197results about How to "Improve control effect" patented technology

The invention relates to the technical field of laser control, in particular to a high-power fiber laser stable output control method and system. The method comprises the following steps: monitoring a multi-mode sensing signal of an optical fiber laser in real time based on an optical fiber sensor array; performing dynamic optical fiber sensing change analysis on the multi-mode sensing signal of the optical fiber laser to generate a dynamic optical fiber sensing change characteristic; laser output phase distribution analysis is carried out on the dynamic optical fiber sensing change characteristics, real-time power feedback adjustment is carried out, and a dynamic light beam power feedback adjustment strategy is constructed; overheat power unbalance analysis is carried out based on a fiber laser multi-mode sensing signal, and local temperature control power fine tuning is carried out, so that a local temperature control power fine tuning strategy is constructed; and performing sensor position calculation on the optical fiber sensor array one by one, and performing nonlinear optical effect analysis to generate nonlinear optical effect characteristics. According to the invention, efficient and stable laser output control is realized.

The embodiment of the invention provides an aircraft attitude control model generation method and device, equipment and a medium, and is applied to the technical field of aircraft control. The method comprises the following steps: acquiring a flight task and a flight environment; according to a pre-constructed simulation model, carrying out analogue simulation on the flight task and the flight environment, and outputting simulated flight data; training a pre-constructed reinforcement learning model by taking a flight strategy as an output and the simulation flight data as an input; and when a preset stop condition is met, stopping training, and taking the trained reinforcement learning model as an aircraft attitude control model. In this way, the training period and training cost of the controller can be reduced, and the aircraft attitude control model with a better control effect can be trained.

The invention provides a stabilization control method and system for a fuel filling ship at a zero navigational speed. The method provided by the invention comprises the following steps: acquiring rolling data and wind wave data of a refueling ship under a target sea condition in a fuel refueling process in real time; the rolling data and the wind wave data are processed based on a radial basis function neural network, and the precession angular velocity of the stabilization gyro device under the target sea condition is obtained through calculation; the stabilization gyro device is controlled to rotate at the precession angular speed, the stabilization gyro device generates a gyroscopic effect and generates rolling moment, the rolling moment is converted into stabilizing moment for resisting rolling through precession motion, and the rolling angle of the filling ship is reduced; and the stabilizing moment is opposite to the vibration direction of the rolling. According to the method and system, rolling control of the filling ship at the low speed or the zero navigational speed is achieved, the stabilization torque can be adjusted in real time according to sea wave changes, and the stability and safety of the filling ship in the fuel filling operation process are improved.

The invention belongs to the technical field of AC motor transmission control, and relates to a permanent magnet synchronous motor dead zone compensation method based on a nonlinear flux observer. Measuring a motor induction current under a natural coordinate system, and obtaining an alpha-beta axis current through conversion; a non-linear flux observer in an alpha-beta coordinate system is used as a position observation model to obtain an actual rotor position estimation value, a rotating speed ring is formed, and sensorless control of the permanent magnet synchronous motor is achieved; constructing a q-axis voltage disturbance observer by measuring the phase voltage output by the inverter; taking the output of the q-axis disturbance observer as the input of a dead time calculation module to obtain a dead time estimation value; and according to the estimated value, calculating and obtaining a dead-zone compensation voltage, and compensating the output phase voltage of the inverter to realize dead-zone compensation. On the basis of a non-linear flux observer, a position-free control closed-loop structure is constructed, and instruction voltage is corrected, so that the influence of inverter dead time on the permanent magnet synchronous motor is reduced, and the position-free control performance is improved.

The invention discloses a motor electric control brake system clamping force self-adaptive correction method based on deep learning, and belongs to the technical field of chassis control, the method fully considers the wear condition of a brake pad in the use process, introduces a deep learning neural network optimization control strategy for the nonlinear change problem caused by the wear of the brake pad, and corrects the clamping force of the motor electric control brake system. The complex nonlinear relation between the clamping force estimated by the rotation angle of the motor and the actual clamping force is modeled as predictable probability distribution, and self-adaptive correction is performed, so that the clamping force control is optimized under the brake pad abrasion condition, the dynamic change caused by the brake pad abrasion is effectively dealt with, the real-time performance of system control is enhanced, and the system reliability is improved. The prediction precision and the response speed of the system are greatly improved, the stability, the reliability and the safety of the brake system are comprehensively enhanced, and meanwhile, the situation that a large number of sensors are adopted for real-time clamping force monitoring is avoided.

