194 results about "Fuzzy pid controller" patented technology

The invention relates to the technical field of control on production equipment, and particularly relates to an intelligent control system for a vertical mill based on a fuzzy PID (proportion integration differentiation) algorithm. The intelligent control system comprises the vertical mill, a dust remover and a feeding device, wherein the feeding device comprises an unloader, a bucket elevator and a storage bin; and the intelligent control system is characterized in that an air inlet in the bottom of the vertical mill is connected with a fan via a pipeline, a cold-air device and a hot-air stove are arranged on the pipeline between the air inlet and the fan, a cold-air adjusting valve and a hot-air adjusting valve are respectively arranged on the cold-air device and the hot-air stove, a vertical mill material layer PID controller is arranged on the feeding device, and an in-mill pressure difference fuzzy PID controller is arranged on the cold-air adjusting valve. According to the intelligent control system disclosed by the invention, mathematical models of the change of the vertical mill material layer thickness and an in-mill pressure difference along with parameters of a feeding amount, a mill inlet hot-air temperature and the like can be established only by inputting and outputting data without analyzing the complex grinding process of the vertical mill; and the intelligent control system is simple in process, high in adaptability, fast in the dynamic response time of a controller algorithm, high in robustness, high in control accuracy, and good in market prospect.

The invention discloses a fuzzy PID (Proportion Integration Differentiation) controller based on genetic algorithm and a control method thereof. The control method comprises the following steps in sequence: controlling a controlled object by a fuzzy control algorithm; dynamically generating three parameters of the PID controller in an online manner; selecting a proper fitness function by virtue of the genetic algorithm; searching based on the fitness function of each individual in the population; increasing the speed of convergence of the genetic algorithm; calculating to obtain the optimal solution; and further optimizing three basic parameters output in the fuzzy control. By adopting the control method, dynamic and static performances of a control system can be improved while the accuracy in control detection is ensured.

The invention discloses an intelligent anti-swinging crane control system based on fuzzy PID control. The intelligent anti-swinging crane control system based on fuzzy PID control comprises a fuzzy PID controller, an industrial personal computer, an industrial camera, a lifting encoder, a human-computer interface, a trolley encoder and a gantry encoder. The human-computer interface is connected with the fuzzy PID controller. The industrial camera is installed on the lower side of a lifting operation mechanism. The lifting encoder is installed at one end of a lifting winding drum. The trolley encoder and the gantry encoder are installed on a trolley and a gantry correspondingly. The crane comprises the lifting operation mechanism, a trolley operation mechanism and a gantry operation mechanism. The lifting operation mechanism is connected with a lifting motor and a lifting frequency converter. The trolley operation mechanism is connected with a trolley motor and a trolley frequency converter. The gantry operation mechanism is connected with a gantry motor and a gantry frequency converter. The lifting frequency converter, the trolley frequency converter and the gantry frequency converter are connected with the fuzzy PID controller. The invention further discloses an intelligent anti-swinging crane control method based on fuzzy PID control. By the adoption of the intelligent anti-swinging crane control system and method based on fuzzy PID control, accurate control over the movement displacements of the gantry and the trolley of the crane and effective control over the swinging angle of a load can be achieved.

The invention discloses a speed and current double closed-loop control system and method for a permanent magnet synchronous linear motor. The method comprises the steps of: designing a permanent magnet synchronous linear motor vector control system; designing a fuzzy adaptive sliding-mode speed controller; designing a nonlinear disturbance observation; designing a d-axis fuzzy PID controller; designing a q-axis fuzzy PID controller; obtaining a desired q-axis current reference value as an input of the q-axis fuzzy PID controller according to the designed nonlinear disturbance observer and thedesigned fuzzy adaptive sliding-mode speed controller; setting a d-axis reference current value as 0, and using the id obtained by subtracting park transform from 0 as the input of the d-axis fuzzy PID controller; after the processing by the d-axis fuzzy PID controller and the q-axis fuzzy PID controller, obtaining the ud, uq of the vector control system, and finally outputting the current operating driving voltage of the permanent magnet synchronous linear motor by the anti-park transformation and SVPWM modulation through the vector control and an inverter. The method enhances the robustnessof the system.

