• Journal of applied mathematics & informatics
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• 제16권1_2호
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• pp.515-524
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• 2004

We prove the local existence of solution for nonconvex-valued differential inclusion under time-varying state constraints.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1905-1910
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• 2003

It is well known that parameter uncertainties and time-delays cannot be avoided in practice and result in poor performance and even instability. Nevertheless, to the authors' best knowledge, there exist few results on model predictive control (MPC) handling explicitly uncertain time-delayed systems. In this paper, we present an MPC algorithm for uncertain time-varying systems with input constraints and state-delay. An optimization problem is suggested to find a memoryless state-feedback MPC law and the closed-loop stability is established under feasibility and certain conditions.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2005년도 전기학술대회논문집
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• pp.287-292
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• 2005

In this paper, a state steering strategy using digital control method for chained system is presented. The chained system can be derived from the velocity or acceleration constraints that cannot be integrable. Especially, the chained system derived from an acceleration constraints is called the high order chained system. Such a system classified as a nonholonomic systems and cannot be controlled to its equilibrium points by continuous and time-invariant controller. Therefore discontinuous and time varying controller should be applied to control nonholonomic system. Using variable transformation, two sub system can be obtained from the chained or high order chained system. Deadbeat control and iterative state steering methods are proposed to control the systems that obtained from the variable transformation. Simulation results are given to show the effectiveness of the proposed control scheme.

• 전기학회논문지
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• 제61권7호
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• pp.1019-1023
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• 2012

This paper considers a model predictive control problem of discrete-time constrained systems with time-varying delay. For this problem, a delay dependent state feedback control approach is used to achieve asymptotic stabilization of systems with input constraints. Based on Lyapunov stability theory, a new stability condition is obtained via linear matrix inequality formulation to find cost monotonicity condition of the model predictive control algorithm which guarantee the closed loop stability. Finally, the proposed method is applied to a numerical example in order to show the effectiveness of our results.

• Journal of Information Processing Systems
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• 제8권2호
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• pp.191-212
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• 2012

Since a social network by definition is so diverse, the problem of estimating the preferences of its users is becoming increasingly essential for personalized applications, which range from service recommender systems to the targeted advertising of services. However, unlike traditional estimation problems where the underlying target distribution is stationary; estimating a user's interests typically involves non-stationary distributions. The consequent time varying nature of the distribution to be tracked imposes stringent constraints on the "unlearning" capabilities of the estimator used. Therefore, resorting to strong estimators that converge with a probability of 1 is inefficient since they rely on the assumption that the distribution of the user's preferences is stationary. In this vein, we propose to use a family of stochastic-learning based Weak estimators for learning and tracking a user's time varying interests. Experimental results demonstrate that our proposed paradigm outperforms some of the traditional legacy approaches that represent the state-of-the-art technology.

• Transactions on Control, Automation and Systems Engineering
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• 제2권1호
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• pp.31-39
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• 2000

We present a robust and reliable H$\infty$ state-feedback controller design for linear uncertain systems, which have norm-bounded time-varying uncertainty in the state matrix, and their prespecified sets of actuators are susceptible to failure. These controllers should guarantee robust stability of the systems and H$\infty$ norm bound against parameter uncertainty and/or actuator failures. Based on the linear matrix inequality (LMI) approach, two state-feedback controller design methods are constructed by formulating to a set of LMIs corresponding to all failure cases or a single LMI that covers all failure cases, with an additional costraint. Effectiveness and geometrical property of these controllers are validated via several numerical examples. Furthermore, the proposed LMI frameworks can be applied to multiobjective problems with additional constraints.

• International Journal of Control, Automation, and Systems
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• 제3권3호
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• pp.397-402
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• 2005

The guaranteed cost control problem for a class of linear systems with norm-bounded time-varying parameter uncertainties and input constraints is considered. A sufficient condition for the existence of guaranteed cost state feedback controllers is derived via the linear matrix inequality (LMI) approach, and a design procedure to guaranteed cost controllers is given. Furthermore, a convex optimization problem is formulated to determine the optimal guaranteed cost controller. An example is given to illustrate the effectiveness of the proposed results.

