88 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 discloses a two-degree-of-freedom thrust vector dual-rotor flight control method and device. The method comprises the following steps: analyzing and designing a two-degree-of-freedom thrust vector dual-rotor structure; according to the two-degree-of-freedom thrust vector dual-rotor structure, deriving a two-degree-of-freedom thrust vector dual-rotor dynamic model; a control distribution equation is deduced according to the kinetic model of the two-degree-of-freedom thrust vector double rotors, the kinetic model is decomposed into a matrix combination form through the control distribution equation, and the rotation angle of a joint and the rotation speed of the rotors are solved through the control distribution equation; according to the dynamic model of the two-degree-of-freedom thrust vector dual-rotor, a pose cascade PID-ADRC controller is designed, and the pose cascade PID-ADRC controller comprises a position cascade PID-ADRC controller and an attitude cascade PID-ADRC controller. The method has good control and stabilization effects on the two-degree-of-freedom thrust vector double rotors.

The invention provides an all-working-condition denitration system control method based on generalized predictive control and intelligent feedforward. The method comprises the following steps that a neural network algorithm is adopted, a transfer function model is obtained according to a historical data set and input into a generalized predictive controller, and a main loop controller is obtained; the main loop controller is used for main loop control to obtain a denitration inlet concentration prediction instruction, an ammonia spraying amount prediction instruction and denitration outlet concentration; and according to the ammonia injection amount prediction instruction, the denitration inlet concentration prediction instruction combined with the inlet concentration compensation algorithm, the denitration outlet concentration combined with the deviation protection logic, and the current ammonia injection amount combined with the historical optimal ammonia injection amount, obtaining a feed-forward master controller for controlling a feed-forward loop and updating the current ammonia injection amount. The control method provided by the invention has the advantages of good stability, reliability, predictive capacity, strong adaptability and good control quality, and can realize the optimal balance of denitration efficiency and economy.

The invention provides a control method and device of a parallel robot, a storage medium and the parallel robot, and the control method of the parallel robot comprises the steps: constructing a novel sliding mode function which is a function for describing a global nonsingular fast terminal sliding mode surface; acquiring an equivalent control law corresponding to the novel sliding mode function; obtaining an approaching control law corresponding to the novel sliding mode function; and controlling the parallel robot based on the equivalent control law and the approaching control law. In the process, the global non-singular fast terminal sliding mode surface is adopted, so that the global convergence speed of terminal sliding mode control can be improved, and the problems of singularity of the terminal sliding mode surface and low global convergence speed of the terminal sliding mode surface are solved. Besides, by utilizing the designed equivalent control law and approaching control law, the problem of uncertain disturbance caused by perturbation of kinetic model parameters can be improved, and meanwhile, when an external load changes, good control performance can be ensured.

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.

A non-strategy output feedback optimal tracking control method for a time-delay industrial process with unknown interference belongs to the field of advanced control of industrial processes, can overcome the problem that a conventional time-delay process control method excessively depends on a system model, and specifically comprises the following steps: step 1, describing a time-delay space expression form with interference, introducing a state increment and an output error to establish a new augmentation model; 2, introducing a time delay performance index, and designing a control strategy; 3, proposing a Q learning algorithm with fault-tolerant performance under a time delay condition, and solving an optimal control gain through continuous learning; according to the method, the optimal controller gain matrix can be found through continuous learning under the condition that a system accurate model is unknown, and a system output track can well track an expected value and achieve a good control effect under the condition that the system has state time delay and unknown interference.

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 system and method of a flexible interconnection device based on a back-to-back converter. The method comprises the following steps: establishing a nonlinear model of a BTB-VSC according to a topological structure of the BTB-VSC; the nonlinear model of the BTB-VSC is linearized, and a linear model of the BTB-VSC is obtained; designing a controller according to the linear model of the BTB-VSC; meanwhile, dynamic changes of alternating-current side inductance and direct-current side capacitance are considered, an augmented matrix K of state feedback control in a controller is calculated, it is guaranteed that all poles in the system are distributed in corresponding areas of a complex plane, and the system operates stably under the condition that bidirectional power flow and power grid equivalent impedance are uncertain. According to the method, good control performance can be achieved under the nondeterminacy of bidirectional power flow and power grid equivalent impedance, and the controlled variable has small overshoot on the step change of the reference value and the sudden change of the power grid equivalent inductance value.

The invention relates to the technical field of underwater vehicle control, in particular to an underwater vehicle attitude active-disturbance-rejection control method, system and equipment and a medium, which can construct a dynamic model, enable linear active-disturbance-rejection to be suitable for underwater vehicle attitude control and enable the active-disturbance-rejection control method to be more suitable for the engineering field. According to the method, the linear active-disturbance-rejection control theory developed on the basis of nonlinear active-disturbance-rejection control is adopted, the control system parameters are reduced to two, namely the controller bandwidth and the extended state observer bandwidth, the complexity of the control system is reduced, the number of the control parameters is reduced, engineering implementation is facilitated, a good control effect is achieved, and the method is suitable for large-scale popularization and application. The method is more suitable for the field of aircraft control system engineering application, and the design problem of an underwater aircraft attitude control system is solved.