The invention discloses a ship container battery management system and a ship. The ship container battery management system comprises at least one battery management module which is connected with at least one battery pack and is used for acquiring data information of each battery cell in the battery pack; the cluster control management module is arranged corresponding to the battery cluster, and the cluster control management module is connected with the battery management module and used for generating state information of the battery cluster according to the data information; the battery cluster comprises at least one battery pack; a first control module and a second control module, the first control module and the second control module are connected with each other and are redundant standby for each other, and the first control module and the second control module are both connected with each cluster control management module; and the first control module or the second control module is used for controlling the cluster control management module to manage connection or disconnection of the battery cluster according to the data information and / or the state information. According to the technical scheme provided by the embodiment of the invention, the reliability of the battery management system is improved.

The invention discloses a flywheel energy storage control method, system and device and a storage medium, and is applied to the technical field of magnetic suspension flywheels, and the method comprises the steps: when a flywheel is in a static state and the charging work of the flywheel is started, controlling a machine side converter according to a principle that the rotation acceleration of the flywheel remains unchanged, the rotating speed of the flywheel is increased from zero to the minimum working speed nmin; when the rotating speed of the flywheel is within the range from nmin to the switching speed ns, the machine-side converter is controlled according to the principle that the output current of the machine-side converter is kept unchanged so as to charge or discharge the flywheel; and when the rotating speed of the flywheel is within the range from the switching speed ns to the maximum speed nmax, controlling the machine-side converter according to the principle that the output power of the machine-side converter is kept unchanged so as to charge or discharge the flywheel. By applying the scheme of the invention, the control of flywheel energy storage can be effectively realized, the charging and discharging efficiency is ensured, and the stability during charging and discharging and the power supply quality are ensured.

The invention relates to the technical field of multi-agent control, in particular to a second-order multi-agent system control method based on dynamic event triggering, and the method comprises the steps: building a kinetic model of a leader-follower second-order multi-agent system considering unknown external interference, and designing a distributed fixed time observer on the basis, so as to achieve the control of the leader-follower second-order multi-agent system. State information of the leader is estimated in real time; introducing a fixed time extended state observer to estimate external disturbance; proposing a sliding mode surface based on the observation error; a distributed fixed-time sliding mode consistency tracking control protocol is designed, so that tracking errors are accurately converged within fixed time, an ideal control effect can be achieved even if external interference exists, the communication burden is effectively reduced through introduction of a dynamic event triggering mechanism, and the sesame phenomenon is avoided; tracking consistency control of the multi-agent system can be realized in a fixed time, the robustness and reliability of the system are improved, and communication resources are saved.

The invention discloses a PMSM (permanent magnet synchronous motor) AC servo system speed control method based on improved particle swarm optimization optimization RBF (radial basis function) fuzzy neural network PID control, the system is composed of a speed outer ring and a current inner ring, and the current ring adopts a PI regulator. A speed loop is designed to be an RBF fuzzy neural network PID speed controller, an RBF fuzzy neural network is optimized by improving a particle swarm optimization algorithm, and optimal parameters kp, ki and kd suitable for the PID controller are output. Simulation analysis and experiment results show that compared with a common PID control strategy, a BP algorithm optimization fuzzy neural network PID control strategy and a particle swarm algorithm optimization RBF fuzzy neural network PID control strategy, the particle swarm algorithm optimization RBF fuzzy neural network PID control strategy based on the improved particle swarm algorithm has optimal control performance; the method has the advantages of being high in dynamic response speed, good in control stability, resistant to load disturbance and high in robustness, and the excellent speed control effect of the PMSM alternating current servo system can be achieved.

