• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.317-323
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• 2007

Quality of Service (QoS) in the Internet depends on queuing and sophisticated scheduling in routers. In this paper, we address the issue of managing traffic flows with different priorities. In our reference model, incoming packets are first classified based on their priority, placed into different queues with different capacities, and then multiplexed onto one router link. The fuzzy nature of the information on Internet traffic makes this problem particularly suited to fuzzy methodologies. We propose a new solution that employs a fuzzy inference system to dynamically and efficiently schedule these priority queues. The fuzzy rules are derived to minimize the selected Lyapunov function. Simulation experiments show that the proposed fuzzy scheduling algorithm outperforms the popular Weighted Round Robin (WRR) queue scheduling mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1989년도 한국자동제어학술회의논문집; Seoul, Korea; 27-28 Oct. 1989
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• pp.901-906
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• 1989

A robust stability problem for time delay systems is discussed by using a property of Lyapunov type operator equation. We propose a method to check the robust stability against the parameter perturbations occurring in both lumped parameter part and distributed delay element.

• 한국해양공학회지
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• 제25권5호
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• pp.1-8
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• 2011

This paper proposes a controller design for an omnidirectional mobile platform (OMP) with three wheels using backstepping control. A kinematic model and dynamic model of the system are presented. Based on the dynamic modeling, a backstepping controller is designed to stabilize the OMP when following a desired path. The controller is designed based on a backstepping control theory. It includes two steps: first, a virtual state and a stability function are introduced. Second, Lyapunov functions for the system are chosen and an equation for the virtual control that makes the system stabile is obtained. The system stability is guaranteed by the Lyapunov stability theory. The simulation and experimental results are presented to demonstrate the effectiveness of the proposed controller.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권2호
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• pp.96-101
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• 2007

Neural networks are known as kinds of intelligent strategies since they have learning capability. There are various their applications from intelligent control fields; however, their applications have limits from the point that the stability of the intelligent control systems is not usually guaranteed. In this paper we propose an adaptive tracking control for robot manipulators using the radial basis function network (RBFN) that is e. kind of neural networks. Adaptation laws for parameters of the RBFN are developed based on the Lyapunov stability theory to guarantee the stability of the overall control scheme. Filtered tracking errors between actual outputs and desired outputs are discussed in the sense of the uniformly ultimately boundedness(UUB). Additionally, it is also shown that parameters of the RBFN are bounded. Experimental results for a SCARA-type robot manipulator show that the proposed adaptive tracking controller is adaptable to the environment changes and is more robust than the conventional PID controller and the neuro-controller based on the multilayer perceptron.

• Journal of Power Electronics
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• 제17권6호
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• pp.1611-1624
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• 2017

With the rapid development of microgrid technology, microgrid projects are no longer limited to laboratory demonstrations and pilot platforms. It shows greater value in practical applications. Hence, the smooth interaction between a microgrid and the main grid plays a critical role. In this paper, a control method based on active disturbance rejection control (ADRC) is proposed in order to realize seamless transitions between grid-connected and islanding operation modes and stable operation with variable loads. It is verified by simulations that the proposed ADRC-based method features better performance when compared to conventional proportional-integral-differential (PID) control. Meanwhile, the stability of the third-order extended state observer (ESO) in second-order ADRC is validated by using Lyapunov stability criteria.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.700-705
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• 2005

The purpose of this project is the derivation and development of techniques for the new estimation of robustness for the systems having uncertainties. The basic ideas to analyze the system which is the originally nonlinear is Lyapunov direct theorems. The nonlinear systems have various forms of terms inside the system equations and this investigation is confined in the form of bounded uncertainties. Bounded means the uncertainties are with same positive/negative range. The number of uncertainties will be the degree of freedoms in the calculation of the stability region. This is so called the robustness bounds. This proposition adopts the theoretical analysis of the Lyapunov direct methods, that is, the sign properties of the Lyapunov function derivative integrated along finite intervals of time, in place of the original method of the sign properties of the time derivative of the Lyapunov function itself. This is the new sufficient criteria to relax the stability condition and is used to generate techniques for the robust design of control systems with structured perturbations. Using this relaxing stability conditions, the selection of Lyapunov candidate function is of various forms. In this paper, the quadratic form is selected. this generated techniques has been demonstrated by recent research interest in the area of robust control design and confirms that estimation of robustness bounds will be improved upon those obtained by results of the original Lyapunov method. In this paper, the symbolic algebraic procedures are utilized and the calculating errors are reduced in the numerical procedures. The application of numerical procedures can prove the improvements in estimations of robustness for one-and more structured perturbations. The applicable systems is assumed to be linear with time-varying with nonlinear bounded perturbations. This new techniques will be extended to other nonlinear systems with various forms of uncertainties, especially in the nonlinear case of the unstructured perturbations and also with various control method.

• 동력기계공학회지
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• 제21권4호
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• pp.18-25
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• 2017

This paper deals with vibration control of a small mount with MR(Magneto-Rheological) fluid as a functional fluid mount for precision equipment of automobiles. Damping and stiffness coefficients of the mount with MR fluid are changed by variations of the applied magnetic field strength. We present the robust control scheme, based on a conventional sliding mode control theory, for the design of a stable controller that is capable of vibration control due to various disturbances such as impact and periodic excitations, and is insensitive to dynamic properties of the mount. We got stable controller by using Lyapunov stability theory. The controller is then realized by using a semi-active control condition in simulations. Chattering problem of the sliding mode control is eliminated by saturation function instead of signum function. The sliding mode control with Lyapunov stability theory is superior to passive and Sky-Hook control in performance.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.12-15
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• 1996

In this paper, a new shape control law is derived as a result of introducing the parametric curve representation. This control alw is based on the estimation of the curve parameters corresponding to the target joint positions and the target tip position. Estimating target curve parameters makes it possible to find, easily, a simple shape control law by the Lyapunov design method.

• KIEE International Transaction on Systems and Control
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• 제12D권1호
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• pp.43-50
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• 2002

In the recent years neural networks have fulfilled the promise of providing model-free learning controllers for nonlinear systems; however, it is very difficult to guarantee the stability and robustness of neural network control systems. This paper proposes an adaptive neural network control for robot manipulators based on the radial basis function netwo.k (RBFN). The RBFN is a branch of the neural networks and is mathematically tractable. So we adopt the RBFN to approximate nonlinear robot dynamics. The RBFN generates control input signals based on the Lyapunov stability that is often used in the conventional control schemes. The saturation function is also chosen as an auxiliary controller to guarantee the stability and robustness of the control system under the external disturbances and modeling uncertainties.

• 드라이브 ㆍ 컨트롤
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• 제14권4호
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• pp.61-70
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• 2017

In this study, an extended-state-observer (ESO) based non-linear servo control is introduced for an electro-hydrostatic actuator (EHA). Almost hydraulic systems not only are highly non-linear system that has mismatched uncertainties and external disturbances, but also can not measure some states. ESO that only use an output signal can be used to compensate these uncertainties and estimate unmeasurable states. To improve the position tracking performance, the barrier Lyapunov function (BLF) that can guarantee an output tolerance is introduced for the position tracking error signal of back stepping control procedures. Finally, the proposed servo control is compared with the proportional-integral (PI) control.