10 results about "Optimal control system" patented technology

The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a wide rotating speed range, and relates to the technical field of motor control. The application discloses an online optimization control system for realizing optimal efficiency of a motor in a

The invention discloses a sewage treatment process optimization control system based on ASM2 and BP models. The system comprises a data acquisition module for acquiring sewage parameters; the ASM2 mechanism modeling module is used for constructing an ASM2 dynamic mechanism model to simulate organic matter degradation, nitrification and denitrification, biological phosphorus removal and sludge generation and attenuation processes, and determining key state variables; the BP neural network prediction module obtains a joint prediction value of the effluent quality and the sludge yield according to the key state variable; the sludge reduction prediction and control module dynamically generates a sludge reduction control strategy on the basis of the joint prediction value in combination with a sludge generation mechanism of an ASM2 dynamic mechanism model; and the optimization control module optimizes the treatment process through a control strategy. According to the invention, the effluent quality prediction precision can be improved, stable and standard reaching is ensured, the strategy of dynamically optimizing the aeration rate, the reflux ratio and the sludge discharge rate is realized, the energy consumption is reduced, a sludge yield prediction model is established, and sludge reduction is realized.

The invention discloses an intelligent analysis system for public health decision and trend prediction. The intelligent analysis system comprises the following steps: establishing a random optimal control system state equation containing a drift term, a diffusion term and a control function, and an objective function; a disturbance term is introduced into the state equation, and an original optimal control problem is converted into a random differential game problem; constructing a smooth trajectory estimation function based on the observation data, and defining a joint objective function; solving a random differential game problem to obtain an optimal control function and a system parameter estimator; the method is applied to a random control SIRD infectious disease model, and dynamic estimation of time-varying parameters is achieved; and on the basis of an estimation result, predicting a future disease transmission trend, and providing decision support for prospective planning and accurate configuration of public health resources. According to the method, a system with high noise and time-varying parameters can be effectively processed, the prediction precision and robustness are improved, and a quantitative basis is provided for prevention and control of infectious diseases.

The application provides an optimization control method and an optimization control system for a refrigerating device of a liquid flow energy storage system. The optimization control method comprises: obtaining historical operation data of the liquid flow energy storage system under multiple complete charge-discharge cycles; constructing a regression model based on the historical operation data, the regression model comprising an output parameter and multiple input parameters, the multiple input parameters comprising a starting temperature of electrolyte in a charging stage, a set frequency of the refrigerating device in a constant-power charging stage, a set frequency of the refrigerating device in a constant-voltage charging stage, and a set temperature of electrolyte in a discharging stage, and the output parameter comprising an overall energy conversion efficiency of the liquid flow energy storage system; in the historical operation data, obtaining a data combination of the multiple input parameters corresponding to the highest overall energy conversion efficiency; obtaining an optimized combination of the input parameters based on the data combination and the regression model; and determining a control strategy of the refrigerating device according to the optimized combination.

This invention provides a greenhouse water, fertilizer, and pesticide optimization control system and method based on multi-factor coupling of environment, crop, and inputs. The system includes deploying a sensor network to collect greenhouse data, processing the data to generate a spatiotemporally continuous dataset, quantifying the dynamic causal chain of environment, crop, and inputs based on the generated dataset, generating a decision rule base, and fusing the decision rule base with the real-time simulation results of a root zone three-dimensional digital twin model to generate water, fertilizer, and pesticide control commands. This invention achieves continuous spatiotemporal acquisition and fusion processing of greenhouse environment, crop, and input data through a multimodal sensor network, constructs a decision rule base containing dynamic causal chains, and combines real-time simulation of the root zone three-dimensional digital twin model with Bayesian causal inference to generate precise water, fertilizer, and pesticide control commands. This effectively quantifies the nonlinear causal relationships between multiple factors and improves the scientific nature of decision-making.