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 invention discloses an electromechanical coupling resonance suppression method, a controller and a motor drive system, which relate to the field of electromechanical control technology and solve the problem that electromechanical coupling resonance between an electrical system and a mechanical system of existing complex electromechanical equipment affects system stability and accelerates component failure. The invention comprises the following steps: constructing a dynamic model of a mechanical system; constructing a control algorithm model of a control system: determining that a mathematical model of a control object in the control system includes a mathematical model of a permanent magnet motor and a converter, and designing a motor controller according to the mathematical model; constructing an electromechanical coupling model based on the dynamic model of the mechanical system and the control algorithm model of the control system; and analyzing the resonance characteristics of an electromechanical system based on the electromechanical coupling model to determine a resonance point. The method proposed by the invention combines ADRC, has good control performance when motor parameters change, and is robust to changes in PMSM parameters.

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 present application provides a method, device, electronic device and storage medium for self-tuning control parameters of an actuator. The method for self-tuning control parameters of an actuator includes: obtaining a response signal of an actuator control system; constructing an objective function according to a given command signal and an obtained response signal, wherein the objective function characterizes the dynamic performance index of the actuator control system, and the optimization variables of the objective function include control parameters; performing Bayesian optimization processing on the objective function to determine the optimal control parameters; and updating the control parameters of the actuator control system according to the optimal control parameters. The technical solution provided by the present application can reduce human intervention while improving the response speed and control accuracy of the actuator control system.

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.

The invention discloses a layered servo control method for a traveling tracked vehicle. A layered control framework is divided into a planning layer and a control layer; the planning layer receives the target position and speed and the current position and speed of the artillery through a dynamic planning model, plans a group of artillery position and speed sequences with shortest time consumption by taking the speed and acceleration of the artillery as constraints, and outputs the artillery position and speed sequences to the control layer; and the control layer receives the artillery position, the speed sequence and the design control law output by the planning layer through a model prediction controller, outputs a voltage control signal to a servo control system of the tracked vehicle, obtains a prediction error through feedback control, and obtains the voltage control signal through rolling optimization. According to the method, the servo system of the tracked vehicle during running is controlled by utilizing a dynamic planning algorithm and model prediction control, a planning layer provides a good signal for a control layer in hierarchical control, the control layer and the planning layer form a virtual closed loop, planning of the planning layer is influenced, a good control effect on the servo system of the tracked vehicle is achieved, and the control efficiency of the tracked vehicle is improved. And the convergence speed and the stability precision of the servo system are improved to a certain extent.

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 present invention discloses a feed-back type suspension control system based on a PI feed-forward model predictive control algorithm, which belongs to the field of vehicle control and includes the following steps: S1, establishing a dynamic model of a feed-back suspension system; S2, establishing a simulation model of an energy feedback control system; S3, designing a voltage outer loop controller, calculating a reference current through a PI controller and a model-based feed-forward compensator; and designing a load disturbance observer to observe changes in the load; S4, designing a current inner loop controller, calculating an optimal duty cycle through a model predictive control algorithm; and designing an inductor current observer to perform an equivalent estimation of the inductor current to avoid the influence of changes in input voltage and inductor resistance on the quality of the feedback power. The present invention can effectively improve the quality of the feedback power, and at the same time, can still maintain a good control effect when external disturbances occur. In addition, the present invention can also effectively improve the ride comfort and handling stability of the vehicle.

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 present invention discloses an event-triggered iterative learning consistency control method for a multi-agent system under FDI attack, which belongs to the field of intelligent control. The technical scheme proposed by the present invention is as follows: an autoregressive model of the output sequence is established, and the model parameters are trained and predicted in the first m iterations; after m iterations, an attack detection and compensation mechanism is added; based on the topological structure information, the consistency error ε is obtained by the state transfer iterative dynamic linearization technology. k,j (t+1) and the multi-lag input vector u k,j (t); design parameter estimator and iterative learning control law; establish event trigger mechanism model in order to reduce network communication resources. The present invention discloses an event triggered iterative learning consistency control method for a multi-agent system under FDI attack, which adds corresponding compensation schemes to the system after the attack to reduce the impact of the attack and ensure good control performance of the system.

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 directional energy deposition cooling rate active regulation and control system and method, and a storage medium, and the system comprises a temperature monitoring module which is used for collecting the temperature information of different positions; the LSTM model prediction module is used for predicting future temperature change according to the real-time temperature data and outputting a prediction result; the MPC control module is used for optimally calculating a cooling rate control strategy; wherein an optimal control parameter is calculated according to a prediction result of the LSTM model prediction module, and a cooling rate control signal is output; the cooling medium control module is used for adjusting the cooling rate according to the cooling rate control signal; and the feedback adjusting module is used for monitoring the actual temperature of the workpiece in real time, evaluating the cooling effect and transmitting feedback data to the MPC optimization control module to complete dynamic adjustment. By the adoption of the technical scheme, the problems that in the existing directional energy deposition process, the cooling rate is not accurately regulated and controlled, and changing working conditions cannot be adapted are solved.