Results 281 to 290 of about 649,170 (367)
Riemannian Manifolds for Biological Imaging Applications Based on Unsupervised Learning. [PDF]
Larin I, Karabelsky A.
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ABSTRACT The issue of master‐slave synchronization tracking control for uncertain teleoperation systems with input saturation and asymmetric time‐varying output constraints under actuator failure is investigated. Firstly, a neural network‐based nonlinear disturbance observer is designed to mitigate the negative impact of the compound uncertainty ...
Longnan Li+3 more
wiley +1 more source
Transecting and contrasting the feeding designs of the astigmatan community from bird nests. [PDF]
Bowman CE.
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ABSTRACT Effective physical human–robot collaboration (pHRC) requires strict safety guarantees since robots coordinate with human actions in a shared workspace. Moreover, compliance is essential, enabling robots to adjust their stiffness and behavior in response to human interaction forces. This paper presents a novel fixed‐time adaptive neural control
Yuzhu Sun+6 more
wiley +1 more source
Adaptive formation learning control for cooperative AUVs under complete uncertainty. [PDF]
Jandaghi E, Zhou M, Stegagno P, Yuan C.
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Safe Continual Learning in Model Predictive Control With Prescribed Bounds on the Tracking Error
ABSTRACT We develop a three‐component Model Predictive Control (MPC) algorithm to achieve output‐reference tracking with prescribed performance for continuous‐time nonlinear systems. One component is the so‐called funnel MPC, which achieves reference tracking with prescribed performance for the model output for suitable models.
Lukas Lanza+3 more
wiley +1 more source
Appointed time tracking control for marine surface vessels using the novel integral barrier function. [PDF]
Zhang T, Zhang G, Yan P, Zhang J.
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A condition for positive-definiteness of the Schur complement matrix of the magnetostatic problem
Hiroshi Kanayama+3 more
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Perturbation analysis of the Hermitian positive definite solution of the matrix equation X−A*X−2A=I
Mingsong Cheng, Shufang Xu
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ABSTRACT This work addresses the problem of developing a nonfragile sliding mode observer for fractional‐order complex networked systems (FO‐CNS) under stochastic network attacks. The proposed approach employs a combination of event‐triggered techniques. First, a nonfragile fractional‐order state observer is developed, enabling the design of a suitable
Xin Meng+2 more
wiley +1 more source