(Georgia Institute of Technology, 2004-06)
Hovakimyan, Naira; Lavretsky, Eugene; Yang, Bong-Jun; Calise, Anthony J.
A decentralized adaptive output feedback control design
is proposed for large-scale interconnected systems. It is
assumed that all the controllers share prior information
about the system reference models. A linearly parameterized
neural network is introduced for each subsystem to partially
cancel the effect of the interconnections on tracking performance.
Boundedness of error signals is shown through
Lyapunov's direct method.
(Georgia Institute of Technology, 2003-08)
Yang, Bong-Jun; Hovakimyan, Naira; Calise, Anthony J.; Craig, James I.
A method of adaptive output feedback design for
uncertain nonlinear systems is presented. The development
is in a form that is suitable for augmenting a
linear controller. The approach is applicable to non-affine,
non-minimum phase systems having parametric
and dynamic uncertainties. A requirement is that the
non-minimum phase zeros are represented to a sufficient
accuracy in the linear controller design. The
approach has been experimentally validated using a
3-disk torsional pendulum and an inverted pendulum.