Results 21 to 30 of about 698 (138)

Optimal Gain Selection for the Arbitrary‐Order Homogeneous Differentiator

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Differentiation of noisy signals is a relevant and challenging task. Widespread approaches are the linear high‐gain observer acting as a differentiator and Levant's robust exact differentiator with a discontinuous right‐hand side. We consider the family of arbitrary‐order homogeneous differentiators, which includes these special cases.
Benjamin Calmbach, Jaime A. Moreno, Johann Reger   +2 more
wiley   +1 more source

Discrete Implementations Modify the Intuition of Final Set Adjustment in Barrier Function Based Control

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper establishes an implementation‐aware framework for Barrier Function Adaptation (BFA) and shows that discrete‐time realizations fundamentally alter the logic of final‐set adjustment. In particular, sufficient conditions are derived to preserve the key benefits of BFA (predefined performance, gain adaptation with uncertain perturbation
Luis Ovalle, Andrés González, Leonid Fridman, Meléndez Alfredo   +3 more
wiley   +1 more source

Exact Robust Filtering and Differentiation Based on Sliding Modes and Homogeneity

International 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

Multi‐Objective Bayesian Co‐Optimization of Parameterized Moving Horizon Estimation and Model Predictive Control

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper proposes a Machine Learning (ML)‐enabled estimator‐controller design framework, in which a parameterized Model Predictive Controller (MPC) and a parameterized Moving Horizon Estimator (MHE) are jointly refined using Bayesian Optimization (BO).
Hossein Nejatbakhsh Esfahani, Javad Mohammadpour Velni   +1 more
wiley   +1 more source

Study of the Blow Up of the Maximal Solution to the Three-Dimensional Magnetohydrodynamic System in Lei-Lin-Gevrey Spaces

International Journal of Analysis and Applications, 2020
In this paper, we investigate existence, uniqueness and blowup in finite time of the local solution to the three dimensional magnetohydrodynamic system, in Gevrey-Lei-Lin spaces. To prove the blowup results and give the blow profile as a function of time,
Ridha Selmi, Jamel Benameur
doaj  

Feedback Linearisation with State Constraints

International 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

AGT: Efficient Offline Reinforcement Learning With Advantage‐Guided Transformer

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Offline reinforcement learning (RL) is a paradigm that seeks to train policies directly based on fixed datasets derived from previous interactions with the environment. However, offline RL faces critical challenges in environments characterised by sparse rewards and datasets dominated by suboptimal trajectories.
Jiaye Wei, Xin Xu, Yixing Lan, Tenglong Liu, Yueying Wang   +4 more
wiley   +1 more source

Identifiability conditions in cognitive diagnosis: Implications for Q‐matrix estimation algorithms

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract The Q‐matrix of a cognitively diagnostic assessment (CDA), documenting the item‐attribute associations, is a key component of any CDA. However, the true Q‐matrix underlying a CDA is never known and must be estimated—typically by content experts.
Hyunjoo Kim, Hans Friedrich Köhn, Chia‐Yi Chiu   +2 more
wiley   +1 more source

Calibrating Bayesian inference

British Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu, Jonathan P. Williams, Jan Hannig   +2 more
wiley   +1 more source

Nonlinear anisotropic elliptic equations with variable exponents and degenerate coercivity

Electronic Journal of Differential Equations, 2018
In this article, we prove the existence and the regularity of distributional solutions for a class of nonlinear anisotropic elliptic equations with $p_i(x)$ growth conditions, degenerate coercivity and $L^{m(\cdot)}$ data, with $m(\cdot)$ being small,
Hocine Ayadi, Fares Mokhtari
doaj