416 results about "Fuzzy control algorithm" patented technology

The invention discloses a control method of a multiple connected air conditioning system. The control method comprises the following steps of: calculating a target temperature by using a fuzzy control algorithm according to operating parameters of an air conditioning system; converting an actual pressure measured by a pressure sensor into a saturated refrigerant temperature as an actual temperature and calculating a difference value of the actual temperature and the target temperature; and calculating and adjusting capacity output of a compressor, wind speed of an outdoor fan and openings of indoor and outdoor electronic expansion valves by using a proportion integration differentiation algorithm according to the difference value of the actual temperature and the target temperature, a change rate of the actual pressure and a change rate of the actual temperature and the target temperature so that the actual temperature and the target temperature are consistent. The invention also discloses the multiple connected air conditioning system. The air conditioning system has little wave property, stability, favorable refrigeration and heating effects and favorable energy saving effect.

The invention discloses a fuzzy-control-based internet of things intelligent irrigation and fertilization control method and system. The method comprises the first step of data collection and processing, wherein limiting values of the soil humidity, nutrients and pond water level and the irrigation and fertilization planning time are set and stored in a database according to the water demand regulation and a fertilization formula of crops, and collected soil temperature and humidity, soil nutrients, air temperature and humidity, air speed, rainfall, flow, pond water level and pipe network pressure data; the second step of intelligent control, wherein corresponding data are read from the database and an irrigation valve and a fertilization valve are intelligently controlled by the adoption of the fuzzy control algorithm and a water and fertilizer coupling mode, by comparing the current pond water level with the set limiting value of the pond water level, starting and stopping of a water pump are intelligently controlled, and the speed of the water pump is adjusted and controlled by a PID algorithm. The fuzzy-control-based internet of things intelligent irrigation and fertilization control method and system have the advantages of being good in performance, complete in function, high in expansibility, easy to operate and manage and the like, and intelligent management and control are achieved by the adoption of fuzzy control.

The invention relates to an initiative anticollision self-adapting fuzzy control method for a vehicle. The method comprises the following steps: measuring the relative speed of a self vehicle and a front vehicle and the speed of the self vehicle respectively by a radar speed measurement sensor and a hall vehicle speed sensor on the self vehicle; according to the situations of weather, road surfaces, vehicle types and loads and manual input information, obtaining the largest braking deceleration that the self vehicle and the front vehicle possibly achieve, and at the same time, according to a distance between the two vehicles, dividing the control behavior of the self vehicle into four grades; and comparing the actual distance D between the two vehicles, measured by a radar distance measurement sensor, with a safe vehicle following distance, a warning distance, a fuzzy control automatic brake distance and an emergency braking distance, and determining which section the actual distance between the vehicles falls into, so as to make a corresponding action. According to the method disclosed by the invention, a control system can be adjusted in a self-adapting manner without changing a fuzzy control rule list and a fuzzy control algorithm list, so that the control system can be adaptive to the changes of the situations of individual types of drivers, the weather, the road surfaces, the vehicle types, the loads and the like, and the stability, the reliability and the robustness of automatic brake are maintained.

The invention relates to an automatic control system during the combustion process of a hot air furnace of a blast furnace, belonging to the field of automatic combustion control technique of the hot air furnace of the blast furnace. Firstly, the system self-learns the historical combustion data of the furnace according to the specified conditions, and determines the best coal gas and air flux of the furnace and the best initial openness of an adjusting valve to be as the initial parameters of the next combustion period. During the normal combustion stage, a control method that fuzzy control is combined with self-optimization control is adopted, the fastest increment of the temperature at the arch is taken as the object, and the air combustion proportion coefficient is quickly optimized according to the temperature change of the combustion chamber. Simultaneously, by adopting a non-difference self-adaptive single closed ring control system combined with the methods such as fuzzy control, self-learning and pulse driving and the like, the action of the adjusting valve can be effectively controlled, and precise and quick adjustment and control of the flux are realized. According to the trend change of the temperature of the waste gas, the system adopts the fuzzy control arithmetic to control the combustion rhythm. Simultaneously, the system comprehensively summarizes the manual combustion experience and achieves the object of completely automatic control without man-watching during the whole combustion process.

