rule, and calculating the membership degree of each input variable; determining the fuzzy quantity output of the dynamic boundary adjustment value according to the fuzzy rule activation condition and the membership function value; and performing precision on fuzzy quantity output of the dynamic boundary adjustment value by adopting a gravity center method to obtain an accurate dynamic boundary adjustment value. According to the invention, the pump station can be controlled more accurately under various dynamic hydrological conditions.

The invention relates to the technical field of power distribution and utilization, and provides a community-level electric vehicle-household energy storage collaborative scheduling method and system. The method comprises the following steps: dividing real-time electricity price, battery SOC and external temperature into a plurality of fuzzy subsets, and determining a membership function of each fuzzy subset based on a TSK fuzzy mathematical model; introducing a price sensitivity parameter, a battery state parameter and a temperature sensitivity parameter, formulating a fuzzy rule of each fuzzy subset in three dimensions, and quantitatively evaluating the response willingness of the electric vehicle through fuzzy reasoning of all membership functions; an SAC algorithm is adopted, a state space and an action space are respectively designed according to the community environment, and an overall reward function is constructed by combining power grid benefit rewards, user comfort rewards and electric vehicle demand response rewards; and inputting a quantitative evaluation result into an SAC algorithm to obtain an optimal scheduling strategy of the energy storage resources. According to the invention, collaborative scheduling optimization of the electric vehicle cluster and the household energy storage device is realized.

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 provides an offshore wind power and marine ranch fusion development suitability evaluation method and system, and the method comprises the following steps: obtaining an evaluation index system which comprises a target layer structure, a criterion layer structure and an index layer structure; determining a target weight of each evaluation index in the evaluation index system, wherein a judgment matrix is constructed to calculate the target weight; performing fuzzy comprehensive evaluation on the target weight to obtain a fuzzy subset, and performing comprehensive evaluation index calculation based on the fuzzy subset to obtain a calculation result; and matching a preset grading table based on the calculation result to obtain a suitability evaluation result, and outputting the evaluation result. According to the method and the system for evaluating the suitability of the fusion development of the offshore wind power and the marine ranch, the suitability and the subsequent development direction of the fusion development of the offshore wind power and the marine ranch can be accurately known, and the blank of a current method for researching the suitability of the fusion development of the offshore wind power and the marine ranch is filled.

The invention belongs to the technical field, and discloses a control method and device for a high-speed motor and electromagnetic bearing system, and the method comprises the following steps: selecting an input variable and an output variable of a fuzzy controller; fuzzifying the input variable and the output variable, and determining a quantization factor, a basic discourse domain and a fuzzy discourse domain; defining a fuzzy subset and a membership function in the fuzzy domain of the input variable and the output variable; the membership degree is calculated through a membership degree function; substituting the membership degree into a fuzzy value formula to obtain a fuzzy value of the output variable, and performing defuzzification to obtain an accurate control quantity of the output variable; and outputting the precise control quantity of the output variable to an electromagnetic bearing model for control. The method provided by the invention can effectively reduce the oscillation and oscillation phenomenon of the system, improves the stability of the whole system, and can adapt to the situation of large disturbance or complex environment.

The application provides a kind of hybrid model fault early warning method and system based on timing prediction and fuzzy logic, device state feature set is constructed by collecting the operation and maintenance data of equipment in continuous operation cycle, feature correlation analysis is carried out on device state feature set, device state potential vector reflecting the dynamic coupling relationship between parameters is generated, fuzzy rule matching is carried out by calling pre-trained fuzzy logic inference model, and fuzzy state set containing multi-dimensional fuzzy subset is generated;Fuzzy state set is processed by space-time correlation, and multi-dimensional decision cloud chart is generated, which is reconstructed in space by quantization weight distribution mechanism, and the optimized decision matrix is obtained;Based on the confidence distribution characteristics corresponding to each fault type, the fault early warning signal containing fault early warning level and fault location positioning information is generated.The application can improve the accuracy and timeliness of fault early warning, and provides reliable decision support for equipment operation and maintenance management.

