Results 181 to 190 of about 17,642 (312)

Phase-Space Admissibility Geometry

open access: yes
This paper interprets phase space through the admissibility framework of the Paton System. Traditional dynamical systems describe evolution as trajectories through phase space defined by state variables and their derivatives.
Paton, Andrew John
core  

Control Systems Design With Enlarged Stability Domains for Nonlinear Constrained Systems via Sum‐of‐Squares Optimization

open access: yesInternational Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT Designing safe control laws for nonlinear systems is challenging, especially when ensuring stability under actuator saturation and state constraints. A key aspect is embedding controllers with a Region of Attraction (ROA), which defines initial conditions guaranteeing convergence to a stable equilibrium point (EP).
Bhaskar Biswas   +3 more
wiley   +1 more source

Response to the Letter to the Editor. [PDF]

open access: yesForensic Sci Int Synerg
Karie NM.
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

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

open access: yesInternational 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   +1 more
wiley   +1 more source

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