A New Adaptive Controller for Systems with Multilinear Parameterization

Netto, Mariana; Annaswamy, Anuradha M.; Mammary, Saïd; Minoiu, N.

doi:10.1002/9780470612217.ch29

Cited by 1 publication

(1 citation statement)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [6], the authors present the adaptive control of a class of nonlinear systems which have a triangular structure. Similarly, the authors of [7] present an adaptive controller for multi-linear parameterized systems and show the convergence properties of the adaptation algorithm. Both of the above papers concentrate on adapting the original system parameters without resorting to over-parameterizations.…”

Section: Parametric Adaptive Controlmentioning

confidence: 99%

Self-Organizing Radial Basis Function Networks for Adaptive Flight Control

Shankar

Yedavalli

Burken

2011

Journal of Guidance, Control, and Dynamics

View full text Add to dashboard Cite

The performance of nonlinear control algorithms such as feedback linearization and dynamic inversion is heavily dependent on the fidelity of the dynamic model being inverted. Incomplete or incorrect knowledge of the dynamics results in reduced performance and may lead to instability. Augmenting the baseline controller with approximators which utilize a parametrization structure that is adapted online reduces the effect of this error between the design model and actual dynamics. However, currently existing parameterizations employ a fixed set of basis functions that do not guarantee arbitrary tracking error performance. To address this problem, we develop a self-organizing parametrization structure that is proven to be stable and can guarantee arbitrary tracking error performance.

show abstract

Section: Parametric Adaptive Controlmentioning

confidence: 99%