66results about How to "Solve overshoot" patented technology

The invention discloses an end effect suppression method based on the neural network ensemble and B-spline empirical mode decomposition (BS-EMD). The end effect suppression method includes the steps as follows: A, vibration signals are measured and obtained by utilizing a speed sensor; B, the signals are continued leftwards and rightwards by adopting the neural network ensemble; C, a mean curve of the signals is obtained by utilizing a B-spline mean function; and D, empirical mode decomposition (EMD) is conducted, data at the two ends of the mean curve are abandoned, and a plurality of intrinsic mode function (IMF) components corresponding to original signals are obtained; and E, each IMF component is analyzed, and fault feathers are extracted. The end effect suppression method has the advantages that an end effect can be effectively suppressed, and the influence of the end effect on BS-EMD results is avoided.

A SRD narrow pulse signal generator basis on clock drive belongs to the electronic technical field, which relates to the technique of super wide-band communication, pulse radar and pulse source. The generator comprises a clock source, a coupling capacitance, a resonance matching circuit, a pulse forming circuit and a pulse shaping circuit. The invention has simple circuit and convenient modulation. Complexity and power consumption of the circuit is reduced under the help of automatic bias circuit of SRD which is formed by the matching network and the load resistance, extended power consumption and thermal noise of the circuit are further reduced since all the resonance matching circuits adopt reactive element, particularly a lumped inductance L3 and a Schottky diode are introduced to be a shaping circuit, pulse stretching is effectively inhibited, and pulse delay fall time is greatly compressed, and simultaneously the problem of pulse side lobe and overshoot can be effectively solved. Narrow pulse signals which are generated by the invention have good wave shaping symmetrical characteristic, which can be used as triggering source of gaussian pulse of higher order differential with high quality and signal source of super broadband wireless communication and impacting radar.

The invention discloses a permanent magnet brushless DC motor driver control method. The method is used for control of a motor drive servo control system. The system has relatively good control accuracy and dynamic response performance. The method comprises the steps of firstly reading values of three commutation HALLs through software to obtain an actual position of a rotor when a motor is started, detecting an angular position omega<ref> of the rotor through a rotor position sensor after starting, and simultaneously calculating a speed n of the rotor; detecting a stator current FOC control algorithm to obtain detection values i<d> and i<q>; outputting AC / DC shaft voltage values u<d> and u<q> through a PI adjuster separately, generating voltage values u<alpha> and u<beta> after coordinate transformation to obtain an SVPWM drive signal; and finally outputting sixth paths of control pulse signals and driving six MOSs to drive the motor. The permanent magnet brushless DC motor driver control method is suitable for control of an intelligent obstacle avoidance robot and is achieved by adopting a DSP processor; the control process is achieved through a vector control strategy of which direct axis current is zero; the contradiction between overshoot and the rapidity is solved; the anti-jamming capability of the system is improved; and the high-performance requirement is met.

The invention discloses a method for adjusting pressure of an anesthesia machine and a breathing machine through flow and pressure common control, which is characterized by comprising the following steps of: calculating a pressure value under the current flow by using a formula P=F*R in a pressure control mode, wherein P is pressure; F is the current flow; and R is air resistance; estimating the pressure at a next moment under the current pressure value by using a Kalman estimation algorithm into which sub-items with control parameters influencing an overall estimation result are added; substituting the estimated pressure value into an error system to calculate a control error quantity, performing proportion integration differentiation (PID) control on the control error quantity, and converting into control pressure required at the next moment; converting the control pressure into standard control flow by using the formula P=F*R; and inputting the converted control flow into a flow PID ratio controller for flow feedback control.

The invention discloses a manipulator motion planning method based on a bias redefined neural network. The manipulator motion planning method based on the bias redefined neural network comprises the steps of establishing a kinematics equation of a redundant manipulator according to a model and parameters of an actual manipulator; transforming the kinematics equation of the redundant manipulator into a kinematics equation of a velocity layer, and describing the kinematics equation of the velocity layer as a smooth time-varying linear equation; acquiring a joint angle of the manipulator and endtrack information, constructing a time-varying parameter matrix according to the parameters of the manipulator, the joint angle of the manipulator and the end track information, and acquiring a corresponding time derivative; designing a bias function according to the smooth time-varying linear equation; designing a time-varying linear equation solver for a redundant robot arm by redefining a recurrent neural network with the bias function and combining the time-varying parameter matrix and the time derivative thereof; and obtaining a desired trajectory by solving the time-varying linear equation solver. According to the manipulator motion planning method based on the bias redefined neural network provided by the invention, the redundant manipulator motion planning can be carried out stablyand accurately by using the bias redefined neural network solver.

