4 results about "Stochastic control" patented technology

This invention discloses an elevator bearing safety early warning method, device, and medium based on the Internet of Things (IoT), relating to the field of control testing and monitoring technology. The method includes: acquiring raw analog signals and preprocessing them to generate synchronous data frames; decomposing fault impact sequences from the synchronous data frames and obtaining a bearing safety status index through weighted D-S evidence, while simultaneously matching a pre-diagnostic control logic library to generate a pre-diagnostic confidence identifier; based on the pre-diagnostic confidence identifier and the bearing safety status index, obtaining a dynamic health baseline through sliding retrieval and elastic tracking compensation, and dynamically extrapolating the control envelope through a stochastic control boundary evolution algorithm to generate a dynamic safety threshold; comparing the bearing safety status index with the dynamic safety threshold, evaluating link quality, and selecting a candidate route set; and obtaining the optimal route through a shortest delay tree to form an encrypted alarm stream. This invention achieves accurate generation of the dynamic safety threshold.

This invention relates to the field of new energy microgrid technology, specifically providing a method for calculating the probabilistic energy flow of an electricity-heat-gas-hydrogen multi-energy microgrid. The method includes: generating a set of correlated random control variables based on uncertainties on both the source and load sides of the multi-energy microgrid; establishing a linearized energy flow model of the multi-energy microgrid based on the physical characteristics of hydrogen-blended natural gas systems; generating a set of operating variables using the random control variable set and the linearized energy flow model, and obtaining a set of basic operating points for the power grid, heating network, and gas network subsystems; and performing multi-point linearized Monte Carlo probabilistic energy flow calculations on the basic operating point sets of multiple subsystems to obtain the probabilistic energy flow calculation results for the electricity-heat-gas-hydrogen multi-energy microgrid. This invention combines computational accuracy and efficiency, effectively reflecting the operating characteristics of multi-energy microgrids under hydrogen blending, and is suitable for calculating the probabilistic energy flow of electricity-heat-gas-hydrogen multi-energy microgrids in scenarios with a high proportion of new energy access.

The predictive controller determines, using the deep generative decoder model, a conditional probability distribution of latent representations of the perturbation conditioned on the portion of the observations of the perturbation, and samples the conditional probability distribution of latent representations to produce a latent sample of time series values of the perturbation that affects the mechanical system over a time horizon. The predictive controller decodes the latent sample using the deep generative decoder model to produce predicted values of the perturbation that act on the system over the time horizon using probabilities of the latent sample under the conditional probability distribution of latent representations, and controls the mechanical system using the predictive controller that determines control commands that change operating states of the mechanical system using probabilities of at least some of the predicted values of the perturbation.