The invention discloses an optimal control system and method for the hydrogen content in oxygen of an alkaline water electrolysis hydrogen production system. According to the optimal control system, a cooling water flow regulating valve, an alkali liquor heat exchanger, an alkali liquor circulating pump, a heater, an alkali liquor flow meter, an alkali liquor flow regulating valve, a temperature transmitter, a pressure transmitter, a hydrogen-in-oxygen detection instrument, an oxygen outlet film regulating valve, a vacuum degassing device and a controller are correspondingly arranged on an alkali water electrolysis hydrogen production system; key technological parameters such as current density, alkali liquor flow, tank temperature and system pressure in the operation process of the alkaline water electrolysis hydrogen production system are integrally regulated and controlled, and meanwhile hydrogen bubbles dissolved in alkali liquor in an alkali liquor circulation system are cooperatively treated, so that the hydrogen content in finally output oxygen is further greatly reduced, the efficiency of reducing the hydrogen content in the oxygen by the system is remarkably improved, and the energy consumption of the system is reduced. The safety of the system is ensured, and the performance of the system is improved.

The invention discloses a power distribution network fault rapid recovery optimization control system based on a low-voltage flexible interconnection device, and relates to the technical field of power grid fault optimization control, and the system comprises the following modules: a main network operation state prediction module which respectively obtains the voltage, current, phase and frequency of each line of a main network, and obtains a power grid operation state prediction module; a fault risk line is captured in main network lines through parameter periodicity judgment in each line of a main network, an off-network island data adjustment module is executed according to the fault risk line, a involved line is obtained according to a fault result of the fault risk line, and a involved database is established through the involved line; according to the scheme, the difference of voltage, phase and frequency of a grid-connected line in a main network and an off-grid island is calculated in an off-grid island data adjustment module, and an adjustment strategy is formulated according to a predicted fault line risk level; therefore, quick adjustment is facilitated, off-network switching is facilitated, and meanwhile, off-network island electronic equipment damage caused by frequent and large-amplitude adjustment of the catastrophe is avoided.

The invention relates to the technical field of greenhouse environment control, and provides a greenhouse environment man-machine cooperation optimal control system, which comprises a cloud platform, a local controller and a sensor, the cloud platform is used for implementing remote control, control decision support and hosting control of the greenhouse environment adjusting equipment; the local controller is used for implementing manual control and automatic control of the greenhouse environment adjusting equipment; the sensor is used for acquiring environment data in real time; wherein the cloud platform comprises a decision support module, a hosting control module and an optimal control generation module; the decision support module is used for pushing decision support information of greenhouse environment control to the planter; the trusteeship control module is used for sending a trusteeship control instruction aiming at the automatic control environment adjusting equipment to the local controller; and the optimal control generation module is used for deploying a greenhouse environment man-machine cooperation optimal control algorithm. According to the greenhouse environment man-machine cooperation optimal control system, optimal control over the greenhouse environment can be achieved, and the economic performance of greenhouse production is improved.

The present application relates to source network load storage collaborative control technical field, especially to a kind of based on intelligent fusion terminal's table area source network load storage collaborative optimization control system, the present application is collected by acquisition module, collects the energy characteristic parameter and collaborative response characteristic parameter of target table area historical period;Through analysis module, based on the energy characteristic parameter analysis energy characteristic representation value, based on the collaborative response characteristic parameter calculates collaborative response characteristic representation value;Through control module, based on the energy characteristic representation value determines corresponding control strategy;Through verification module, based on the collaborative response characteristic representation value determines whether the stability of table area source network load storage meets standard;Through feedback module, based on the difference between energy characteristic representation value and predetermined energy characteristic representation threshold determines the adjustment range of collaborative response characteristic representation threshold, and reacquire verification.The present application improves the response rate of source network load storage each link collaborative control by verification module and feedback module.

The application provides an optimization control method and an optimization control system for a refrigerating device of a liquid flow energy storage system. The optimization control method comprises: obtaining historical operation data of the liquid flow energy storage system under multiple complete charge-discharge cycles; constructing a regression model based on the historical operation data, the regression model comprising an output parameter and multiple input parameters, the multiple input parameters comprising a starting temperature of electrolyte in a charging stage, a set frequency of the refrigerating device in a constant-power charging stage, a set frequency of the refrigerating device in a constant-voltage charging stage, and a set temperature of electrolyte in a discharging stage, and the output parameter comprising an overall energy conversion efficiency of the liquid flow energy storage system; in the historical operation data, obtaining a data combination of the multiple input parameters corresponding to the highest overall energy conversion efficiency; obtaining an optimized combination of the input parameters based on the data combination and the regression model; and determining a control strategy of the refrigerating device according to the optimized combination.