608 results about "Pid control algorithm" patented technology

A control method of a two-wheeled self-balance vehicle comprises the steps as follows: (1), performing initialization: (2), reading values of a gyroscope, an accelerometer and a rotation angle sensor as well as the pulse number of an encoder respectively; (3), obtaining a vehicle body inclination, a handlebar turning angle, motor speeds and a vehicle speed; (4), then calculating PWM (pulse width modulation) values of vertical control, direction control and speed control respectively through a PID (proportion integration differentiation) control algorithm; (5), superposing the three PWM values together and outputting the three PWM values to left and right motors; (6), then sending data of the gyroscope, the accelerometer, the vehicle body inclination, a battery voltage, motor currents and the vehicle speed to an upper computer so as to monitor the operating status of the whole vehicle; (7), when the battery voltage is monitored to be smaller than a preset value, and the motor currents or the vehicle speed is monitored to be larger than the preset value through monitoring, turning on corresponding LED warning lights; and (8), when the vehicle body inclination is larger than a preset angle through monitoring when the vehicle body inclination is monitored to be larger than a preset angle, determining that the vehicle body falls down, stopping the operation and returning to an initializer. According to the control method, a more accurate operational method is adopted.

The invention relates to a machinery automatic steering control method which comprises the following steps that: positional deviation and course deviation are determined; according to the variance in the practical front wheel rotating angle of an agricultural machine, online setting of PID parameter is completed by means of parameter self-setting PID control algorithm; moreover, the expected front wheel rotating angle of the next moment is calculated, thereby realizing automatic steering control of the agricultural machine. Based on conventional PID navigation control method, the invention makes full use of the fuzzy control method; according to the variance in the practical front wheel rotating angle of an agricultural machine, the invention meets the different requirements of the machine on PID control parameter under different errors and error change rate, thereby realizing online setting of PID parameter. The invention not only has the advantages of fuzzy control such as flexibility and adaptability, but also has the characteristics of higher precision of PID control; therefore, the invention can increase the stability and precision of agricultural machine automatic steering control and the robustness of a control system.

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.

A method of form copying laser carving processing belongs to the laser carving processing field. The method uses a CCD laser displacement sensor to detect the distance between a laser head and a workpiece for processing to generate a three-dimensional relief map of the material for carving; a PID control arithmetic is used to control the position of the laser head to ensure that a focus of the laser falls at the surface of the workpiece for processing, so as to realize laser cutting and carving towards irregular materials. A laser carving machine is also provided, including a machine frame, a leaser head, an X-axial and Y-axial flying mechanism which is connected with the laser head, a Z-axial driving mechanism which is vertical with the surface of the workpiece, a CCD laser displacement sensor and an upper controller which is used for controlling form copying carving. The present invention provides a method of form copying laser carving processing which can realize dynamic focusing and real-time focusing during the course of carving and can realize plane carving of the irregular materials, and also provides the laser carving machine of the method.

The invention discloses an underwater structure detection robot control system and a motion control method. A water surface system comprises a water surface console, a water surface communication transceiver and an umbilical cable, and an underwater system comprises an underwater communication transceiver, a power supply unit, an embedded microcontroller, a power-propelled unit, a vision illumination unit, a motion switching unit, a safety protection unit and a sensor unit. Each function module is in a modular design, mounting and dismounting are convenient, the water surface console has an emergent stopping function, a wireless connection tablet personal computer is configured, movable monitoring can be achieved, communication modes are various, the data volume is large, the motion switching unit supports switching of two motion modes such as swimming and crawling, and reliable safety protection such as data storage and voltage and current detection can be achieved. By means of the underwater structure detection robot control system and the motion control method, the motion control method is based on a generalized prediction proportion integration differentiation (PID) control algorithm, system energy consumption can be effectively reduced, loads of components and parts are decreased, and a robot can be conveniently and stably controlled.

