64 results about "Good control" patented technology

The invention relates to the technical field of solar thermal power generation, and discloses a mirror field and heat absorber cooperative control method and system, and the system comprises a simulation coupling module which determines a light incident angle based on irradiation data and a sun position model, builds a heliostat model in a simulation environment, simulates a three-dimensional thermal fluid, determines a heat absorber model, and controls the heliostat model and the heat absorber model; the control strategy module determines a control strategy according to the heliostat model and the heat absorber model, the control strategy module integrates a plurality of intelligent control algorithms, predicts a future state and adjusts control input based on the models, and the environment simulation module provides a training scene and a fault working condition scene of extreme weather and sets the extreme weather as a plurality of risk levels. The data analysis module collects and stores operation data, the operation state and performance indexes are displayed through a visual interface, control input is adjusted for the actual working condition and the future state on the basis of a dynamic model, and good control stability is achieved.

The invention belongs to the technical field of fabric process chain control, and particularly relates to a multi-process cooperative control system and method based on an open-width processing process chain. According to the method, the downstream is compensated in advance through disturbance source identification and feed-forward prediction, response lag and overshoot caused by disturbance transmission are remarkably reduced, the cloth cover is restored to a target state more quickly, and full-line tension fluctuation and breadth deviation are effectively reduced by coupling feed-forward and feedback and combining self-adaptive control of fabric humidity and temperature weighting; the defect rates of breadth breaking, wrinkling, edge warping and the like are reduced, the qualified rate and consistency of finished products are improved, a good control effect can be kept under different raw material, humidity and temperature conditions based on dynamic weight adjustment of historical data and fabric states, manual intervention and frequent parameter resetting are reduced, a disturbance source positioning mechanism can rapidly indicate the problem occurrence procedure, and the working efficiency is improved. And maintenance and root cause analysis are facilitated.

The invention discloses a data-driven modeling and predictive control method for an electroslag remelting process with a time delay characteristic. The data-driven identification modeling is performed on the electroslag remelting process based on a mechanism relationship between the stroke of a servo motor encoder and the output position of a consumable electrode; converting the transfer function model into a standard linear regression form; estimating a nonlinear time delay parameter by using a one-dimensional search algorithm, and constructing an adaptive forgetting factor by using an estimated parameter change rate; an augmented state vector is introduced into a historical control input sequence, so that an original time-delay system is converted into an equivalent time-delay-free augmented state space model; phase lag caused by multi-source time lag is dynamically compensated through a rolling optimization mechanism, interference of uncertain factors is effectively restrained in combination with feedback correction, an optimal control sequence is obtained, and a controller is made to control an electroslag remelting system with strong nonlinearity and multi-time-lag coupling dynamic characteristics in real time through the optimal control sequence. The method has excellent tracking precision and good control stability in the electroslag remelting tracking control process.

The invention discloses an industrial automatic control system based on batch production, and relates to the technical field of industrial automatic control, a matrix construction module compares the importance of indexes in pairs to obtain a judgment matrix, the judgment matrix is subjected to normalization processing, and then the weight vector of each index is calculated; the strategy output module generates the grey correlation degree of each alternative control strategy according to the difference coefficient, then substitutes the grey correlation degree of each alternative control strategy and the weight vector of the index into a fusion algorithm so as to calculate the comprehensive score of each alternative control strategy, sorts all the alternative control strategies according to the comprehensive score, and finally outputs the sorted alternative control strategies. And selecting the alternative control strategy with the first sequence to be applied to the current production scene of the production line. The control system can carry out multi-target comprehensive evaluation under an uncertain condition, so that the model can adapt to different production scenes, comprehensive optimization of multiple indexes is realized, and an optimal control strategy is selected for use.

The invention discloses a control method, a circuit and a driving mechanism of an underground three-phase brushless motor, and the control method achieves the high-adaptability control of an underground extreme working condition through fuzzy intelligent decision, directly generates a PWM duty ratio through the fuzzy reasoning taking the current deviation and change rate as the input, can rapidly inhibit the sudden change of a load, improves the response speed, and improves the reliability of the system. PID is combined with fuzzy control, so that a good control effect on nonlinearity, time-varying property and uncertainty of a controlled object can be achieved; in the driving mechanism, a driving combination composed of a three-phase brushless motor and a planetary gear reducer is connected with a transmission shaft through a flexible coupler, so that violent vibration impact of the driving mechanism in an oil well is reduced, the peak load of the driving mechanism is reduced, and the reliability of the driving mechanism is improved; and the wires are prevented from being broken in the assembly process.