Aiming at the defects in the prior art, the invention discloses a control method of a speed regulator of a servo system of a flat knitting machine. A system in the prior art has low adaptability and low stability. According to a fuzzy proportional-integral (PI) control algorithm of the control method, the running speed of a transmission mechanism of the computerized flat knitting machine is used as a control object; the difference value between the practical reference speed and the feedback speed and the change rate of the difference value are served as input of a fuzzy controller; the input quantity is fuzzified through selecting an appropriate universe of discourse and an appropriate membership function; appropriate fuzzy rule tables are set by utilizing the practical tuning strategies of PI parameters; and after a Mamdani fuzzy reasoning algorithm and defuzzification processing are adopted, the variable quantities of parameter values of the PI controller are output, thereby realizing on-line correction of the PI parameters. By adopting the control method, the disadvantages of a traditional manual correction method for the PI parameters are overcome, and on-line real time correction of the PI parameters is realized, thereby improving the adaptability and the stability of the system.

The invention discloses an automatic navigation control method of an agricultural machine. The method comprises the following steps of 1, measuring motion state data of the agricultural machine at current time in real time by a GPS receiver; 2, performing comparison and analysis on motion state data and predefined path data according to a preview control method, thereby calculating transverse deviation and operation direction deviation; 3, performing fuzzification through a fuzzy control algorithm, then introducing a fuzzy amount into a fuzzy controller, thereby obtaining a front-wheel rotation angle; establishing geometric model through an improved pure tracking algorithm, thereby calculating the front-wheel rotation angle; combining the front-wheel rotation angles which are obtained through the two algorithms for obtaining a combined front-wheel rotation angle; and 4, controlling the agricultural machine in real time according to the combined front-wheel rotation angle, thereby realizing path tracking. According to the automatic navigation control method of an agricultural machine, two navigation methods are combined for realizing automatic control, thereby realizing high stability, high interference resistance and effective system robustness improvement. Through combining the two navigation methods, the advantages of the two navigation methods are combined so that the automatic navigation control method satisfies operation requirement in dry land and paddy field.

The invention discloses a load feedback speed regulation device for a combined harvester and a control method in the field of agricultural machinery. The load feedback automatic control device comprises a controller and a sensing system, and is connected with a speed regulation executing mechanism with functions of automatic speed regulation and manual speed regulation; a motor driver is respectively connected with the controller and a motor; the controller is respectively connected with a liquid crystal display, a sound and light alarming system and the sensing system, and is formed by a single chip microcomputer and peripheral circuits thereof; the sensing system is formed by various sensors and a conditioning circuit thereof; and working state signals of the combined harvester are collected by the sensing system, and the working state signals enter the controller to carry out treatment such as a multi-signal fusion fuzzy control algorithm, a forecast control algorithm and the like,and a corresponding control strategy is selected to drive the executing mechanism to work. Therefore, the invention realizes the automatic control of work load of the combined harvester, displays a working state of a unit in real time, carries out sound and light alarm in time when the combined harvester meets faults, has simple and compact structure as well as flexible and overall functions, andis convenient to expand.

The automatic control method for steel ball coal mill in thermal power plant adopts a double-layer control structure, including an upper layer of self optimizing algorithm and a lower layer of multidimensional fuzzy control algorithm. The self optimizing algorithm finds out the optimal inside coal storage quantity inside the coal mill, the optimal outlet temperature of the coal mill and the optimal inlet negative pressure value of the coal mill as the controlling set values; and the multidimensional fuzzy control algorithm realizes the automatic regulation of the coal feed quantity, the hot air valve opening, and the recirculating air valve opening or the cold air valve opening, so as to ensure the safe and reliable running of the steel ball coal mill system in optimal mode.