The invention discloses a lane keeping and automatic centering system and method based on a deviation prediction algorithm. A lane keeping and automatic centering controller detects lane marking line information of a road ahead of a vehicle in real time through a camera; a vehicle body controller acquires current steering lamp information and headlamp information of the vehicle, and a vehicle body electronic stabilization system acquires current vehicle speed information of the vehicle; an electric power steering system acquires current steering angle information of the vehicle; an expected steering angle of the current vehicle is worked out through a deviation prediction algorithm and a PID control algorithm in the lane keeping and automatic centering controller, an expected steering angle signal is transmitted to the electric power steering system through a CAN to request for active steering, and the electric power steering system receives the expected steering angle signal and switches the current steering angle into the expected steering angle by rotating a steering wheel; meanwhile, a warning signal and a man-machine interaction signal are generated and transmitted to a vehicle warning system and a man-machine interaction interface through the CAN. The system and method can achieve the lane keeping and automatic centering functions.

The invention provides a difference active steering system of an electric wheel driving automobile and a difference active steering control method. The difference active steering system consists of a left steering electric wheel, a right steering electric wheel, a difference active steering mechanism and a difference active steering control system; the difference active steering control method uses a steering angle of the steering electric wheels and a vehicle speed dual PID (proportion integration differentiation) control arithmetic to determine target values of the torques of left and righthub electric motors in the left and right steering electric wheels. The novel steering method provided by the invention is applied to the vehicle having a steering mechanism; each steering electric wheel rotates around respective main pin to form a coordinated steering angle according to the driving force difference of the left and right steering electric wheels and the limitation of a trapezoidal steering mechanism, so that the vehicle is steered; and the active steering mechanism is simple and has steering energy consumption.

The invention discloses an adaptive suppression method for rapid acceleration shaking of a pure electric vehicle. The adaptive suppression method comprises the following steps that a vehicle control unit works out the torque required by a driver; the vehicle control unit receives an actual revolving speed signal feed back from a motor and conducts filtering through a high-order band filter; a deviation revolving speed is obtained by subtracting the control target zero revolving speed and revolving speed of the motor after filtering; a self-adaptive anti-shake dynamic torque output by a PID controller is obtained through a PID control algorithm according to the deviation revolving speed; the maximum saturation value and the minimum saturation value of the self-adaptive anti-shake dynamic torque output by the PID controller are limited to obtain the final self-adaptive anti-shake dynamic torque; and the torque required by the driver and the self-adaptive anti-shake dynamic torque are added, and the final targeted torque value sent to a motor controller is obtained. Compared with a PID control method aiming at limiting the torque growth slope and utilizing the motor revolving speed smoothing value, the adaptive suppression method is good in adaptability, can achieve calibration and verification easily and can take vehicle comfort and accelerating performance into consideration.

The invention discloses an oil injection combustion-supporting regeneration temperature control method for a DPF diesel engine particle filter system. The method comprises the steps that a DPF system temperature numerical value is collected through a temperature sensor in real time and transmitted to an electronic control unit, the electronic control unit is used for working out the fuel injection amount needed for adjusting the current temperature of a DPF into a target temperature through an open loop control algorithm and a closed loop PID control algorithm according to the temperature numerical value and transforming the fuel injection amount into a corresponding pulse width signal to drive a fuel control valve, the accurate control over the current fuel injection amount of a DOC catalyst is achieved, the exhaust temperature of an engine is controlled, and thus the temperature of the DPF is controlled. According to the method, the amount of fuel injected by the fuel control valve is controlled through open loop control and closed loop control, the flexible variable control over the temperature of the DPF diesel engine particle filter system in the regeneration process is achieved, it can be ensured that smoke particles captured in the DPF are combusted, and the phenomenon that the regeneration temperature is out of control, and consequently the DPF diesel engine particle filter system is aged and damaged can be avoided.

