• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.40.5-40
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• 2001

In this paper, a new on-line parameter estimation methodology for the general continuous time Takagi-Sugeno(T-S) fuzzy model whose parameters are poorly known or uncertain is presented. An estimator with an appropriate adaptive law for updating the parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the plant parameterized model. By the proposed estimator, the parameters of the T-S fuzzy model can be estimated by observing the behavior of the system and it can be a basis for the indirect adaptive fuzzy control.

• Journal of Communications and Networks
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• 제18권5호
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• pp.784-795
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• 2016

In this paper, we investigate the resource allocation problem in time-varying heterogeneous wireless networks (HetNet) with multi-homing user equipments (UE). The stochastic optimization model is employed to maximize the network utility, which is defined as the difference between the HetNet's throughput and the total energy consumption cost. In harmony with the hierarchical architecture of HetNet, the problem of stochastic optimization of resource allocation is decomposed into two subproblems by the Lyapunov optimization theory, associated with the flow control in transport layer and the power allocation in physical (PHY) layer, respectively. For avoiding the signaling overhead, outdated dynamic information, and scalability issues, the distributed resource allocation method is developed for solving the two subproblems based on the primal-dual decomposition theory. After that, the adaptive resource allocation algorithm is developed to accommodate the timevarying wireless network only according to the current network state information, i.e. the queue state information (QSI) at radio access networks (RAN) and the channel state information (CSI) of RANs-UE links. The tradeoff between network utility and delay is derived, where the increase of delay is approximately linear in V and the increase of network utility is at the speed of 1/V with a control parameter V. Extensive simulations are presented to show the effectiveness of our proposed scheme.

• 전자공학회논문지CI
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• 제37권1호
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• pp.21-31
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• 2000

본 논문에서는 이산 시간 신경망 제어 시스템의 안정도에 대한 해석을 하도록 한다. 우선 리아프노프의 직접법을 이용하여 신경망제어기를 포함하고 있는 시스템의 안정조건을 체계적으로 유도하고 이 유도된 안정조건을 반영하여 수정된 역전파 알고리즘을 제안한다. 이 수정된 역전파 알고리즘은 유도된 신경망 제어기 시스템의 안정조건을 반영한 학습 규칙이고 따라서 이를 이용하여 학습된 신경망 제어기의 경우 안정성을 보장하게 된다. 끝으로 컴퓨터 모의 실험에서는 제안한 신경망 제어 시스템의 안정조건과 이를 반영한 수정 역전파 알고리즘을 통하여 주어진 플랜트를 학습 제어하도록 한다.

• International Journal of Control, Automation, and Systems
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• 제5권4호
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• pp.397-409
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• 2007

In this paper, we propose a nonlinear guidance law for missiles against maneuvering targets. First, we derive the equations of motion described in the line-of-sight reference frame and then we define the equilibrium subspace of the nonlinear system to guarantee target interception within a finite time. Using Sontag's formula, we derive a nonlinear guidance law that always delivers the state to the equilibrium subspace. If the speed of the missile is greater than that of the target, the proposed law has global capturability in that, under any initial launch conditions, the missile can intercept the maneuvering target. The proposed law also minimizes the integral cost of the control energy and the weighted square of the state. The performance of the proposed law is compared with the augmented proportional navigation guidance law by means of numerical simulations of various initial conditions and target maneuvers.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.640-645
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• 2004

This paper proposes a direct adaptive control method using self-recurrent wavelet neural network (SRWNN) for stable path tracking of mobile robots. The architecture of the SRWNN is a modified model of the wavelet neural network (WNN). Unlike the WNN, since a mother wavelet layer of the SRWNN is composed of self-feedback neurons, the SRWNN has the ability to store the past information of the wavelet. For this ability of the SRWNN, the SRWNN is used as a controller with simpler structure than the WNN in our on-line control process. The gradient-descent method with adaptive learning rates (ALR) is applied to train the parameters of the SRWNN. The ALR are derived from discrete Lyapunov stability theorem, which are used to guarantee the stable path tracking of mobile robots. Finally, through computer simulations, we demonstrate the effectiveness and stability of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.494-494
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• 2000