The invention belongs to the technical field of hydraulic adjustment and particularly relates to an automatic oil feeding type isomorphic double-cylinder leveling system. The system comprises a driving cylinder, a controller, a proportional solenoid valve, a driven cylinder and a redundancy inclined angle sensor, wherein rodless cavities of the driving cylinder and the driven cylinder are communicated and rod cavities of the driving cylinder and the driven cylinder are communicated; the controller is respectively and electrically connected with the redundancy inclined angle sensor and the proportional solenoid valve; the redundancy inclined angle sensor is used for feeding a detection result back to the controller; an output signal of the controller drives the opening and closing of the proportional solenoid valve; the proportional solenoid valve (3) can be used for carrying out oil supplementation on oil leaking cavities in the driving cylinder (1) and the driven cylinder (4). With the adoption of the system, the leveling process is safe and convenient and does not need to be subjected to artificially interfered; the problem that a working platform of an overhead working truck is inclined, caused by leaking of oil, is solved.

The invention provides a method and device for controlling pan-tilt tracking camera shooting, and the method comprises the steps: calculating the speed v and the speed v1 of a previous frame accordingto the positions of a tracking target in a current frame of picture and the previous frame of picture, and determining the acceleration delta(v) through the speed v and the speed v1; determining a distance difference value x with the center of the picture; determining the maximum detection distance Smax of the distance tracking target; determining whether the tracking target and the pan-tilt movein the same direction or not according to the positive and negative values of delta(v)*delta(x), and adjusting the Smax by using delta(x) in combination with the positive and negative values of v; and determining the maximum acceleration Amax of the cradle head according to the adjusted Smax, and controlling the cradle head to rotate by utilizing the final issuing speed v2 of which the differencevalue with the speed v1 is not greater than the Amax. According to the invention, the problems of overshoot and oscillation generated when a traditional algorithm is used for carrying out pan-tilt tracking motion control are solved; the success rate of tracking the tracking target is improved by combining the characteristics of the detection algorithm.

The invention discloses a quick precise stable-control method for controlling output of a belt weigher system. The method is realized in a way that: when a target flow error range is smaller than a threshold, controlling by using a PID model; and when the target flow error range is greater than the threshold, adjusting to a linear model to find out the optimal control output point, and limiting the upper and lower limits of the control output. After the control method is used in a belt weigher instrument, when a user uses the belt weigher control instrument with on-line linear adjustment function, only one target value needs to be provided; and if the target value is within the reasonable range, the model can quickly find out the optimal control value. The invention solves the contradiction between overshooting and response time, and thus, the invention has the advantages of small overshooting of control effect, small fluctuations and quick reaction.

The invention discloses a ship flow prediction method based on deep learning. The ship flow prediction method is based on an improved isolated forest-complementary set empirical mode decomposition-long short-term memory neural network. Firstly, the problems of noise and abnormal points in original data are considered, and the abnormal points in the data are eliminated by using an isolated forest algorithm; secondly, in order to further improve the prediction precision, input data is decomposed into intrinsic mode function components and residual components of different frequencies by using animproved complementary set empirical mode decomposition algorithm, each intrinsic mode function and residual error are predicted by using a long-term and short-term memory neural network separately, and finally, superposition reconstruction is carried out on a prediction result. According to the method, the prediction precision is improved, and the method has good adaptability to long-term or short-term time series data.

The invention discloses a non-overshooting servo control method for an aerial camera stabilization platform, and belongs to the technical field of automatic control. A position command of a rolling channel is planned, a curve in which transition to the position command angle from the initial gesture angle according to a 1 / 4 positive rotation curve is carried out is obtained, and thus the step position command given by a camera control system is converted into a smooth transition curve; and the gesture angle of an aiming line is calculated through gesture calculation algorithm, and thus the angle position of the stabilization platform at the geographic coordinates can be obtained. According to the method of the invention, the problem that overshooting happens during the known stabilization platform step process can be solved, and the efficiency of overhead shooting can be greatly improved; the sight line of the camera stabilization platform can be controlled to precisely point to the target channel at the geographic coordinates; and the curve planning algorithm and the gesture calculation algorithm used by the invention is simple, convenient to realize, and good to transplant, and thus, the method has wider application prospect.