The invention discloses a platform type auxiliary rehabilitation training device for a hemiplegic finger of a patient. The auxiliary rehabilitation training device for the hemiplegic finger of the patient comprises a finger training mechanism, a hybrid driving mechanism, a sensing device and a control system, wherein the hybrid driving mechanism comprises a motor and a magnetorheological fluid damper, the finger training mechanism comprises a slider-crank mechanism and a finger moving device which can rotate freely and slide forwards or backwards under the driving of the slider-crank mechanism, the control system comprises an upper computer and a lower computer, the PID control algorithm is configured in the lower computer, and a virtual scene module and a virtual reality feedback force module are arranged in the upper computer. By the adoption of the auxiliary rehabilitation training device for the hemiplegic finger of the patient, combination of active training and passive training can be achieved for the patient, the mechanical structure, the hybrid driving mechanism, the sensing device and the control system cooperate with one another to achieve man-machine interaction, a training process is controlled strictly, and the interestingness of the training process is improved by the adoption of game images.

The invention discloses a magnetic suspension bearing control power amplification integrated system. An FPGA chip is used as a core processor. The system comprises an FPGA control circuit (1), a full bridge circuit and an isolation driving part thereof (2) and an analog-to-digital conversion circuit (3). The analog-to-digital conversion circuit (3) converts a rotor displacement feedback signal (32) which is provided by a displacement sensor on a magnetic suspension bearing and a coil current feedback signal (31) which is provided by a coil current sensor into digital signals, and transmits the digital signals to the FPGA control circuit (1); and the FPGA control circuit (1) performs digital calibration and the operation of a suspension PID control algorithm, a current PD correction algorithm and a three-level pulse width modulation algorithm on the digital signals to generate multi-path switching signals, and controls the coil current through the full bridge circuit and the isolation driving part thereof (2). The FPGA control circuit (1) integrates a suspension controller, a power amplifier stage controller and the function of conditioning the current and displacement signal, fully utilizes the logical resources in the chip and reduces the circuit volume and power consumption.

The invention provides a train speed automatic control method based on PID and a filtering algorithm. The method includes the steps of obtaining the current running target speed and actual speed of atrain, calculating speed tracking errors, calculating error deviation and updating the state amount of an error deviation differential filter, calculating a PID control amount and updating the state amount of a PID controller in the integral process, adjusting the PID control amount, modifying the adjusted PID control amount, updating the modified PID control amount, converting the updated PID control amount into corresponding control force and modifying the control force, and outputting the modified control force to the train. In combination with the advantages of the filtering algorithm anda PID control algorithm, deviation modification is conducted on the speed tracking errors, the speed tracking errors in the train driving process are reduced, the train is more precisely controlled, it is ensured that the train can more smoothly and stably run, and the sitting comfort degree is improved.

The invention discloses a lightweight quick response aerial remote sensing inertial-stabilized platform controlling system used for carrying out initiative controlling upon triaxial frames of stabilized platforms. The system comprises a DSP module, an FPGA module, a PWM power driving module, brushless DC torque motors, a stabilized platform frame, a measuring sensor, and an interface circuit. Angular position information, angular rate information and attitude information of the frame output by the measuring sensor are acquired by the DSP module and the FPGA module through the interface circuit in real time. PID controlling algorithm is executed by the DSP module and the FPGA module, and 18 PWM signals for controlling the three brushless DC torque motors are generated. The signals are converted into voltage signals by the PWM power driving module, and the brushless DC torque motors are driven, and the frame is driven to rotate, such that the initiative controlling upon the triaxial frame is realized. According to the invention, an independent mode and a combined mode are realized, and a frame soft lock function and an independent course configuration function under the combined mode are realized. Therefore, the operation of the platform is more reliable and intelligent.

