〈속보논문〉 이산 선형 비최소위상 시스템을 위한 반복 학습 제어의 수렴조건에 대한 연구

다국어 초록 (Multilingual Abstract)

This paper investigates the convergence condition of ADILC (iterative learning control with advanced output data) for nonminimum phase systems. ADILC has simple learning structure including both minimum phase and nonminimum phase systems. However, for nonminimum phase systems, the overall time horizon must be considered in input update law. This makes the dimension of convergence condition matrix large. In this paper, a new sufficient condition is proposed to satisfy the convergence condition. Also, it has been shown that this sufficient condition can be satisfied although it is not full impulse response.

목차 (Table of Contents)

• Abstract
• 1. 서론
• 2. ADILC
• 3. 새로운 수렴 조건의 유도
• 4. 임펄스 응답을 이용한 수렴 조건 해석
• 5. 모의 실험
• 6. 결론
• 참고문헌

참고문헌 (Reference)

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2 G.-M. Jeong, "Iterative learning control with advanced output data for nonlinear nonminimum phase systems" 37 (37): 1051-1058, 2006

3 K. Kinosita, "Iterative learning control using adjoint systems and stable inversion" 4 (4): 60-67, 2002

4 G.-M. Jeong, "Iterative learning control for linear discrete time nonminimum phase systems" 38 (38): 287-291, 2002

5 Z. Bien, "Iterative learning control analysis, design, integration and applications" Kluwer Academic Publishers 1998

6 S. Arimoto, "Bettering operations of robots by learning" 1 (1): 123-140, 1984

7 J. Ghosh, "A peudoinverse-based iterative learning control" 47 (47): 831-837, 2002