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Data‐Driven and Physics‐Informed Modeling Perspectives for Soft Manipulators: From SINDy to Hybrid Intelligence

Advanced Science, EarlyView.
This Perspective charts the modeling landscape for soft manipulators, spanning sparse system identification, neural dynamics, physics‐informed models and hybrid intelligence. We examine how physics, data, sensing, adaptation and control can assume complementary roles within this landscape, and provide a framework for selecting modeling approaches ...
Wenbo Hui, Yunyi Wang, Teng Zhang, Yang Chen, Min Pan   +4 more
wiley   +1 more source

Stability control of suspended monorail vehicles based on PID and quadratic programming allocation. [PDF]

Sci Rep
Jiang Y, Wang D, Chen R, Wang Q, Du Z.
europepmc   +1 more source

Adaptive Integral Sliding Mode Control for Temperature Regulation in Gas-Phase Ethylene Polymerization Fluidized Bed Reactors. [PDF]

Polymers (Basel)
Ghasem N.
europepmc   +1 more source

Latency-aware attitude control of underactuated quadrotor UAVs using barrier Lyapunov and fuzzy Padé approximation. [PDF]

Sci Rep
Abro GEM, Memon SA, Hoshu AA, Saeed N.
europepmc   +1 more source

An Outline of New Approach to Computation with Z-Numbers Based on the Concept of Lower Prevision. [PDF]

Entropy (Basel)
Aliev R, Huseynov O, Nuriyev A.
europepmc   +1 more source

A Caputo fractional-order SEIHRD model for Ebola: theoretical analysis, sensitivity, bifurcation, and numerical simulations. [PDF]

Sci Rep
Malathy R, Krishnan GSS, Loganathan K.
europepmc   +1 more source

Optimizing green hydrogen production: a comparative analysis of MPPT control strategies for PV-powered PEM electrolyzers using differentiated creative search optimization algorithm. [PDF]

Sci Rep
Mohamed AA, Ali MH, Omar AI, Mehanna M.
europepmc   +1 more source

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Fuzzy measures and integrals

Fuzzy Sets and Systems, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Radko Mesiar
exaly   +4 more sources

Fuzzy ontologies and fuzzy integrals

2011 11th International Conference on Intelligent Systems Design and Applications, 2011
Fuzzy ontologies extend classical ontologies to allow the representation of imprecise and vague knowledge. Although a relatively important amount of work has been carried out in the last years and they have been successfully used in several applications, several notions from fuzzy logic, such as fuzzy integrals, have not been considered yet in fuzzy ...
Bobillo F, Straccia U
openaire   +2 more sources