The invention discloses a hoisting load anti-swing control device, method, system and engineering machinery. The hoisting load is hoisted by a cantilever crane through a lifting rope. The hoisting load anti-swing control device comprises a receiving device and a control device, wherein the receiving device is used for receiving the horizontal position of the top end of the cantilever crane and / or receiving the tilt angel of the hoisting load and the rate of the tilt angle; the control device is used for carrying out one of the followings: when the horizontal position of the top end changes, controlling an anti-swing device to compensate the horizontal displacement of part of the lifting rope so as to enable the horizontal position not to change before the horizontal position of the top end of the cantilever crane changes; when the tilt angle and rate of the tilt angle of the hoisting load are greater than the preset values, adopting fuzzy PID control algorithms to enable the anti-swing device to control the horizontal displacement of part of the lifting rope so as to restrain the tilt angle and the rate of the tilt angle. Through the adoption of the technical scheme, various interferences can be counteracted, greater swing can be restrained, and higher positioning precision can be reached.

The invention discloses a geometric coordinate transformation guide control method for achieving positioning rotation of a dynamic positioning ship. The geometric coordinate transformation guide control method for achieving positioning rotation of the dynamic positioning ship comprises the steps of (1) setting target heading of the dynamic positioning ship and a hull coordinate of the center of rotation, calculating an expected track of the dynamic positioning ship in the process of positioning rotation by combining a mathematic model of movement of the dynamic positioning ship and introducing a geometric coordinate transformation guide strategy, (2) calculating an expected heading and an expected position of the dynamic positioning ship at the current moment, and (3) applying a PID control algorithm to obtain force and torque needed for controlling longitudinal movement, transverse movement and yawing of the dynamic positioning ship to enable the dynamic positioning ship to reach the expected position and the expected heading so as to achieve the positioning rotation, of the dynamic positioning ship, around the center of the rotation according to the difference between an actual position at the current moment and the expected position and the difference between an actual heading at the current moment and the expected heading. The geometric coordinate transformation guide control method for achieving positioning rotation of the dynamic positioning ship does not need to change a thrust distribution center, can ensure the fact that a positioning rotation system is in a closed-loop control loop, improves accuracy of control, and is simple and practicable in process of calculation, and applicable to operation of ocean engineering.

The invention provides a micro fluid flow adjusting device based on air pressure drive, belongs to the field of micro fluids, and aims to solve the problems of low flow adjusting precision, low dynamic response speed and absence of capacity of measuring actual flow when an injection pump is adopted to adjust the flow in a micro fluid system. The micro fluid flow adjusting device adopts an air pressure drive mode, an air supply source supplies compressed air, outlet pressure is adjusted and set by a pressure reducing valve to obtain stable air supply pressure, the pressure is measured by a pressure sensor, a liquid in a liquid container passes a valve and a flow meter to enter a liquid micro-channel under the pushing of the air pressure, the actual liquid flow is measured by the flow meter and fed back to a microprocessor, the microprocessor outputs a control signal to change the working state of a micro valve, the liquid flow of the liquid micro-channel is adjusted, and closed-loop control of the flow is realized; further, a PID (proportion integration differentiation) control algorithm can be adopted, the adjusting precision and the dynamic response speed of the flow can be increased, and the liquid flow in the micro-channel can be adjusted accurately and rapidly.

The invention discloses a light high-accuracy digital control system for a miniature flywheel. The system belongs to a kind of posture control execution mechanism applied to miniature satellites which are lighter than 100Kg, and mainly comprises a field programmable gate array (FPGA) module, a three-phase full-bridge driving device, an RS-232 communication circuit, a Buck converter, an analogue-to-digital (AD) sampling circuit and a signal conditioning circuit, a Hall signal filter and the like, wherein the FPGA module comprises an instruction parser, a moment-current converter, a single-neuron adaptive proportion integration differentiation (PID) controller, a pulse width modulator (PWM), a commutation logic signal generator and the like. By the invention, a nonlinear transformation online correction method is adopted; the digital control system for the miniature flywheel is formed by taking the FPGA module as a control core based on a single-neuron adaptive PID control algorithm; and the high-accuracy moment output of the posture control execution mechanism for the miniature satellite is realized by adopting a moment mode. The invention has the characteristics that: the algorithm is simple and easy to implement; the system is quick in response, low in power consumption, high in reliability, flexible in design and particularly suitable for the miniature satellite; the power density of the miniature flywheel is increased; the mass and volume of the miniature flywheel are decreased; and cost is decreased.