The invention relates to the technical field of motor control, in particular to a control method and system for a motor. The method comprises the following steps that a motor main control unit MCU obtains a motor angle parameter by obtaining a corresponding target motor rotating speed set by a receiving user and carrying out angle parameter reverse solution endowing; obtaining a direct axis direction current and a cross axis direction current and carrying out motor load control calculation to obtain a direct axis voltage control quantity and a cross axis voltage control quantity; transmitting the motor angle parameter, the direct axis voltage control quantity and the cross axis voltage control quantity to a space vector pulse width modulation (SVPWM) module and carrying out SVPWM modulation processing to generate a motor rotor control SVPWM waveform; and determining a phase voltage control value applied to each motor winding, carrying out control duty ratio adjustment analysis, and controlling the corresponding rotating speed and direction of each motor at the same time. The operation efficiency and the response speed of the motor can be improved.

The invention relates to the technical field of hybrid energy storage control strategies, and discloses a hybrid energy storage progressive model prediction control method based on optimal duty ratio tracking. The method comprises the following steps: setting a front-end MPC and a rear-end MPC which are used for controlling the on-off of a switching tube in a system, selecting an optimal duty ratio output corresponding to the minimum cost function of the front-end MPC, driving the on-off of the corresponding switching tube to stabilize the bus voltage, calculating the real-time optimal reference power of hybrid energy storage at the next moment, and taking the real-time optimal reference power as the real-time optimal reference value of the rear-end MPC after passing through a high-pass filter; and selecting the corresponding optimal switching state output when the cost function of the rear-end MPC is minimum, and driving a corresponding switching tube to be switched on and switched off, so that the output power of the super capacitor tracks a real-time optimal reference value given by the front-end MPC in real time, the power fluctuation is stabilized, and the bus voltage is further stabilized. According to the invention, the fluctuation of the bus voltage is smaller under the fluctuation of the load power; and optimal reference power transmission under model prediction control is considered, so that the control performance is optimized.

The invention relates to an input-limited optimal formation tracking control method based on adaptive dynamic programming. The method comprises the following steps: firstly, establishing a formation tracking consistency error model and a cluster communication model of each agent, and designing a feedforward control rate; defining a performance index function of each agent; secondly, deriving a Hamiltonian-Jacobian-Bellman equation corresponding to the defined performance index function according to a Bellman optimality principle, and solving an optimal feedback control rate theoretical formula; and finally, establishing a single evaluation network structure by using an adaptive dynamic programming method, performing approximate solution on the optimal feedback control rate, and designing a network weight update rate. The invention establishes an input-limited optimal formation tracking control method based on adaptive dynamic programming, and the method can be used for unmanned aerial vehicle cluster formation tracking control.

The invention relates to a vehicle control method and device, a vehicle, a storage medium and a program product. Driving parameters of the vehicle can be obtained; determining a target slip rate of each wheel of the vehicle according to the driving parameters, wherein the target slip rate represents a slip rate lower limit value for starting anti-slip control on the wheel; and performing driving anti-slip control on the wheels according to the driving parameters and the target slip rate. Therefore, the target slip rate for judging whether the anti-slip control needs to be started or not can be set for a single wheel, so that the driving anti-slip control of the vehicle is advanced from axle control to wheel control, and the anti-slip control of the vehicle can achieve a better control effect.

The invention discloses an electric vehicle auxiliary ridge crossing method and system, a storage medium and a vehicle. Whether a user selects an auxiliary ridge crossing function or not is judged through an information entertainment system; the vehicle control unit judges whether the vehicle running state, the power battery state, the driving motor system state, the gear state, the accelerator pedal state, the brake pedal state and the current vehicle speed state meet the auxiliary threshold crossing function requirement or not, and only needs to utilize an existing system to collect data and judge the data; related switching instructions and control instructions are sent to the driving motor controller and the information entertainment system according to the judgment result, extra related structures do not need to be added, the control cost is low, and the control effect is good. Through data interaction among the whole vehicle controller, the driving motor controller and the information entertainment system, auxiliary ridge crossing of the vehicle is achieved, the vehicle is switched from the torque mode to the rotating speed mode, the controlled object is changed from the motor torque to the motor rotating speed, the vehicle runs more stably, and the user experience feeling is better.

The invention discloses a long-acting anti-aging composition capable of quickly removing dark circles and application of the composition. The composition is prepared from the following components: beta-nicotinamide mononucleotide, glutathione, acetyl hexapeptide-8, acetyl tetrapeptide-5, snake venom-like peptide, arginine / lysine polypeptide, tocopheryl acetate and ergothioneine. According to the present invention, multiple functions are adopted, such that the effects of dark circle removing, repair, elasticity recovery, aging resistance and the like are provided so as to block the generation of dark circle, and the normal function of skin is ensured. The composition disclosed by the invention has the effect of quickly removing dark circles, and when the eye cream contains the composition, the eye cream can effectively remove the dark circles and has an obvious and quick effect within 15 minutes; after being used for a long time, the eye mask can remove dark circles and play a good control role.

