385 results about "Proportional integral differential" patented technology

The invention discloses a heterogeneous double-mechanical-arm tail end pose mapping method, system and device and a storage medium, and the method comprises the following steps: S1, obtaining the angular velocity, position and tail end pose information of each joint of a main mechanical arm, and calculating the spatial position and pose of the tail end of the main mechanical arm; s2, motion trail data in the teaching process of the main mechanical arm is collected, a long-short-term memory network model is established, the pose of the future time step length is predicted, and the motion trail of the auxiliary mechanical arm is planned; s3, data information is transmitted, and the problem of communication delay is solved; s4, the pose information of the tail end of the main mechanical arm is solved, the joint angle is adjusted, and the error is adjusted in combination with proportional-integral-differential control; s5, the position and speed signals are filtered, a mechanical arm dynamic model is established, an adaptive control law is designed, and a trajectory smoothing algorithm is adopted; and S6, establishing a virtual obstacle map, and limiting a safe working space. According to the method, comprehensive and accurate mapping and prediction of the tail end poses of the heterogeneous double mechanical arms are achieved.

The invention relates to the technical field of electromagnetic flowmeter calibration, and discloses an electromagnetic flowmeter online calibration system and an acquisition and storage device. The system comprises a signal acquisition module, a data processing module, an error analysis module, a parameter calibration module and a real-time monitoring module. The signal acquisition module captures an original signal waveform through a multi-channel sensor array and acquires flow signal data to generate a state set; the data processing module uses a wavelet packet transformation and adaptive filtering combined algorithm to reduce noise and extract features; the error analysis module constructs a dynamic time warping error matching model to obtain an error correction coefficient; the parameter calibration module adopts a fuzzy control and proportional integral differential composite strategy, and adjusts excitation current and electrode sensitivity according to an error correction coefficient; the real-time monitoring module establishes a rolling optimization model with time-varying constraints, and generates a calibration instruction in combination with signal stability and power consumption limitation. According to the system, online accurate calibration of the electromagnetic flowmeter is realized, and the measurement accuracy and the equipment operation stability are improved.

The invention provides a chip welding method based on machine vision and control, and the method comprises the steps: obtaining a three-dimensional model of a chip and a substrate, obtaining an initial relative position of a chip welding spot and a substrate welding pad, and generating a mechanical arm initial motion instruction; images of the chip and the substrate are shot, pose deviation is calculated through image registration, if the deviation exceeds a threshold value, a compensation instruction is generated to be fused with an initial instruction, and the track of a mechanical arm is adjusted to be aligned with a bonding pad; a temperature sensor array is constructed to monitor the temperature of the welding area, the average temperature is calculated, and if a difference exists between the average temperature and the ideal welding temperature interval, the heater power is adjusted through a proportional integral differential algorithm; a piezoelectric sensor is used for obtaining a mechanical arm joint vibration signal, the dominant vibration frequency and amplitude are extracted through fast Fourier transform, and a piezoelectric actuator is used for generating an anti-phase driving signal to counteract vibration.

The invention relates to the technical field of computers, in particular to a temperature control method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining an estimated temperature of a heat dissipation part based on a pre-established physical model, and obtaining an actual temperature of the heat dissipation part based on the estimated temperature and the actual temperature of the heat dissipation part; judging whether parameters of a pre-established physical model meet preset updating conditions or not; if the parameters of the physical model meet preset updating conditions, the parameters of the pre-established physical model are updated, and based on the updated parameters, regulation and control parameters of a proportional integral differential controller are determined according to a preset objective function, so that the proportional integral differential controller controls the operating temperature of the server based on the regulation and control parameters. Therefore, the problems that in PID regulation and control of the server fan, parameter setting depends on artificial experience, efficiency is low, subjectivity is high, and power consumption, noise and heat dissipation performance cannot be effectively balanced in the prior art are solved, and effective control over the temperature, the power consumption and the noise of the server is achieved.