The invention discloses a parameter self-tuning method for a fuzzy PID controller, comprising steps of calculating original quantification factor numerical value combination according to deviation of a control system, a deviate changing rate and basic discourse domains and fuzzy disclosure domains of ratio, differential and integral coefficient in the PID control, reasonably choosing interval radius of the interval to obtain value-taking intervals of all quantization factors to be optimized by taking all original quantization factor values to be centers of interval, evenly selecting values in all value-taking intervals to obtain different quantization factor value combinations, testing control performance of the control system under the combination of all quantization factor values; taking a quantization factor value combination and a corresponding control performance value as a sample data, repeating the test to obtain enough sample data used as training data for an extreme learning machine, training the control system model in an off-line state, and perform optimizing on the system off-line model by using a non-dominated sorting genetic algorithm of an elitist strategy in order to obtain the quantization factor value combination enabling the control performance to be multi-object optimization.

The invention belongs to the aircraft fuel system full-mold test field and relates to an adaptive PID control method and control system of an executing mechanism. The objective of the invention is to solve the problems of poor effects and low precision of an existing PID control method. The adaptive PID control system includes an expert PID controller and a fuzzy PID controller which are respectively connected with the executing mechanism, a state information acquisition device used for monitoring the current status information of a system to be controlled in real time, and a processor used for selecting the expert PID controller or the fuzzy PID controller according to the current status information and expected status information to control the executing mechanism. According to the adaptive PID control system of the invention, the expert PID controller or the fuzzy PID controller is selected to perform control, and therefore, the adaptive PID control system has the advantages of high adjustment speed, short rise time, low overshoot and high control precision. With the control system adopted, requirements for high speed of a servo system can be satisfied, and the control quality of the servo system can be improved.

The invention discloses an electro hydraulic servo system self-correction fuzzy PID control method. In the prior art, the problems that error accuracy is not high and stability and adaptability are not high exist. According to the self-correction fuzzy PID control method, an electro hydraulic servo control mechanism serves as a controlled object, a feedback value of the controlled object and the error E and the error change rate EC of a target value serve as input of a fuzzy PID controller, appropriate fuzzy control rules are set, parameter self-correction is conducted on PID parameters including Kp, Ki and Kd through a fuzzy reasoning method, the requirements of E and EC on PID parameter control at different moments can be met, the variable quantities including delta kp, delta ki and delta kd of PID controller parameter values are output, and the PID parameters are corrected on line according to the self-correction fuzzy control rules. The electro hydraulic servo system self-correction fuzzy PID control method overcomes the disadvantages caused by manual PID parameter correction, online real-time self-correction is achieved for the PID parameters, high robustness is achieved for system parameter correction, and therefore error accuracy and stability of the system are improved, and high application value is achieved.

The invention relates to a respirator, and discloses a breathing pressure fuzzy control type respirator and a breathing pressure fuzzy control method. The breathing pressure fuzzy control type respirator controls action of each part by means of actual control output of fuzzy piping and instruments diagram (PID) controller in a template embodiment, and each sensor collects signal variable of each part and transfers to the fuzzy PID controller to do fuzzy control operation. An air suction electromagnetic proportional valve is capable of controlling opening of a valve hole to continuously vary in a certain range according to corresponding control signal (voltage or current signal). The fuzzy PID controller is capable of controlling flow which enters back stage gas channel to continuously vary in a certain range through controlling opening of each valve and further controlling airway pressure. Breath becomes more comfortable and safer after patients using the respirator.

