Contraction theory for nonlinear stability analysis and learning-based control: A tutorial overview

H Tsukamoto, SJ Chung, JJE Slotine - Annual Reviews in Control, 2021 - Elsevier
Contraction theory is an analytical tool to study differential dynamics of a non-autonomous
(ie, time-varying) nonlinear system under a contraction metric defined with a uniformly …

Systematic and effective design of nonlinear feedback controllers via the state-dependent Riccati equation (SDRE) method

T Çimen - Annual Reviews in control, 2010 - Elsevier
Since the 1990s, state-dependent Riccati equation (SDRE) strategies have emerged as
general design methods that provide a systematic and effective means of designing …

Survey of state-dependent Riccati equation in nonlinear optimal feedback control synthesis

T Cimen - Journal of Guidance, Control, and Dynamics, 2012 - arc.aiaa.org
AEROSPACE engineering applications greatly stimulated the development of optimal
control theory during the 1950s and 1960s, where the objective was to drive the system …

Probability-guaranteed distributed filtering for nonlinear systems with innovation constraints over sensor networks

L Ma, Z Wang, Y Chen, X Yi - IEEE Transactions on Control of …, 2021 - ieeexplore.ieee.org
In this article, the distributed filtering problem is investigated for a class of nonlinear systems.
Each individual sensing node provides the state estimate by using not only its own …

[HTML][HTML] Tutorial and review on the state-dependent Riccati equation

SR Nekoo - Journal of Applied Nonlinear Dynamics, 2019 - lhscientificpublishing.com
This paper presents an extensive tutorial and a complete review on the state-dependent
Riccati equation (SDRE). The review covers contributions from the beginning to (near the …

Robust controller design for stochastic nonlinear systems via convex optimization

H Tsukamoto, SJ Chung - IEEE Transactions on Automatic …, 2020 - ieeexplore.ieee.org
This article presents ConVex optimization-based Stochastic steady-state Tracking Error
Minimization (CV-STEM), a new state feedback control framework for a class of Itô stochastic …

Crowd dynamics: Modeling and control of multiagent systems

X Gong, M Herty, B Piccoli… - Annual Review of Control …, 2023 - annualreviews.org
This review aims to present recent developments in modeling and control of multiagent
systems. A particular focus is set on crowd dynamics characterized by complex interactions …

[HTML][HTML] Speed and current regulation of a permanent magnet synchronous motor via nonlinear and adaptive backstep** control

M Karabacak, HI Eskikurt - Mathematical and Computer Modelling, 2011 - Elsevier
This paper proposes a new speed and current control scheme for a Permanent Magnet
Synchronous Motor (PMSM) by means of a nonlinear and adaptive backstep** design. All …

Dynamics and biological control of the sugarcane borer with two parasitoids

A Molter, JIM Bezerra, E Rafikova, DE Nava… - Ecological Modelling, 2023 - Elsevier
The purpose of this work is to study an interaction between the sugarcane borer and its
parasitoids (Trichogramma galloi, and Cotesia flavipes). The interaction between these …

Data-driven tensor train gradient cross approximation for hamilton–jacobi–bellman equations

S Dolgov, D Kalise, L Saluzzi - SIAM Journal on Scientific Computing, 2023 - SIAM
A gradient-enhanced functional tensor train cross approximation method for the resolution of
the Hamilton–Jacobi–Bellman (HJB) equations associated with optimal feedback control of …