The invention discloses a self-adapting charging method for a vehicle-mounted power battery. The method comprises the steps that when the battery is charged, a main control module calculates the state of charge (SOC) of the battery according to battery current, voltage and temperature information collected by a battery sensor module; a temperature variable quantity delta H and the SOC are input to a fuzzy controller in the main controller module, and the optimal charging current in the current state is output through a fuzzy control algorithm; A PID controller controls a PWM driver to produce a control signal with a proper duty ratio; a current regulation module dynamically regulates charging current according to the control signal, and therefore the purpose of self-adapting charging is achieved. In order to make the charging current quickly and accurately reach the optimum value, a fruit fly optimization algorithm (FOA) is adopted to dynamically regulate parameters of the PID controller. According to the self-adapting charging method, the charging current can be regulated in a self-adapting mode, the charging time of the battery can be effectively shortened, the charging efficiency of the battery can be effectively enhanced, and the service life of the battery can be effectively prolonged.

The invention discloses application of a fuzzy proportion integration differentiation (PID) algorithm in a fuel cell radiating system. The fuel cell radiating system comprises a water tank connected with a fuel cell, wherein the water tank is connected with a radiator and a radiator fan through a circulating water pump and a corresponding pipeline; a main controller acquires a data signal of the fuel cell through a sensor and transmits the data signal to a fan controller; and the fan controller controls the rotating speed of the radiator fan, and obtains a corresponding rotating speed of the radiator fan through the fuzzy PID algorithm to realize corresponding radiating capacity. The application of the fuzzy PID algorithm combines fuzzy control and PID control and has the advantages of flexible fuzzy control, strong adaptability and high control accuracy.

The invention discloses a permanent magnet synchronous motor control method based on a model reference adaptive system (MRAS) and fuzzy control. The rotor speed of a permanent magnet synchronous motor is estimated by using the MRAS, the problem caused by installation of a mechanical sensor is solved, the reliability of a control system is improved, and the cost of the control system is reduced. Meanwhile, when the permanent magnet synchronous motor rotates at low speed, a control effect based on a speed-sensorless vector control method is poor, and load capacity is low. The vector control method for the permanent magnet synchronous motor which rotates at the low speed is replaced by a fuzzy control algorithm, so a control algorithm for the permanent magnet synchronous motor which rotates at the low speed is simplified, and the control system quickly passes through a low-speed stage.

The invention discloses an intelligent drilling control system and a method for a petroleum drilling machine. The intelligent drilling control system comprises a drilling driving module, a drilling detection module and a drilling control module. The intelligent control method is a fuzzy control algorithm with a parameter self-adjusting capability; the fuzzy control algorithm consists of two control loops, wherein an inner loop is drilling speed control and the outer loop is drilling pressure control; each control loop comprises a fuzzy controller unit, a performance evaluating unit, a parameter correcting unit and a decision unit; and according to each loop, the intelligent control over the drilling pressure and the drilling speed of the petroleum drilling machine can be realized by self-adaptively adjusting the parameters of the fuzzy controller and improving the performance of the fuzzy controller. According to the intelligent drilling control system and the method disclosed by the invention, the labor intensity of workers in the drilling process of the petroleum drilling machine can be reduced, the track precision of a well hole of a drilling well can be improved, the wear to a drill bit is reduced and the drilling speed is increased.

The invention discloses an automatic thickness control system and method of a blown film. The automatic thickness control system of the blown film comprises a film thickness detection module, a film thickness control module, a film cooling and forming mold with a plurality of brushless direct-current motors as well as a control panel. According to the invention, an FPGA (field programmable gate array) control chip of a programmable logic device is utilized to achieve a fuzzy control algorithm so as to obtain the speed control quantity of the brushless direct-current motors; by combining a double-closed-ring control algorithm for the brushless direct-current motors a control signal output by the FPGA control chip is changed and adjusted correspondingly when the thickness of the film is changed; the thickness uniformity of the films at different circumferential parts can be controlled by acquiring horizontal thicknesses of the films at controlled subzones and the positions of air flue openings corresponding to the films via transmission and decoupling control, so that the control requirement on horizontal thickness uniformity of the films can be met; the automatic thickness control system and method of the blown film are high in integrity, small in volume, good in robust performance, stable and reliable in operation, high in expansibility, high in control precision, low in accumulative error, and high in adaptability.

