Results 201 to 210 of about 569,781 (362)
ABSTRACT This paper presents a robust control synthesis and analysis framework for nonlinear systems with uncertain initial conditions. First, a deep learning‐based lifting approach is proposed to approximate nonlinear dynamical systems with linear parameter‐varying (LPV) state‐space models in higher‐dimensional spaces while simultaneously ...
Sourav Sinha, Mazen Farhood
wiley +1 more source
Algebraic Approach to Maximum Likelihood Factor Analysis. [PDF]
Fukasaku R +3 more
europepmc +1 more source
ABSTRACT This study presents a novel Distributed Robust Adaptive Model Predictive Control (DRAMPC) for tracking in multi‐agent systems. The framework is designed to work with dynamically coupled subsystems and limited communication, which is restricted to local neighborhoods.
Fabio Faliero +2 more
wiley +1 more source
Geometric and arithmetic characterization of [Formula: see text]-module flatness with applications to tensor products. [PDF]
Tang JG, Lei HR, Liu M, Peng JY.
europepmc +1 more source
Arithmetical properties of finite rings and algebras, and analytic number theory [PDF]
John Knopfmacher
openalex +1 more source
The role of identification in data‐driven policy iteration: A system theoretic study
Abstract The goal of this article is to study fundamental mechanisms behind so‐called indirect and direct data‐driven control for unknown systems. Specifically, we consider policy iteration applied to the linear quadratic regulator problem. Two iterative procedures, where data collected from the system are repeatedly used to compute new estimates of ...
Bowen Song, Andrea Iannelli
wiley +1 more source
Reliability as Projection in Operator-Theoretic Test Theory: Conditional Expectation, Hilbert Space Geometry, and Implications for Psychometric Practice. [PDF]
Zumbo BD.
europepmc +1 more source
Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley +1 more source

