Backstepping Adaptive Iterative Learning Control for Robotic Systems

Ying Chung Wang; Chiang Ju Chien; Chi Nan Chuang

doi:10.4028/www.scientific.net/AMM.284-287.1759

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 284-287Backstepping Adaptive Iterative Learning Control...

Backstepping Adaptive Iterative Learning Control for Robotic Systems

Abstract:

A backstepping adaptive iterative learning control for robotic systems with repetitive tasks is proposed in this paper. The backstepping-like procedure is introduced to design the AILC. A fuzzy neural network is applied for compensation of the unknown certainty equivalent controller. Using a Lyapunov like analysis, we show that the adjustable parameters and internal signals remain bounded, the tracking error will asymptotically converge to zero as iteration goes to infinity.

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Periodical:

Applied Mechanics and Materials (Volumes 284-287)

Pages:

1759-1763

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.284-287.1759

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Online since:

January 2013

Authors:

Ying Chung Wang, Chiang Ju Chien, Chi Nan Chuang

Keywords:

Adaptive Iterative Learning Control, Backstepping, Fuzzy Neural Network (FNN), Robotic Systems

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References

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