The invention discloses a cooperative control method of a four-wheel independent-drive electric car based on CPS. The cooperative control method comprises an ECU, SR electromotor driving systems, a vehicle-mounted battery group and a communication network. Power of the four SR motor driving systems and the ECU are all supplied by the vehicle-mounted battery group. The ECU is communicated with four motor controllers via the communication network. The ECU serves a control network core and is used for collecting and analyzing information of all sub-controllers and all sensors and then sending an execution instruction to all the motor controllers which are used for controlling SR motors to output rotating speed and torque. In-loop feedback control of an overall car is achieved in a real-time manner. A driving torque distribution strategy adopts fuzzy control based on slip rate and yawing moment. Control of the SR motors adopts a self-adaptive fuzzy control algorithm. The cooperative control method of a four-wheel independent-drive electric car based on CPS has following advantages: energy utilizations rate is increased; manipulation stability is improved; and driving safety of the four-wheel independent-drive electric is enhanced.

The invention discloses a smart energy management device of a multi-energy power supply system. The smart energy management device of the multi-energy power supply system comprises a photovoltaic power generation device, a wind power generation device, a diesel generator device, an energy storing device, an alternating load, a direct current bus device, an alternating current bus device, a smart controller device, a rectifier, a detection device and an inverter device. The multi-energy power supply system integrates solar energy, wind energy, a diesel generator and a storage battery device, has strong nonlinearity, and has a certain degree of inertia. According to the smart energy management device of the multi-energy power supply system, fuzzy control algorithm is used for integrated management of energy. The smart energy management device is characterized by intelligent control, effectively solves the nonlinear problem of the system, enables overshoot of the system to be reduced, even enables overshoot not to occur, and enables the system to have strong robustness and adaptivity.

The invention discloses a photovoltaic grid-connected inverter MPPT (Maximum Power Point Tracking) system based on the admittance optimization algorithm. In the invention, the advantages of the conductance increment algorithm and the fuzzy control algorithm are combined, the admittance optimization algorithm is independently researched and developed, and the fuzzified transfer function and the defuzzification judgment are established. A photovoltaic array Pmax is calculated through a photovoltaic array P-U curve, the voltage level fluctuation can be fast followed, no complex algorithm is required, the maximum power of a solar battery can be fast tracked, and the requirement for MPPT control on the photovoltaic system in various occasions can be well satisfied. Test results verify that the algorithm has better effects such as compatibility with different systems, fastness and the like in comparison with the conductance increment algorithm. The results of a great deal of experiments and test show that the photovoltaic grid-connected inverter MPPT system based on the admittance optimization algorithm has excellent real-time performance and dynamic performance, and is stable in tracking without misjudgment, with tracking accuracy reaching up to 99%.

The invention discloses a controlling method and a system for intelligent signal lights based on big data. The signal lights is precisely controlled in real time according to current traffic flow at an intersection based on image recognition technology of YOLO algorithm and adaptive fuzzy control algorithm, so that traffic flow information collection and intelligent traffic lights control is realized; the big data sharing is performed in real time, and the current traffic lights and future traffic flow changes can be judged in time based on information sharing of the big data; and the trafficlights can be coordinated and controlled in real time by adjusting corresponding control strategy so as to effectively solve the traffic congestion problem caused by the traffic lights. Meanwhile based on real-time sharing of the big data realized by the controlling system for intelligent signal lights and through big data analysis, public transportation speed is configured to improve the abilityof public transportation, which is conducive to reducing fuel consumption and vehicle exhaust gas emissions, and achieving energy saving and emission reduction.