The invention discloses a test system for electro-hydraulic servo online self-adjusting fuzzy PID control and an online self-adjusting fuzzy PID control method for an electro-hydraulic servo position system. The test system for the electro-hydraulic servo online self-adjusting fuzzy PID control comprises an industrial personal computer, a data processing system, an electro-hydraulic servo control system, an online self-adjusting fuzzy PID controller, a processing circuit and a sensor. Different sensor signals in the sensor pass through the processing circuit, digital signals are gathered, and the online self-adjusting fuzzy PID control is performed through an electro-hydraulic servo system to realize the test control for the electro-hydraulic servo system. The test system for the electro-hydraulic servo online self-adjusting fuzzy PID control is featured with high test efficiency, good stability, strong practicability and the like, realizes the online real-time regulation for PID parameters and has strong identification performance and robustness for the online system parameter self-adjusting, and accordingly the system test precision and stability are improved, and the economical benefit and social benefit are good.

The invention discloses a four-rotor aircraft attitude control method, which comprises the steps of: firstly, acquiring current attitude angle information of a four-rotor aircraft, wherein attitude angles include a pitch angle, a roll angle and a yaw angle; calculating an error amount between a given desired attitude angle and the current attitude angle; then determining a fuzzy logic relationshipamong a quantization factor, a scaling factor and errors and an error change rate, and developing a fuzzy rule table; and finally, regarding the errors and the error change rate as input, and regarding the quantization factor and the scaling factor as output to establish a fuzzy PID controller based on factor self-adaption, thereby realizing online real-time adjustment of the quantization factorand the scaling factor. The four-rotor aircraft attitude control method has better dynamic tracking effect and system robustness, and provides a reliable guarantee for the four-rotor aircraft to complete a flight mission more flexibly.

The invention discloses a nonlinear feed-forward and fuzzy PID combined variable pitch control method for a wind generating set. The method comprises based on an active power deviation feed-forward control strategy, using active power P and rated power P0 of a generator to obtain the power deviation delta P when a generator unit operates above the rated wind speed; giving variable pitch control expected output pitch angle beta1 through an MAPSO fuzzy PID controller; obtaining a variable pitch control expected feed-forward pitch angle beta2 through a nonlinear feed-forward controller; adding the pitch angle beta1 obtained by the MAPSO fuzzy PID controller to the feed-forward pitch angle beta2 to obtain a pitch angle set value beta. By means of the method, the system adjusting time is reduced, the stability and the reliability of the system are increased, and compared with traditional controllers, apparent advantages are provided.

The invention provides a water temperature control method and a control system thereof based on adaptable fuzzy PID. Fuzzy control and a PI algorithm in the PID algorithm are combined to form a fuzzy PID controller to carry out real-time monitoring and adjusting on the water temperature, that is, a microprocessor acquires cold water temperature, hot water temperature and mixed warm water outlet temperature in real time, the mixed warm water outlet temperature is compared with the preset temperature, the fuzzy PID algorithm is used for controlling flow speeds of the cold water and the hot water, and thus the mixed warm water outlet temperature is constant. The temperature adjustment reaction is quick, and the accuracy is high.

The invention provides a brushless DC motor fuzzy PID control speed regulation system and method. The method comprises steps of according to the fuzzy control theory, establishing a fuzzy PID controller module of a brushless DC motor speed regulation system; establishing a brushless DC motor speed regulation system module; establishing the objective function of fuzzy PID controller parameter optimization of the brushless DC motor speed regulation system; and obtaining the fuzzy relation between the fuzzy PID controller Kp, Ki, Kd and the error e and the error rate of change ec, and according to the values of the error e and the error rate of change ec, and fuzzy control rules, modifying the three parameters Kp, Ki, Kd. The invention also correspondingly provides a fuzzy control device. The method of the invention adopts the fuzzy PID control for the speed regulation in the PID control system, and has the advantages of good dynamic performance, fast rising speed, small overshoot and good robustness.

