Results 161 to 170 of about 20,027 (232)
ABSTRACT This paper develops a framework for designing output feedback controllers for constrained linear parameter‐varying systems that experience persistent disturbances. We specifically propose an incremental parameter‐varying output feedback control law to address control rate constraints, as well as state and control amplitude constraints.
Jackson G. Ernesto +2 more
wiley +1 more source
Evaluating Pancreatic Cancer Treatment Strategies Using a Novel Polytopic Fuzzy Tensor Approach. [PDF]
Bilal M +3 more
europepmc +1 more source
Optimal Homogeneous ℒp$$ {\boldsymbol{\mathcal{L}}}_{\boldsymbol{p}} $$‐Gain Controller
ABSTRACT Nonlinear ℋ∞$$ {\mathscr{H}}_{\infty } $$‐controllers are designed for arbitrarily weighted, continuous homogeneous systems with a focus on systems affine in the control input. Based on the homogeneous ℒp$$ {\mathcal{L}}_p $$‐norm, the input–output behavior is quantified in terms of the homogeneous ℒp$$ {\mathcal{L}}_p $$‐gain as a ...
Daipeng Zhang +3 more
wiley +1 more source
A Study on the Structure of Ideal-Based Non-Zero Divisor Graphs Associated with <i>Z</i> <sub><i>n</i></sub>. [PDF]
Kadem S, Abd Aubad A.
europepmc +1 more source
ABSTRACT Data‐based learning of system dynamics allows model‐based control approaches to be applied to systems with partially unknown dynamics. Gaussian process regression is a preferred approach that outputs not only the learned system model but also the variance of the model, which can be seen as a measure of uncertainty.
Daniel Landgraf +2 more
wiley +1 more source
Adjoint <i>L</i>-functions, congruence ideals, and Selmer groups over GL n. [PDF]
Fong HL.
europepmc +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
The detection of algebraic auditory structures emerges with self-supervised learning. [PDF]
Orhan P, Boubenec Y, King JR.
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

