Implicit regularization and momentum algorithms in nonlinearly parameterized adaptive control and prediction

Implicit regularization and momentum algorithms in nonlinearly parameterized adaptive control and prediction

Stable concurrent learning and control of dynamical systems is the subject of adaptive control. Despite being an established field with many practical applications and a rich theory, much of the development in adaptive control for nonlinear systems revolves around a few key algorithms. By exploiting...

Full description

Bibliographic Details
Main Authors: Boffi, N.M (Author), Slotine, J.-J.E (Author)
Format: Article
Language:English
Published: MIT Press Journals 2021
Subjects:
Adaptive Control
Adaptive control systems
Adaptive dynamics
Adaptive nonlinear control
algorithm
Algorithm development
article
Concurrency control
Control theory
Dynamical systems
Dynamics
Equations of motion
Euler-Lagrange equations
Forecasting
geometry
Gradient methods
Hamiltonian systems
Hamiltonians
human
Lagrange multipliers
Lagrangian system
Learning systems
machine learning
Mirrors
Parameter vectors
prediction
recurrent neural network
Recurrent neural networks
simulation
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items