27 results about "Model control" patented technology

The invention relates to an energy storage electric power spot market simulation clearing method based on hierarchical model control prediction, and the method comprises the following steps: S1, building an electric power spot market global simplified clearing model containing energy storage, and taking the model as an upper prediction control model; s2, establishing an electric power spot market detailed clearing model containing energy storage as a lower execution model; s3, dividing long-time simulation into M solving periods; in each solving period, global simplification clearing optimization is firstly utilized to obtain an energy storage final state SOC constraint value of each remaining period; on the basis of the energy storage final state SOC constraint value of the current period, market simulation clearing of the current period is completed by using a detailed clearing model; and finally, updating the system state according to the current clearing result, and rolling to advance to the next cycle until clearing of all cycles is completed. According to the method, dynamic global optimization of the energy storage SOC constraint is realized through a hierarchical model prediction control mechanism, and the calculation efficiency and the market simulation clearing effect are effectively balanced.

This application discloses a method and apparatus for constructing a Traditional Chinese Medicine (TCM) diagnostic and treatment knowledge model. The method includes: transforming a general-purpose basic language model into a model specifically for the TCM field to obtain a basic TCM model; controlling the obtained basic TCM model to learn diagnostic and treatment thinking within the TCM field to obtain a basic TCM diagnostic and treatment model; aiming to enhance the flexibility of logical reasoning in the obtained basic TCM diagnostic and treatment model, controlling the obtained basic TCM diagnostic and treatment model to learn the diagnostic reasoning paths of clinical cases in the TCM field to obtain a TCM reasoning diagnostic and treatment model; controlling the obtained TCM reasoning diagnostic and treatment model to learn the unique TCM knowledge and unique diagnostic and treatment thinking of a target renowned physician to obtain a unique TCM diagnostic and treatment model; and controlling the obtained unique TCM diagnostic and treatment model to favor the unique diagnostic and treatment thinking of the target renowned physician to obtain a TCM diagnostic and treatment knowledge model. This improves the diagnostic accuracy and clinical decision-making reliability of the model.

The embodiment of the invention provides a thermal management control method and device, a model training method and device, equipment and a storage medium. The method comprises the following steps that: cloud equipment constructs a multi-physical domain coupling training environment, customizes a multi-target reward function and a training model, and adapts the computing power of a vehicle controller through lightweight; the vehicle end is provided with progressive access mechanisms such as driving working condition judgment and heat management request recognition, three-level grading fault processing is matched, five-layer engineering post-processing such as amplitude limiting and rotating speed fusion is carried out on a model control signal, cooperative control over a battery and a cabin shared compressor is achieved, and finally closed-loop rolling regulation and control are formed. According to the scheme, the problems that a traditional strategy has no dynamic decision-making ability, a reinforcement learning model falls to the ground and breaks down, thermal management starting is extensive, and fault management and control are failed are solved, the battery temperature is accurately stabilized in the target interval, system energy consumption is dynamically optimized, and the vehicle end adaptability, the operation robustness and the whole vehicle safety guarantee ability of a thermal management system are greatly improved.

The utility model discloses a semitrailer driving simulation system, and belongs to the technical field of driving simulation training. Which comprises a cockpit, a main control circuit is arranged in the cockpit, and is characterized in that a semitrailer model is arranged, a model control circuit is arranged in the model, and a main controller circuit is in wireless connection with the simulation control circuit; the model comprises a vehicle body plate (10), a model control circuit and the vehicle body plate (10) are relatively fixed, a power unit and a steering unit are arranged at the bottom of the vehicle body plate (10), the model control circuit is connected with the steering unit, and front wheels (8) are symmetrically installed on the two sides of the steering unit. According to the semitrailer driving simulation system, by arranging the model in wireless connection with the cockpit and controlling the action of the model through the cockpit, the trainee can observe the driving state of the semitrailer at the third visual angle, and especially the training level of operation such as backing up of the semitrailer can be improved.