The present invention discloses a human-in-the-loop human-machine collaborative driving method. This method uses the vehicle steering system as the control mechanism, integrates online identification of driver behavior and vehicle lateral stability control, and realizes human-machine collaborative driving for lane keeping tasks. It mainly includes establishing a vehicle chassis dynamics model and a driver behavior prediction model for lane keeping tasks; then, according to the established models, designing a model predictive controller based on Gaussian processes; then, dynamically updating the driver model based on road and vehicle state information and driver model uncertainty; finally, based on the adjusted driver model, calculating the control input according to the MPC control algorithm, and realizing lane keeping control by the steering system. The present invention first proposes a human-machine collaborative driving method based on the driver Gaussian process model, taking into account the requirements of model prediction accuracy and vehicle control real-time performance, and having good control performance in the lane keeping task scenario.

To obtain a control characteristic that is good for control objects having a strongly nonlinear characteristic.SOLUTION: A PC 1 for industrial use comprises: a contradiction determination unit 14 that determines whether there is a contradiction between first and second datasets among datasets of time-series data of controlled variables and time-series data of manipulated variables; a contradiction evaluation unit 16 that, when there is the contradiction, determines whether there is a contradiction between first and third datasets and whether there is a contradiction between the second and third datasets, and gives an evaluation point to either of the first and second datasets that does not contradict the third dataset; a priority evaluation execution unit 17 that gives a priority point to all datasets stored in a storage unit 11 in such a way that the order of priority heightens in decreasing order of the sum total of evaluation points; and a transmission unit 23 that transmits data generated from the dataset whose priority order is highest among the datasets stored in the storage unit 11, to a PID controller 2.SELECTED DRAWING: Figure 2

The invention provides a high-precision tandem cold mill second flow thickness control method which comprises the following steps: firstly, integrating an inlet / outlet second flow difference to correct a strip steel inlet speed, and pre-calculating a strip steel outlet thickness difference by using a second flow equation; compensating the speed difference between the inlet tension roller and the first rack, and correcting the second flow pre-calculation thickness difference by using the monitoring thickness difference; and finally, a self-adaptive PI controller is used for calculating the second flow thickness control quantity. According to the method, the error of the second flow of the inlet and the outlet and the speed difference between the inlet tension roller and the first rack are compensated, and the monitoring thickness difference correction is used, so that the high-precision outlet thickness difference value can be obtained. Proportions and integral parameters which change adaptively along with the speed and the response time of the adjusting mechanism are used to adapt to different working conditions, so that good control performance can be kept in the rolling process, and the overall precision of the second flow AGC is improved to a large extent.

The control system and method of the sock moving grabbing device have the advantages of being high in intelligent degree, good in control precision, high in self-adaptability and the like, the machine vision and sensor fusion technology is introduced, the edge position of a sock toe and the sock material characteristics are recognized in real time, and the sock moving grabbing device can be controlled in real time. Key parameters such as the opening angle, the downward moving distance and the folding time of the sheet grabbing needle are dynamically calculated based on a self-adaptive control model, and the socks of different specifications are accurately grabbed; meanwhile, a closed-loop control strategy and an online learning mechanism are adopted in the system, control parameters can be corrected in real time in the grabbing process, the grabbing success rate and stability are improved, the problems that in the prior art, sock bodies are prone to falling off, clamping stagnation is prone to occurring, and diversified production requirements are difficult to meet are effectively solved, and the automation level and production efficiency of the sock moving procedure are remarkably improved.

The application discloses a set top box control method and system, and relates to the technical field of data processing.The method comprises the following steps: generating a control instruction, generating a dynamic check code, and acquiring a main channel and a backup channel; acquiring a historical data processing period, acquiring a historical response time sequence and a historical calling time sequence, acquiring a historical channel stability index based on a stability model, the historical response time sequence and the historical calling time sequence, acquiring a correction ratio according to the historical channel stability index, and acquiring n' according to the correction ratio and n; acquiring a current response time sequence of the main channel and a current calling time sequence of the backup channel in a current data processing period; and acquiring a risk control strategy according to the historical response time sequence, the historical calling time sequence, the current response time sequence and the current calling time sequence.The application has the advantages of dynamic adjustment, good control effect and intelligent self-optimization.