The invention discloses a photoelectric tracking system control method based on a differential tracker, and belongs to the field of photoelectric system tracking control. For the current situations that only the position is used for back feeding signals, negative factors of amplifying the noise through a differentiation element, and the like exist in traditional PID controllers cannot meet the tracking control requirements with the higher precision. According to the photoelectric tracking system control method based on the differential tracker, the differential tracker and a PID controller arecombined effectively, the transition process is arranged reasonably, fast tracking without overshooting and synchronous differential output for input signals are realized, the noise amplification effect can be effectively lowered, the steady-state error is reduced, controller design is simplified and the control quality is improved, and the tracking performance of photoelectric tracking equipmentof a moving platform is further improved.

The invention provides a heat dissipation control method and device for a vehicle-mounted fuel cell, belongs to the technical field of fuel cell temperature control, and aims to solve the problems that heat dissipation control in the prior art is relatively high in difficulty and cannot be compatible. The method comprises the following steps that: the real-time water temperature at a cell stack cooling liquid outlet at the current moment is acquired; the difference value between the real-time water temperature and target temperature is input into a temperature control model, the initial rotating speed of a cooling fan is obtained, and the cooling fan is controlled to be started and operates at the initial rotating speed; the real-time water temperature change at the cell stack cooling liquid outlet after the cooling fan operates is monitored; according to the real-time water temperature change, whether the current working condition meets a feed-forward updating requirement or not is judged, if the current working condition does not meet the feed-forward updating requirement, feed-forward parameters in the temperature control model are kept unchanged, and the cooling fan is controlled to operate at the original rotating speed, and otherwise, the feed-forward parameters are updated according to a preset rule, the new rotating speed of the cooling fan is obtained, and the cooling fan is controlled to operate at the new rotating speed. The method and device can automatically adapt to factors such as environment temperature, vehicle speed, altitude and the like.

The invention discloses a built-in permanent magnet synchronous motor anti-interference controller and a design method thereof. The controller comprises a controller unit, a nonlinear observation unitand an execution unit. The designed anti-interference controller does not depend on an accurate mathematical model, and the overshoot problem is solved. It can be known from the simulation tracking effect that no overshoot phenomenon occurs. The designed nonlinear observation unit has the characteristic of higher response speed. The number of adjustable parameters is reduced to two, and the complexity of parameter adjustment is greatly reduced through the design of the nonlinear observation unit by adjusting the parameters beta and delta. According to the nonlinear observation unit, externalload disturbance and internal uncertain parts of the built-in permanent magnet synchronous motor are used as total disturbance. The built-in permanent magnet synchronous motor can accurately observe and estimate the total disturbance, speed and position, the simulation result shows that good tracking performance can be realized. The dynamic performance and anti-interference capability of the built-in permanent magnet synchronous motor are improved. The built-in permanent magnet synchronous motor is beneficial to the application in a control servo system.

The invention discloses a method and a circuit for the overvoltage protection control of a four-switch Buck-Boost converter. First, whether overvoltage occurs in the output voltage of the converter is judged. If overvoltage exists, no matter the converter works in which mode at the moment, a first switch and a fourth switch are controlled to be turned off, and a second switch and a third switch are turned on. On one aspect, the energy input of an input end and the energy transmission of an output end are cut off. On the other aspect, energy in an inductor is consumed by an open circuit which is formed by the second switch, the inductor and the third switch. The problem that the overvoltage is output when the load suddenly changes is well solved.

The invention belongs to the technical field of control technology and metal forming, and particularly relates to a limited control set-based sensorless press machine full-closed-loop control system and method. According to the system and method, the difference between a forming process curve and the actual position of a sliding block is used as a whole machine control system control instruction position input, a kinetic model is established, torque calculation is carried out, and the calculated result is taken as an input of a torque prediction control algorithm. The system and method have the advantages that a non-sensing control algorithm module and a torque prediction algorithm module of a limited control set are arranged in a servo motor driver, the rotating speed and the electromagnetic torque prediction value are calculated, the value function is finally obtained, the position information of the sliding block can be added into the value function to control the position of the sliding block to not be overly controlled, the dynamic performance is obviously improved, the anti-interference performance of the motor servo driver can be improved, the reliability is remarkably improved, and the cost of a servo motor is greatly reduced.

The invention discloses a boiler flue gas denitrification control method based on a self-adaptive fuzzy PID algorithm. The implementation processes comprises the following steps of collecting an actual measured value of the nitrogen oxide at a flue gas outlet, and calculating a deviation value and a change rate of the nitrogen oxide at the flue gas outlet; determining membership functions of nitrogen oxide deviation, a deviation change rate, a proportion change value, an integral change value and a differential change value; outputting a new fuzzy set membership function according to a fuzzy control rule, calculating the proportional change value, the integral change value and the differential change value according to the fuzzy set membership function, and adjusting corresponding parameters in the PID in real time to obtain new PID parameters; and controlling the ammonia spraying amount according to the new PID parameters. According to the denitrification control method disclosed by the invention, the PID control parameters can be adjusted by adopting a fuzzy control algorithm, on one hand, the condition that the content of nitrogen oxide at the outlet exceeds the standard irregularly can be avoided; on the other hand, the usage amount of ammonia gas can be more reasonably and efficiently controlled.