The application discloses a control method for switching of an excitation power supply of a superconducting phase modifier. The method includes sampling actual current and reference current of an excitation winding of the superconducting phase modifier, obtaining a current error through difference, determining an output mode through a fuzzy controller, and switching a circuit. The fuzzy controller includes a fuzzy data set and a fuzzy rule set. The fuzzy data set includes a plurality of range intervals, and a partially overlapping interval is arranged between adjacent range intervals. The union of each fuzzy subset is a maximum error limit of the current error. The fuzzy rule set includes a plurality of judgment rules. The judgment rules determine the output mode according to whether the value of the current error falls within the detection value of the corresponding range interval. Through the "soft" decision of the fuzzy logic, the mode is prevented from being frequently switched due to small error fluctuations, the switching loss of the power device is significantly reduced, and the system reliability and service life are improved.

The application belongs to the technical field and discloses a control method and equipment of a high-speed motor and an electromagnetic bearing system, the method comprising the following steps: selecting input variables and output variables of a fuzzy controller; fuzzifying the input variables and the output variables, determining a quantization factor, a basic domain and a fuzzy domain; defining fuzzy subsets and membership functions in the fuzzy domain of the input variables and the output variables; calculating the membership degrees through the membership functions; substituting the membership degrees into a fuzzy value formula to obtain fuzzy values of the output variables, obtaining accurate control amounts of the output variables through defuzzification; and outputting the accurate control amounts of the output variables to an electromagnetic bearing model for control. The method can effectively reduce the oscillation and vibration of the system, improve the stability of the overall system, and adapt to large disturbances or complex environments.

This invention provides a method and system for controlling construction waste crushing based on load feedback. The method includes: acquiring the stator current signal of the crusher's main shaft motor; extracting the active current component representing torque; constructing a time sliding window sequence; calculating the algebraic difference between the current active current component and a preset target value to obtain the original load deviation; constructing a weighted function to correct the load deviation amplitude; obtaining the load change rate by taking the first derivative with respect to time; building a fuzzy logic controller, using a Gaussian membership function in the fuzzification stage to establish a mapping between sample entropy and the width of the Gaussian distribution, and setting the membership function width in real time; adjusting the fuzzy subset of PID parameters according to fuzzy rules; using the peak-to-mean ratio of the sliding window sequence as an impact factor to weight and correct the centroid method defuzzification results; superimposing the adjustment increment onto the PID reference parameters; and combining the corrected load deviation to calculate the control command and adjust the output frequency of the feed motor inverter. This invention enables multi-dimensional adjustment of the crusher.

The present invention discloses a fuzzy control method for insulin dosage integrating emotional and motion information, belonging to the technical field of diabetes insulin treatment, which comprises the following steps: S1, estimating the emotional state and exercise intensity; S2, calculating the current insulin dosage; S3, determining the structure of the fuzzy controller, defining the input-output fuzzy distribution with the emotional state and exercise intensity information as inputs and the insulin dosage adjustment step as the output, and calculating the membership degrees of the inputs with respect to different fuzzy subsets; S4, establishing fuzzy rules; S5, performing fuzzy logic reasoning to obtain the output of the fuzzy system, and multiplying the output by the insulin dosage obtained in step S2 to determine the final insulin dosage. By adopting the above-mentioned fuzzy control method for insulin dosage integrating emotional and motion information, the present invention can achieve a more personalized and dynamic insulin administration strategy, make a more reasonable decision on the insulin dosage, and improve the blood glucose management effect of patients.

The invention discloses a sludge incineration ash bin discharging system and a control method, and belongs to the field of sludge incineration equipment. The discharging system comprises a bin body, a weighing device, a pneumatic gate valve, a variable-frequency discharger, an expansion joint and a PLC; the control method comprises the following steps: S1, setting sampling periods and the ideal unloading amount of each sampling period, and starting unloading according to the upper limit value of the unloading frequency; s2, constructing an input fuzzy membership function and an associated fuzzy rule base, and defining input variables of the input fuzzy membership function and the associated fuzzy rule base; constructing an associated output fuzzy subset; s3, in each sampling period, whether the current discharging frequency needs to be corrected or not is judged again; and S4, when correction is needed, the corrected discharging frequency is obtained through a fuzzy algorithm, and discharging operation is executed according to the frequency. And S5, when the discharging amount reaches the standard, discharging is stopped. According to the method, the mathematical modeling difficulty and the control complexity can be reduced, and flying dust is inhibited while the unloading uniformity and stability are guaranteed.