• 한국컴퓨터정보학회논문지
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• 제29권1호
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• pp.1-9
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• 2024

본 논문에서는 LoRaEnergySim에 최적의 실시간 스케줄링 알고리즘으로 알려진 ED-H 스케줄링 알고리즘을 연동하여 LoRaWAN 클래스-A 단말기에 슈퍼 커패시터 기반의 에너지 하베스팅 시스템을 전원 공급 장치를 적용하였을 때 시간 제약성을 갖는 LoRaWAN 컨트롤러의 태스크와 응용 태스크의 실시간 스케줄링 알고리즘 간의 상호 시뮬레이션이 가능하도록 한다. 이를 위해 LoRaWAN의 상태와 상태 전환에 따른 시간과 에너지 특성을 로그 형태로 추출하고 타임 슬롯 기반의 ED-H 스케줄링 알고리즘에 적합하도록 태스크 모델을 수립하고 태스크가 CPU에 의해서 수행되는 특성에 따라 알고리즘이 시간 제약성을 만족하며 태스크를 수행할 수 있도록 확장하였다. 본 논문에서 제안한 기법의 평가를 위해 LoRaEnergySim 시뮬레이션 결과가 제시된 동일 환경에서 패킷 송수신이 수행되는 것과 동시에 10%에서 90%의 CPU 점유율을 갖는 다양한 시간과 에너지 특성을 갖는 태스크 집합에 대해 ED-H 스케줄링 알고리즘을 수행하였으며, 실험 결과로 스케줄링 알고리즘에 따라 시간 제약성의 만족을 위해 슈퍼 커패시터의 에너지가 고갈되지 않는 한 태스크의 시급성을 우선하여 사용하는 것을 확인하여 상호 시뮬레이션의 적용 가능성을 확인하였다.

• Journal of Electrical Engineering and Technology
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• 제9권1호
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• pp.27-36
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• 2014

This paper presents an adaptive wide-area damping controller (WADC) based on generalized predictive control (GPC) and model identification for damping the inter-area low frequency oscillations in large-scale inter-connected power system. A recursive least-squares algorithm (RLSA) with a varying forgetting factor is applied to identify online the reduced-order linearlized model which contains dominant inter-area low frequency oscillations. Based on this linearlized model, the generalized predictive control scheme considering control output constraints is employed to obtain the optimal control signal in each sampling interval. Case studies are undertaken on a two-area four-machine power system and the New England 10-machine 39-bus power system, respectively. Simulation results show that the proposed adaptive WADC not only can damp the inter-area oscillations effectively under a wide range of operation conditions and different disturbances, but also has better robustness against to the time delay existing in the remote signals. The comparison studies with the conventional lead-lag WADC are also provided.

• 한국통신학회논문지
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• 제34권5A호
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• pp.355-362
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• 2009

In real-time communication services, delay constraints are among the most important QoS (Quality of Service) factors. In particular, it is difficult to guarantee the delay requirement over wireless channels, since they exhibit dynamic time-varying behavior and even severe burst-errors during periods of deep fading. Channel throughput may be increased, but at the cost of the additional delays when ARQ (Automatic Repeat Request) schemes are used. For real-time communication services, it is very essential to predict data deliverability. This paper derives the delay distribution and the successful delivery probability within a given delay budget using a priori channel model and a posteriori information from the perspective of queueing theory. The Gilbert-Elliot burst-noise channel is employed as an a Priori channel model, where a two-state Markov-modulated Bernoulli process $(MMBP_2)$ is used. for a posteriori information, the channel parameters, the queue-length and the initial channel state are assumed to be given. The numerical derivation is verified and analyzed via Monte Carlo simulations. This numerical derivation is then applied to a rate control scheme for real-time video transmission, where an optimal encoding rate is determined based on the future channel capacity and the distortion of the reconstructed pictures.