286 results about "Proportional integral differential" patented technology

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 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 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 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 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 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 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.

The invention provides a vehicle control method and device based on rear wheel steering. The method comprises the steps that whether a target vehicle is in an unstable state or not is judged based on a two-degree-of-freedom vehicle dynamics model of the target vehicle; when the target vehicle is in the unstable state, a rear wheel steering mode is determined according to the vehicle speed of the target vehicle; based on the deviation between the actual yaw velocity and the expected yaw velocity of the target vehicle, determining a rear wheel steering angle by adopting a proportional-integral-derivative controller; and controlling rear wheels of the target vehicle to steer according to the rear wheel steering mode and the rear wheel steering angle. By actively adjusting the steering angle of the rear wheel, the dynamic control capability of the vehicle is remarkably improved.

The invention discloses a grooving positioning system based on a paperboard digital intelligent grooving machine, relates to the technical field of grooving machine positioning adjustment, and solves the technical problems of insufficient transverse deviation adjustment precision and incomplete longitudinal deviation compensation. Proportional, integral and differential parameters of the incremental PID are dynamically adapted according to the deviation, compared with a fixed parameter PID, the adjustment response time is shortened, the overshoot is controlled within + / -0.01 mm, the transverse positioning precision is improved, and the high-precision grooving requirement is met. A total error model of a linear error and a periodic error is established through a laser interferometer for encoder error calibration. And in combination with a PLC position-compensation amount comparison table, encoder positioning errors are reduced, dynamic environment compensation fits a paperboard stretching model through a humidity sensor, an equipment thermal deformation model is established through a temperature sensor, temperature and humidity influences are comprehensively compensated, and the longitudinal positioning precision fluctuation range is narrowed.

The invention discloses an excrement liquid dynamic proportion regulation and control method based on sensing feedback, and particularly relates to the technical field of waste fluid control, and the method comprises the following steps: arranging a plurality of sensors in an excrement liquid conveying pipeline, collecting multi-parameter data such as flow, conductivity, solid content and the like, calculating a load fluctuation entropy value and a control conflict count value, and calculating a load fluctuation entropy value and a control conflict count value; the current control state is judged, the priority and the execution frequency of proportional integral differential control and self-adaptive control are dynamically adjusted based on the state result, a dilution ratio control signal is generated, a variable frequency pump is driven to be linked with an electric valve, clear water injection and excrement liquid mixing control are achieved, and the solid content is stabilized within the target range; according to the invention, the system state is identified through the combination of entropy and conflict counting, the priority and frequency of the control strategy are dynamically switched, and accurate adjustment under steady state and disturbance is realized; and meanwhile, a dilution ratio control signal is linked with the variable frequency pump and the electric valve, a closed-loop dilution control channel is constructed, and the intelligence and stability of solid content regulation and control are improved.

Methods and systems are disclosed for controlling device movement based on a movement command. Issues on accurately controlling movement of a device such as a programmable robot and rover are addressed by first determining a command type of the movement command, followed by determining specific types of controllers for a high-level controller and a low-level controller based on the determined command type. When the command type is a linear movement, a Proportional-Integral-Derivative (PID) controller is used at the high-level controller and a Proportional / Proportional-Integral (PPI) controller is used at the low-level controller to accurately control a target distance. When the command type is an angular movement, the PPI controller is used at the high-level controller and the PID controller is used at the low-level controller to accurate control the end-heading of the device.

The invention provides a fuel cell cooling system, and relates to the technical field of fuel cells. The fuel cell cooling system comprises the following modules: a cooling cycle control module, a heat dissipation management module, a hydrogen pretreatment module, a hydrogen cycle regulation and control module, a gas-liquid treatment module and a heat recycling module, and the cooling cycle control module is used for dynamically adjusting the rotating speed of a cooling water pump by adopting a proportional integral differential algorithm on the basis of the pile temperature monitoring data, realizing closed-loop control of the temperature of cooling liquid through a PTC heater, establishing a three-loop cooperative control mechanism in combination with opening adjustment of a thermostat, and generating optimized flow parameters. A three-loop flow matching mechanism is established by dynamically adjusting the rotating speed of a cooling water pump and cooperatively controlling a PTC heater, the pile temperature control precision is remarkably improved, the radiator structure is optimized by adopting computational fluid mechanics, and the rotating speed of a fan is dynamically adjusted in combination with fuzzy control, so that the energy consumption is reduced while the heat dissipation efficiency is improved; and constructing a pressure-temperature coupling model to optimize a hydrogen heating curve.