The application relates to a catheter control device, method and storage medium. The device comprises an acquisition module for acquiring a catheter radius, a real-time position of the catheter, a real-time respiratory amplitude of a target object and a first three-dimensional model; a determination module for determining a target object radius according to the real-time position; a first control module for controlling the catheter to run in a first branch of the target object according to a first registration matrix and the first three-dimensional model when the difference between the target object radius and the catheter radius is greater than a preset difference value; and a second control module for determining a second three-dimensional model according to the real-time respiratory amplitude, a preset respiratory amplitude, the real-time position, the first registration matrix and the first three-dimensional model, and controlling the catheter to run in a second branch of the target object when the difference between the target object radius and the catheter radius is not greater than the preset difference value. The method can improve the catheter control accuracy.

The invention discloses a refrigerating machine room intelligent management and control system and method based on dynamic correction, and relates to the technical field of intelligent management and control. The system comprises a data acquisition module, a model management and control module, a scheme optimization module and an instruction execution module. The method comprises the steps of collecting and verifying full-link equipment operation data of a refrigerating machine room, and generating an initial adjustment scheme; deducing a linkage failure path caused by an adjustment action in the management and control model and quantifying the probability, rejecting over-limit adjustment content in combination with a dynamic failure probability threshold, and obtaining a target adjustment scheme through collaborative verification iterative optimization; and based on the failure rule correction model parameters, converting the target scheme into a time sequence regulation and control instruction to be issued and executed, and forming closed-loop management and control through execution effect verification. According to the method, the failure risk can be pre-judged and adjusted in advance, equipment regulation and control conflicts and cascading failures are avoided, the adaptive capacity of the model is improved, the operation energy efficiency and stability of the refrigerating machine room are improved, and the operation requirements of the efficient refrigerating machine room are met.

The invention provides an intelligent nursing system and method integrating personalized traditional Chinese medicine fumigation physiotherapy and active pressure protection, and belongs to the technical field of medical nursing equipment. The system comprises a treatment applicator with a non-treatment area and a treatment area, a patient state sensing module, a body pressure distribution sensing device, a posture adjusting mechanism and a control module. The control module executes two control logics in parallel: the first control logic controls the treatment intensity based on patient state data and a machine learning model to realize personalized physiotherapy; the second control logic adjusts the patient posture to achieve active pressure protection when the stress exceeds a threshold based on the body pressure data and an internal stress calculated by the biomechanical model. According to the invention, cooperative work of treatment and prevention is realized, and the comprehensive nursing quality is improved.

The invention relates to a method for improving the adding precision of a denitration agent and controlling the response speed of a system, and belongs to the technical field of sintering desulfurization and denitration system control methods. According to the technical scheme, system operation state parameters are obtained through a sensor system, and a data training set is prepared; a denitration agent consumption prediction model is constructed, a data training set is used for learning, and model control parameters are obtained through online operation; constructing a cascade PID (Proportion Integration Differentiation) regulator which takes the NOx concentration of a chimney outlet as a set value and takes the frequency of an ammonia water motor as an output value in the L1 system; model control parameters serve as controller feedforward and are used for L1 closed-loop control, and the running frequency of the ammonia water motor is adjusted. The method has the advantages that the control precision of denitration agent adding and the response speed of an actuator can be remarkably improved, the method is suitable for various industrial application scenes, and the control effect can be continuously optimized through a machine learning model.

The invention discloses an aluminum oxide evaporation multi-stage flash tank control method based on model control, and the control method is used for stably and accurately controlling the temperature difference, liquid level and pressure parameters of each stage of flash tank in an evaporation process. The MPC model predictive control system intelligently analyzes the change of multi-parameter data to realize the output of control data, and module combination application can be carried out on different evaporation technological processes through a universal evaporation multistage flash tank MPC control module. Through a universal evaporation multistage flash tank MPC control module, a control method that a flash tank only controls a single parameter liquid level in a traditional method is changed into liquid level, temperature and pressure multi-parameter cooperative control. According to the method, the influence of multiple parameters on the flash evaporation intensity is considered, the problems that the aluminum oxide evaporation multi-stage flash evaporation tank is large in control fluctuation and prone to scabbing are solved, the control precision can be improved, the recovery amount of secondary steam is more stable, local concentrated scaling is avoided, and the equipment operation rate is increased.