The embodiment of the invention provides a fuzzy model prediction active equalization method and an equalization circuit, and relates to the technical field of power batteries. The active equalization method comprises the following steps: acquiring an SOC mean value and an SOC difference value as input values of a controller; obtaining a difference value between the reference current and the equalizing current as an equalizing error; taking the weight ratio of the equalization error to the equalization current as an output value; according to a membership function, establishing a relationship between the input value and the output value and the fuzzy discourse domain and the fuzzy subset; determining a fuzzy control rule table according to the input value and the fuzzy subset; obtaining a membership degree of an output value corresponding to the input value according to a fuzzy control rule table; performing defuzzification operation on the membership degree to obtain an actual current weight; constructing a weight matrix according to each current weight; and constructing a state equation and a cost function, and according to the weight matrix, determining an equalization current and performing active equalization. The equalization current is determined through model prediction, the equalization current value changes along with the equalization state, and the equalization efficiency is improved.

The invention relates to the field of quadruped robots, in particular to a fuzzy control-based quadruped robot joint motor parameter adaptive adjustment method. Comprising the following steps: S1, calculating a current error and an error change rate according to a current reference instruction and a feedback current; s2, dividing the current error and the error change rate into a minimum value, a small value, a medium value and a large value, performing fuzzification through a triangular membership function, forming a fuzzy set, and calculating the membership of the fuzzy set; s3, according to a fuzzy rule, obtaining fuzzy subsets and membership degrees of the proportionality coefficient and the integral coefficient; and S4, clear values of the proportionality coefficient and the integral coefficient are obtained through an inverse triangle membership function, and the clear values are transmitted to a current loop proportional-integral parameter. The control precision can be improved, the adaptability is enhanced, the electromagnetic noise influence is reduced, and the parameter adjusting process is simplified.

The embodiment of the invention provides a self-adaptive cruise control method and system and a vehicle, and the method comprises the steps: determining a workshop time interval value and a collision risk degree value of two workshops according to a driving state; according to the two values, determining a target fuzzy subset corresponding to the workshop time interval value in the workshop time interval fuzzy set and a target fuzzy subset corresponding to the risk degree value in the risk degree fuzzy set; according to a fuzzy rule, determining a first fuzzy subset corresponding to the target fuzzy subset in a first fuzzy set of a first correction variable, the first correction variable being a correction variable corresponding to the first index weight; performing defuzzification on the first fuzzy subset to obtain a corresponding target value; correcting the first index weight through the target value to obtain a first corrected index weight; and performing adaptive cruise control based on the first correction index weight. The adaptive cruise control method aims at improving the adaptability of adaptive cruise control so as to improve the comfort and reliability of driving.

The embodiment of the application provides a kind of adaptive cruise control method, system and vehicle, method includes: according to driving state, the risk degree value of the time interval between two vehicles and the risk degree value of collision are determined;According to the two values, the target fuzzy subset corresponding to the time interval between vehicles in the fuzzy set of time interval between vehicles and the target fuzzy subset corresponding to the risk degree value in the risk degree fuzzy set are determined;According to fuzzy rule, the first fuzzy subset corresponding to the target fuzzy subset in the first fuzzy set of first correction variable is determined, and the first correction variable is the correction variable corresponding to the first index weight;By defuzzification to first fuzzy subset, the corresponding target value is obtained;The first index weight is corrected by target value, and the first correction index weight is obtained;Adaptive cruise control is carried out based on the first correction index weight. It aims to improve the adaptability of adaptive cruise control, to improve the comfort and reliability of driving.

The present invention discloses a servo hydraulic clamping control method and system based on fuzzy backward time domain control; the present invention relates to the field of numerical control electromechanical technology. A fuzzy controller receives the control axis variable X(t) transmitted by the CNC control system at the current time step t; a membership function is used to convert the control axis variable X(t)' into a fuzzy variable. The membership of the displacement error e1 and the displacement error change rate e2 is calculated; the fuzzy set of the displacement error e1 and the displacement error change rate e2 is divided into three fuzzy subsets: negative N, zero Z and positive P; the present invention introduces a fuzzy controller, and utilizes the membership function and the fuzzy rule base to achieve accurate modeling and intelligent control of the state of the hydraulic clamping mechanism. Fuzzy control effectively overcomes the limitations of traditional control methods by fuzzifying precise input parameters, performing reasoning using fuzzy logic, and then defuzzifying to obtain precise control signals.