The embodiment of the invention provides an intelligent power optimization and control method for an all-vanadium redox flow energy storage system, which comprises the following steps: establishing a mathematical model of the all-vanadium redox flow energy storage system, the mathematical model comprising a galvanic pile model, an electrolyte circulation model and a pump model, and setting a state variable, an input variable and an output variable; based on historical day illumination, temperature and wind speed data, photovoltaic and wind power generation and power grid load demands are predicted by using a machine learning method, and the total power demand of an energy storage system is calculated; inputting the total power demand signal to the energy storage system, and generating a power distribution and control instruction; constructing a multi-objective optimization model for the operation of the all-vanadium redox flow battery energy storage system, wherein the multi-objective optimization model comprises a multi-objective function, a constraint condition and a power distribution evaluation index; adopting a fuzzy mathematics theory to carry out membership degree unification processing on the multi-objective function; distributing power based on a two-step method strategy; and executing a power instruction based on the segmented quantized cerebellum model neural network-proportional integral differential composite control strategy.

The invention discloses a method for accurately testing and controlling tension in a rotating state, and belongs to the technical field of tension control. The method comprises the following steps: acquiring a tension value, a pulley inclination angle and a vibration acceleration of each strand of wire rod in a plurality of strands of wire rods; the virtual instrument architecture platform executes real-time operation; the virtual instrument architecture platform writes a frequency instruction into the frequency converter and sends a target position pulse sequence to the servo motor at the same time; the frequency converter adjusts the rotating speed of the winch driving motor according to the frequency instruction. The servo motor controls the linear speed of the traction roller according to the target position pulse sequence. The control precision is optimized through multi-mode sensing data fusion and a dynamic compensation mechanism, a dynamic weight distribution PID control strategy is combined, the weight coefficients of proportion, integral and differential items are adjusted in a self-adaptive mode according to the tension change rate, a feed-forward compensation mechanism is introduced, collaborative optimization control over the frequency converter and the servo motor is achieved, and the control precision is improved. And the tension control precision and the abnormal response efficiency under the complex working condition are obviously improved.

The invention discloses a double-section type drying temperature control system, which relates to the technical field of drying and comprises a drying state sensing module, a state recognition and analysis module, a thermal load prediction modeling module, an inter-section switching judgment module, a thermal inertia compensation control module, a parameter self-adaptive adjustment module and a control logic learning optimization module. The drying state sensing module is used for acquiring temperature, humidity and heat flow data in the material drying process to construct an inter-segment multi-dimensional temperature feedback matrix; and the state recognition and analysis module is used for executing manifold clustering analysis based on the inter-segment multi-dimensional temperature feedback matrix and extracting dry state distribution characteristics. According to the method, accurate identification and intelligent switching control of the drying state are realized through multi-point temperature and humidity sensing, manifold clustering and thermal load modeling; thermal inertia prediction and power decline regulation are introduced, so that temperature overshoot is effectively inhibited; and a closed-loop steady-state control and dynamic learning mechanism is constructed by combining self-adaptive adjustment of a proportional-integral-derivative controller, so that the drying quality and the operation stability are improved.

The invention relates to the technical field of automatic control, and discloses a large-scale organ uniform controllable cooling method and system based on deep reinforcement learning and fuzzy control. The method comprises the following steps: constructing a high-precision temperature sensor array, and collecting multi-point temperature data on the surface and in the organ in real time; based on a biological heat transfer theory inverse problem model, reconstructing an organ three-dimensional temperature field in real time; a depth deterministic strategy gradient algorithm is adopted to optimize a fuzzy proportional-integral-differential controller. The depth deterministic strategy gradient algorithm takes minimization of organ internal temperature gradient as a primary optimization target, and parameters of a fuzzy PID controller are adjusted on line through interactive learning of an intelligent agent and a cooling environment, so that the power and the rate of a cooling module are accurately controlled. By means of the method, intelligent prediction and dynamic optimization of the cooling process can be achieved, the temperature gradient in the organ is smaller than 10 K / cm while it is guaranteed that the cooling rate reaches 15 K / min, and the success rate of low-temperature preservation of the large-scale organ and the activity of the large-scale organ after resuscitation are improved.

