제어로봇시스템학회:학술대회논문집
- 1996.10a
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- Pages.91-94
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- 1996
Estimation of learning gain in iterative learning control using neural networks
- Choi, Jin-Young (School of Electrical Eng., Seoul National University) ;
- Park, Hyun-Joo (School of Electrical Eng., Seoul National University)
- Published : 1996.10.01
Abstract
This paper presents an approach to estimation of learning gain in iterative learning control for discrete-time affine nonlinear systems. In iterative learning control, to determine learning gain satisfying the convergence condition, we have to know the system model. In the proposed method, the input-output equation of a system is identified by neural network refered to as Piecewise Linearly Trained Network (PLTN). Then from the input-output equation, the learning gain in iterative learning law is estimated. The validity of our method is demonstrated by simulations.