The invention relates to an intelligent fish blocking and ship passing system based on multi-mode AI fusion and self-adaptive control, and belongs to the field of water conservancy projects and intelligent control. Aiming at the problems that a traditional electric fish blocking device is low in ship communication efficiency, poor in environmental adaptability and high in maintenance cost, a multi-mode sensor (laser radar, sonar, infrared thermal imaging and the like) fusion technology is adopted, and a reinforcement learning optimization proportion-integral-differential (PID) control parameter and a graph neural network (GNN) path planning algorithm are combined. All-weather high-precision sensing and dynamic gate regulation and control are realized; and equipment faults are predicted through a long short-term memory (LSTM) model, so that the shutdown risk is reduced. According to the system, the ship dredging efficiency is improved by 25%, the accident rate is reduced by 70%, the maintenance cost is reduced by 40%, the system adapts to extreme environments, and intelligent water conservancy construction is supported.

The invention provides a knowledge distillation temperature parameter dynamic adjustment method based on a PID (Proportion Integration Differentiation) controller, which is applied to the field of deep learning. In order to solve the problem that temperature parameters are fixed and are difficult to adapt to model performance changes in the existing knowledge distillation technology, a PID controller is adopted to adjust the temperature parameters in real time, and KL divergence and cross entropy loss between student and teacher models are dynamically balanced. Through a proportional-integral-differential control strategy, temperature parameters in the distillation process are automatically adjusted to enhance the model adaptability, and the distillation efficiency and the student model generalization ability are improved. The method mainly comprises the following steps: monitoring loss difference in real time, calculating temperature adjustment amount by using a PID controller, dynamically updating temperature parameters to balance distillation loss, automatically adjusting to reduce manual parameter adjustment, and improving model performance. The method is mainly used for automatically adjusting temperature parameters of knowledge distillation, manual parameter adjustment is reduced, model performance is improved, and the method is suitable for various deep learning models and data sets and has wide application value.

The invention relates to a vehicle lithium ion power battery charge state estimation method based on an improved extended Kalman filtering algorithm, and belongs to the technical field of lithium ion batteries. The method comprises the following steps: firstly, establishing a second-order RC equivalent circuit model of the lithium ion battery, and carrying out linearization processing by utilizing Taylor expansion; and then, searching an optimal noise covariance matrix by adopting a sunflower optimization algorithm, and applying the optimal noise covariance matrix to charge state online estimation of an extended Kalman filtering algorithm. In order to ensure that the extended Kalman filter can be in contact with sufficient state parameter information, a proportional integral differential control method is introduced to correct a Kalman gain matrix, so that accurate and stable estimation of the state of charge of the lithium ion battery is realized. According to the method, a voltage accumulative error judgment and charge state initial correction method is adopted, so that the precision of charge state estimation is improved. Compared with a traditional ampere-hour integral method and an extended Kalman filtering algorithm based on sunflower optimization, the method has higher charge state estimation precision.

The invention relates to the technical field of continuous casting equipment, and discloses a crystallizer control method and system based on proportional integral differential, and the method comprises the steps: converting analog signals of liquid level height and wall surface temperature into analog control signals, and adjusting parameters of a cooling water inlet of a crystallizer; constructing a cooling water database according to the flow and temperature of the generated cooling water and the heat transfer information of each area in the crystallizer; calculating proportional control output which is in direct proportion to the difference value, calculating integral of past errors, predicting changes of the errors, combining the outputs of all the parts, and calculating a final control signal; according to the calculation result of the final control signal, the flow and the temperature of cooling water are adjusted, and the liquid level height and the wall surface temperature in the crystallizer reach set values. The system comprises a database construction module, an intelligent control module and a result evaluation module. According to the invention, the operation performance of the crystallizer is effectively maintained, and support is provided for further improvement.

Provided is an apparatus for controlling a road wheel actuator (RWA) system, the apparatus including a sensor module configured to detect sensing data of at least one of a steering angle, rack position information, angular velocity of a steering wheel, and column torque, and a processor configured to perform a Proportional Integral Differential (PID) control logic based on the sensing data detected by the sensor module and the RWA position information fed back from the RWA system.