The invention discloses an automatic control method and system for a gas power generation boiler burner in the iron and steel industry. The method comprises the steps that an initial pressure set value is generated according to the mapping relation between a target load and main steam pressure, and the initial pressure set value is superposed with manual bias to serve as set value input of a proportional-integral-derivative controller; actual main steam pressure is collected to serve as process variable input of a proportional-integral-derivative controller, and then a first feed-forward signal is output through proportional-integral adjustment; the deviation between the main steam pressure set value and the actual main steam pressure is calculated to serve as steam pressure deviation, the steam pressure deviation is corrected through a lead-lag function, and then a second feedforward signal is generated through filtering processing; and calculating the deviation between the target load and the actual load, and generating a third feed-forward signal through piecewise linear function mapping. According to the design scheme, disturbance factors directly act on feed-forward compensation by bypassing a traditional control method, adjustment is rapid, and system fluctuation is reduced.

According to one aspect, the invention relates to a method (100) for controlling a position of a throttle valve of an engine, the method (100) comprising, when a difference in position between a position of the throttle valve and a position setpoint is determined, the steps that consist in: • - controlling (103) the position of the throttle valve by means of a proportional-integral-derivative controller applied to a pulse width modulation control of an electric motor configured to position the throttle valve, each of the terms of the controller being tabulated; • - adding (104) a first positive or negative offset to the proportional term when the determined position offset is positive or negative, respectively; • - adding (105) a second offset to the proportional term as a function of a pressure drop determined between the air inlet and the air outlet of the throttle valve body assembly; • - adding (106) a first oscillatory value dependent on the pressure drop to a value output by the controller; • - adding (107) a second value to the value output by the controller, the second value being selected from a table of throttle valve position differences measured with respect to a rest position of the throttle valve.

This invention provides a constant temperature and pressure control method and a high and low temperature low pressure test chamber. Through high-precision sensor array multi-source data acquisition, signal filtering and feature extraction, combined with improved Granger causality test and coupling spectrum construction, the main propagation path and propagation characteristics of various disturbances are identified. By using sliding window online optimization and dynamic weight matrix, the disturbance suppression mechanism is embedded in the PID loop to achieve multi-channel weighted compensation of proportional, integral and derivative components. This invention can accurately identify and compensate for external disturbances of different paths, time sequences and frequency bands in real time, improve the control accuracy and anti-interference ability of the system, and ensure the stability and robustness of the test chamber operation.

The invention relates to the technical field of shield tunneling machines, in particular to a shield tunneling machine continuous counter-pull control system for tunnel shield construction, which comprises a master control base station unit, a hydraulic pump station unit and a hydraulic execution module, the shield tunneling machine is subjected to continuous counter-pull starting driving through the hydraulic execution module, and the hydraulic pump station unit is communicated with the hydraulic execution module through a hydraulic pipeline. The hydraulic pump station unit provides a power source for the hydraulic execution module, and drive control over the hydraulic execution module is achieved. According to the control system, data are collected in real time through various sensors and fused, accurate state information is provided for the system, high-precision synchronous telescopic operation of all the hydraulic execution modules is achieved, proportion, integral and differential coefficients can be dynamically adjusted in cooperation with a self-adaptive PID control algorithm, and when errors are large due to the change of working conditions, the control precision is improved. And the proportionality coefficient can be quickly adjusted.