The application provides a kind of impact hydraulic bulging branch pipe rebound measurement and control method, comprising S1 positioning installation mould, install pipe in mould, and set the best bulging parameter according to the characteristics of pipe and historical experimental data;S2 parameter setting is carried out based on XTDIC system measurement software, monitors the three-dimensional deformation of pipe in the bulging process;S3 marks the three-dimensional coordinates and coordinate displacement of key point position of bulging site;Real-time transmission displacement data to PLC program, obtains rebound displacement and its direction;PID control logic is constructed, and the amount of material supplement of punch is adjusted.The application uses PID control algorithm, according to the calculated error, continuously obtains the actual bulging value in the control cycle, generates control signal, adjusts the amount of material supplement, realizes accurate control rebound, ensures the forming quality of pipe, and the whole process depends on experiment and experience to optimize PID parameter, achieves the best control effect.

The invention relates to the technical field of hydroelectric generation, and discloses a multi-working-condition self-adaptive control method under optimized operation of a hydroelectric generating set, which comprises the following steps of: dividing working conditions of a hydroelectric generating set system, and taking a hydroelectric generating set speed regulator control performance comprehensive evaluation index and a set damping characteristic evaluation index as two optimization targets; a multi-target particle swarm optimization algorithm is adopted to solve the Pareto front of the system under each working condition, so that the Pareto front under all working conditions is obtained, and a thin-plate spline method is utilized to fit the optimal control parameter at the position with the minimum Euclidean distance from the original point on the front, so that the optimal control parameter curved surface under all working conditions is obtained; according to the method, the safety problem caused by primary frequency modulation of the unit in a traditional hydroelectric generating set control method is solved, the negative damping characteristic is prevented from being formed, meanwhile, the adjusting speed of the hydroelectric generating set is increased, and the system can be more rapidly kept stable and has good control performance.

A fully distributed control method for heterogeneous spacecraft formations considering time-varying topology and time-varying time delays is proposed. The method includes establishing an orbital dynamics model of the accompanying satellite formation with distinct input time delays and obtaining its state-space equations; establishing a signal model of the master spacecraft to be tracked and obtaining its state-space equations; constructing explicit fully distributed observers for each accompanying satellite to obtain the master spacecraft's state information constrained by time-varying communication time delays; designing explicit linear state feedback gains and feedforward gains respectively; and using the state feedback gains, feedforward gains, and fully distributed observers, establishing a corresponding fully distributed control protocol for the accompanying satellite formation system affected by time-varying topology and time-varying time delays to ensure that each accompanying satellite completes its tracking mission of the master spacecraft. This invention exhibits good control performance, ensuring stable operation of the heterogeneous spacecraft formation system and achieving the task of accompanying satellites tracking the master spacecraft.

The application discloses a kind of inhibiting overvoltage disturbance of double-fed wind turbine's collaborative control method belonging to wind power system control field.The rotor side converter control law of double-fed wind turbine is deduced by defining double-fed wind turbine machine side macro variable, the rotor side converter control law of double-fed wind turbine is deduced by defining double-fed wind turbine network side macro variable, and collaborative controller is constructed, above-mentioned control law replaces the current inner ring structure of classic double-loop control, parameter vector is selected using the parameter selection method of collaborative controller, and the collaborative control of inhibiting overvoltage disturbance of double-fed wind turbine is realized.The method disclosed by the application can reduce the influence of overvoltage impact on DFIG, reduce the reactive current output by DFIG, achieve the effect of inhibiting overvoltage, ensure the stable operation of DFIG, and has significant advantages in inhibiting overvoltage peak value and peak value duration and reducing electrical quantity overshoot, and has good control effect on high-dimensional nonlinear wind power system.

The application provides a cascade type multi-level rectifier topology and a control method thereof, a data model is established based on the topology, is discretized, a prediction model is formed, a reference voltage vector at a next moment is predicted, two basic voltage vectors closest to the reference voltage vector are selected by using a first value function, the action time of the two basic voltage vectors is calculated respectively, the action time is distributed to the corresponding basic voltage vectors, and double vector control is realized. The application can have the advantages of various topologies, has less current ripple, and has good control effect.