The invention discloses a proportional-integral-derivative loop control method and a related device, and relates to the technical field of automatic control, after a set value and a current measurement value of a controlled object are obtained, the deviation of the controlled object is calculated, and the set value, the current measurement value and the deviation are input into a data analysis module; the current variation trend information of the controlled object is obtained, the current variation trend information and the current deviation state information are input into the parameter group selection unit, a sub-parameter group matched with the current working condition of the controlled object is determined, and the sub-parameter group is input into the proportional integral differential control unit to adjust the current measured value. And outputting the current operation value of the controlled object, and finally, controlling the controlled object by adopting the current operation value. According to the method, the sub-parameter group suitable for the current working condition can be matched for the controlled object in real time according to the trend change and the deviation state of the controlled variable, the current measurement value is adjusted by adopting the sub-parameter group, the current operation value is output to control the controlled object, and the parameter adjustment efficiency is high.

The invention discloses a fan control method and device, a product, a server and a medium, and relates to the field of computer hardware control. Under the condition that the temperature value of the server component is larger than or equal to the new current temperature threshold value, the target rotating speed value of the fan is output through the proportional-integral-differential control model, then the fan is controlled to rotate according to the target rotating speed value, and cooling of the server component through the fan is achieved; secondly, when the temperature threshold value is determined, the historical temperature values of the components under the multiple environment temperatures are considered, and the temperature threshold value is updated, that is, the fan is controlled by depending on the dynamic threshold value. The threshold value is adjusted in advance according to the environment temperature, so that frequent triggering of starting of the fan due to transient fluctuation of the environment temperature is avoided, and the stability of the server is ensured; and thirdly, based on an environment-load combined compensation mechanism, the rotating speed of the fan is dynamically adjusted to offset the influence of the environment temperature, the influence of the environment temperature and load factors on fan control is avoided as much as possible, and the fan control precision is improved.

The invention discloses a method and system for controlling the opening degree of a pipeline flow automatic adjusting valve, and relates to the technical field of automatic control. The method comprises the steps that real-time flow data in a pipeline and real-time pressure difference data of upstream and downstream of a valve are obtained; comparing the real-time flow data with a preset target flow to obtain a flow deviation, and generating a feedforward compensation signal by a proportional-integral-differential controller according to the flow deviation and the real-time pressure difference data; the flow deviation is input into a PID controller, and a proportional-integral-differential controller generates a feedback control signal; generating a composite control signal according to a superposition result of the feed-forward compensation signal and the feedback control signal; and the electric actuating mechanism is driven to adjust the opening degree of the valve according to the compound control signal, the actual opening degree of the valve is obtained through the position sensor, and the actual opening degree is fed back to the proportional-integral-differential controller. The invention provides a brand new solution with high robustness, high precision and low maintenance cost for industrial fluid control.

The present disclosure provides a control method and control apparatus for a voltage source-type wind turbine. The control method comprises: performing a proportional-integral-derivative operation on a deviation between a DC bus voltage measurement value and DC bus voltage reference value of a wind turbine to obtain an active power deviation; determining a virtual angular frequency deviation on the basis of the active power deviation; determining a virtual internal potential phase on the basis of the virtual angular frequency deviation; obtaining a d-axis virtual impedance output and an q-axis virtual impedance output by means of inputting a grid-connected current in a dq coordinate system to a virtual impedance module; on the basis of the virtual angular frequency deviation, a reactive power setting value and reactive power measurement value of the wind turbine, a rated voltage amplitude of a grid, the d-axis virtual impedance output and the q-axis virtual impedance output, determining a d-axis component and q-axis component of a modulation voltage; and controlling an injection voltage of a grid-connected point of the wind turbine according to the virtual internal potential phase and the d-axis component and q-axis component of the modulation voltage.