The invention relates to a method for adjusting the AGC (Automatic Generation Control) of a water turbine generator set, which includes the following steps: (1) dividing the load of a generator set into load segments; (2) carrying out large load disturbance test and small load disturbance test on N different load segments, and determining the target load of large load disturbance test and the target load of small load disturbance test; (3) determining the power adjustment quantity corresponding to the N different load segments in the processes of large load disturbance test and small load disturbance test; (4) establishing a generator set AGC parameter adjustment table; and (5) importing the AGC parameter adjustment table to the AGC to adjust the parameters of the generator set. The problem of overshoot and undershoot during AGC adjustment under part of working conditions is solved. Thus, the method adapts to different load segments and different eligible adjustment quantity.

The invention relates to the field of power management, and discloses an output voltage regulation device and method used for achieving rapid voltage regulation and restraining overshooting or over-dropping in output voltage regulation. The device comprises a voltage regulation circuit, a control circuit, a power-level circuit, a filter network and feedback network. The input end of the feedback network is connected with the output end of the filter network and used for collecting the output voltage VO of the filter network, the output end of the feedback network is connected with a feedback voltage node of the control circuit and used for outputting feedback voltage to the feedback voltage node of the control circuit, and the output end of the voltage regulation circuit is connected between the output end of the feedback network and the feedback voltage node of the control circuit and sued for regulating the current I of the feedback voltage node; the output end of the control circuit is connected with the input end of the power-level circuit and used for regulating the output duty ratio of the filter network according to the current I of the feedback voltage node, and the filter network is used for filtering the output duty ratio to obtain the regulated output voltage VO.

The invention discloses a fault crossing control method of a wind farm based on a synchronous camera adjuster, which detects alternating voltage value of a grid-connected point of the wind farm in real time, and starts the synchronous camera when judging the voltage sag fault; The difference between the AC voltage standard per-unit value and the rated voltage standard per-unit value of the grid-connected point is made, and after the difference value is limited, the PI control is carried out to obtain the processed difference value; The processed difference value is added with the voltage rating per-unit value to obtain the input value of the exciter in the synchronous adjuster. The exciter changes the output reactive power of the synchronous adjuster according to the change of the input value, pulls up the voltage at the grid point until the voltage sag fault is eliminated, turns off the synchronous adjuster, and completes the fault crossing. The invention realizes the fault crossing of a wind farm in practice, solves the problem of voltage overshoot after the fault ends, and is suitable for wind farms made of different types of wind turbines.

The invention discloses a position servo control system based on stepping drive and a control method thereof. The control system comprises a controller, a stepping motor driver, a stepping motor, a speed reducer and a servo rotating platform. The controller receives position setting of an upper computer to finish position control of the rotating platform, and transmits a speed command to a stepping motor driver through a connection cable between the controller and the stepping motor driver to finish speed control of the stepping motor. The controller receives the position setting through an upper computer interface, finishes position control operation in a processor and outputs pulse output signals and direction output signals to the stepping motor driver to control operation of the stepping motor. Closed-loop position control is formed in the processor through the position setting of the upper computer and the virtual position feedback, and a control function of the position servo system is realized through maximum frequency limit and frequency fluctuation rate control.

The invention discloses an online adjustment method for the control parameters of an autonomous aircraft based on MCMC optimized Q learning, which includes the following steps: first, doing statisticsof possible changes of the PID control parameters of an aircraft according to the actual situation to get an action set of parameter adjustment, and initializing the PID control parameters accordingto the aircraft control experience; then, randomly selecting an action to act on the autonomous aircraft, carrying out sampling through an MCMC algorithm according to the function value Q* of each action obtained in a Q learning algorithm to get an action to be taken next moment, and adjusting the learning factor l in the Q learning algorithm through an SPSA step size adjustment algorithm with thepassage of time; and finally, getting the optimal control parameters in the current environment through repeated adjustment of the control parameters. The problems of overshoot and delay in the navigation process of an autonomous aircraft are solved, and an autonomous aircraft can quickly adapt to the change of the environment and quickly and steadily reach the destination.