The application provides a self-reconfigurable carrying equipment control system adaptive reconfiguration method. According to different configurations of the self-reconfigurable carrying equipment, the internal control system of the cell unit is quickly reconfigured by itself, and the control system of the self-reconfigurable carrying equipment is jointly constituted, so that good control of different configurations of the equipment is realized. The control system reconfiguration adaptive method has an adaptive capability. After the mechanical reconfiguration of the cell unit is completed, the current equipment configuration state is autonomously detected, and adaptive reconfiguration of the control system is performed according to the current equipment configuration state, so that the corresponding hardware architecture and software algorithm are adjusted and matched. In the case of high-frequency reconfiguration of the self-reconfigurable carrying equipment, manual switching and other operations for the control system are not required, the automation degree of the self-reconfigurable carrying equipment is improved, and the time, manpower and other additional costs brought by the reconfiguration process are saved.

The application relates to a predictive control method and device based on an unknown parameter model, wherein the method comprises the following steps: parameter setting is performed on an unknown parameter model used for simulating a controlled real system to obtain model parameters; the model parameters of the unknown parameter model are updated through an adaptive observer, and a terminal domain of the unknown parameter model is calculated; based on the model parameters of the unknown parameter model, the adaptive observer and the terminal domain of the unknown parameter model, iterative calculation of a control quantity of the controlled real system is repeatedly performed, and when the number of times of the iterative calculation reaches a preset total iteration number, an optimal control quantity of the controlled real system is obtained. Through the application, the problem of how to perform predictive control based on an unknown parameter model is solved, the model parameters are updated based on the adaptive observer and are input into the unknown parameter model, the best control quantity is calculated by the model using the terminal domain, the robustness of the system is improved, and good control performance is achieved under the condition that the model parameters are unknown.

The invention discloses a multi-model adaptive control method based on robust optimization. The multi-model adaptive control method comprises the steps of obtaining a plurality of working condition sub-model prediction errors according to refrigerator operation parameters; respectively determining a prediction error index corresponding to each sub-model according to the plurality of sub-model prediction errors; obtaining the weight of each sub-model controller according to a preset normalization coefficient and each prediction error index; and performing fusion output on all the sub-model controller outputs and the corresponding sub-model controller weights to obtain an execution instruction. Perception-decision-execution closed-loop control is taken as core logic, self-adaptive control of the refrigerator is realized through a three-stage process of online monitoring (perception)-dynamic estimation (decision)-real-time adjustment (execution) in combination with an MMC system and a robust optimization technology, dynamic performance of the system is approached by utilizing multiple models, and a multi-model self-adaptive controller is designed based on the multiple models, so that the control precision of the refrigerator is improved. Good control precision, speed and stability are achieved for a complex system.

The invention discloses a dual-rotor unmanned aerial vehicle control method based on fuzzy control and active disturbance rejection control, and the method comprises the steps: S1), building a novel kinematics and dynamics model of a dual-rotor unmanned aerial vehicle, and constructing a complete model from input to control; s2) constructing an expansion state observer and a corresponding rule thereof in an inner layer by using active disturbance rejection control; s3) performing accurate sensing and recording on the attitude of the unmanned aerial vehicle on the outer layer by applying fuzzy control; and S4) constructing a cascade optimization strategy including analog control and active disturbance rejection control. According to the method, fuzzy control and active disturbance rejection control are integrated into a control framework of the double helicopters, the complexity of a dynamic model is solved, it is ensured that the unmanned aerial vehicle has excellent controllability and responsiveness in various foreign scenes, the control method of the double-helicopter unmanned aerial vehicle is enhanced, and the control efficiency of the double-helicopter unmanned aerial vehicle is improved. The method particularly focuses on the anti-interference control field of the double-helicopter unmanned aerial vehicle, has a good control effect, and can be widely applied to other anti-interference control systems.

