8 results about "Uncertain systems" patented technology

A computer implemented method for obtaining a real-time map, h(x), of a distribution in a D-dimensional space of a physical quantity, ƒ(x), describing a true phenomenon characterizing a complex uncertain system, wherein said physical quantity, ƒ(x), is inaccessible to direct measurements. The method can be utilized to obtain real time maps characterizing complex uncertain systems from scarce and indirect measurements, using non-invasive techniques.

This invention discloses an integrated optimization control method for multi-axle vehicles under hub motor failure and in-wheel motor malfunction, belonging to the field of multi-axle vehicle multi-wheel independent drive lateral dynamics control technology. First, an ideal dynamic model and reference behavior of the multi-axle vehicle are established. Then, based on the uncertainty of the vehicle dynamics system caused by tire cornering stiffness changes due to tire nonlinearity, the dynamics system of the multi-axle vehicle is rewritten to obtain an uncertain system. Next, based on the uncertain system, top-level and bottom-level controller designs are performed for the multi-axle vehicle under hub motor failure and in-wheel motor malfunction, realizing the yaw moment reconstruction and allocation constraints for each wheel, thus obtaining the optimal control method for the multi-axle vehicle under hub motor failure and in-wheel motor malfunction. This invention achieves optimal tracking performance under hub motor failure, realizing driving safety and energy efficiency for multi-axle vehicles.

This invention discloses an elastic control method for linear uncertain systems based on multi-rate state measurement information. The method includes establishing a linear dynamic model and a state estimation model based on multi-rate state measurement information of the controlled system; acquiring state measurement information of the controlled system; resetting the state of the state estimation model based on the state measurement information; designing an elastic control law based on the linear dynamic model and the state estimation model; inputting control commands based on the elastic control law into the actuator to stabilize the state of the controlled system; and controlling the system with a period T. s The above process is repeated at intervals until control ends. This invention can maintain stable system operation even when there are parameter uncertainties, actuator errors, and irregular updates of state measurement information.

The invention relates to the technical field of electronic manufacturing, and discloses an AOI detection collaborative optimization method and system applied to an AI re-judgment and intelligent screening mechanism, and the method comprises the following steps: S1, automatic optical detection data collection; s2, establishing AI server communication; s3, data extraction and transmission; s4, a data caching and delay control mechanism; s5, checking bad data; s6, carrying out secondary re-judgment by the re-judgment station equipment; s7, data file generation and tracing query; and S8, performing closed-loop feedback and model optimization. According to the AOI detection collaborative optimization method based on the AI re-judgment and intelligent screening mechanism, efficient transmission and scheduling of detection data, intelligent screening of AI results and closed-loop feedback of manual re-check are achieved, the problems that in the prior art, the re-judgment process depends on manual work, the judgment opportunity is uncertain, and system response is lagged are effectively solved, and the AOI detection collaborative optimization method based on the AI re-judgment and intelligent screening mechanism is achieved. And the intelligent level and the production efficiency of production line quality management are obviously improved.

The invention relates to the technical field of electric power system operation and control, in particular to application of a time-delay uncertain singular system based on an alpha-pessimistic value criterion in electric power. The method comprises the following steps: establishing a time-delay uncertain singular system model of a power system; based on an alpha-pessimistic value criterion, constructing an index function for evaluating the operation performance of the power system; constructing a zero-sum game framework; and equivalently converting the time-delay uncertain singular system model into a standard uncertain system model through model transformation to obtain an optimal source side control sequence and an optimal load side control sequence. According to the application of the time-delay uncertain singular system based on the alpha-pessimistic value criterion in power, time delay, uncertainty and system singularity are considered in power system optimization, and the alpha-pessimistic value criterion is introduced, so that a decision maker can flexibly express the risk preference of the decision maker by adjusting the confidence level alpha; extreme risks caused by uncertainty are avoided according to the alpha value, and the toughness of the power system in an uncertain environment is enhanced.

This invention discloses a method for predicting the dynamic response and reliability of a hybrid uncertain system, belonging to the field of uncertain system dynamics and reliability prediction. The implementation method of this invention is as follows: A polynomial surrogate model of the hybrid uncertain system is represented based on the PCLM method. An orthogonal polynomial basis corresponding to the random variables is established based on data-driven methods: a one-dimensional orthogonal polynomial basis is represented based on the origin moments of the random variables; a tensor product operation is performed to obtain a multi-dimensional orthogonal polynomial basis corresponding to the random variables; and Legendre polynomials are used as the orthogonal polynomial basis corresponding to the interval parameters. The coefficient matrix γ in the polynomial surrogate model of the hybrid uncertain system is solved using a double-weighted least squares method. Based on the established polynomial surrogate model, the dynamics and reliability of the hybrid uncertain system are predicted respectively. This invention can improve the accuracy and efficiency of predicting the dynamic response and reliability of hybrid uncertain systems.

The invention relates to an automatic driving fleet transverse dynamics inclusion control method based on output feedback, and the method comprises the steps: constructing a transverse dynamics model of an automatic driving vehicle, abstracting the transverse dynamics model as a leader following multi-agent system, and constructing a communication topological graph; designing an open-loop reference model and a closed-loop reference model for the follower agent; an open-loop reference model is constructed, the open-loop reference model comprises a controller, reference control input of a follower agent is solved, and the open-loop reference model is converged into a convex hull formed by the system state of the leader vehicle; and constructing a decentralized model reference adaptive output controller, updating the gain matrix and resolving the control input of the follower vehicle, so that the follower vehicle tracks the open-loop reference model, and the inclusion control of the automatic driving vehicle is realized. According to the method, when uncertain system parameters, unknown input gains and directed communication topology exist, the stability of a closed-loop system can still be ensured, a multi-agent inclusion control target is realized, and the engineering realizability and robustness of the method are improved.