• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.386-386
• /
• 2000

Cell mapping is a powerful computational technique for analyzing the global behavior of nonlinear dynamic systems. It simplifies the task of analyzing a continuous phase space by partitioning it into a finite number of disjoint cells and approximating system trajectories as cell transitions. A cell map for the system is then constructed based on the allowable control actions. Next search algorithms are employed to identify the optimal or near-optimal sequence(s) of control actions required to drive the system from each cell to the target cell by an "unravelling algorithm." Errors resulting from the cell center-point approximation could be reduced and eliminated by fuzzifying the bonders of cells. The dynamic system control method based on the cell mapping has been demonstrated for a motor control problem.l problem.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.4B
• /
• pp.683-691
• /
• 2000

In this paper, we proposed the cell multiplexer using Hopfield neural network and the bandwidth predictor using the backpropagation neural network in order to make an accurate call setup decision. The cell multiplexer controls heterogeneous traffic and the bandwidth predictor estimates minimum bandwidth which satisfies traffic's QoS and maximizes throughput in network. Also, a novel connection admission controller decides on connection setup using the predicted bandwidth from bandwidth predictor and available bandwidth in networks. And then, we proposed a fuzzy traffic policer, when traffic sources violate the contract, takes an appropriate action and aim proved traffic shaper, which controls burstness which is one of key characteristics in multimedia traffic. We simulated the proposed controller. Simulation results show that the proposed controller outperforms existing controller.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.1565-1568
• /
• 1997

In this paper, a fuzzy based machine-cell formation algorithm for cellular manufacturing is presented. The fuzzy lovic is employed to express the degree of appropriateness when alternative machnies are specified to process a part shape. For machine grouping, the similarity coefficient based approach is used. The algorithm produces efficient machine cells and part families which maximize the similarity values.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.7B
• /
• pp.1215-1225
• /
• 2000

본 논문에서느 윈도우에 기반을 둔 지능적인 폴리싱 메커니즘을 제안하다. 이전의 메커니즘들이 소스 파라메터만을 인수로 삼은 반면에, 제안 알고리즘은 링크의 현재 상태를 고려할 수 있도록 망으로부터 얻어진 추가 파라메터를 이용한다. ATM 교환기 노드에서 링크이 점유율을 나타내는 버퍼점유율을 추가 파라메터로 제안하였다. 또한, 소스 트래픽의 효과적인 제어를 위해서 퍼지 논리에 따라 다음 윈도우의 셀 허용치를 결정한다. 제안 알고리즘으 모의실험 결과는 본 알고리즘이 기존 퍼지 알고리즘과 같이 기본 요구사항을 잘 수행함을 보여준다. 그리고, 제안한 버퍼정유율을 포함시킴으로서 다중화기의 셀량에 따른 분산치가 다른 알고리즘에 비해 훨씬 안정되어 감을 보이고 있다. 이러한 점에서, 제안 알고리즘이 귀한 정보인 버퍼점유율을 이용해 폭주를 피하는 등의 더 좋은 망 상태를 추가적인 장점으로 확인할 수 있다.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.8
• /
• pp.2188-2195
• /
• 1999

This paper proposes a new call admission control scheme utilizing an inverse fuzzy vector quantizer(IFVQ) and neuralnet, which combines benefits of IFVQ and flexibilities of FCM(Fuzzy-C-Means) arithmetics, to decide whether a requested call not to be trained in learning phase to be connected or not. The system generates the estimated traffic pattern for the cell stream of a new call, using feasible/infeasible patterns in codebook, fuzzy membership values that represent the degree to which each pattern of codebook matches input pattern, and FCM arithmetics. The input to the NN is the vector consisted of traffic parameters which are the means and variances of the number of cells arriving in decision as to whether to accept or reject a new call depends on whether the NN is used for decision threshold(+0.5). This method is a new technique for call admission control using the membership values as traffic parameter which declared to CAC at the call set up stage, and this is valid for a very general traffic model in which the calls of a stream can belong to an unlimited number of traffic classes. Through the simulations, it is founded the performance of the suggested method outperforms compared to the conventional NN method.

• Journal of Sensor Science and Technology
• /
• v.12 no.2
• /
• pp.79-87
• /
• 2003

In this paper, we propose a method to obtain a linear characteristic using soft computing for systems which have array sensors of nonlinear characteristics. Also a procedure utilizing the pattern information of array sensors without additional sensors is proposed to reduce disturbance effects. For a typical example, even a single CdS cell for CdS array has nonlinear characteristics. Overall linear characteristic for CdS array is obtained using fuzzy logic for each cell and overlapped portion. In addition, further improvement for linearization is obtained applying genetic algorithms for the parameters of membership functions. Also the effect of disturbing external light changes to the CdS array can be reduced without using any additional sensors for calibration. The proposed method based on fuzzy logic shows improvements for position measurements and disturbance reduction to external light changes due to the fuzziness of the shadow boundary as well as the inherent nonlinearity of the CdS array. This improvement is shown by applying the proposed method to the ball position measurements of a magnetic levitation system.