The invention relates to a pure electric vehicle cooling system control method based on deep reinforcement learning, which comprises the following steps: first, obtaining the temperature of the powerbattery of the pure electric vehicle, the working current of the power battery, and the ambient temperature information; Construct DDPG algorithm model, carry on reinforcement learning training, get agroup of optimal PID control parameters of electronic pump. The PID control quantity is obtained by the PID input quantity, and the electronic pump is controlled based on the PID control quantity. The work of the electronic pump changes the flow rate of coolant in the power battery cooling system to achieve the purpose of cooling the power battery. At the same time, the information of the power battery is transmitted to the environment sensing module, and the first step is returned to circulate the whole process. The invention introduces the depth reinforcement learning into the PID control algorithm, the depth reinforcement learning can better interact with the environment, has the self-learning function, adapts to the dynamic characteristics of the uncertain system, and therefore can adapt to the complex and changeable characteristics of the pure electric vehicle running environment, and realizes on-line control under different actual scenes.

The invention discloses a high-speed nano precision movement control method and system for a piezoelectric ceramic driver and belongs to the technical field of movement control and precision manufacturing. The high-speed nano precision movement control method for the piezoelectric ceramic driver comprises firstly establishing a magnetic hysteresis nonlinear accurate model H [.] and an inverse character expression H <-1> [.] and designing a feedforward controller based on the H [.] to eliminate magnetic hysteresis nonlinearity of the piezoelectric ceramic driver; identifying a linear dynamic model G (s) of a piezoelectric ceramic driver with magnetic hysteresis compensation through a system identification method and designing an initiative damp controller which is used for increasing the gain margin of the system according to dynamic characteristics of the G (s); finally achieving high-speed nano precision movement control through a PID (Proportion Integration Differentiation) control algorithm. The high-speed nano precision movement control method for the piezoelectric ceramic driver can eliminate piezoelectric ceramic driver magnetic hysteresis nonlinearity and resonance vibration influences to the system movement speed and precision, is convenient and practical and can achieve real-time control.

The invention relates to a control system for flue gas denitration based on a mathematical model. According to the invention, the difference between the actual emission of a flue gas NOx and the theoretical emission calculated by a NOx model acts as a modified value of a NOx emission set value, then an inverse model of a controlled object is used as a controller, and a real-time control instruction of an ammonia injection actuator for the next step is calculated. Meanwhile, the control system is designed to be a following control system, and the NOx set value is realized by superposing a function of a boiler main control instruction and a function of the boiler total air volume through a manual operating instruction of the operating personnel, thereby solving a problem that denitration control cannot pre-judge or accurately control the ammonia injection amount in a control strategy based on PI and PID control algorithms at present.

The invention provides a three-phase voltage type rectifier and a control method thereof. Through providing the high-robustness three-phase voltage type rectifier, a better inhibition effect on both overshooting and steady state error of a system is achieved while the high utilization rate of the voltage of an electric grid is guaranteed. The three-phase voltage type rectifier and the control method thereof have the following advantages: 1, the utilization rate of the electric grid can be increased by 15.4% through adopting an SVPWM (Space Vector Pulse Width Modulation) method compared with that achieved by an ordinary PWM (Pulse Width Modulation) method; 2, a voltage loop adopts a sliding-mode variable structure control (VSC) algorithm to replace the traditional PID (Proportion Integration Differentiation) control algorithm, thus the three-phase voltage type rectifier can rapidly respond to the voltage change of a direct current side; and 3, the voltage loop adopts a PID and VSC combined control method to replace the traditional PID control algorithm, so that the three-phase voltage type rectifier can rapidly respond to current change and can output stable control signals, and then, the overshooting and steady state error of the direct current side are reduced.

