Adaptive fuzzy super-twisting sliding mode control with nonlinear active disturbance rejection for electromechanical stabilizer bars to improve vehicle roll stability. [PDF]
Nguyen TA.
europepmc +1 more source
From Artificial to Embodied and Physical Intelligence in Smart Manufacturing
Smart manufacturing is reframed through complementary artificial, embodied, and physical intelligence, spanning computational reasoning, perception‐action coupling, and material‐level adaptation. Their integration across design, fabrication, operation, and maintenance reveals how intelligence can be co‐designed across algorithms, embodied agents, and ...
Kang Wang +9 more
wiley +1 more source
Metasurface‐Based Multidimensional Light‐Field Manipulation: From Technologies to Applications
Multidimensional metasurfaces enable versatile manipulation of multiple optical degrees of freedom, including phase, amplitude, polarization, wavelength, and orbital angular momentum. This review summarizes their fundamental mechanisms, emerging strategies for multidimensional light‐field control, and key applications in optical computing, imaging ...
Heliang Yin +6 more
wiley +1 more source
Residual-activated smooth sliding-mode control for actuator-limited quadrotor UAV attitude-altitude tracking. [PDF]
Le TL, Hsieh MF.
europepmc +1 more source
Hydrodynamic Selection of Polymorphic Assembly Pathways in Plant Protein Amyloid Fibrils
Hydrodynamic conditions are revealed to govern polymorphic assembly of soy protein amyloid fibrils. Distinct flow‐induced drafting, kissing, and docking dynamics direct fibril growth into multiple morphologies, linking fluid mechanics with nanoscale assembly and enabling rational design of functional amyloid materials.
Zejian Xu +8 more
wiley +1 more source
Implementation and experimental validation of a hybrid intelligent sliding mode control strategy for induction motor drives. [PDF]
Pham NT.
europepmc +1 more source
Device Stochasticity Directly Implements Bayesian Sampling in Spiking Neurons
Brain‐inspired stochastic spiking turns device noise into Bayesian uncertainty for robust, low‐power neuromorphic computing. ABSTRACT Device stochasticity is considered a non‐ideality in neuromorphic hardware, although stochastic neural activity supports probabilistic computation in biological systems.
Huannan Zheng, Jingli Liu, Kezhou Yang
wiley +1 more source
Design of dynamic adaptive control framework for exoskeleton robot driven by neuromuscular signal based on deep reinforcement learning. [PDF]
Ma K.
europepmc +1 more source
A chip‐level VCMA‐MTJ array is demonstrated for stochastic neural‐network computing. Combined with a tail‐truncation strategy to compensate for device‐to‐device variations, it establishes a hardware–software co‐design approach for scalable probabilistic computing.
Jiachen Bao +15 more
wiley +1 more source
Electro-Ribbon Actuator-Driven, Responsive Skating Robot Inspired by Water Striders. [PDF]
Liu J, Zhao Y, Fu H, Liu Y, Zhou X.
europepmc +1 more source

