대한기계학회:학술대회논문집 (Proceedings of the KSME Conference)
- 대한기계학회 2001년도 춘계학술대회논문집B
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- Pages.724-729
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- 2001
실시간 적응 학습 제어를 위한 진화연산(I)
Evolutionary Computation for the Real-Time Adaptive Learning Control(I)
초록
This paper discusses the composition of the theory of reinforcement learning, which is applied in real-time learning, and evolutionary strategy, which proves its the superiority in the finding of the optimal solution at the off-line learning method. The individuals are reduced in order to learn the evolutionary strategy in real-time, and new method that guarantee the convergence of evolutionary mutations are proposed. It possible to control the control object varied as time changes. As the state value of the control object is generated, applied evolutionary strategy each sampling time because the learning process of an estimation, selection, mutation in real-time. These algorithms can be applied, the people who do not have knowledge about the technical tuning of dynamic systems could design the controller or problems in which the characteristics of the system dynamics are slightly varied as time changes. In the future, studies are needed on the proof of the theory through experiments and the characteristic considerations of the robustness against the outside disturbances.