Abstract: In the research on stabilizing continuous-time randomly sampled systems (RSSs) via a discrete-time approach, the objects of analysis and synthesis are mostly discrete-time stochastic models ...

Gear-obsessed editors choose every product we review. We may earn commission if you buy from a link. Why Trust Us? Here’s what you’ll learn when you read this story: Time crystals oscillate in ...

The increasing penetration of distributed generation and the evolving requirements of smart grids have heightened the demand for fast, accurate, and robust reactive power control in Static Synchronous ...

Zeroing neural network (ZNN) is viewed as an effective solution to time-varying nonlinear equation (TVNE). In this paper, a further study is shown by proposing a novel combined discrete-time ZNN ...

Researchers demonstrate a novel method for transforming continuous time crystals into discrete ones using subharmonic injection locking, offering new insights into ...

Recently I am working on a project called torchcontrol, which aims implementing parallel control system simulation and control library based on PyTorch. At the begining, I also tried to use state ...

Framework that allows the design, execution and analysis of generalized stochastic Petri nets (GSPN). It allows capturing multi-robot problems as a GSPN and simulate the model. Basic operations for ...

This paper proposes an analytic representation of sequence-space Jacobians in heterogeneous agent models with aggregate shocks in continuous time. Our approach is based on a pen-and-paper perturbation ...

Key Laboratory of Smart Manufacturing in Energy Chemical Process, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China ...

This paper presents an advanced control strategy for DC-DC buck converters utilizing Non-Minimal State Space (NMSS) representation combined with Proportional-Integral-Plus (PIP) control, optimized ...

Masked diffusion has emerged as a promising alternative to autoregressive models for the generative modeling of discrete data. Despite its potential, existing research has been constrained by overly ...