An intelligent cooling system for dynamic monitoring, prediction and optimization of storage conditions in real time, consisting of: a refrigerator with heat-insulated walls; a sensor array in the refrigerator comprising temperature sensors, humidity sensors, pressure sensors, and pathogen detection biosensors, the sensor array being configured to continuously monitor internal environmental parameters in the refrigerator and external environmental conditions; a control dashboard configured to display real-time environmental data and enable remote monitoring and manual adjustment of the environment in the refrigerator; an Internet of Things (IoT) communication module configured to transmit the monitored internal and external environmental data to the control dashboard; a proportional-integral-derivative (PID) controller operatively connected to the IoT communication module and configured to analyze the monitored data and calculate correction factors to maintain optimal environmental conditions; a plurality of actuators within the refrigerator, the plurality of actuators comprising a temperature actuator, a humidity actuator, and a pressure actuator, the actuators being configured to independently adjust temperature, humidity, and pressure within the refrigerator based on the control instructions; a processor configured to execute machine learning algorithms to analyze historical and real-time sensor data, predict optimal environmental conditions based on the analyzed data, and generate control instructions for the actuators based on the predicted optimal environmental conditions and the calculated correction factors; and a solar power supply configured to provide energy for operating the system.

The invention provides an ultra-supercritical thermal power generating unit flexible operation control method based on automatic start-stop, and relates to the technical field of thermal power generation, and the method comprises the steps: obtaining thermodynamic system parameters of a thermal power generating unit in the start-stop process, and building a thermodynamic system parameter coupling model; setting the load change rate of each stage by using the multi-stage load change track; a dynamic compensation algorithm based on proportional integral differential control is adopted, and a load control instruction is generated according to the multi-stage load change track and the dynamic compensation algorithm; acquiring peak regulation demand data from a power grid dispatching system, and judging whether the load regulation time meets the peak regulation demand or not; and according to the adjusted load change track, recalculating the load change rate of each stage, updating dynamic compensation algorithm parameters, and generating a new load control instruction. Key parameters are monitored in real time, and the adjustment effect is evaluated through deviation analysis. Stable adjustment of thermal power generating unit loads is achieved, and the power grid peak regulation capacity and the unit operation efficiency are improved.

The embodiment of the invention provides a non-directional force sensor control method and system based on real-time force trend prediction, and the method comprises the steps: collecting a real-time force signal sequence generated when a target mechanical device carries out the contact operation, and inputting the real-time force signal sequence into a pre-trained force trend prediction model; and obtaining a force direction trend prediction result output by the force trend prediction model, generating a multi-dimensional force compensation signal according to the matching degree of the force direction trend prediction result and the current closed-loop control parameter, adjusting a proportion-integral-differential coefficient in the current closed-loop control parameter based on the multi-dimensional force compensation signal, generating an updated closed-loop control parameter, and outputting the updated closed-loop control parameter. The updated closed-loop control parameters are input into an actuator of the target mechanical device, and the contact operation track of the target mechanical device is dynamically adjusted through the actuator according to the updated closed-loop control parameters, so that the multi-dimensional force amplitude data output by the non-directional force sensor are converged to a preset force control target interval. The response speed and stability of the force control system can be improved.

The invention relates to the technical field of voltage control, and discloses an ESC voltage regulator voltage control method and system based on fuzzy adaptive PID, and the method comprises the steps: collecting the output voltage of an ESC voltage regulator and a preset target voltage in real time, calculating a voltage error and an error change rate after filtering, and carrying out the calculation of the error change rate; dividing fast tracking, precise adjustment and anti-interference stability maintenance stages according to errors and change rates and generating control signals, calling corresponding fuzzy rule subsets to deduce proportional, integral and differential gain adjustment amounts, generating real-time gains in combination with initial PID parameters, calculating control amounts by using position type PID based on the real-time gains, converting the control amounts into signals to drive power switch tubes, and controlling the power switch tubes. And closed-loop adjustment is formed. According to the method, the problem that a traditional control method is poor in performance under multiple working conditions is solved, cooperative control over rapid tracking, precise adjustment and anti-interference stability maintenance of the output voltage of the ESC voltage regulator is achieved, it is ensured that the ESC voltage regulator can output stable voltage under the working conditions of starting, steady-state operation and load sudden change, and the requirement for high voltage control precision and dynamic response is met.