The invention provides a consumable rewarming device and system, and the device comprises a rewarming heating module which is used for carrying out the constant-power heating of a built-in electric heating element of a consumable; the temperature acquisition module is used for acquiring the temperature of the consumable target area where the electric heating element is located in real time in the constant-power heating process; and the data processing module is used for dynamically adjusting the output power of the rewarming heating module by adopting a proportional integral differential control algorithm based on the temperature of the consumable target area so as to maintain the temperature of the consumable target area at a preset target temperature. According to the method, the control accuracy of the consumable temperature is improved by adopting the proportional integral differential control algorithm. In addition, constant-temperature control over the consumables is achieved by dynamically adjusting the output power of the rewarming heating module; the hardware structure is optimized through multiplexing of the load detection module and the rewarming heating module; by adopting the high-precision temperature acquisition chip, high-real-time monitoring of the temperature of the consumable is realized.

The invention discloses a control torque determining method of a motor in a wheel steering system and a rear wheel steering method, the wheel steering system comprises the motor and a rack, the control torque determining method of the motor comprises the steps that input information is acquired, and the input information comprises target parameter information and actual parameter information of the rack or the motor; according to an error between the actual parameter information and the target parameter information, performing proportional-integral-differential operation to obtain a target control torque for controlling the motor, so that the motor drives the rack to move under the control of the target control torque; wherein when the integral operation of the proportional-integral-differential operation is carried out, the integral operation result is limited within a set range, and the set range is related to the error. According to the method for determining the control torque of the motor in the wheel steering system, the operation range of the integral term in PID control is limited, so that overlarge motor control torque and system oscillation caused by excessive accumulation of the integral term are avoided, and the energy consumption of continuously outputting high torque by the motor is reduced.

This invention discloses a method and system for dynamically adjusting the calibration cycle of electricity meters, relating to the field of smart grid electricity metering technology. The invention first uses an edge computing module to receive multiple self-diagnostic signals uploaded by the electricity meter. After judging the validity of the signals, it calculates the comprehensive degradation trend index and its rate of change. Based on the rate of change, it generates calibration cycle compression or extension instructions in real time. Simultaneously, an incremental proportional-integral-derivative controller corrects the adjustment strategy based on measured error feedback. The intermediate correction data is then uploaded to the cloud-based metering data center, where the cloud updates the degradation model parameters for the same batch and issues the long-term baseline calibration cycle. This invention enables closed-loop dynamic adaptive adjustment of the electricity meter calibration cycle, effectively improving the reliability of electricity metering, reducing metering operation and maintenance costs, and is applicable to the full lifecycle operation and maintenance management of smart grid electricity meters.

The invention discloses a satellite orbit simulation method and system based on a quad-rotor unmanned aerial vehicle, and belongs to the field of spaceflight technology and unmanned aerial vehicle systems.The method comprises the following steps that a satellite orbit and speed information are generated based on six elements of the satellite orbit, the satellite orbit is mapped according to a preset scaling, and the speed information of the satellite orbit is obtained; generating a reference orbit of flight of the four-rotor unmanned aerial vehicle; establishing a four-rotor unmanned aerial vehicle kinetic model; controlling the quadrotor unmanned aerial vehicle by using a proportional-integral-differential (PID) control algorithm for the obtained kinetic model; and filtering observation noise and external interference by using extended Kalman filtering (EKF), so that the quadrotor unmanned aerial vehicle can stably track and simulate a satellite orbit in a ground environment. The problems that satellite orbit in-orbit verification is high in cost, large in risk and non-repeatable can be effectively solved, ground rehearsal and advanced layout can be achieved on the strategic level, and the method has important significance on space task deployment and space safety in the future.

The invention provides a double-closed-loop decomposition prediction fractional order reinforcement learning power generation control method and device of a power system, computer equipment and a medium. A control framework of the method comprises an outer ring and an inner ring, and the frequency deviation of the power system is used as the input of the outer ring; firstly, a complete adaptive noise complete set empirical mode decomposition method is adopted to perform mode decomposition on frequency deviation; secondly, a Transform model is introduced to carry out prediction on the decomposed signals; classifying the signals on the basis of k-means clustering; and finally, through the synergistic effect of fractional order proportional integral differential and Q (lambda) learning, outputting an outer ring power generation instruction of the power system unit and taking the outer ring power generation instruction as the input of an inner ring. And the inner ring adopts a fractional order proportional integral differential method to learn and follow and output an inner ring power generation instruction of the power system unit. The method can solve the problem of uncertainty of power generation control in a novel power system, reduces frequency deviation, and improves control precision and system robustness.