The invention relates to the technical field of data processing of a control system, in particular to an internal model control system based on real-time self-adaptive online identification of an industrial system, which comprises a real-time data acquisition unit for acquiring an actuator opening instruction value, an actual controlled system output value and a model controlled system output value; the deviation calculation unit outputs a deviation value between the actual output value of the controlled system and the output value of the model controlled system; the dynamic parameter identification unit generates a weight factor in a linear proportional relationship with the square of the deviation value, outputs an adjusted gain parameter when the weight factor is greater than a preset threshold value, and outputs an adjusted time constant parameter when the weight factor is smaller than the preset threshold value; the internal model control model updating unit reconstructs a transfer function model; the controller parameter optimization unit outputs an optimized actuator opening instruction value; and the control execution unit drives the execution mechanism to enable the actual controlled system output value to respond to the instruction change. According to the method, the problems of dynamic response degradation and steady-state error increase caused by fixed parameter model mismatch are solved.

The application discloses an augmented reality-based model control method and system and a head-mounted display. The method comprises the following steps: generating a tooth model corresponding to patient gum data collected by a mouth scanning device based on an augmented reality environment of the head-mounted display; when the augmented reality environment enters a model editing interface, triggering a mouth scanning software in the head-mounted display to execute a corresponding control instruction based on somatosensory interaction information collected by the head-mounted display, so that the tooth model changes in a manner matched with the control instruction. The control instruction can realize editing control of the tooth model, so that a doctor can see an intuitive and accurate three-dimensional model in a head portrait, and edit the tooth model conveniently and quickly by using somatosensory interaction behavior, thereby abandoning a traditional mouse keyboard+screen mode and completing editing control of the tooth model by using augmented reality.

The present disclosure provides a substrate conveyance device and a substrate conveyance method that can perform accurate motion control even when a conveyance object other than a substrate is conveyed using a substrate conveyance module. A control section of the substrate conveyance device adjusts a magnetic force of a first magnet provided at a bottom surface section of a substrate conveyance chamber, a substrate is conveyed by a substrate conveyance module provided with a second magnet, a parameter storage section stores model parameters for expressing a relationship between a work force applied to a control model and a motion, the control model is a model that expresses a conveyance object and the substrate conveyance module as a whole, a control time table creation section outputs a control time table that specifies a work force for causing the substrate conveyance module to act, using model parameters corresponding to the conveyance object and an action time table that specifies a motion of the substrate conveyance module. A magnetic force adjustment section performs feedforward control in which the magnetic force of the first magnet is adjusted to apply the work force based on the control time table.

The utility model provides a kind of capsule robot device based on coil built-in exciting force drive, it is related to medical technical field.The utility model controls the axial pre-tightening force of magnetic field coupling drive module by pre-tightening force control module, effectively promotes the magnetic mechanical coupling efficiency of material, enhances the linearity and stability of exciting force output, secondly, by dynamic feedback control module, the motion state of capsule robot device is accurately controlled, closed-loop control is realized, and motion control precision is improved, then, by motion control module, the switching of the basic motion state and fixed-point fixed motion state of capsule robot device is realized, the positioning and inspection efficiency of pathological change position are improved, finally, by multi-module collaborative integration, device energy density is greatly improved, and high-reliability miniature driving solution is provided for robot endoscope, targeted drug delivery and other minimally invasive medical scenarios.

The invention provides a method for realizing uplink and downlink balance of a repeater based on a model control algorithm, and the method comprises the steps: monitoring and obtaining related data of the repeater based on a preset sampling frequency, and carrying out the preprocessing of the related data, the related data comprising a plurality of repeater parameters and a plurality of performance indexes of the uplink and the downlink; based on the plurality of performance indexes, determining the unbalance state of the uplink and downlink of the repeater, and a repeater parameter adjustment strategy and adjustment frequency corresponding to the unbalance state; determining a plurality of candidate adjustment schemes matched with the repeater parameter adjustment strategy; determining an output variable corresponding to each candidate adjustment scheme based on a link parameter coupling model, wherein the link parameter coupling model is constructed by adopting a model control algorithm in combination with related data; and determining a target adjustment scheme from the plurality of candidate adjustment schemes according to the output variable. Therefore, the repeater parameters can be automatically optimized through data driving and model prediction, and the uplink and the downlink can be accurately and quickly balanced.