The invention relates to a wind storage power station frequency control method and a wind storage power station, and the method comprises the steps: constructing a power system model, and obtaining the working parameters of the power system model; the power system model comprises a wind power generation system model, an energy storage system model and a load; the actual input variable quantity of the composite controller is obtained based on the working parameters, and the key coefficient of the proportional-integral-derivative controller is adjusted according to the fuzzy rule of the fuzzy logic system; adjusting a control coefficient of the power system model output by the composite controller based on the key coefficient so as to realize dynamic adjustment of the frequency of the power system model; the composite controller comprises a fuzzy logic system and a proportional-integral-derivative controller. The wind power generation frequency is jointly adjusted through the fuzzy logic system and the proportional-integral-derivative controller, so that accurate control is quickly performed when the system frequency deviates, and the capability of the system for dealing with quick frequency disturbance is enhanced.

The invention belongs to the field of shield tunneling machines, and discloses an intelligent posture deviation correction control method and system for a continuous tunneling shield tunneling machine, and the method comprises the steps: carrying out a pushing and splicing synchronous construction experiment to collect data; integrating the BiLSTM and the KAN, and predicting the posture of the continuous tunneling shield tunneling machine; in combination with an MOGWO method, an optimal proportional-integral-differential (PID) parameter is determined, and attitude deviation is minimized. The invention provides a shield attitude intelligent control method integrating deep learning, physical modeling and an intelligent optimization algorithm. The key innovation point is that the KAN model and the BiLSTM model are combined to accurately predict the attitude of the continuous tunneling shield machine in various assembling hydraulic oil cylinder missing scenes. And then combining the improved BiLSTM model with an MOGWO algorithm to optimize the response performance of the propulsion hydraulic system, and finally improving the efficiency and quality of tunnel construction. Verification research is carried out by utilizing actual measurement data of a continuous tunneling shield tunneling machine test bed, and the effectiveness of the method is verified.

The invention discloses a cutting fluid full-automatic centralized liquid supply control method and system, cutting fluid concentration data and liquid supply system pressure data are obtained through a sensor array, real-time monitoring data are generated by adopting a high-frequency sampling technology, and if the cutting fluid concentration data deviates from a preset threshold range or the liquid supply system pressure data exceeds a stable range, the cutting fluid is monitored. If so, generating an abnormal signal; according to the abnormal signal, the operation frequency of a liquid supply pump is adjusted through a proportional-integral-differential algorithm, a closed-loop control system is formed to maintain a target pressure value, and meanwhile the opening value of a liquid distribution valve is adjusted according to the concentration deviation signal; and the cutting fluid return liquid is extracted from the adjusted liquid supply system, the cutting fluid return liquid is treated through a multi-stage filtering device and a centrifugal separation device, and if it is detected that the impurity content of the cutting fluid return liquid is lower than a preset threshold value, it is judged that purification treatment is completed. The stable performance of the cutting fluid can be kept, the service life of equipment is prolonged, the processing quality and the production efficiency are improved, and the cutting fluid has important practical value.

The invention provides a PID parameter setting method based on a large language model, and belongs to the technical field of industrial automation control. Aiming at the problems that a traditional PID setting method depends on expert experience, is long in debugging period and lacks theoretical interpretation, adaptive optimization of PID parameters is realized by fusing dynamic response characteristics of a control system and inference capability of a large language model. The method comprises the following steps: collecting time sequence data of process variables, and extracting dynamic characteristics such as overshoot, oscillation period, attenuation ratio and integral absolute error (IAE); comparing the feature vector with a preset industrial standard threshold value, and generating a natural language cue word containing quantitative analysis; inputting the large language model, and outputting adjustment suggestions including proportion, integral and differential parameters; evaluating a parameter effect through a closed-loop verification experiment, and if the parameter effect does not reach the standard, combining historical debugging data to carry out iterative optimization; and finally, an optimal PID parameter is generated. Experiments prove that the method has a good effect in the industrial process containing pure delay and large inertia.