The invention discloses a tracking control method and a tracking control system. According to the invention, a target with the highest matching degree with feature information of a tracking target in a current video frame image is taken as a target to be tracked, the position deviation of a central position of the target to be tracked relative to a central position of the current video frame image in real time and a proportional change rate of the area occupied by the region area of the target to be tracked in the current frame image are calculated in real time, a PID control algorithm is adopted for the position deviation and the proportional change rate, and accurate control for the rotation angle and focusing of a spherical camera is realized, so that the target to be tracked is ensured to stay at the middle of the view field of the spherical camera in a fixed size, and the tracking performance for the target to be tracked is enhanced.

The invention relates to a motor speed regulation control algorithm, in particular to a BP (back-propagation) neural network PID speed regulation control algorithm based on fuzzy control. The BP neural network PID speed regulation control algorithm based on fuzzy control is designed in order to solve the problems of static difference and low convergence rate of a traditional dual closed-loop DC speed regulation system based on BP neural network PID control. The BP neural network PID speed regulation control algorithm based on the fuzzy control comprises steps as follows: firstly, the structureof a BP network is determined, input and output of each layer of the network are calculated, then output of a controller is calculated with an incremental PID control algorithm, parameters of the PIDcontroller are adjusted online in real time according to self-learning ability of the BP network, the optimal PID control parameter is obtained, static errors of the system are eliminated by the aidof the fuzzy control, and accordingly, adjustment of the rotating speed of the DC motor is realized. The BP neural network PID speed regulation control algorithm has beneficial effects as follows: theBP neural network PID controlled DC motor speed regulation system based on the fuzzy control can eliminate the static errors, the convergence speed is high, and good static and dynamic performance, anti-interference performance and robust performance are achieved.

The invention relates to an energy-controllable output device for a fuel cell and a control method. Through modularized structural design, the energy-controllable output device can control energy output of the fuel cell. The energy-controllable output device comprises a voltage-boosting regulating module, a voltage-reducing regulating module, a CAN (Controller Area Network) bus-based main control module and a fault diagnosing and alarming module. Through 2-stage conversion technology, the input voltage withstanding range is wide, the output voltage, the output current and the output power are controllable, and the power output energy of a load can be automatically tracked; the energy-controllable output device is provided with an IGBT (insulated gate bipolar translator) driving circuit with electrification protection, and the fault diagnosing and alarming module, so that the working safety of the energy-controllable output device is improved; through a soft start control and a 4-combination PID (proportion integration differentiation) control algorithm, the working accuracy and the working stability of the energy-controllable output device are improved; and the energy-controllable output device is high in conversion efficiency, can be applied to not only a fuel cell, but also other energy devices with very wide voltage output ranges, and is applicable to various electrical and electronic fields.

The invention provides a high-speed high-accuracy multi-axis PCB (Printed Circuit Board) numerical control drilling machine, which comprises a servo driving system, a multi-axis controlled mechanical transmission system, a motor device, a coupling, a position feedback module and a motion controller, wherein the mechanical transmission system is connected with the servo driving system through the coupling and the motor device in sequence; the position feedback module is connected with the mechanical transmission system and the servo driving system; the servo driving system is used for generating a driving signal by using a PID (Proportion Integration Differentiation) control algorithm according to a received control signal and a received feedback signal to drive the motor device; then the mechanical transmission system is driven to move stably by the motor device through the coupling; and the motion controller is built in a computer for controlling and coordinating the motion of each component in the mechanical transmission system. Thus, shock can be reduced during movement and drilling of the drilling machine, and the entire drilling machine can be quickly, accurately and stably controlled.

A worm wheel type driving pipeline robot system based on a high-strength spring wall press apparatus is characterized by comprising a body mechanical structure and a control system; the body mechanical structure comprises a spiral head, a body and a holding frame; the body is a main body of the robot; the working method is that the robot system is a fully-closed loop servo control system taking wheel linear speed as a feedback quantity through a fuzzy adaptive PID control algorithm. The advantages of the robot system are: (1) the robot system can steadily and flexibly move within a tilted and vertical pipeline with a minimal variable diameter; (2) the robot system exhibits good dynamic responsiveness, robustness and stability; (3) signal transmission is convenient; and (4) the robot system is highly controllable and is high in accuracy.