The present invention provides a quasi-resonant Boost soft start circuit. The circuit comprises an input voltage interface, a working power supply Vcc, a boost circuit, a quasi-resonant control chip, an output voltage detection feedback circuit, a soft start circuit and an output circuit. The input voltage interface is connected with the boost circuit; the output voltage detection feedback circuit is electrically connected with the boost circuit and the output circuit respectively; the quasi-resonant control chip and the soft start circuit are both connected with the working power supply Vcc; the output voltage detection feedback circuit is provided with a detection feedback end; the soft start circuit is provided with a soft start end; the quasi-resonant control chip is provided with a feedback pin; and the detection feedback end of the output voltage detection feedback circuit, the soft start end of the soft start circuit and the feedback pin of the quasi-resonant control chip are connected together. According to the quasi-resonant Boost soft start circuit provided by the present invention, the soft start circuit is added to a quasi-resonant mode boost PFC, so that the overshoot and inductance saturation problems of an electrolytic capacitor are perfectly solved.

The invention provides a double proportional integral controller parking control method and device, electronic equipment and a storage medium, and relates to the technical field of brake control. Themethod comprises the steps of obtaining a reference braking speed curve; obtaining a first output result through a first proportional integral control module based on the reference braking speed in the reference braking curve, and the first proportional integral control module being used for processing first-order speed control; obtaining a second output result based on the first output result through a second proportional-integral control module, the second proportional-integral control module being used for processing first-order acceleration rate or deceleration rate control; performing time domain conversion on the second output result to obtain an actual braking speed curve; and braking the controlled object based on the actual braking speed curve through a train automatic driving system. According to the method, through rapid level adjustment of the second-order PI, the problem that the speed value obtained through a common PI algorithm is large in fluctuation is solved, the speed is converged within a small range, and the subsequent parking accuracy is improved.

The invention provides a double-iron-core closed-loop current sensor, which comprises a circuit board, a winding coil and an iron core shell wound by the winding coil, and is characterized by furthercomprising an iron core without an opening, an iron core with an opening and a magnetic field detection element, wherein both the iron core without an opening and the iron core with an opening are located in the iron core shell, the iron core with an opening is provided with an opening running through the iron core with an opening, and the magnetic field detection element is placed in the opening.The double-iron-core closed-loop current sensor solves problems of output current oscillation, overshoot and inaccurate eccentricity measurement existing in dynamic response of a single iron core through placing the magnetic field detection element in the opening of the iron core with an opening, can greatly improve the dynamic index of the double-iron-core closed-loop current sensor, effectivelyreduces the output current oscillation and overshoot and greatly reduces an eccentric phenomenon caused by unequal reluctance at the same time.

This invention relates to a transmission line distribution structure in high speed printed circuit board, which is in the connection of north bridge chip, AGP slot and S terminal, said north bridge chip connected with AGP slot and S terminal by T type topological transmission line structure. Said invention can effectively solves the crosstalk and overshoot problems in current line distribution structure and raises the signal transmission quality.

The invention provides a low-dropout linear voltage stabilizing circuit and electronic equipment, the circuit comprises a feedback unit and a transient response unit, the feedback unit comprises a power transistor and a load module, the power transistor is electrically connected with the load module, and the feedback unit adjusts the output voltage of the feedback unit by adjusting the current flowing through the power transistor; the output end of the transient response unit is electrically connected with the power transistor, the voltage of the power transistor is changed when the current of the load module is subjected to step-type jump, and the transient response unit adjusts the output voltage of the feedback unit under the condition that the voltage of the power transistor is changed, so that the output voltage of the load module is adjusted. The low dropout linear voltage regulator solves the problem of overlarge overshoot or undershoot voltage of a low dropout linear voltage regulator in the prior art, effectively improves the transient response characteristic of the low dropout linear voltage regulator circuit, reduces output voltage overshoot or undershoot caused by load abrupt change or power supply voltage abrupt change, and keeps the output voltage stable.

The invention aims to solve a problem of course angle control of an autonomous underwater vehicle. An improved firefly algorithm is used; the invention provides an autonomous underwater vehicle attitude control method based on an improved firefly PID method. PID control parameters are used as values of a firefly solution space; the error performance is used as an evaluation function of an improvedfirefly algorithm; the parameters of the PID controller for the course angle of the autonomous underwater vehicle are adaptively adjusted, a simulation result shows that the improved algorithm solvesthe problems of overshoot and overlong response time caused by improper selection of the parameters of the controller, and the improved firefly algorithm can be used for adaptively modulating the PIDcontrol parameters.