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Sampled-data iterative learning control for nonlinear systems with arbitrary relative degree

✍ Scribed by Mingxuan Sun; Danwei Wang

Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
173 KB
Volume
37
Category
Article
ISSN
0005-1098

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✦ Synopsis

In this paper, a sampled-data iterative learning control method is proposed for nonlinear systems without restriction on system relative degree. The learning algorithm does not require numerical di!erentiations of any order from the tracking error. A su$cient condition is derived to guarantee the convergence of the system output at each sampling instant to the desired trajectory. Numerical simulation is conducted to demonstrate the theoretical result.

πŸ“œ SIMILAR VOLUMES

Control of uncertain nonlinear systems w
Control of uncertain nonlinear systems with arbitrary relative degree and unknown control direction using sliding modes
✍ Oliveira, T. R. (author);Peixoto, A. J. (author);Nunes, E. V.L. (author);Hsu, L. πŸ“‚ Article πŸ“… 2007 πŸ› John Wiley and Sons 🌐 English βš– 274 KB πŸ‘ 1 views

## Abstract The control of uncertain nonlinear systems by output feedback is addressed. A model‐reference tracking sliding mode controller is designed for uncertain plants with arbitrary relative degree. Nonlinearities of a given class are incorporated as state dependent and possibly unmatched dist