The invention provides a PLC-based solar energy automatic irrigation system and an irrigation method thereof. The PLC-based solar energy automatic irrigation system comprises a photovoltaic power supply module, a detection module, a PLC control module and an irrigation module, the irrigation system is controlled by the PLC control module, a fuzzy PID controller is adopted to control opening of an electromagnetic valve, the irrigation amount can be controlled more precisely, intellectualization of the irrigation system is greatly improved, and intelligent and water-saving irrigation is achieved. The tail end of a water-outlet valve is connected with a winch type irrigation machine, self-waking, self-stopping and self-adjustment of spray irrigation height can be achieved in the spray irrigation process, limitation of the geological environment is avoided, adaptability is high, and spray irrigation tasks in different environments can be completed. The photovoltaic power supply module is utilized to provide electricity for the irrigation system, the problem concerning energy required for irrigation in the irrigation area is solved, quite good energy-saving and emission-reducing effects are also achieved, and the ecological environment is protected.

The invention discloses an optical guiding recovery system of an autonomous underwater robot and a recovery method of the optical guiding recovery system. The method includes the following steps that: the autonomous underwater robot performs pectination search on a linear guide light source array; if guide light sources are found, the three-dimensional spatial coordinates of the guide light sources are calculated; a sightline method or a lateral trajectory deviation method are adaptively adopted to plane the heading angle of the target according to the number of the guide light sources; and a two-layer tracking control system is designed based on a fuzzy PID controller and an S surface controller. With the system and the method of the invention adopted, the autonomous underwater robot can realize high-reliability, high-robustness and high-success rate underwater autonomous docking, and effective guide distances which can satisfy practical application requirements can be obtained through increasing the length of the light source array.

The invention provides a fuzzy PID based automobile cruise control system which comprises an automobile cruise control system module, a fuzzy control module, a traditional PID module, a fuzzy PID controller design module and an MATLAB simulation result module, and the modules are connected via electric signals. According to the invention, overshoot of the automobile cruise control system is correspondingly reduced, reaction speed is increased, the driving speed is effectively kept at the cruise speed, an accurate mathematical model is not relied on, the system is not sensitive to parameter change, and the robustness is very high.

The invention discloses an electric power steering system and a control method. The electric power steering system comprises a collector, a processor, a fuzzy PID controller and a motor, wherein the collector is used for collecting manual torque applied to a steering wheel and the current speed of the vehicle; the processor is connected with the collector for receiving the manual torque and the speed, acquiring expected target steering torque applying to the steering mechanism after the motor is power-on according to the manual torque, the speed and the preset steering control strategy, and further acquiring target current needed when the motor outputs the target steering torque; the fuzzy PID controller is connected with the output end of the processor for receiving the target current and the present current of the motor, adopting fuzzy PID control algorithm to adjust the output current of the fuzzy PID controller according to the target current and the present current of the motor until the present current is the same as the target current; and the motor is used for controlling the steering mechanism according to the output current of the fuzzy PID controller. Accuracy and stability of the electric power steering system are enhanced.

The invention discloses a reaction vessel negative pressure rectification fuzzy control method which is characterized in that a reaction still, a rectification tower, and a water tank are involved; a negative pressure pumping apparatus, a first control valve and a second control valve are controlled through a controller; a rotation speed of the negative pressure pumping apparatus is real-time and dynamicly regulated in accordance with pressure deviation in the reaction still and pressure deviation variation rate through a fuzzy-PID controller, which improves reaction still negative pressure rectification in terms of speed, precision and stability; and when an actual pressure value in the reaction still is overstruck, the actual pressure value is rapidly stabilized with an expected pressure value error range through pressure compensation regulation.