The invention provides a temperature and humidity optimization control method and device based on sensor adaptive calibration. The method comprises the steps that reading sets corresponding to all temperature and humidity sensors in an air conditioning system are obtained in real time; a to-be-calibrated reading in the reading set is determined through a preset calibration strategy, and the temperature and humidity sensor corresponding to the to-be-calibrated reading is calibrated; judging whether the temperature and humidity of the current environment of the target area indicated by the calibrated reading set are within a preset temperature and humidity allowable deviation range or not; if yes, the preset temperature and humidity are in a change following state, and variable reset of the proportional-integral-differential controller is triggered; if not, a corresponding temperature and humidity adjusting strategy is executed according to the deviation between the actual temperature and humidity and the preset temperature and humidity. The air conditioning system can accurately sense the environment temperature and humidity change, accurate calibration and effective adjustment are achieved, and a stable and appropriate temperature and humidity environment is provided for a target area.

The invention provides a self-adaptive state prediction control method for improving the stability of a grid-forming type new energy shafting, and belongs to the technical field of wind power generation, and the method comprises the steps: determining an extended state observer based on a nonlinear function and a closed-loop system; obtaining a virtual torque compensation item by using the extended state observer, and feeding back the virtual torque compensation item to a virtual rotor motion equation of the virtual synchronous machine to perform additional power compensation; in the additional power compensation process, when the rotating speed of the draught fan is lower than a preset safety value, proportional integral differential control is set to zero through a rotating speed protection module, the wind power virtual synchronous machine system is controlled to exit additional power compensation, and the active supporting system is controlled to operate stably; in the stable operation process of the active support system, the rotating speed of the fan is recovered to the optimal value through the rotating speed recovery module, and the influence caused by unreasonable parameters is reduced and the dynamic stability of the wind power VSG grid-connected system is effectively enhanced by estimating the imbalance between the external disturbance power and the internal state quantity and performing tracking compensation in the controller.

The invention provides an attitude control method and device for a vertical take-off and landing unmanned aerial vehicle, equipment and a medium, relates to the technical field of flight control law design, and is used for solving the problem of how to realize rapid transition of the vertical take-off and landing unmanned aerial vehicle from a horizontal state to a vertical state. The method comprises the following steps: determining a current stage of the vertical take-off and landing unmanned aerial vehicle in a transition process according to a pitch angle and a flight speed of the vertical take-off and landing unmanned aerial vehicle; the transition process refers to the process of transition from a horizontal state to a vertical state; determining a pitch angle speed control target according to the current stage; a proportional integral differential control law structure is adopted, and a pitching control surface control instruction is determined according to the pitching angular velocity control target and the pitching angular velocity; the vertical take-off and landing unmanned aerial vehicle can be controlled to be rapidly transited to a vertical state from a horizontal state through a pitching control surface control instruction.

The invention relates to the technical field of fire fighting, in particular to an intelligent control method and system for a smoke exhaust fireproof valve, and the method comprises the steps of initial state setting, fire signal detection, smoke exhaust fireproof valve control and state monitoring and feedback. Compared with the prior art which only depends on temperature and particulate matter concentration data to carry out fire monitoring and control and has the defects of insufficient monitoring on internal air pressure change of the smoke exhaust fireproof valve and inflexible control response, the scheme is characterized in that an air pressure sensor is additionally arranged in a data acquisition module; an air pressure data processing step based on a sliding window average value method is introduced into the control module in a targeted manner, and the opening and closing degree of the smoke exhaust fireproof valve is adjusted by combining a proportion, integral and differential control algorithm, so that the scheme can monitor the air pressure change in the smoke exhaust fireproof valve in real time, improve the accuracy of fire early warning, and improve the safety of the fire. And opening and closing of the smoke exhaust fireproof valve can be dynamically adjusted according to air pressure changes, and the stability of smoke exhaust efficiency and the sensitivity of control response are ensured.

