Results 191 to 200 of about 16,861 (262)

Deterministic, stochastic, and mean-field PDE models in neuroscience. [PDF]

open access: yesFront Comput Neurosci
Çetin C   +5 more
europepmc   +1 more source

Exact Robust Filtering and Differentiation Based on Sliding Modes and Homogeneity

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This article addresses the problem of online estimation of the derivatives of a signal corrupted by measurement noise. The measured signal is modeled as the sum of a smooth nominal component and a uniformly bounded noise term. A key objective is to attenuate the effect of high‐frequency noise.
Jaime A. Moreno, Arie Levant
wiley   +1 more source

High‐Order Sliding‐Mode control for MIMO Systems

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper extends Lyapunov‐based homogeneous high‐order sliding‐mode control to a class of uncertain non‐square multi‐input multi‐output (MIMO) nonlinear systems with a well‐defined vector relative degree. The considered systems admit a normal‐form representation with an uncertain but full‐row‐rank input‐gain matrix.
Jaime A. Moreno, Angel Mercado‐Uribe
wiley   +1 more source

Nonlinear Receding‐Horizon Differential Game for Drone Racing Along a Three‐Dimensional Path

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Drone racing requires high‐speed navigation through three‐dimensional paths, posing significant challenges in control engineering. Existing control methods lack a feedback control framework that simultaneously addresses nonlinear drone dynamics and multi‐agent competitive interactions, such as overtaking or obstructing opponents.
Kijin Sung   +4 more
wiley   +1 more source

Feedback Linearisation with State Constraints

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Feedback Linearisation (FBL) is a widely used technique that applies feedback laws to transform input‐affine nonlinear control systems into linear control systems, allowing for the use of linear controller design methods such as pole placement.
Songlin Jin, Yuanbo Nie, Morgan Jones
wiley   +1 more source

Redefining Optimal Coverage Path Planning for FLS‐Equipped AUVs With Deep Reinforcement Learning

open access: yesJournal of Field Robotics, EarlyView.
ABSTRACT Autonomous Underwater Vehicles (AUVs) have emerged as indispensable tools for a variety of subsea tasks, from habitat monitoring and seabed mapping to infrastructure inspection and mine countermeasures. A fundamental challenge in this field is Coverage Path Planning (CPP), the problem of ensuring complete and efficient area coverage.
Lorenzo Cecchi   +3 more
wiley   +1 more source

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