The invention provides a fuzzy neural network PID (proportion integration differentiation) control system and a fuzzy neural network PID control method for a fin stabilizer. After quantization, address mapping and CMAC storage are performed on a detected sea wave dip angle signal by a CMAC (cerebellar model articulation controller) neural network feed-forward control unit, by combining online learning of a fin angular displacement signal output by a fuzzy PID controller, CMAC operation is performed on the fin angular displacement signal and the quantized sea wave dip angle signal to obtain a fin stabilizer anti-interference offset angular displacement signal to be input into a fin stabilizer servodrive unit; a PLC (programmable logic controller) control unit is used for receiving signals detected by a velocity log and an angular velocity sensor, and the signals are output to the fuzzy PID controller after being fitted; the fin angular displacement signal processed by the fuzzy PID controller is sent to the fin stabilizer servodrive unit; the fin stabilizer is driven to rotate by the fin stabilizer servodrive unit according to the fin angular displacement signal and the offset angular displacement signal, and moreover, an angular displacement sensor is used for detecting a current fin angular displacement signal of the fin stabilizer, and the current fin angular displacement signal is sent onward to the fuzzy PID controller after the current fin angular displacement signal and the fin angular displacement signal sent by the PLC control unit are subtracted to drive the fin stabilizer to perform adaptive adjustment, and therefore, the adaptability of a control process is improved.

The invention provides a fuzzy-PID control device for steam pressure of a once-through steam generator and a coordinated control method. A fuzzy-PID controller is a core part of the fuzzy control device for steam pressure of the once-through steam generator, comprising a fuzzy-controller and a PID-controller, and smooth transition of the two controls can be guaranteed by adopting fuzzy switching. With the implementation of an excellent stability of the PID controller and a good rapidity of the fuzzy controller, when the deviation is larger, a proper action can be provided rapidly by means of the characteristic of human-simulated intelligent control so as to suppress interference rapidly and smoothly, thereby guaranteeing the rapidity and robustness of dynamic response of the system; when the deviation is smaller, a conventional PID plays the leading role to guarantee the excellent steady-state performance. The fuzzy-PID control device is applicable to the system with serious non-linearity and time variance, such as the once-through steam generator, and has high control precision and good robustness. The fuzzy-PID control device can be practically applied to the design of the control system of the once-through steam generator so as to improve the control quality of the system.

The invention discloses an EKF-based rotating speed control method of a sensorless ultra-high speed permanent magnet synchronous motor. The method comprises the following steps of building a mathematical model of the motor and converting the mathematical model into a state equation; carrying out linearization and discretization, substituting the discrete linear state equation into an extended Kalman filter (EKF) for recursive computation, updating a variance matrix P and a gain K in the EKF in real time to update a state variable; and finally estimating the rotating speed of the motor in the dynamic operation process in real time. The rotating speed estimation method is applied to an SVPWM-based ultra-high speed motor direct torque control system; the adaptivity of the system is improved by a fuzzy PID controller; and fast, stable and reliable rotating speed control on the ultra-high speed permanent magnet synchronous motor is effectively achieved.

The invention discloses a novel power battery pack system based on fuzzy PID control and a control method thereof. The system comprises a battery management system, a cooling liquid circulating main pipeline, cooling liquid primary / secondary branch pipes, cooling liquid flow control valves, primary / secondary spherical liquid distribution pivots and s-shaped flat heat exchange pipes. The cooling liquid circulating main pipeline is communicated with a cooling liquid primary branch pipe through a primary spherical liquid distribution pivot, and the cooling liquid primary branch pipe is connectedwith a cooling liquid secondary branch pipe through a secondary spherical liquid distribution pivot. The tail end of each cooling liquid secondary branch pipe is connected with two s-shaped flat heatexchange pipes which are arranged on the outer surface of the battery cell at an interval of 180 degrees, and a cooling liquid flow control valve is arranged on each cooling liquid primary branch pipeand is driven by a stepping motor controlled by a fuzzy PID controller. According to the invention, the power battery pack can be controlled to always work in the optimal temperature range; the balance of the internal temperature of the battery pack is ensured; the disadvantage of unbalanced overall temperature of the battery pack is solved; and the service life is prolonged.

