8 results about "Artificial systems" patented technology

The invention belongs to the technical field of unmanned surface vessel control, and particularly relates to an unmanned surface vessel trajectory tracking method based on parallel model predictive control, which comprises the following steps: S1, establishing an unmanned surface vessel mathematical model including dynamic uncertainty and external unknown disturbance; s2, constructing a mathematical model of the virtual artificial system, and designing a finite time auxiliary parallel controller based on the virtual artificial system; s3, constructing a Lyapunov tightening constraint condition with virtual and real information; s4, designing a predictive control optimization problem based on a flat luggage apunov model, and proving the stability of the dynamic model of the unmanned surface vessel; s5, the stability of the finite time auxiliary parallel controller is proved; s6, analyzing the feasibility of the prediction control optimization problem based on the flat luggage Yapunov model; and S7, simulation verification research is carried out, trajectory tracking is carried out on the unmanned ship under the dynamic uncertainty and external unknown disturbance conditions, and the effectiveness of the trajectory tracking method is verified.

The invention discloses a multi-agent-based enterprise operation automatic control system and method, and relates to the technical field of enterprise operation management and artificial intelligence. The system comprises a data modeling and storage layer, a data acquisition and perception layer, a multi-agent operation brain layer and an execution and feedback layer. The data modeling and storage layer constructs a unified operation data model containing three core entities of Item, Actor and Event; the data acquisition and sensing layer acquires heterogeneous data and converts the heterogeneous data into standard Event; the multi-agent operation brain layer generates a global optimal decision set through parallel decision making of a plurality of service agents and overall planning and optimal selection of coordination agents; and the execution and feedback layer converts the decision into a standardized instruction adaptive to manpower, a system and a robot to realize execution and adaptive optimization. According to the invention, multi-industry adaptation, automatic decision making and full-link closed loop are realized, the future robot operation form is supported, and the enterprise operation cost is reduced.

The invention relates to the field of coal water control, in particular to a safety early warning method for coal water coordination control, which comprises a data acquisition module, a danger early warning module, an early warning processing module and a manual optimization module, the danger early warning module comprises sensing data transmission comparison and early warning response, the early warning processing module comprises instrument automatic processing and manual processing, the manual optimization module comprises manual system improvement and manual training drilling, sensors can be placed at different positions, data collection can be increased on a large scale, the data accuracy is improved, and the accuracy of the data is improved. According to the utility model, the data is analyzed through the controller, grading early warning is carried out, small alarm situations can be automatically processed through the controller, when large alarm situations occur, related personnel can be assisted to process the large alarm situations, the labor intensity of the related personnel is reduced, and the emergency processing capability is improved by training operators and organizing emergency drilling at regular intervals.

This application provides a method for controlling the adhesive amount of corrugated cardboard based on industrial artificial system optimization, comprising: acquiring adhesive amount data and coating thickness data of coating equipment; processing the adhesive amount data and coating thickness data using a machine learning algorithm to obtain adhesive amount control parameters and thickness optimization parameters; acquiring real-time monitoring signals from the optimized equipment configuration; transmitting the real-time monitoring signals for environmental factors during the substrate coating process to obtain environmental data; analyzing the environmental data using a machine learning algorithm to determine the relationship between humidity adjustment requirements and temperature control requirements; if the humidity adjustment requirement is higher than the temperature control requirement, prioritizing the determination of a humidity adjustment command; acquiring the current humidity value according to the humidity adjustment command; optimizing the adjustment path using an evolutionary algorithm to obtain a supplementary temperature control command; acquiring micro-control updates from the final adjustment scheme and transmitting them to an intelligent optimization network to obtain an overall operation optimization result.

A construction method of a derrick parallel control digital twinning system comprises the steps that S1, a digital twinning geometric model of a derrick is constructed based on derrick work site and derrick structure data, a knowledge graph of the derrick is constructed based on data related to the derrick, and the knowledge graph and the digital twinning geometric model of the derrick are fused to deduce a construction planning process scheme; s2, on the basis of the digital twinborn geometric model of the derrick, simulation of derrick operation is carried out according to different working conditions, an intelligent derrick parallel controller is constructed, intelligent prediction is carried out on the basis of a simulation result by using an extreme random tree algorithm in combination with a Donglong optimization algorithm, and a multi-target optimization solution model is constructed; and S3, integrating the multi-target optimization solution model into a derrick parallel controller, and realizing parallel control of the derrick by taking a construction planning process as a target. The deduction result of the design serves as a control target of a physical system, parallel control of the physical system and an artificial system is achieved, and then digital management and control of power grid tower building construction are achieved.

The invention provides a test method and system for a vehicle-mounted infotainment system, and the method comprises the steps: obtaining a test demand of the vehicle-mounted infotainment system, and generating a test case of the vehicle-mounted infotainment system based on the test demand; wherein the test case comprises user operation simulation and environment scene simulation; performing combination optimization on the test case, and generating an automatic test script based on the optimized test case; and executing the automatic test script, collecting test data in a test process, and generating a test report based on the test data. According to the invention, the problems of low test efficiency, unstable test quality and high test cost in the traditional manual IVI system test are solved.

The application provides a power generation control method based on a distributed parallel multi-layer model predictive control, which comprises two modules of a distributed parallel system and a multi-layer input model predictive control. The distributed parallel system constructs a multi-region power generation control model based on model predictive control according to an actual power system, forms a distributed multi-agent virtual system, and corrects each other with the actual system. The regional control deviation, the frequency deviation, the epidemic prevention and health management information, the weather information, the four-hour predicted load value and the day-ahead scheduling constitute the multi-layer input of the model predictive control module. The distributed parallel multi-layer model predictive control method can solve the problems existing in the current power generation control method, effectively balance the active power of the power generation control system, reduce the frequency deviation, fully develop the potential of the artificial system, solve the problem of establishing an accurate mathematical model for a complex system, optimize the difference between the states evaluated by the actual system and the artificial system, and improve the fitting degree of the actual system and the virtual system.

Artificial material systems that seek to mimic the basic processes of life must perform multiple complex functions including responsiveness, motion, and metabolism. Networks of programmable materials offer a pathway toward achieving these functions by altering local chemical, physical, and structural properties to enable control. We demonstrate the ability to perform multiple complex functions in a single soft elastomeric material system by reconfiguring, in situ, passive bistable fluidic diodes that are inspired by mammalian venous valves. We show how pneumo-mechanical programmability allows these silicone elastomer diode assemblies to accomplish, without rearranging the fluidic circuit, multiple functions including pumping (motion), energy storage / discharge (metabolism), logic operations (response), and signal filtering / rectification. The ability to achieve multiple functions through in situ programming may lead to the development of efficient artificial systems capable of complex functions in compact, remote applications.