Results 151 to 160 of about 7,730 (247)

Privacy‐Preserving Data‐Driven Distributed MPC for Heterogeneous Nonlinear Multi‐Agent Systems

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Distributed model predictive control (DMPC) is a cornerstone for coordinating multi‐agent systems, yet simultaneously ensuring data privacy, handling unknown nonlinear dynamics, and managing heterogeneous constraints remains an open challenge.
Mahmood Mazare, Hossein Ramezani
wiley   +1 more source

Friction‐Aware Force‐Realizable Safety Control for Four‐Wheel Independently Steered and Driven Mobile Robots

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Safety‐critical control remains a major challenge for four‐wheel independently steered and driven (4ISD) mobile robots, where high‐accuracy path tracking and obstacle avoidance must be achieved under over‐actuated steering–driving coordination, tire–ground friction limits, and wheel‐torque constraints.
Ruitong Liu, Kenji Hashimoto
wiley   +1 more source

Initial State Privacy of Nonlinear Systems on Riemannian Manifolds

open access: yesInternational 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
wiley   +1 more source

Hexapod Locomotion Across Structured and Unstructured Terrains: A Data‐Driven Review of Modeling, Control, and Validation

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT The design of a hexapod is complex and requires integration between kinematic models, control systems, and sensing. Existing literature has reviewed these sub‐systems in isolation. Since 2021, there has been no review of the field despite significant advancements in soft soil, lunar traversal, and artificial intelligence.
Akhil Rampersad, Bashan Naidoo
wiley   +1 more source

Covariant Approach to the Geometric Dilution of Precision. [PDF]

open access: yesSensors (Basel)
Montesinos RS   +2 more
europepmc   +1 more source

Machine learning‐driven advances in carbon‐based quantum dots: Opportunities accompanied by challenges

open access: yesResponsive Materials, EarlyView.
Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen   +8 more
wiley   +1 more source

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