The invention relates to an enthalpy difference temperature and humidity decoupling control method based on adaptive fuzzy PID decoupling control. The method comprises the following steps: (1) determining a model of a temperature and humidity coupling object in an enthalpy difference lab system, and using an identification model parameter; (2) performing enthalpy difference lab temperature and humidity decoupling design; (3) designing an adaptive fuzzy PID controller; and (4) designing an enthalpy difference lab temperature and humidity decoupling controller. The method can realize the complete decoupling of the temperature and humidity of the enthalpy difference lab, and further proves the simple practicability of the feedforward compensation algorithm, can shorten the adjustment time ofthe system, meets the requirements of national standards, and improves the working efficiency of the enthalpy difference lab. The method can improve the stability of the system and reduce the steady-state errors, so that the average variation range of the dry bulb temperature is less than or equal to + / -0.3 DEG C, and the average variation range of the wet bulb temperature is less than or equal to+ / -0.2 DEG C. The temperature and humidity adjustment accuracy of the enthalpy difference lab can be improved.

The invention discloses a chilled water loop control method based on a fuzzy PID and a neural internal model. An air conditioner performs real-time control over a compressor through the method after collecting the water outlet temperature of chilled water, wherein the compressor is a controlled object in a chilled water loop. The method includes the steps that step1, a target value of the controlled object is set; step2, a fuzzy PID controller and a neural network estimator together form internal model control; step3, the controlled object is trained through the neural network estimator to be a controlled object model in an ideal state; step4, deviation is adjusted through the fuzzy PID controller, finally, self-adaptation control over the chilled water loop of a variable-air-volume air conditioner system is achieved, and stable output of the controlled object is achieved. The fuzzy PID and the neural internal model control are combined, the defects of nonlinearity and time varying in the chilled water loop can be overcome, and accurate and rapid control is achieved.

The invention relates to the technical field of automobile electronic sensing detection, and particularly relates to a wide-band oxygen sensor temperature control method which concretely comprises the steps that a temperature signal in a wide-band oxygen sensor is acquired firstly, the temperature signal is converted through an A / D converter and then compared with a target temperature value, deviation e and deviation change rate e<delta> are calculated, deviation and deviation change rate can act as input of a fuzzy PID controller, and the three parameters K, K and K<D> of the PID controller are regulated online through fuzzy reasoning; and then PID control operation is performed and duty ratio of a corresponding temperature control PWM signal is outputted to regulate power of a heater so as to realize temperature control. According to realization of wide-band oxygen sensor temperature control based on a fuzzy PID control algorithm, establishment of an accurate model of a wide-band oxygen sensor temperature control object can be avoided. Meanwhile, temperature control accuracy can be enhanced through combination of fuzzy control and PID control, and the dynamic and static performance of wide-band oxygen sensor temperature control can be enhanced.

The invention discloses an STATCOM / BESS-based wind turbine group coordinated self-starting control method, which comprises the steps of: S1, designing a self-starting controller based on a feedback linear control algorithm for model characteristics of a DFIG in self-starting when the self-starting of the DFIG under an off-grid condition begins; S2, merging the self-starting controller into an STATCOM / BESS after the self-starting controller detects that islanding operation voltage and frequency of a draught fan are stable; S3, and merging the STATCOM and the DFIG equipped with an energy storage system into the DFIG which is not equipped with an energy storage system after the STATCOM and the DFIG are started, and coordinating a fuzzy PID controller to start, wherein the fuzzy PID controller utilizes a fuzzy PID algorithm, monitors voltage and frequency stabilization conditions of the newly-merged DFIG continuously, optimizes PID controller parameters of the STATCOM and the DFIG equipped with the energy storage system continuously through fuzzy reasoning, and coordinates active and reactive power output of the draught fan and the STATCOM. The STATCOM / BESS-based wind turbine group coordinated self-starting control method enables the double-feeding asynchronous wind turbine group to achieve self-starting under the off-grid condition, and further achieves stable islanding operation.