The invention provides a reactive navigation control method for an underground mining vehicle. The reactive navigation control method comprises establishing a front axle pose state vector estimation value model of a next moment based on a vehicle hinge joint, a front axle midpoint, front axle velocity, front axle yaw angular velocity, front axle turning radius, a rear axle midpoint, rear axle velocity, rear axle yaw angular velocity and rear axle turning radius; establishing a course deviation angle model; establishing an articulated vehicle front axle center position deviation model; establishing a turning angle control model which comprises a safety prediction model and a fuzzy control algorithm; and establishing an articulated vehicle velocity control model, and controlling the underground mining vehicle based on the articulated vehicle velocity control model.

The invention discloses a polishing and grinding force-position mixed control method and system so that control precision is enhanced when contact force is generated between a grinding and polishing robot and an external environment, and grinding force is ensured to be constant in the grinding process. The method comprises that: a pressure sensor acquires current grinding force Fc between a grinding tool and a workpiece; a comparator calculates a difference value between the expected grinding force Fd between the grinding tool and the workpiece and the current grinding force Fc; and a fuzzy controller outputs a control variable U to control the grinding force between the grinding tool and the workpiece according to rate of change Ec of the difference value by adopting a fuzzy control algorithm. The method provided by the embodiment of the invention can enhance control precision when the contact force is generated between the grinding and polishing robot and the external environment, the grinding force is ensured to be constant in the grinding process and thus the grinding effect is ensured.

The load control method for ball mill in powdering loop cement plant adopts a double-layer control structure, including an upper layer of self optimizing algorithm and a lower layer of multidimensional fuzzy control algorithm. The self optimizing algorithm finds out the optimal inside material storage quantity inside the ball mill as the controlling set value; and the multidimensional fuzzy control algorithm controls the material compounding links to realize the automatic regulation of the material feed quantity, so as to reach the required components in the cement production, lower the raw material amount and the cement screen residue, raise grinding fineness, ensure cement quality, increase output of ball mill and lower production cost.

The embodiments of the invention disclose an automated guided vehicle, a control method thereof, and a control system thereof. The control method of the automated guided vehicle includes the steps: establishing a kinetics model of the automated guided vehicle, and by means of the kinetics model, calculating the pose data of the automated guided vehicle; according to the pose data and the error ofthe target movement path, by means of a section II type fuzzy control algorithm, calculating the adjustment amount of the automated guided vehicle; and through the adjustment amount, controlling the automated guided vehicle to move along the target movement path. The control method of the automated guided vehicle employs the control strategy of section II type fuzzy control, so as to enable AGV (Automated Guided Vehicle) to have higher robustness during the path tracking process, and can be applied to more different scenes.

The invention discloses a device for monitoring corrosion of oil and gas field gathering pipelines. The device comprises an MCU, a signal generator, a constant-potential circuit, a power amplifier, a corrosion monitoring probe low-pass filter and an A/D data acquisition unit. The MCU controller is used for transmitting waveform data to the signal generator to generate sine waves at certain frequency, loading the sine waves to the constant-potential circuit to form polarization current and outputting the polarization current to a corrosion monitoring probe through the power amplifier. Polarization potential and the polarization current of the corrosion monitoring probe are filtered through the low-pass filter and then transmitted to the A/D data acquisition unit to be acquired, the MCU is used for processing acquired potential and current data, dielectric resistance and polarization resistance of a working electrode can be obtained, the corrosion rate of the working electrode can be obtained, and then pipeline corrosion monitoring is achieved. The invention further discloses an intelligent corrosion inhibitor filling device. The filling concentration of corrosion inhibitor can be adaptively and dynamically adjusted according to the measured value of the pipeline corrosion rate and a fuzzy control algorithm, and therefore the pipeline corrosion control strategy is optimized accordingly, and scientific filling of the corrosion inhibitor is achieved.

