• 전기학회논문지
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• 제56권2호
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• pp.389-395
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• 2007

In this paper, we consider the robust non-fragile $H_{\infty}$ output feedback controller design method for uncertain descriptor systems with feedback and observer gain variations. The existence condition of observer-based robust and non-fragile $H_{\infty}$ output feedback controller and the controller design method are Presented on the basis of linear matrix inequality approach. The proposed robust non-fragile $H_{\infty}$ output feedback controller guarantees asymptotic stability, non-fragility, $H_{\infty}$ norm bound within a prescribed level in spite of disturbance, parameter uncertainty, and feedback/observer gain variations.

• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.24-34
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• 2008

A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

• 제어로봇시스템학회논문지
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• 제21권3호
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• pp.233-236
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• 2015

In this paper, a nonlinear optimization problem is proposed to obtain a structured static output feedback controller for discrete time linear systems. The proposed optimization problem has LMI (Linear Matrix Inequality) constraints and a non-convex objective function. Using the conditional gradient method, we can obtain suboptimal solutions of the proposed optimization problem. Numerical examples show the effectives of the proposed approach.

• 전자공학회논문지SC
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• 제39권3호
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• pp.183-190
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• 2002

본 논문에서는 구조화된 어파인(affine) 파라미터 불확실성을 가지는 시변 선형시스템과 구조적 불확실성을 가지는 상태궤환 제어기에 대한 견실 비약성 H∞ 제어기 설계방법을 다루었다. 또한 견실 비약성 H∞ 제어기가 존재할 충분조건, 제어기 설계방법 및 비약성을 만족하는 제어기의 꽉찬 집합(compact set)을 제시하였다. 이 때 제시한 조건은 변수치환과 슈어 여수(Schur complement)정리를 통하여 선형행렬부등식 (LMI : Linear Matrix Inequality)의 계수가 꽉찬 집합 내의 파라미터의 함수로 정의되는 파라미터화 선형 행렬부등식(PLMls: parameterized Linear Matrix Inequalities)으로 표현되므로 분리 볼록개념 (separated convexity concepts)에 기초한 완화기법을 이용하여 유한개의 LMI로 변환하였다. 그리고 본론문에서 제시한 견실 비약성 H∞ 제어기가 제어기이득의 변화에도 불구하고 폐루프시스템의 점근적 안정성 (asymptotic stability)과 외란감쇠 성능을 보장함을 보였다.

• 제어로봇시스템학회논문지
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• 제10권7호
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• pp.590-596
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• 2004

A passivity-based dynamic output feedback controller design is considered for a finite collection of non-square linear systems. Design of a single controller for a set of plants i.e. simultaneous stabilization is an important issue in the area of robust control design. We first determine a squaring gain matrix and an additional dynamics that is connected to the systems in a feedforward way, then a static passivating control law is designed. Consequently, the actual feedback controller will be the static control law combined with the feedforward dynamics. A necessary and sufficient condition for the existence of the parallel feedforward compensator is given by the static output feedback formulation. In contrast to the previous result [1], a technical condition for constructing the parallel feedforward compensator is removed by proposing a new type of the parallel compensator.

• International Journal of Ocean System Engineering
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• 제1권3호
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• pp.120-135
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• 2011

This paper proposes a model based trajectory tracking control scheme for under-actuated underwater robotic vehicles. The difficulty in stabilizing a non-linear system using smooth static state feedback law means that the design of a feedback controller for an under-actuated system is somewhat challenging. A necessary condition for the asymptotic stability of an under-actuated vehicle about a single equilibrium is that its gravitational field has nonzero elements corresponding to non-actuated dynamics. To overcome this condition, we propose a continuous time-varying control law based on the direct estimation of vehicle dynamic variables such as inertia, damping and Coriolis & centripetal terms. This can work satisfactorily under commonly encountered uncertainties such as an ocean current and parameter variations. The proposed control law cancels the non-linearities in the vehicle dynamics by introducing non-linear elements in the input side. Knowledge of the bounds on uncertain terms is not required and it is conceptually simple and easy to implement. The controller parameter values are designed using the Taguchi robust design approach and the control law is verified analytically to be robust under uncertainties, including external disturbances and current. A comparison of the controller performance with that of a linear proportional-integral-derivative (PID) controller and sliding mode controller are also provided.

• 전기학회논문지
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• 제59권5호
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• pp.1001-1004
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• 2010

Acoustic feedback and background noise variation can degrade the performance of an active noise control (ANC) system. In this paper, nonlinear ANC using a non-parametric VSS-NLMS (or NPVSS-NLMS) algorithm and online feedback path modeling is proposed, whereby the conventional linear ANC with online acoustic feedback-path modeling is further extended to nonlinear Volterra ANC with a linear acoustic feedback path. In particular, the step-size of the NPVSS-NLMS algorithm is controlled to reduce the effect of background noise variation in the ANC system. Simulation results demonstrate that the proposed approach yields better nonlinear ANC performance compared with the conventional nonlinear ANC method.

• 대한전기학회논문지:시스템및제어부문D
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• 제53권11호
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• pp.747-752
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• 2004

This paper presents an iterative linear matrix inequality (LMI) approach to the design of a static output feedback (SOF) stabilization controller. A linear penalty function is incorporated into the objective function for the non-convex rank constraint so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. Hence, the overall procedure results in solving a series of semidefinite programs (SDPs). With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Extensive numerical experiments are Deformed to illustrate the proposed algorithm.

• 한국통신학회논문지
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• 제26권10A호
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• pp.1639-1644
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• 2001

Two decision feedback equalizer structures employing recurrent neural network (RNN) used for non-linear channels with severe intersymbol interference (ISI) and non-linear distortion are proposed in this paper, which skillfully put the traditional decision feedback structure for linear channels equalization into RNN, replace decision feedback signal with training signal in the learning process and adaptively adjust the learning step. Simulative results of the first type of two new equalizer structures have shown that it has better equalization performances than traditional recurrent neural network equalizer (RNNE) under the same condition.

• Journal of applied mathematics & informatics
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• 제9권1호
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• pp.61-76
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• 2002

The robust non-fragile guaranteed cost control problem is studied in this paper for class of uncertain linear large-scale systems with time-varying delays in subsystem interconnections and given quadratic cost functions. The uncertainty in the system is assumed to be norm-hounded arid time-varying. Also, the state-feedback gains for subsystems of the large-scale system are assumed to have norm-bounded controller gain variations. The problem is to design state feedback control laws such that the closed-loop system is asymptotically stable and the closed-loop cost function value is not more than a specified upper bound far all admissible uncertainties. Sufficient conditions for the existence of such controllers are derived based on the linear matrix inequality (LMI) approach combined with the Lyapunov method. A parameterized characterization of the robust non-fragile guaranteed cost contrellers is 7iven in terms of the feasible solution to a certain LMI. Finally, in order to show the application of the proposed method, a numerical example is included.