To optimize a control target to be subjected to model prediction control by use of a black-boxed control target model.SOLUTION: Provided are: a black boxed control target model; a control input data group that indicates a time-series change of a plurality of pieces of control input data over a predicted time section with a first time as a start point; a predicted time section data acquisition unit that acquires a control output data group indicating a time-series change of a plurality of pieces of control output data corresponding to the control input data group; and an optimization input determination unit that generates, based on a degree of deviation between the control output data group acquired by the prediction time section data acquisition unit and a target value of a state of the control target, a favorable control input data group as the control input data group that brings the state of the control target closer to the target value and then determines an optimum value as control input data that optimizes the state of the control target from among the generated favorable control input data group.SELECTED DRAWING: Figure 1

The invention discloses a dynamic adaptive control system design method suitable for a modular aircraft, and belongs to the field of aircraft control. According to the method, a six-degree-of-freedom dynamic model of the modular aircraft is established; a module database of the modular aircraft is constructed; all modules are selected according to a flight task and a target to be assembled into an aircraft, and a flight program angle is selected according to a range table of the modularized aircraft; a BP neural network is used for designing an adaptive control system of the modular aircraft, the range of the modular aircraft and the speed, mass, rotational inertia, height and the like at the current moment are used as input quantities, and control parameters are used as output quantities. The adaptive control system has a good control effect on all combined modular aircrafts, so that technical support can be provided for the modular aircrafts to execute complex tasks.

The application discloses a kind of machine arm two degrees of freedom deformation quadcopter flight control method and device, comprising: S1, machine arm two degrees of freedom deformation quadcopter is designed in structure;S2, according to machine arm two degrees of freedom deformation quadcopter structure, derive the dynamics model and kinematics model of machine arm two degrees of freedom deformation quadcopter;S3, according to step S1, S2 derive the control allocation model of machine arm two degrees of freedom deformation quadcopter;S4, according to the control allocation model of machine arm two degrees of freedom deformation quadcopter in step S3 deduced, singularity problem is analyzed to control allocation model, and special control allocation model is designed to singularity;S5, according to the dynamics model, kinematics model, control allocation model and special control allocation model of machine arm two degrees of freedom deformation quadcopter, design pose quaternion nonsingular terminal sliding mode flight controller.The application has good control and stabilizing effect to machine arm two degrees of freedom deformation quadcopter.

The invention discloses a compensation loop low-frequency approximation-based second-order active-disturbance-rejection controller parameter setting method, which comprises the following steps of: deducing parameters of an active-disturbance-rejection controller, establishing a second-order large-inertia object transfer function model, and converting the transfer function model of a controlled object into a state space model; defining an extended state observer of the active disturbance rejection controller; compensating the total disturbance through a compensation loop to obtain a total control effect, and defining an outer loop controller based on the total control effect; on the basis of definitions of an extended state observer and an outer loop controller, a dimensionless number, a characterization observer bandwidth, a proportional gain parameter and a differential gain parameter are introduced, quantitative comparison is carried out on the basis of maximum sensitivity, then the dimensionless number and the dimensionless number are determined, and setting is completed. According to the method, the stability and robustness of a closed-loop system after parameter setting are guaranteed, the method is suitable for most thermal processes with second-order large inertia, and good control quality can be obtained.

The invention discloses a marine lightering device tail end horizontal stability maintenance control method based on NTSMC, and the method comprises the following steps: S1, building a horizontal luffing mechanism kinematic model based on kinematic analysis; s2, establishing a function relationship between the amplitude variation angle and the stroke of the driving device by using the mathematical model of the driving device and the kinematic model of the amplitude variation mechanism; s3, establishing a driving device mathematical model; s4, deducing an NTSMC control law by using the driving device mathematical model; and S5, establishing a system control model in combination with the NTSMC control law and the luffing mechanism transmission relationship. The method has relatively good control robustness and control precision, can realize efficient and safe lightering operation of personnel and materials, and is suitable for equipment for personnel and material maritime lightering such as a maritime wind turbine embarkation device; according to the invention, the safety and efficiency of the lightering operation of offshore personnel and materials can be obviously improved.

The application discloses a vehicle control method and a driving direction control system, which acquires the lateral deviation of a vehicle from a lane center line in real time, and when a preset compensation condition is met, dynamically compensates a proportional integral differential controller for lateral control according to the lateral deviation and its associated characteristic parameters, and then generates a direction correction instruction to adjust the driving direction of the vehicle. The method can adaptively match the PID control parameters to the current driving condition, effectively overcome the defects of response lag or control overshoot of fixed parameter control in complex scenes, significantly improve the accuracy and stability of the vehicle in the middle of the lane, and maintain good control performance under different conditions.

