By Jin Woo Park, Tag-Gon Kim, Yun-Bae Kim
This publication contains chosen papers of the Asia Simulation convention 2007, held in Seoul, Korea, October 10-12, 2007.
The forty two revised complete papers awarded have been rigorously reviewed and chosen from one hundred twenty submissions; after the convention, the papers went via one other around of revision. The papers are prepared in topical sections on production, Numerical Simulation I, normal program, Agent established Simulation, Aero house, method Dynamics, Numerical Simulation II, net dependent Simulation, common Engineering, Logistics Simulation, Simulation and AI, Simulation instruments, Statistical equipment, well-being Care/Education in addition to technique.
Read or Download AsiaSim 2007: Asia Simulation Conference 2007, Seoul, Korea, October 10-12, 2007, Proceedings (Communications in Computer and Information Science) PDF
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Additional info for AsiaSim 2007: Asia Simulation Conference 2007, Seoul, Korea, October 10-12, 2007, Proceedings (Communications in Computer and Information Science)
In the pull system, part with lower level in BOM structure that serves for many higher levels requires larger number of Kanbans. Meanwhile, in the push system, part with higher level that is processed through many stages (longer lead-time) requires larger safety stock. Event Graph Models for Generic Manufacturing Systems with Push and Pull Policies 11 References 1. : Trade-off between maximizing throughput rate and minimizing system time in Kanban systems. International Journal of Operations and Production Management 17, 429–445 (1997) 2.
Dt ⎭ Let (19) d [Δf ( y ) + d (t )] is bounded, and d [Δf ( y) + d (t )] ≤ k f . There, we have dt dt V ≤ −k f s . (20) The reaching condition ss < 0 is maintained and lim s (t ) → 0 . This completes the t →∞ proof. 4 Numerical Example In this section, simulation results are presented to demonstrate the effectiveness of the proposed fuzzy sliding-mode controller for chaos synchronization problem. Consider two coupled Duffing-Holmes systems as follows x1 = x 2 x 2 = − p1 x1 − p 2 x 2 − x13 + q cos(ω t ) , (21) y1 = y 2 y 2 = − p1 y1 − p 2 y 2 − y13 + Δf ( y ) + d (t ) + q cos(ω t ) + u (t ) .
I: Fundam. Theory Appl. 38, 453–456 (1991) 2. : Sliding mode control for non-linear system with global invariance. Proc. Inst. Mech. Engrs. 211, 75–82 (1997) Design of Fuzzy Sliding-Mode Controller for Chaos Synchronization 45 3. : Chaotification via arbitrarily small feedback controls: theory, method, and applications. Int. J. Bifur. Chaos 10, 549–570 (2000) 4. : From chaos to order: methodologies, perspectives and applications. World Scientific, Singapore (1998) 5. : Adaptive synchronization of two Lorenz system.