• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제22권1호
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• pp.29-62
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• 2018

We investigate a class of HIV infection models with two kinds of target cells: $CD4^+$ T cells and macrophages. We incorporate three distributed time delays into the models. Moreover, we consider the effect of humoral immunity on the dynamical behavior of the HIV. The viruses are produced from four types of infected cells: short-lived infected $CD4^+$T cells, long-lived chronically infected $CD4^+$T cells, short-lived infected macrophages and long-lived chronically infected macrophages. The drug efficacy is assumed to be different for the two types of target cells. The HIV-target incidence rate is given by bilinear and saturation functional response while, for the third model, both HIV-target incidence rate and neutralization rate of viruses are given by nonlinear general functions. We show that the solutions of the proposed models are nonnegative and ultimately bounded. We derive two threshold parameters which fully determine the positivity and stability of the three steady states of the models. Using Lyapunov functionals, we established the global stability of the steady states of the models. The theoretical results are confirmed by numerical simulations.

• 제어로봇시스템학회논문지
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• 제20권12호
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• pp.1238-1245
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• 2014

This paper proposes an RBFN-based adaptive tracking controller for an electrically driven mobile robot with parametric uncertainties and external disturbances. A mobile robot model considered in this paper includes all models of the robot body and actuators with uncertain kinematic and dynamic parameters, and uncertain frictions and external disturbances. The proposed controller consists of an RBFN(Radial Basis Function Network) and a robust adaptive controller. The presented RBFN is used to approximate unknown nonlinear robot dynamic functions. The proposed controller is adjusted by the adaptation laws obtained through the Lyapunov stability analysis. The proposed control scheme does not a priori need the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. Also, nominal parameter values are not required in the controller. The global stability of the closed-loop robot control system is guaranteed using the Lyapunov stability theory. Simulation results show the validity and robustness of the proposed control scheme.

• 한국지능시스템학회논문지
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• 제25권4호
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• pp.349-354
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• 2015

본 논문은 비선형 시스템을 위한 T-S 퍼지 샘플치 필터의 안정도 조건을 제시한다. 퍼지 시스템과 퍼지 필터 사이의 에러 시스템을 제시하며, 리아푸노프 안정도 해석 기법을 이용해 에러 시스템의 안정도 조건을 선형행렬부등식의 형태로 표현한다. 제안된 안정도 조건은 기존과는 다른 접근법을 이용하며, 더 나은 성능을 보인다. 모의실험을 통해 제안한 기법의 효용성을 검증한다.

• 전력전자학회논문지
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• 제4권2호
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• pp.138-143
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• 1999

본 논문에서는 직접 구동용 브러쉬 없는 직류 전동기(BLDD)에 있어서 외란에 강인한 위치 제어를 하기 위한 새로운 제어 방법으로 적응 제어형 외란 관측기를 제시하였다. 정밀 위치 제어를 위해서 Field-orientation 방법을 통해 선형화 하였다. BLDC 전동기는 뒤틈(backlash)이 없는 반면에 높은 가격과 비선형 특성에 의한 복잡한 제어기가 필요하다는 단점이 있다. 또한 외부 외란은 전동기의 축에 직접 영향을 미치고 있다. 이 외란은 영향을 줄이기 위해서 Lyapunov 안정성 이론을 이용하였다. 이 이론을 바탕으로 제안된 시스템의 안정성을 증명하였으며, 관측기에서 취한 값을 순간적으로 등가 전류로 계산하여 정궤환(feedforward)하여 보상하였다.

• 전자공학회논문지
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• 제50권8호
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• pp.292-298
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• 2013

본 논문은 동일하지 않는 노드들을 갖는 복잡동적 네트워크의 동기화문제를 고려한다. 이 문제에서 타켓 노드는 별도의 독립노드 대신에 네트워크내의 한 노드를 택하였다. 더욱이 본 논문의 동기화기법에서는 기존에 존재하는 연결행렬의 정보나 부가적인 조건을 필요하지 않는 장점이 있다. 리아프노프 안정성기법에 의거하여 타켓 노드와 다른 노드들 사이의 동기화를 위한 새로운 적응제어기를 위한 조건을 유도한다. 마지막으로 제안된 기법의 효율성을 보이기 위하여 수치적인 예제를 제시한다.

• Journal of Mechanical Science and Technology
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• 제18권8호
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• pp.1288-1296
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• 2004

Wall-following control problem for a mobile robot is to move it along a wall at a constant speed and keep a specified distance to the wall. This paper proposes wall-following controllers based on Lyapunov function candidate for a two-wheeled mobile robot (MR) to follow an unknown wall. The mobile robot is considered in terms of kinematic model in Cartesian coordinate system. Two wall-following feedback controllers are designed: full state feedback controller and observer-based controller. To design the former controller, the errors of distance and orientation of the mobile robot to the wall are defined, and the feedback controller based on Lyapunov function candidate is designed to guarantee that the errors converge to zero asymptotically. The latter controller is designed based on Busawon's observer as only the distance error is measured. Additionally, the simulation and experimental results are included to illustrate the effectiveness of the proposed controllers.

• 한국생산제조학회지
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• 제6권1호
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• pp.7-17
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• 1997

During the past decade, there were many well-established theories for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of industrial robot control. Neural network computing methods provide one approach to the development of adaptive and learning behavior in robotic system for manufacturing. Computational neural networks have been demonstrated which exhibit capabilities for supervised learning, matching, and generalization for problems on an experimental scale. Supervised learning could improve the efficiency of training and development of robotic systems. In this paper, a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator using digital signal processors is proposed. Digital signal processors, DSPs, are micro-processors that are developed particularly for fast numerical computations involving sums and products of variables. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. The proposed adaptive-neuro control scheme is illustrated to be an efficient control scheme for implementation of real-time control for SCARA robot with four-axes by experiment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4342-4366
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• 2016

Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur'e type system. In the context of delayed Lur'e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

• International Journal of Aeronautical and Space Sciences
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• 제14권2호
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• pp.172-182
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• 2013

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-II fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-II fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-II fuzzy neural network based adaptive sliding mode controller could guarantee the Eight-Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-I fuzzy neural network based sliding mode controller.

• 한국정밀공학회지
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• 제25권10호
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• pp.130-136
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• 2008

The purpose of this study was to investigate chaotic characteristics of major joint motions during treadmill walking. Gait experiments were carried out for 20 healthy young women. The subjects were asked to walk on a treadmill at their own natural speeds. The chaos analysis was used to quantify nonlinear motions of eleven major joints of each woman. The joints analyzed included the neck and the right and left shoulders, elbows, hips, knees and ankles. The recorded gait patterns were digitized and then coordinated by motion analysis software. Lyapunov exponent for every joint was calculated to evaluate joint characteristics from a state space created by time series and its embedding dimension. This study shows that differences in joint motion were statistically significant.