The invention relates to a method and apparatus for synchronously controlling a lifting device of a self-elevating ocean platform. The method comprises: (1), measuring rotating speeds and positions of a plurality of groups of motors of a lifting device of a self-elevating ocean platform; (2) selecting an average rotating speed of the plurality of groups of motors and comparing the average rotating speed with the rotating speed of each motor to obtain a difference value, and carrying out processing by using a PID control algorithm to obtain a speed synchronization compensation control value; (3) selecting a position average value of the plurality of groups of motors and comparing the position average value with the position of each motor to obtain a different value, and carrying out processing by using a PID control algorithm to obtain a position synchronization compensation control value; (4) measuring a tilt angle of the self-elevating ocean platform by using a tilt angle sensor; (5), synthesizing a speed tracking controller output signal, the speed synchronization compensation control value and the position synchronization compensation control value to obtain a control signal and outputting the control signal; and (6), with the control signal, controlling the rotating speeds of the motors to achieve an objective of synchronous controlling of the plurality of groups of motors. With the control technique, the lifting speed and the lifting height can be taken into consideration simultaneously and thus the stable lifting requirement of the platform can be met.

The invention discloses an FPGA-based thin film rolling tension control system and method. The system comprises a tension signal collection module, a thin film rolling tension control module, a thin film rolling module and an upper computer operation panel. A programmable logic device FPGA controls a chip to achieve a fuzzy PID control algorithm, the speed controlled quantity of a brushless direct current motor is obtained, a double closed-loop control algorithm of the brushless direct current motor is combined, then signals are controlled to be correspondingly changed and adjusted when tension changes in the rolling process of a thin film, and constant control over the tension in the rolling process of the thin film can be achieved through real-time collection of tension of the thin film by utilization of the fuzzy PID control algorithm; the development cost is low, the integration level of the system is high, the steady state performance is good, the response speed is high, the control precision is high, and adaptability is high.

The present invention discloses a variation particle swarm optimized BP neural network PID control algorithm. The algorithm comprises a step 1 of initializing a BP neural network; a step 2 of initializing a variation particle swarm optimization algorithm; a step 3 of determining an input signal of the BP neural network; a step 4 of calculating a PID control system output adjustable parameter; a step 5 of updating a particle individual optimal value and a global optimum value; a step 6 of carrying out an variation operation; a step 7 of determining whether to end iteration; and a step 8 of determining the PID control system output adjustable parameter. The variation particle swarm optimized BP neural network PID control algorithm of the present invention does not need to establish an accurate mathematical model, can automatically identify a controlled process parameter and an automatic setting control parameter and adapt to the parameter change of a controlled process, and also overcomes the defects that a reverse propagation error correction method of the conventional BP neural network is slow in execution speed, and is caught in the local minimum very easily, and possesses a stronger robustness and a more excellent control effect.

The invention relates to a control method applied to a threshing and redrying production line, providing a predictive PI controller based on a model. The control method is composed of a PI control item and a predictive control item. Based on a flue-curing barn temperature object, four flue-curing barn temperature controllers are designed by an advanced predictive PI control algorithm, thus avoiding the problems of low regulation speed and big fluctuation of the traditional PID control algorithm; based on a cooling room generalized moisture object and an outlet generalized moisture object, thecooling room moisture control scheme and the outlet moisture control scheme are respectively designed by adopting self-adaption anti-interference pseudo prediction PI control algorithm, thereby greatly improving control precision and enterprise economic benefit. The invention has the advantages that the control method is a control algorithm based on the model, and the PI control item can improve controller robustness; the predictive control item can predict future control function according to the control function in a certain past period, eliminating control blindness, and ensuring that the production is totally in autocontrol in the closed loop mode.