The invention discloses a VSG current balance control method and system in a voltage imbalance state, and relates to the technical field of power electronics and power system application, and the method comprises the steps: taking current balance control as a core of integral control, building a VSG model, analyzing the output condition of the VSG in an imbalance power grid state, and obtaining a VSG current balance control result. VSG is controlled through active-frequency and reactive-voltage droop control, the instantaneous output power of the VSG is analyzed according to the instantaneous power theory, positive and negative sequence currents are decomposed when an unbalanced fault occurs in a power grid, and the targets of current balance and power constancy are achieved by controlling the positive and negative sequence currents and adding voltage correction. According to the invention, the current and electric energy quality control of the VSG is designed, and the output current balance, the active power constancy or the reactive power constancy are realized on the premise of not changing the characteristics of the VSG.

The invention relates to an intelligent inflation algorithm applied to an upper arm type upper-air sphygmomanometer, which comprises the following steps of: 1, after the sphygmomanometer enters a measurement state, acquiring and processing a pressure value signal by a central processing unit; 2, eliminating the interference of the pulse wave signal on the inflation slope through a filtering algorithm; 3, after the central processing unit obtains data from the pressure sensor, the increasing slope of the pressure value in the cuff is calculated at fixed time intervals; 4, after the slope is obtained through calculation, the slope is compared with a set target slope, and the inflation rate of the inflator pump is adjusted according to the slope difference degree. The low-pass filter is strong in denoising capability, can effectively filter high-frequency noise and a part with rapid data change, enables signals to be clear and reliable, and can reduce the influence and ensure the stability of inflation slope calculation due to the fact that pulse waves are coupled with noise signals generated by an inflation pump in the inflation process.

The invention discloses an emulsion pump loading valve speed regulation control system and a working method thereof. The emulsion pump loading valve speed regulation control system comprises a servo motor, a servo driver and an upper computer. The working method comprises the following steps: S1, inputting a pressure set value of the loading valve of the emulsion pump; s2, the upper computer calculates the input pressure set value of the loading valve of the emulsion pump through a PID (Proportion Integration Differentiation) controller to obtain a required rotating state and a required rotating speed of a servo motor and transmits the required rotating state and the required rotating speed to a servo driver; s3, controlling a servo motor by a servo driver, and enabling the servo motor to drive an emulsion pump loading valve to work; s4, the pressure sensor feeds back the pressure acquisition value to the upper computer; s5, the upper computer carries out comparison calculation on the pressure parameters of the loading valve of the emulsion pump through a PID (Proportion Integration Differentiation) controller; and S6, the servo driver adjusts and controls the servo motor according to the comparison calculation result, and precise pressure control over the loading valve of the emulsion pump is achieved.

The invention provides a control method and system of a converter, the converter and a wind generating set. The method comprises the steps that the current rotor speed of a doubly-fed wind generator is determined; in response to the fact that the difference between the rotor speed and the synchronous speed of the doubly-fed wind generator is smaller than a preset threshold value, for each three-level bridge arm, the state of a switching tube is controlled in the following mode that according to a modulation signal used for switching the output level of the three-level bridge arm from the positive level or the negative level to the midpoint level, the output level of the three-level bridge arm is converted into the midpoint level; and turning off the outer tube which is turned on in the current state, and turning on the clamping tubes and the inner tubes under the condition that the turned-on outer tube is turned off. The problem that the thermal stress of the power device near the synchronous speed cannot be properly solved is solved, and the thermal stress of the inner tube can be effectively dispersed by optimizing modulation logic, so that the thermal distribution of the power device of the switch tube is more uniform, and the problem that the thermal stress of the power device is too large is relieved.