The invention provides a control method of a direct-current power transmission system and the direct-current power transmission system. The control method comprises the following steps: acquiring a direct-current voltage difference value between a direct-current voltage reference value sent by a sending end and a direct-current voltage measurement value sent by the sending end; determining a direct-current power reference value based on the direct-current voltage difference value, and taking the direct-current power reference value as an active power limit required by the converter at the sending end to access the direct-current power transmission system; the smaller value in the direct-current power reference value and the direct-current power real-time value is determined as a system power instruction value, auxiliary valve control of the sending end is carried out based on the system power instruction value so as to carry out reactive power control and harmonic cancellation, and the reactive power control comprises auxiliary valve outlet voltage control and angle control. The harmonic counteracting comprises harmonic current counteracting and harmonic voltage counteracting, and the angle is the phase difference between the outlet voltage of the auxiliary valve and the alternating current voltage accessed by the sending end. According to the scheme, the control effect is good, the control logic is simple, no additional coordination control system needs to be added, and the cost is low.

The application discloses a kind of based on model metric index's split-range control system performance evaluation method, belong to control system evaluation field.It includes: acquisition split-range control system output value, split-range control system's controller output value, split-range control system's candidate split-range point value, according to the comparison result of split-range control system's controller output value and candidate split-range point value, the output value of split-range control system obtained in sampling time period is divided into two data sets;Using prediction error algorithm, establish two time series autoregressive model and from discrete domain to continuous domain, with candidate split-range point as boundary, calculate the model metric index value of two continuous domain autoregressive model, the index reflects the split-range control system performance, to determine whether the optimal candidate split-range point is reasonable to judge candidate split-range point selection.The application solves the problem of split-range control system performance evaluation in complex control system, and the split-range control system can maintain good control level by determining the optimal split-range point.

The invention discloses an intelligent deep metal mine stope temperature control strategy, and belongs to the technical field of ore stope temperature control, and the strategy comprises the steps: reading the flow, temperature, pressure head and other actual system information in a PLC data block in real time; identifying characteristic parameters of each power component and the pipe network through experimental measurement and numerical model fitting; predicting the heat conductance of each heat exchanger in real time through an artificial neural network model; the minimum total energy consumption of the system is used as an optimization target, the overall heat transfer constraint and the flow constraint of the thermal management system are combined, a Lagrange optimization equation is established, the optimal frequency of each power component is solved, the frequency is input into a PLC in real time, the ventilation condition of each mine field is changed, and the temperature of each mine field is controlled. The mine field temperature control system integrates data reading, characteristic parameter identification, neural network model prediction, optimization solution and real-time feedback regulation, can effectively control the mine field temperature under the condition of low power consumption, and has the characteristics of high adaptability, high response speed, good control effect, high system robustness and the like.

The present invention proposes a PID soft reinforcement learning spacecraft attitude control method and computer-readable medium. The present invention constructs an improved SAC algorithm network, generates the control action of the spacecraft at the current moment through the improved SAC algorithm network, calculates the state data of the spacecraft attitude at the current moment and the control action of the spacecraft at the current moment through the Runge-Kutta numerical analysis method, and obtains the state data of the spacecraft attitude at the next moment; calculates the reward value at the current moment through an improved reward function model; and updates the policy network and value network based on the state data of the spacecraft attitude at the current moment, the control action of the spacecraft at the current moment, the state data of the spacecraft attitude at the next moment, and the reward value at the current moment. The present invention shortens the learning time of the SAC algorithm, and even when the parameters change, the algorithm can still maintain good control performance. In practical applications, the spacecraft can achieve attitude stability in a relatively short time.

The invention discloses a set top box control method and system, and relates to the technical field of data processing, and the method comprises the steps: generating a control instruction, generating a dynamic check code, and obtaining a main channel and a standby channel; acquiring a historical data processing period, acquiring a historical response time sequence and a historical calling time sequence, acquiring a historical channel stability index based on the stability model, the historical response time sequence and the historical calling time sequence, acquiring a correction proportion according to the historical channel stability index, and acquiring n'according to the correction proportion and n; acquiring a current response time sequence of the main channel and a current calling time sequence of the standby channel in the current data processing period; and obtaining a risk control strategy according to the historical response time sequence, the historical call time sequence, the current response time sequence and the current call time sequence. The method has the advantages of dynamic adjustment, good control effect and intelligent self-optimization.