The invention discloses a functional electro stimulation closed loop fuzzy proportional integral derivative (PID) control method, which includes obtaining an expression of torque of the knee joint; establishing a muscle model; adjusting stimulation current through a fuzzy PID controller, and obtaining a practically output torque value of the knee joint through the muscle model; obtaining errors and error change rate; inputting the errors, the error change rate and the stimulation current into a fuzzy inference system which processes the errors, the error change rate and the stimulation current and converts the errors, the error change rate and the stimulation current into corresponding fuzzy quantity; obtaining control rules, and setting three parameters of the PID controller according to the control rules; adjusting the stimulation current according to parameters after setting, and obtaining newly and practically output torque value of the knee joint through the muscle model; and finishing the process until an error between the newly and practically output torque value of the knee joint and an expected torque value of the knee joint is smaller than a threshold value. The functional electro stimulation closed loop fuzzy PID control method can effectively improve stability and accuracy of the functional electrical stimulator and obtain considerable social benefits and economic benefits.

The invention relates to a controller design method of a duct type multi-rotor mooring UAV, belongs to the field of control algorithms, and aims at solving the problem that a UAV controller is low incontrol capability and anti-interference capability due to the fact that a present simulation platform of a UAV control system is incapable of optimizing control parameters sufficiently. According tothe controller design method, a finite element analysis method is used, pneumatic characteristic parameters of the total structure of the duct type multi-rotor mooring UAV is analyzed, a dynamic modelof the UAV is established and distribution values for tension control of different motors are obtained according to the pneumatic characteristic parameters, and the pneumatic characteristic parameters are measured; the established model is combined with the measured pneumatic characteristic parameters to establish a control simulation platform of a duct type mooring UAV control system is established in the simulink environment; and a fuzzy PID controller is used to design the duct type mooring UAV control system with mooring cables, and the parameters are improved.

The invention relates to a peristaltic pump flow control system based on a LabVIEW fuzzy PID controller. The peristaltic pump flow control system comprises a drive circuit, a peristaltic pump, a flow sensor, a data collection card, an A / D converting circuit, a fuzzy PID controller, a D / A converting circuit, a single-chip microcomputer, and a display screen. The output end of the drive circuit is electrically connected with the peristaltic pump. The output end of the peristaltic pump is connected with the input end of the flow sensor. The output end of the flow sensor is connected with the input end of the data collection card. The output end of the data collection card is connected with the input end of the A / D converting circuit. The output end of the A / D converting circuit is connected with the input end of the fuzzy PID controller. The output end of the fuzzy PID controller is connected with the input end of the D / A converting circuit. The output end of the D / A converting circuit is connected with the input end of the single-chip microcomputer. The output end of the single-chip microcomputer is connected with the drive circuit. The fuzzy PID controller is connected with the display screen through a line. A LabVIEW software system is embedded into the fuzzy PID controller. The peristaltic pump flow control system can improve a flow control effect, the overshoot amount of the system is obviously reduced, the flow control precision is obviously improved, and a defective rate is obviously reduced.

The invention relates to a visual axis stability composite control method based on a velocity disturbance observer and Fuzzy-PID. An angular rate gyroscope and a photoelectric encoder are arranged onstable platform with two axes and two frames; a signal fed bac by the angular rate gyroscope is sent into a visual axis stability controller, the location information acquired by the photoelectric encoder is sent into a location controller, classic PID control is established on the basis of the fixed controlled object model parameters, but in the actual condition, the parameters such as rotationalinertia and friction torque of the controlled object are not unchanged, a fuzzy-PID controller is designed, the condition that the parameter setting of the PID controller is independent of a mathematical model of the controlled object is improved, and the parameter can be adjusted online, the stability precision, the instantaneity and the robustness of the visual axis stability loop are improved;a disturbance observer based on a velocity signal is added in the system, the disturbance observer is used for observing the disturbance and performing a certain compensation, and the visual axis stability precision is correspondingly improved.