Results 91 to 100 of about 10,836 (207)

Physics‐Informed Neural Networks for Battery Degradation Prediction Under Random Walk Operations

Quality and Reliability Engineering International, EarlyView.
ABSTRACT This study addresses the challenge of predicting the state of health (SoH) and capacity degradation in Battery Energy Storage Systems (BESS) under highly variable conditions induced by frequent control adjustments. In environments where random walk behavior prevails due to stochastic control commands, conventional estimation methods often ...
Alaa Selim, Huadong Mo, Hemanshu Pota, Daoyi Dong   +3 more
wiley   +1 more source

End‐to‐End Portfolio Optimization with Hybrid Quantum Annealing

Advanced Quantum Technologies, EarlyView.
This works presents a hybrid quantum‐classical framework for portfolio optimization that combines quantum assisted asset selection and rebalancing with classical weight allocation. The approach processes real market data, embeds it into Quadratic Unconstrained Binary Optimization formulations, and evaluates performance within a unified workflow ...
Sai Nandan Morapakula, Sangram Deshpande, Rakesh Yata, Rushikesh Ubale, Uday Wad, Kazuki Ikeda   +5 more
wiley   +1 more source

An improved quantum genetic algorithm with adaptive dynamic rotation for urban facility spatial optimization. [PDF]

Sci Rep
Tian H, He Y.
europepmc   +1 more source

Output Feedback Design for Parameter Varying Systems Subject to Persistent Disturbances and Control Rate Constraints

International Journal of Robust and Nonlinear Control, EarlyView.
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, Eugênio B. Castelan, Walter Lucia   +2 more
wiley   +1 more source

Mixed-integer, multi-objective layerwise optimization of variable-stiffness composites with gaps and overlaps. [PDF]

Struct Multidiscipl Optim
Zamani D, Racionero Sánchez-Majano A, Pagani A.   +2 more
europepmc   +1 more source

Recursive Feasibility of Nonlinear Stochastic Model Predictive Control With Gaussian Process Dynamics

International Journal of Robust and Nonlinear Control, EarlyView.
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, Andreas Völz, Knut Graichen   +2 more
wiley   +1 more source

Exploring the Boundaries of Modern Quantum Annealers with RNA Structure Prediction. [PDF]

J Phys Chem B
Andrews B, Abraham J, Fox D, Radja A.
europepmc   +1 more source

Periodic Scenario Trees: A Novel Framework for Robust Periodic Invariance and Stabilization of Constrained Uncertain Linear Systems

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This work proposes a new framework for stabilizing uncertain linear systems and for determining robust periodic invariant sets and their associated control laws for constrained uncertain linear systems. Necessary and sufficient conditions for stabilizability by periodic controllers are stated and proven using finite step Lyapunov functions for
Yehia Abdelsalam, Sankaranarayanan Subramanian, Sebastian Engell   +2 more
wiley   +1 more source

The role of identification in data‐driven policy iteration: A system theoretic study

International Journal of Robust and Nonlinear Control, EarlyView.
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

Growing and linking optimizers: synthesis-driven molecule design. [PDF]

Brief Bioinform
Descamps C, Bouttier V, Sanz García J, Lhuillier-Akakpo M, Perron Q, Tajmouati H.   +5 more
europepmc   +1 more source