The invention provides a receiver signal redundancy processing method and system and a storage medium, and the method comprises the steps: a transmitter transmits a judgment rule of signal redundancy to a first receiver, and transmits a first control signal to the first receiver; the transmitter sends a second control signal to the second receiver, and the second receiver outputs and sends the second control signal to the first receiver; and the first receiver performs redundancy processing on the first control signal from the transmitter and the second control signal from the second receiver by using a judgment rule of signal redundancy, and outputs and obtains a target control signal. According to the invention, a plurality of redundancy processing schemes which can be set are provided to optimally configure a signal redundancy switching scheme, so that the best control effect is achieved.

The present invention provides a bionic robot fish control method and system based on fish body wave optimization, belonging to the field of robot control technology. The method comprises the following steps: obtaining the swing angle and swing angular velocity of the head of the bionic robot fish, as well as the joint angle and joint angular velocity of the tail in real time; generating the expected swing angle of the head of the fish, and the expected angle and expected angular velocity of each joint in the tail according to the preset expected trajectory of the bionic robot fish; obtaining the dynamic parameters of the bionic robot fish in the fluid; establishing an optimal control model, and obtaining the current optimal joint acceleration of the tail of the bionic robot fish as the control amount of the bionic robot fish. The method proposed by the present invention can effectively reduce the swing of the fish head during the swimming of the robot fish, and is more robust to parameter changes. When the parameters of the bionic robot fish change, stable control can still be achieved, and migration application can be achieved by simply modifying the joint parameters.

The invention discloses an agricultural machine and an automatic driving control method and system thereof. The automatic driving control method comprises the following steps: acquiring a theoretical target steering angle and a theoretical current steering angle of the agricultural machine; calculating an understeering coefficient of the agricultural machine in the current driving process; calculating a current actual target steering angle of the agricultural machine according to the theoretical target steering angle and the steering insufficiency coefficient; calculating an actual current steering angle of the agricultural machine according to the theoretical current steering angle and the steering insufficiency coefficient; acquiring a target steering angle of the electric steering wheel according to the actual current steering angle and the actual target steering angle; and controlling the agricultural machine to move according to the target steering angle of the electric steering wheel. According to the method, the transverse control parameters can be dynamically adjusted according to the current insufficient steering state of the agricultural machine, and a better control effect is achieved under the conditions that the ground is uneven in dryness, humidity and hardness, the vehicle load change is large and the steering performance is unstable.

The invention discloses a manufacturability air conditioner automatic control system and an environment self-adaption adjusting method. The temperature and humidity control of the technical air conditioner is adjusted through a dual PID algorithm, the control logic is strict, and the temperature or humidity is preferentially adjusted according to the actual situation; the control effect is good, and constant indoor temperature, humidity, pressure and the like are guaranteed; safety, high efficiency and energy conservation are achieved, and high energy waste is avoided; the automatic control degree of the system is high, and the control precision, the anti-interference capability and the reaction speed of the system are improved.

The utility model relates to the technical field of headphones, in particular to a profiling headphone, which comprises a headphone main body, a rotating frame is rotatably arranged in the end part of the headphone main body, a driven contact ring is arranged on a rod body, positioned in the headphone main body, of the rotating frame, a mounting cavity is arranged in the end part of the headphone main body, and a position adjusting plate is arranged in the mounting cavity in a sliding manner; according to the utility model, under the mutual cooperation of all the parts, the profiling earphone is provided with more decoration part installation positions, and the ear decoration parts can be rotated and the angles of the ear decoration parts can be fixed, so that the ear decoration parts are more beautiful, and the profiling degree of the earphone is improved.

The utility model discloses a vehicle data acquisition box, belonging to the vehicle data acquisition field, the vehicle data acquisition box comprises a box body, a pedestal, vibration damping members, heat radiation fins and a heat radiation fan, a plurality of installation cavities are arranged in the pedestal, the vibration damping members are detachably connected in the installation cavities, a plurality of heat radiation fins are fixed on the side wall of the box body, and the heat radiation fins are fixed on the side wall of the box body. Cooling fans are fixed to the front side and the rear side of the interior of the box body, cooling holes are formed in the front side wall and the rear side wall of the box body, the wind directions of the front cooling fan and the rear cooling fan are the same, and the vibration reduction piece is a rubber block or a particle damping vibration reduction block. According to the vehicle data acquisition box, two different modes are adopted for heat dissipation at the same time, the heat dissipation effect is good, and heat can be discharged more efficiently through the arrangement of the heat dissipation fan through which wind passes. In addition, the detachable vibration reduction pieces are adopted, and the number and the positions of the vibration reduction pieces can be adjusted according to actual use requirements so as to meet the vibration reduction requirements of different vibration environments.