This invention provides a torque control method, system, medium, and device for hybrid electric vehicles, comprising: creating a fuzzy control toolbox, taking the total vehicle torque, battery SOC value, and motor speed as inputs, and engine output torque as output; setting fuzzy subsets for the total vehicle torque, battery SOC value, motor speed, and engine output torque, and constructing membership functions; establishing fuzzy rules for the total vehicle torque, battery SOC value, motor speed, and engine output torque; constructing a fuzzy rule library, performing fuzzy inference based on the membership functions, fuzzy inference algorithm, and fuzzy rule library to obtain fuzzy quantities; converting the fuzzy quantities into clear values ​​through a defuzzification algorithm; and calculating the motor output torque based on the clear values. This invention dynamically adjusts the torque distribution rules according to the relationship between motor speed and efficiency. At high speeds, the motor output torque is reduced, and at low speeds, the torque is increased, ensuring that the motor always operates within its high-efficiency range.

The present invention provides a pressure data processing method, device, equipment and storage medium, including: obtaining real-time pressure data obtained by real-time pressure detection of a variable stiffness load of a motor; comparing the real-time pressure data with preset target pressure data to obtain pressure comparison data, the pressure comparison data including pressure deviation and pressure deviation change rate; performing fuzzy control decision on the pressure comparison data according to preset fuzzy control rules to obtain a fuzzy subset, wherein the fuzzy control rule includes a correspondence between different pressure ranges and different load stiffness ranges; performing defuzzification processing on the fuzzy subset using a set defuzzification algorithm to obtain a pressure control quantity, so as to perform closed-loop control of the output pressure of the motor according to the pressure control quantity. The technical solution of the present invention can obtain a better motor control effect under variable stiffness load conditions.

The invention belongs to the technical field of hard disk tuning, and particularly relates to an HDD hard disk automatic tuning method based on a fuzzy algorithm, which comprises the following steps of: mapping core parameters into low, medium and high fuzzy subsets by monitoring and preprocessing multi-dimensional operation data such as I / O load, disk rotating speed, temperature and the like of an HDD hard disk in real time; a load type-tuning parameter fuzzy rule base is called, a tuning parameter fuzzy output set is generated through Mamdani fuzzy reasoning, a gravity center method is adopted for defuzzification, and specific tuning decisions such as the pre-reading size and the I / O scheduler type are obtained and automatically executed. And meanwhile, wear state parameters such as redistributed sector counting are collected in real time, and after fuzzy risk assessment, parameters of the medium / high wear risk hard disk are dynamically corrected and optimized. The limitation of traditional fixed threshold adjustment and optimization is broken through, self-adaptive matching of a load scene is achieved, the performance and the service life of the hard disk are balanced, whole-process automatic execution is achieved, and adjustment and optimization accuracy and stability are improved.

This invention provides a method and system for controlling construction waste crushing based on load feedback. The method includes: acquiring the stator current signal of the crusher's main shaft motor; extracting the active current component representing torque; constructing a time sliding window sequence; calculating the algebraic difference between the current active current component and a preset target value to obtain the original load deviation; constructing a weighted function to correct the load deviation amplitude; obtaining the load change rate by taking the first derivative with respect to time; building a fuzzy logic controller, using a Gaussian membership function in the fuzzification stage to establish a mapping between sample entropy and the width of the Gaussian distribution, and setting the membership function width in real time; adjusting the fuzzy subset of PID parameters according to fuzzy rules; using the peak-to-mean ratio of the sliding window sequence as an impact factor to weight and correct the centroid method defuzzification results; superimposing the adjustment increment onto the PID reference parameters; and combining the corrected load deviation to calculate the control command and adjust the output frequency of the feed motor inverter. This invention enables multi-dimensional adjustment of the crusher.

