• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.550-555
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• 2007

This paper is concerned with the active vibration control of building structure by means of the active tuned mass damper and the modified positive position feedback controller. To this end, one-degree-of-freedom spring-mass-damper system equipped with ATMD is considered. The stability condition for the addressed system when applying the proposed PPF controller is derived by Routh-Hurwitz stability criterion. The stability condition shows that the modified PPF controller is absolutely stable if the controller gain is positive, so that the modified PPF controller can be used without difficulty. Theoretical study shows that the modified PPF controller can effectively suppress vibrations as the original PPF controller does in smart structure applications. To investigate the validity of the modified PPF controller, a simple experimental structure with an ATMD system driven by DC motor was built. The modified PPF control algorithm was implemented on Atmel 128 microcontroller. The experimental result shows that the modified PPF controller can also suppress vibrations for the real structure.

• 한국소음진동공학회논문집
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• 제18권2호
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• pp.224-230
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• 2008

This paper is concerned with the active vibration control of building structure by means of the active tuned mass damper and the modified positive position feedback controller. To this end, one-degree-of-freedom spring-mass-damper system equipped with ATMD is considered. The stability condition for the addressed system when applying the proposed PPF controller is derived by Routh-Hurwitz stability criterion. The stability condition shows that the modified PPF controller is absolutely stable if the controller gain is positive. so that the modified PPF controller can be used without difficulty. Theoretical study shows that the modified PPF controller can effectively suppress vibrations as the original PPF controller does in smart structure applications. To investigate the validity of the modified PPF controller, a simple experimental structure with an ATMD system driven by DC motor was built. The modified PPF control algorithm was implemented on Atmel 128 microcontroller. The experimental result shows that the modified PPF controller can also suppress vibrations for the real structure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권7호
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• pp.2257-2285
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• 2022

Cyber-physical systems (CPS) have been growing exponentially due to improved cloud-datacenter infrastructure-as-a-service (CDIaaS). Incremental expandability (scalability), Quality of Service (QoS) performance, and reliability are currently the automation focus on healthy Tier 4 CDIaaS. However, stable QoS is yet to be fully addressed in Cyber-physical data centers (CP-DCS). Also, balanced agility and flexibility for the application workloads need urgent attention. There is a need for a resilient and fault-tolerance scheme in terms of CPS routing service including Pod cluster reliability analytics that meets QoS requirements. Motivated by these concerns, our contributions are fourfold. First, a Distributed Non-Recursive Cloud Model (DNRCM) is proposed to support cyber-physical workloads for remote lab activities. Second, an efficient QoS stability model with Routh-Hurwitz criteria is established. Third, an evaluation of the CDIaaS DCN topology is validated for handling large-scale, traffic workloads. Network Function Virtualization (NFV) with Floodlight SDN controllers was adopted for the implementation of DNRCM with embedded rule-base in Open vSwitch engines. Fourth, QoS evaluation is carried out experimentally. Considering the non-recursive queuing delays with SDN isolation (logical), a lower queuing delay (19.65%) is observed. Without logical isolation, the average queuing delay is 80.34%. Without logical resource isolation, the fault tolerance yields 33.55%, while with logical isolation, it yields 66.44%. In terms of throughput, DNRCM, recursive BCube, and DCell offered 38.30%, 36.37%, and 25.53% respectively. Similarly, the DNRCM had an improved incremental scalability profile of 40.00%, while BCube and Recursive DCell had 33.33%, and 26.67% respectively. In terms of service availability, the DNRCM offered 52.10% compared with recursive BCube and DCell which yielded 34.72% and 13.18% respectively. The average delays obtained for DNRCM, recursive BCube, and DCell are 32.81%, 33.44%, and 33.75% respectively. Finally, workload utilization for DNRCM, recursive BCube, and DCell yielded 50.28%, 27.93%, and 21.79% respectively.