Results 141 to 150 of about 190,067 (305)
Journal of Physics: Conference Series, 2018 A new approach to preconditioning based on LU - decomposition for solving systems of linear algebraic equations by iterative methods is proposed. The approach makes it possible to effectively to find an acceptable solution with a minimum filling of sparse matrices.
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Digital Twin Simulations Toolbox of the Nitrogen‐Vacancy Center in Diamond
Advanced Quantum Technologies, EarlyView.The Nitrogen‐vacancy (NV) center in diamond is a key platform within quantum technologies. This work introduces a Python based digital‐twin of the NV, where the spin dynamics of the system is simulated without relying on commonly used approximations, such as the adoption of rotating frame. The digital‐twin is validated through three different examples,
Lucas Tsunaki +3 more
wiley +1 more source
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 +2 more
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Optimal Homogeneous ℒp$$ {\boldsymbol{\mathcal{L}}}_{\boldsymbol{p}} $$‐Gain Controller
International Journal of Robust and Nonlinear Control, EarlyView.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
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
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We construct a higher level analogue of Dorey's rule, which describe certain surjective morphisms between Kirillov--Reshetikhin (KR) modules over quantum affine algebras. Building on this, we establish a generalized T-system of short exact sequences and prove the denominator formula between KR modules in all nonexceptional types, except with only mild ...
Oh, Se-jin, Scrimshaw, Travis
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Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
International Journal of Robust and Nonlinear Control, EarlyView.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
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Journal of Field Robotics, EarlyView.ABSTRACT This paper presents a novel cable‐climbing mechanism: the Collaborative Climbing Robot Squad (CCRobot‐S), a variant of Reconfigurable Cable‐Driven Parallel Robots (R‐CDPR), specifically designed for the inspection and maintenance of stay cables.
Zhenliang Zheng +4 more
wiley +1 more source
Assessing Capability Complexity Using Enterprise Architecture Framework
Systems Engineering, EarlyView.ABSTRACT This study proposes a structured and quantitative methodology to evaluate the holistic complexity of system‐of‐systems (SoSs), employing the Zachman Architecture Framework (ZAF) as its foundational analytical tool. A five‐phase analytical procedure is developed and empirically validated, encompassing: (1) refinement of complexity measures, (2)
Javad Bakhshi, Mahmoud Efatmaneshnik
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Enhancing generalized spectral clustering with embedding Laplacian graph regularization
CAAI Transactions on Intelligence Technology, EarlyView.Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang +5 more
wiley +1 more source