According to the split type optical satellite platform oriented to the multiple application modes, physical isolation of the load cabin and the service cabin is achieved through the innovative composite Lorentz force executing mechanism, and interference of vibration of the service cabin on the load cabin is effectively isolated. The composite Lorentz force actuating mechanism not only solves the nonlinear problem and the collision avoidance problem of a traditional actuating mechanism during rotation and large-angle maneuvering, but also has the advantages of being compact in structure, low in control rate, high in response speed, high in output force precision and the like. The platform supports multiple modes such as earth three-axis high-stability imaging, rotary optical imaging and large-angle maneuvering, and the on-orbit application efficiency of an optical satellite is remarkably improved. According to the invention, a new progress of the spaceflight technology in the aspects of high precision and high agility control is displayed, and powerful support is provided for future space tasks.

The present invention discloses an optimization control method and system based on the operation status of a wind turbine generator set, comprising the following steps: 1) real-time monitoring and collection of the operation status information and external environment information of the wind turbine generator set, wherein the operation status information of the wind turbine generator set includes the running status, shutdown status and output power P of the wind turbine generator set; 测 ; 2) Calculate the power judgment standard P based on the collected external environment information 标 ; 3) When P 测 >P 标 , then according to the output power P of the wind turbine 测 and judgment criteria P 标 The deviation between them is controlled by PID control to change the pitch of the wind turbine rotor. This method and system can ensure the stable operation of the wind turbine.

The invention discloses a magnetic random access memory unit, a magnetic random access memory, a phase inverter and a memory, and the magnetic random access memory unit comprises a substrate; the free layer structure is located on the substrate, the free layer structure comprises one or more layers of stacked structures, the stacked structures comprise a first free layer and a plurality of second free layers which are located in the first free layer and are separated from each other, and the first free layer and the second free layers are made of different materials; the multiple layers of stacked structures are stacked in the direction perpendicular to the surface of the substrate; a tunnel layer on the free layer structure; and the fixed layer is positioned on the tunnel layer. The magnetic random storage unit can be used as a basic unit of a logic device and a memory, so that the logic device and the memory have relatively low power consumption, relatively low working voltage and high-temperature reliability.

The invention provides an intelligent water turbine control method based on a digital speed regulator, which comprises the following steps of: forming a first data set by collecting rotating speed frequency, active power and water head signals of a water turbine generator set, and providing a basic data source for a control decision; performing credibility verification on the first data set through a physical rule, generating a verified second data set, and ensuring that the data input into the control logic is accurate and credible; based on the second data set, dynamically selecting at least two control algorithms adaptive to the working condition, fusing the outputs of the algorithms, and calculating to obtain an accurate guide vane opening control instruction, so as to solve the problem of insufficient adaptability of a single algorithm; then the guide vane opening control instruction is converted into a driving signal to operate an electro-hydraulic follow-up system, and adjustment of the guide vane opening is achieved; and finally, guide vane opening feedback is obtained, an instruction and the feedback are compared to generate evaluation data, and control algorithm parameters are adaptively corrected according to the evaluation data, so that the problem that the control effect of a single control algorithm on the water-turbine generator set is poor is solved.

This invention discloses an intelligent model predictive control method for intensive mixing processes based on reinforcement learning. Addressing the degradation of control performance caused by model mismatch due to modeling errors, abrupt state changes, and component degradation in traditional model predictive control, this invention introduces reinforcement learning into the model predictive control framework. The method designs an intelligent model predictive control approach based on reinforcement learning to solve a standard quadratic programming problem with respect to optimization variables. Reinforcement learning selects compensation terms to compensate for model deviations caused by model mismatch, combining this with the controller output and applying it to the system. Finally, the reward is calculated and updated to optimize the control compensation selection for future time steps. As the control cycle progresses, new information is continuously integrated, model predictions are updated, and control inputs are optimized to adapt to potential changes in system behavior or external disturbances. This improves system stability and control accuracy, ensuring that the intensive mixing process can track a preset trajectory.