The present invention relates to a method for allocating weights of human-machine collaboration based on a double-layer fuzzy strategy, and belongs to the field of human-machine collaboration technology. A fuzzy interactive system is constructed, and the fuzzy interactive system includes two layers, the first layer includes a conflict situation fuzzy decision maker, a human-machine level fuzzy decision maker, and a motion risk fuzzy decision maker; the second layer is a weight output fuzzy decision maker; human-machine data is obtained, and the human-machine data is fuzzified and converted into a fuzzy subset of a language variable as a state quantity input into the fuzzy interactive system; the fuzzy interactive system outputs a human-machine collaborative control weight allocation coefficient. By adopting a two-layer fuzzy controller, various influencing factors are fully considered, and the whole process of weight output is made interpretable, which is conducive to mutual trust between humans and machines in collaborative tasks. The fuzzy interactive system is trained by reinforcement learning, which reduces the problems caused by empirical design in traditional methods and can effectively solve the problem of human-machine collaborative weight allocation in different scenarios.

The application provides a new energy station oscillation suppression method and system, comprising: when an oscillation component is greater than an oscillation component threshold, determining a wind turbine generator set grid-connected electrical distance fuzzy subset and a wind turbine generator set operating power relative value fuzzy subset based on acquired parameter information; adopting a fuzzy logic strategy to determine a power instruction distribution coefficient based on the wind turbine generator set grid-connected electrical distance fuzzy subset and the operating power relative value fuzzy subset; and lowering the wind turbine generator set operating power based on the power instruction distribution coefficient. The application adopts a fuzzy logic strategy to determine a power instruction distribution coefficient based on a wind turbine generator set grid-connected electrical distance fuzzy subset and an operating power relative value fuzzy subset, and lowers the wind turbine generator set operating power, thereby minimizing the amount of abandoned wind and light, and improving the safety and stability margin of a new energy grid-connected system.

The present application relates to the field of quadruped robot, in particular to a kind of quadruped robot joint motor parameter self-adaptive adjustment method based on fuzzy control.The present application includes the following steps:S1: current error and error rate of change are calculated according to current reference instruction and feedback current;S2: current error and error rate of change are divided into minimum, small, medium and large, fuzzy by triangular membership function and form fuzzy set, and the membership of fuzzy set is calculated;S3: according to fuzzy rule, obtain proportional coefficient and integral coefficient fuzzy subset and membership;S4: by inverse triangular membership function, clear value of proportional coefficient and integral coefficient is obtained, and clear value is transmitted to current loop proportional integral parameter.The present application can improve control accuracy, enhance adaptability, reduce electromagnetic noise influence and simplify parameter adjustment process.

The invention relates to a parking space identification method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining environment information collected by a plurality of sensors, and carrying out the data fusion of the environment information collected by the plurality of sensors, and obtaining a plurality of environment parameters; fuzzy processing is carried out on the depth of the to-be-recognized parking space, the width of the to-be-recognized parking space, the first obstacle attitude angle and the second obstacle attitude angle, and fuzzy subsets corresponding to the depth of the to-be-recognized parking space, the width of the to-be-recognized parking space, the first obstacle attitude angle and the second obstacle attitude angle are obtained; matching a target fuzzy rule satisfying fuzzy subsets corresponding to the depth of the to-be-identified parking space, the width of the to-be-identified parking space, the first obstacle attitude angle and the second obstacle attitude angle from a preset fuzzy rule base; and determining the parking space type of the to-be-identified parking space according to the target fuzzy rule. Therefore, the accuracy of parking space identification can be improved, and even narrow parking spaces can be accurately identified, so that the utilization rate of the parking spaces is improved.

The invention discloses an adjusting method of a flow adjusting valve for a Christmas tree. The adjusting method comprises the following steps that 110, the flow error value and the flow error change rate of the flow adjusting valve are collected; 120, the flow error value and the flow error change rate are input into a fuzzy PID controller, and the flow control quantity is output; the method specifically comprises the following steps: S121, defining fuzzy distribution of an input quantity and an output quantity; s122, establishing a fuzzy rule, and finding a corresponding fuzzy rule according to the fuzzy subset; s123, through defuzzification processing, the output fuzzy quantity is converted into a clear value; s124, through defuzzification processing, the output fuzzy quantity is converted into a clear value; and 130, the opening degree of the needle valve is adjusted through a driving motor according to the flow control quantity, and therefore the flow is controlled.