The present application relates to the technical field of electromechanical control, and in particular to a dental electric motor rotating speed control method and system for a dental chair, comprising: acquiring a torque constant of a dental electric motor, current data of a current time node and a plurality of historical time nodes thereof; taking the product of the current data acquired at each time node and the torque constant as an instantaneous load at each time node; taking the average of the instantaneous loads at each time node as a dynamic reference load, calculating a load ratio and a load gradient at each time node, constructing a calibration hardness index based on the load ratio and the load gradient, and improving a loss function in a machine learning model based on the calibration hardness index; predicting an operating state of the dental electric motor at a next time point by using the improved machine learning model, and controlling the start and stop of the rotating speed of the dental electric motor based on the operating state. The present application solves the problem of poor control effect of the existing model.

The present application relates to the technical field of water pollution treatment, in particular to a wastewater intelligent denitrification self-adaptive control system and method. The present application integrates online monitoring, intelligent decision-making and automatic execution to build a closed-loop self-adaptive control system, significantly improving the system's adaptability to fluctuations in water quality and water quantity. When an impact load occurs, the system can quickly respond through the early warning mechanism and pre-set control strategy, automatically adjust the operating state, effectively avoid the efficiency decline or collapse risk caused by the poor impact load resistance of traditional systems, and ensure the long-term stable operation of the denitrification process. The control mode relying on artificial experience is changed, and through intelligent decision-making based on the adaptive control algorithm model, the system can dynamically optimize key parameters such as dissolved oxygen, carbon source dosage and reflux ratio according to real-time water quality data, realizing the transformation from experience control to precise model control, and greatly improving the real-time and fine level of control.

This invention discloses a model-based control method for liquid level control in alumina multi-effect evaporators. A universal evaporator liquid level MPC control module can be combined for different evaporation processes to stably and accurately control the liquid level in the multi-effect evaporator. Liquid level control is achieved by setting a liquid level setpoint and corresponding outlet pump frequency or outlet valve opening range. The MPC system intelligently analyzes changes in multiple parameter data to output control data, which is then seamlessly integrated with existing DCS control systems for automatic control. This method considers the interference of changes in evaporation water volume and the flow rate of the evaporating raw material during steam regulation on liquid level control. This invention features a high degree of integration with DCS systems and a high degree of automation, achieving stable and accurate MPC model predictive control of multi-effect evaporator liquid level. This reduces personnel workload and production instability, providing a solid foundation for pursuing automated and intelligent technologies that improve caustic alkali concentration and steam consumption reduction.

This invention discloses an improved extended state observer model-free control method for random load disturbance conditions, relating to the field of speed control technology under nonlinear loads and disturbance conditions. The method includes: establishing the mechanical motion equations of a coal unloading crawler device; the coal unloading crawler device consists of a chain system, a scraper bucket, a tensioning mechanism, a drive motor, and a main frame; establishing a hyperlocal model of the coal unloading crawler device based on model-free control theory and rewriting the extended state equations; addressing the limitations of the finite difference method by introducing an extended state observer to estimate all unknown dynamics in real time; and introducing a compensation function to construct an improved extended state observer, correcting estimation errors, thereby designing a model-free controller. This invention proposes an improved extended state observer structure, which suppresses high-frequency noise interference in disturbance estimation by introducing a filtering compensation mechanism, improving the observer's frequency domain performance and the system's dynamic response speed.

The invention discloses a double-rate model-free control method driven by a high-frequency motor. The core principle of the double-rate model-free control method is that a calculation-intensive task is separated from high-rate control execution; specifically, complex online model identification and time delay compensation are executed through slow-rate interruption, so that an accurate data driving model without physical parameters is obtained; meanwhile, a control sequence of a high-rate control period is generated at a time in slow-rate interruption by using an interpolation time translation prediction method; then, the high-rate interruption is only responsible for executing the pre-calculated control sequences one by one in sequence; due to the fact that correction based on the latest identification model is achieved on each high-speed control point, and the calculation burden of high-speed interruption is extremely low, the method fundamentally solves the problems of calculation real-time constraint and model parameter dependence in high-frequency control, and therefore high-robustness quasi cycle-by-cycle control of the high-frequency motor driving system is achieved.

