Multi‐parametric extremum seeking‐based iterative feedback gains tuning for nonlinear control

DOI10.1002/rnc.3547zbMath1351.93039arXiv1409.2124OpenAlexW2337305132MaRDI QIDQ5298550

Mouhacine Benosman

Publication date: 15 December 2016

Published in: International Journal of Robust and Nonlinear Control (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1409.2124

zbMATH Keywords

nonlinear controlextremum seekingiterative feedback tuninggains auto-tuning

Mathematics Subject Classification ID

Sensitivity (robustness) (93B35) Feedback control (93B52) Nonlinear systems in control theory (93C10) Linearizations (93B18) Control/observation systems governed by ordinary differential equations (93C15)

Related Items (8)

Sparse Sensing and DMD-Based Identification of Flow Regimes and Bifurcations in Complex Flows ⋮ 100 years of extremum seeking: a survey ⋮ Robust nonlinear state estimation for a class of infinite-dimensional systems using reduced-order models ⋮ Data-driven robust state estimation for reduced-order models of 2D Boussinesq equations with parametric uncertainties ⋮ Hybrid online learning control in networked multiagent systems: A survey ⋮ Learning‐based iterative modular adaptive control for nonlinear systems ⋮ Reinforcement learning-based model reduction for partial differential equations: application to the Burgers equation ⋮ Learning-based vs model-free adaptive control of a MAV under wind gust

Cites Work

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• Comparison of Allocation Algorithms for Mesh Structured Networks with Using Multistage Simulation
• Iterative feedback tuning—an overview
• Extremum Seeking for Constrained Inputs
• PID tuning using extremum seeking: online, model-free performance optimization

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