The invention relates to the technical field of laser gyroscopes, and discloses a laser gyroscope threshold processing method and system based on a fuzzy control theory, so as to improve efficiency and accuracy. The method comprises the following steps: controlling a rotary table to rotate 0.03 degree towards a gyro pulse reduction direction every time, sequentially obtaining a point set P of laser gyro static pulse output in a symmetrical starting and ending range, and fitting a standard straight line; the slope between every two adjacent elements in the set P is calculated, and a set Q of the slopes between two adjacent points is obtained; comparing whether the absolute value of the slope between any two adjacent points in the Q set and the absolute value of the difference between the slope and the standard slope meet a preset threshold judgment rule of the fuzzy subset where the corresponding test point is located or not, and then judging whether the test point is located in a nonlinear region or not; subtracting the minimum value from the maximum value of the sequence of the test points in all the non-linear regions and adding 1 to obtain the number w of the test points in the non-linear regions; calculating the threshold value H of the laser gyroscope as H = C * cosA * sin (w * 0.03 degrees); wherein A is the local latitude, and C is the earth rotation angular velocity.

The invention belongs to the technical field of underwater manifold risk early warning, and discloses an FDHHFLTS fuzzy evidence reasoning method for underwater manifold failure risk early warning. The method comprises the following steps: firstly, defining an underwater manifold failure risk early warning problem, then calculating to obtain a basic confidence coefficient through FDHHFLTS, and then carrying out fuzzy subset confidence coefficient redistribution through basic probability quality conversion and aggregation to obtain a final confidence coefficient so as to obtain the safety condition of each early warning target and realize underwater manifold failure risk early warning. Through the FDHHFLTS fuzzy evidence reasoning method, effective evaluation of the safety states of a plurality of early warning targets can be realized at the same time, and the analysis and early warning capabilities of the global risk of the underwater manifold system are improved. The theoretical framework and algorithm design of the method have flexibility and universality, and the method is suitable for failure risk early warning analysis in various complex environments, can also be popularized to other ocean engineering equipment or complex industrial systems, and has wide application prospects.

The invention provides a torque control method, system, medium and equipment for a hybrid electric vehicle, and the method comprises the steps: creating a fuzzy control tool box, taking the total torque of the whole vehicle, the SOC value of a battery and the rotating speed of a motor as input, and taking the output torque of an engine as output; setting fuzzy subsets for the total torque of the whole vehicle, the SOC value of the battery, the rotating speed of the motor and the output torque of the engine, and constructing a membership function; fuzzy rules of the total torque of the whole vehicle, the SOC value of the battery, the rotating speed of the motor and the output torque of the engine are established; constructing a fuzzy rule base, and performing fuzzy reasoning based on a membership function, a fuzzy reasoning algorithm and the fuzzy rule base to obtain a fuzzy quantity; converting the fuzzy quantity into a clear value through a defuzzification algorithm; a motor output torque is calculated based on the clearness value. The torque distribution rule is dynamically adjusted according to the relation between the rotating speed and the efficiency of the motor. The output torque of the motor is reduced at high rotating speed, and the torque is improved at low rotating speed to ensure that the motor is always in a high-efficiency interval.

The invention provides an information flow-based early warning signal generation method and equipment for a manufacturing industry chain. The method comprises the steps of obtaining an information data set to determine a target early warning index system comprising a plurality of target early warning indexes; determining an influence relationship among the plurality of target early warning indexes to construct a network analytic hierarchy structure model, and obtaining weight quantification information of each target early warning index through the network analytic hierarchy structure model; determining a fuzzy evaluation matrix of the target early warning index, obtaining a fuzzy subset based on the fuzzy evaluation matrix, obtaining a weight vector and the fuzzy subset corresponding to the target early warning index according to the weight quantization information, and obtaining a main factor evaluation matrix; according to the main factor evaluation matrix and a pre-configured first formula, determining an early warning grade of a manufacturing industry chain and a comprehensive risk score of a target early warning index located at a bottom layer, and generating a risk sequence according to the comprehensive risk score; and outputting early warning information, wherein the early warning information comprises an early warning level, a comprehensive risk score and a risk sequence.