The invention relates to the technical field of intelligent power regulation, discloses a charger control method and system based on intelligent power regulation, and dynamically adjusts a power distribution strategy by monitoring equipment power consumption and a battery state in real time. The method comprises the following steps: firstly, acquiring an equipment power consumption curve and a battery health index, judging the priority of a power consumption demand and a charging demand according to a preset threshold value, determining a preliminary power distribution scheme, optimizing power distribution by adopting a pulse width modulation technology and a digital signal processor according to the actual conditions of equipment and a battery, and generating a frequency-coordinated power control signal; and finally, calculating progressive power transfer parameters among multiple energy paths through a proportional-integral-differential control algorithm to realize smooth power transfer, and processing feedback data by using an adaptive filtering algorithm to ensure stable power output. Intelligent power balance between equipment operation and battery charging can be achieved, the energy utilization efficiency is effectively improved, the service life of the battery is prolonged, and stable operation of equipment is guaranteed.

The present invention relates to a local micro-scale cooling control optimization method and belongs to the field of biomedical engineering. In the method, the accurate cooling of a therapy region is realized by means of accurately controlling the release of a cryogenic medium. A micro-flow pump and a solenoid control valve are used to accurately adjust the flow and speed of the cryogenic medium, and a temperature sensor built in a probe is used to monitor the temperature of the therapy region in real time. The method further comprises a proportional-integral-derivative (PID)-based control algorithm, which dynamically adjusts the release of the cryogenic medium on the basis of real-time temperature data, so as to maintain a target therapy temperature. In addition, in the method, non-contact temperature monitoring is performed on the therapy region by means of an infrared camera, and data occurring during a therapy process is recorded, thereby optimizing a therapy effect. The technology provides a safe and accurate local cryotherapy method, which is applicable to medical therapy for dermatosis, muscle injury, inflammation, etc.

The invention discloses an unmanned aerial vehicle control method and device for aloft work. The method comprises the following steps: when an unmanned aerial vehicle lifts to a preset height, acquiring an operation video of an operation site through a shooting device configured by the unmanned aerial vehicle, and marking a target object in the operation video by using a detection frame; tracking the target object based on a preset target tracking algorithm and the labeling box to obtain an object position of the target object; and determining a target angle of a pan-tilt of the unmanned aerial vehicle according to the object position through a proportional integral differential controller, and adjusting the pan-tilt to the target angle, so that the target object is located at the central position of the video frame of the target video, thereby solving the problem that the unmanned aerial vehicle cannot automatically and stably track the target in a working site, and improving the working efficiency of the unmanned aerial vehicle. The tracking precision and the video stability are improved, the manual intervention is reduced, and the working efficiency and the safety are enhanced.

A data-knowledge driven multi-objective optimal control method for municipal wastewater treatment process belongs to the field of wastewater treatment. To balance the energy consumption and effluent quality, a data driven multi-objective optimization model, including energy consumption model and effluent quality model are established to obtain the nonlinear relationship along energy consumption, effluent quality and manipulated variables. Meanwhile, a multi-objective particle swarm optimization algorithm, based on evolutionary knowledge, is proposed to optimize the set-points of nitrate nitrogen and dissolved oxygen. Moreover, the proportional integral differential (PID) controller is designed to track the set-points. Then the effluent quality can be improved and the energy consumption can be reduced.

The invention discloses an intelligent temperature control production system for an environment-friendly asphalt cold patch additive, and relates to the technical field of asphalt cold patch additive production, and the system comprises a controller initial modeling module which is used for recording the currently set proportional-integral-differential controller parameters, and constructing a reference control feature vector used for representing the initial response behavior of a controller; and the thermal load response identification module is used for applying micro-amplitude step type temperature disturbance to the to-be-heated environment-friendly asphalt cold patch additive and extracting a thermal load characteristic vector representing the thermal response characteristic of the additive. According to the method, intelligent matching and full-time-domain response evaluation are realized by constructing control and thermal load feature vectors and combining cross-correlation and grey correlation analysis; a sliding spectrum entropy and self-adaptive parameter correction mechanism is introduced, a closed-loop regulation system is constructed, the suitability, stability and additive dispersing performance of a temperature control system are effectively improved, and the problems of control lag and fluctuation are solved.