The invention provides a fitness bike trainer control system realizing stepless control by an Android/IOS mobile terminal APP. The fitness bike trainer control system comprises a display module, an Android/IOS mobile terminal APP master control module, a live-action video module, an information storage module, a Bluetooth module, a fitness trainer master control module, a resistance module and a sensor module. A user uses the Android/IOS mobile terminal APP in a mobile phone to steplessly control the fitness bike trainer; the fitness trainer receives resistance gear information from the Android/IOS mobile terminal APP, PWM output current percentage of the fitness trainer is controlled through combination with a PID fuzzy control algorithm so as to control the magnetic field of an electromagnet of the fitness trainer, the magnetic field of the electromagnet and the magnetic field of a permanent magnet jointly brake an aluminum plate, user riding resistance is generated, and a riding speed is fed back to the Android/IOS mobile terminal APP. The Android/IOS mobile terminal APP can set and store identities and motion information of multiple users, can perform training effect comparison, can display real-time data information about user riding and has a live-action video training function, thereby being capable of meeting fitness requirements of different users.

The invention discloses an intelligent sensing control vision protection method and device. The device consists of a control host computer and a remote controller, wherein the control host computer comprises an embedded controller, an infrared sensing module, an ultrasonic distance measuring module, an illumination sensing module, a temperature sensing module, a gas sensing module, a stepping motor control module, a voice alarm module, a switching quantity control module, a host computer wireless communication module and a host computer key display module; and the remote controller comprises an integrated circuit, a remote controller key display module and a remote controller wireless communication module. Intelligent processing is performed by adopting a fuzzy control algorithm after information such as the eye release, observing time, illumination strength, temperature, gas and the like of a vision-protected person are detected by using the device, the voice alarm module makes a prompting sound when the eye release and the illumination strength are lower than set values and the observing time, temperature or detected gas concentration surpasses a set threshold value, and a relay of the switching quantity control module is used for switching the power supply of a computer or a television set, so that the vision is protected. The device is easy to use, and has complete functions; and effective protection of vision can be realized.

The invention discloses an intelligent agricultural irrigation system, which comprises a data acquisition device, an internet of things terminal controller, a cloud server and irrigation equipment, wherein the data acquisition device is used for acquiring soil humidity information and meteorological data; the internet of things terminal controller is used for sending the data to the cloud server;the cloud server comprises a receiving unit and a data processing unit; the receiving unit is used for receiving the data sent by the internet of things terminal controller; the data processing unit processes soil the humidity information by using a fuzzy control algorithm to obtain an irrigation scheme and sends the irrigation scheme to the internet of things terminal controller; the internet ofthings terminal controller is further used for sending a control instruction to control the operation of the irrigation equipment according to the irrigation scheme of the cloud server; and the irrigation equipment is used for irrigating crops according to the control instruction sent by the internet of things terminal controller. The fuzzy control algorithm is adopted to realize timely and appropriate irrigation, so that the system ensures that crops are in the best growth state at all growth stages and reduces agricultural water consumption.

The invention discloses an air conditioner control method. The air conditioner control method comprises the steps that infrared temperature field data of a detection area are acquired; according to the infrared temperature field data, the fuzzy control algorithm is adopted to determine the number of people in the detection area and position distribution, and a control command controlling the running mode of an air conditioner indoor unit is produced; the control command is transmitted to the air conditioner indoor unit; the running mode of the air conditioner indoor unit is regulated according to the control command. The invention further discloses an intelligent air conditioner correspondingly. By the application of the technical scheme, the air conditioner indoor unit can be controlled intelligently.

The invention provides an automatic vibration calibration system and a calibration method and belongs to the field of vibration metering and calibrating. The automatic vibration calibration system comprises a control part and a measuring part. The control part is used for controlling frequency and amplitude of a vibration table. The measuring part is used for measuring the amplitude and the phase of the vibration table and measuring signals output by a vibration measuring element. The control part comprises a function generator, an amplitude controller, a power amplifier, a self-adaptive control algorithm module and a fuzzy control algorithm module. The function generator outputs a sinusoidal signal of the assigned frequency F and an assigned voltage amplitude value Uci according to a computer instruction, the sinusoidal signal is output to the power amplifier after passing through the amplitude controller to drive the vibration table to start vibration, and the self-adaptive control algorithm module calculates a corresponding output signal according to the input signal.