The application discloses a low-speed wind tunnel test model control surface automatic control device, which comprises a support frame, a lead screw arranged in the support frame, a motor connected to one end of the lead screw and the other end of the lead screw arranged outside the support frame, a support rail parallel to the lead screw arranged on the bottom surface of the support frame, a support sliding block arranged on the support rail, a sliding block connected to the lead screw through a lead screw nut pair, a push rod connected to the side surface of the sliding block and in the same direction with the lead screw, a connecting block connected to the push rod and the support frame through shaft pins, respectively, and a position sensor arranged on the bottom surface of the support frame and below the sliding block. In the use process of the application, after the control surface is driven to the position by the double motors, a group of motors is reversely driven, the double lead screws are locked, and the control surface is stably arranged at the fixed position by utilizing the low reverse transmission efficiency of the lead screw and preventing the lead screw from rotating and the sliding block from moving when the load of the control surface is transmitted to the lead screw.

The present disclosure provides a substrate conveyance device and a substrate conveyance method that can perform accurate motion control even when a conveyance object other than a substrate is conveyed using a substrate conveyance module. A control section of the substrate conveyance device adjusts a magnetic force of a first magnet provided at a bottom surface section of a substrate conveyance chamber, a substrate is conveyed by a substrate conveyance module provided with a second magnet, a parameter storage section stores model parameters for expressing a relationship between a work force applied to a control model and a motion, the control model is a model that expresses a conveyance object and the substrate conveyance module as a whole, a control time table creation section outputs a control time table that specifies a work force for causing the substrate conveyance module to act, using model parameters corresponding to the conveyance object and an action time table that specifies a motion of the substrate conveyance module. A magnetic force adjustment section performs feedforward control in which the magnetic force of the first magnet is adjusted to apply the work force based on the control time table.

The invention discloses a structure fatigue damage prediction method and related equipment, and the method comprises the steps: constructing a double-rectangular spectrum analysis model composed of two independent rectangular power spectrum windows, and precisely representing the multiband, asymmetry and other complex features of a real spectrum through multi-parameter cooperative control; the analysis mapping relation between model control parameters and spectral width parameter pairs is established in combination with spectral moment decomposition, and the construction efficiency of the spectrum feature library is greatly improved on the premise of ensuring traversal comprehensiveness. Candidate frequency spectrums are screened in a spectrum width parameter plane by taking a target spectrum width parameter pair as a core, and weighted calculation is carried out according to parameter distance distribution weights, so that the reliability and stability of a fatigue damage prediction result are effectively guaranteed. The characteristic parameters are extracted based on the real frequency spectrum of the target structure, excessive dependence on empirical data is avoided, the method can adapt to structures of various load types, and the universality of the method is remarkably improved. According to the method, the fatigue damage prediction precision, the calculation efficiency and the scene adaptability are synchronously improved.

The invention discloses an electromechanical equipment energy-saving control method and system, and the method comprises the steps: starting electromechanical equipment, controlling the electromechanical equipment based on an expert strategy in a first time period, and carrying out the control of the electromechanical equipment for a second time period after the first time period; obtaining a first control parameter of an expert strategy at a second time and a second control parameter of the second time predicted based on an AI model; respectively inputting the first control parameter and the second control parameter into an energy consumption evaluation model, and determining first simulation energy consumption corresponding to the first control parameter and second simulation energy consumption corresponding to the second control parameter based on the energy consumption evaluation model; and determining a virtual energy-saving rate corresponding to the AI model according to the first simulated energy consumption and the second simulated energy consumption. And if the virtual energy-saving rate is greater than the preset energy-saving rate threshold, the energy-saving effect of controlling the electromechanical equipment based on the control parameter predicted by the AI model is superior to that of an expert strategy, and the expert strategy is switched to the AI model to control the electromechanical equipment, so that the energy-saving effect of the electromechanical equipment is better.

The application relates to the field of artificial intelligence, and provides an agent control model training method and device, computer equipment and a storage medium. The method comprises the following steps: an initial control model is used to control an agent to interact with a preset virtual environment, so that the agent outputs an interaction action according to a self state and an environment state of the virtual environment; a first execution frequency of each sub operation in the interaction action is counted; a target sub operation to be adjusted is determined from a plurality of sub operations according to the first execution frequency; first parameter information to be adjusted in the initial control model is determined according to the target sub operation, and at least the first parameter information is adjusted until a target control model is obtained, wherein the target control model controls a second execution frequency of the target sub operation in the process of interaction between the agent and the virtual environment to be the first execution frequency. In the process of training the agent control model, each sub operation is balancedly sampled, and the efficiency and training effect of model training are improved.