This paper demonstrates that the largest Lyapunov exponent $\lambda$ of recurrent neural networks can be controlled by a gradient method. The method minimizes a square error $e_{\lambda}=(\lambda-\lambda^{obj})^2$ where $\lambda^{obj}$ is desired exponent. The $\lambda$ can be given as a function of the network parameters P such as connection weights and thresholds of neurons' activation. Then changes of parameters to minimize the error are given by calculating their gradients $\partial\lambda/\partialP$. In a previous paper, we derived a control method of $\lambda$via a direct calculation of $\partial\lambda/\partialP$ with a gradient collection through time. This method however is computationally expensive for large-scale recurrent networks and the control is unstable for recurrent networks with chaotic dynamics. Our new method proposed in this paper is based on a stochastic relation between the complexity $\lambda$ and parameters P of the networks configuration under a restriction. Then the new method allows us to approximate the gradient collection in a fashion without time evolution. This approximation requires only $O(N^2)$ run time while our previous method needs $O(N^{5}T)$ run time for networks with N neurons and T evolution. Simulation results show that the new method can realize a "stable" control for larege-scale networks with chaotic dynamics.

• Journal of Power Electronics
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• 제11권5호
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• pp.719-725
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• 2011

This paper describes a novel Direct Torque Control (DTC) method for adjustable speed Doubly-Fed Induction Machine (DFIM) drives which is supplied by a two-level Space Vector Modulation (SVM) voltage source inverter (DTC-SVM) in the rotor circuit. The inverter reference voltage vector is obtained by using input-output feedback linearization control and a DFIM model in the stator a-b axes reference frame with stator currents and rotor fluxes as state variables. Moreover, to make this nonlinear controller stable and robust to most varying electrical parameter uncertainties, a two layer recurrent Artificial Neural Network (ANN) is used to estimate a certain function which shows the machine lumped uncertainty. The overall system stability is proved by the Lyapunov theorem. It is shown that the torque and flux tracking errors as well as the updated weights of the ANN are uniformly ultimately bounded. Finally, effectiveness of the proposed control approach is shown by computer simulation results.

• Journal of information and communication convergence engineering
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• 제17권3호
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• pp.167-173
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• 2019

This study investigates the problem of leader-following consensus for multi-agent systems with output saturations. This study assumes that the agents are described as a neutrally stable system, and the leader agent generates the bounded trajectory within the saturation level. Then, the objective of the leader-following consensus is to track the trajectory of the leader by exchanging information with neighbors. To solve this problem, we propose an observer-based distributed consensus algorithm. Then, we provide a consensus analysis by applying the Lyapunov stability theorem and LaSalle's invariance principle. The result shows that the agents achieve the leader-following consensus in a global sense. Moreover, we can achieve the consensus by choosing any positive control gain. Finally, we perform a numerical simulation to demonstrate the validity of the proposed algorithm.

• 한국정보통신학회논문지
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• 제25권1호
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• pp.102-107
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• 2021

본 논문에서는 입력 포화가 존재하는 다중 에이전트 시스템의 봉쇄제어 문제를 다룬다. 봉쇄제어의 목표는 추종 에이전트들을 리더 에이전트들에 의해 형성된 convex hull 안으로 몰아넣음으로써 군집 행동을 얻는 것이다. 본 논문에서는 일정한 속도로 움직이는 리더 에이전트들을 고려한다. 움직이는 리더들을 고려한 봉쇄 문제를 해결하기 위하여 PI기반의 분산제어 알고리즘을 제안한다. 다음으로 추종 에이전트들의 목표 위치로의 수렴성을 해석한다. 구체적으로 포화 비선형성을 고려하기 위하여 적분 형태의 리아프노프 함수를 적용한다. 그리고 Lasalle's Invariance Principle을 기반으로 임의의 상수 이득들에 대하여 오차 상태들의 점근적 수렴성을 보인다. 마지막으로 고정된 리더들과 일정한 속도로 움직이는 리더들을 고려한 시뮬레이션을 진행하여 이론적 결과를 검증하였다.

• Journal of Mechanical Science and Technology
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• 제19권3호
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• pp.756-767
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• 2005

This paper presents a decentralized motion control method of welding mobile manipulators which use for welding in many industrial fields. Major requirements of welding robots are accuracy, robust, and reliability so that they can substitute for the welders in hazardous and worse environment. To do this, the manipulator has to take the torch tracking along a welding trajectory with a constant velocity and a constant heading angle, and the mobile-platform has to move to avoid the singularities of the manipulator. In this paper, we develop a kinematic model of the mobile-platform and the manipulator as two separate subsystems. With the idea that the manipulator can avoid the singularities by keeping its initial configuration in the welding process, the redundancy problem of system is solved by introducing the platform mobility to realize this idea. Two controllers for the mobile-platform and the manipulator were designed, respectively, and the relationships between two controllers are the velocities of two subsystems. Control laws are obtained based on the Lyapunov function to ensure the asymptotical stability of the system. The simulation and experimental results show the effectiveness of the proposed controllers.