• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
• /
• pp.523-525
• /
• 2005

This paper deals with a linear matrix inequality (LMI) approach to the design of a static output feedback controller that simultaneously stabilizes a finite collection of linear time-invariant plants. Simultaneous stabilization by static ouput feedback is represented in terms of LMIs with a rank condition. An iterative penalty method is proposed to solve the rank-constrained LMI problem. Numerical experiments show the effectiveness of the proposed algorithm.

• 제어로봇시스템학회논문지
• /
• 제11권8호
• /
• pp.656-661
• /
• 2005

This paper is concerned with an iterative linear matrix inequality (LMI) approach to the design of a structurally constrained output feedback controller such as decentralized control. The structured synthesis is formulated as a novel rank-constrained LMI optimization problem, where the controller parameters are explicitly described so as to impose structural constraints on the parameter matrices. An iterative penalty method is applied to solve the rank-constrained LMI problem. Numerical experiments are performed to illustrate the effectiveness of the proposed method.

• 조명전기설비학회논문지
• /
• 제17권5호
• /
• pp.88-93
• /
• 2003

본 논문에서는 반복법에 의한 쌍선형 시스템의 제어기 설계방법을 제안한다. 보조수열을 갖는 반복과정은 쌍선형 시스템으로부터 선형시변 시스템을 구성하는 과정에서 정의되고, 최적의 2차 가격함수를 갖는 쌍선형 시스템에서 궤환 제어기를 설계하기 위한 최적화 과정이 Riccati 접근법과 관련된 표현에 의해 주어진다. 제안된 방법에 의해서 개선된 성능과 우수한 수렴성이 성취됨을 시뮬레이션 결과에서 보인다.

• 대한전기학회논문지
• /
• 제45권1호
• /
• pp.131-138
• /
• 1996

In this paper, we consider an iterative learning control system(ILCS) consisting of an iterative learning controller, a feedback controller and a controlled plant in the frequency domain. At first, we review the convergence of ILCS. And we give some design guidelines of the ILCS using a nominal model of the plant. Then we present the structured and the unstructured uncertainty bound which guarantees the convergence of the designed iterative learning controller. In particular, we analyze the relationship between the convergence and the magnitude and phase uncertainties. In order to show the usefulness of the proposed analysis and design guidelines, we present some simulation examples. (author). 13 refs., 5 figs.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제55권5호
• /
• pp.226-228
• /
• 2006

This paper deals with a linear matrix inequality (LMI) approach to the design of a static output feedback controller that simultaneously stabilizes a finite collection of linear time-invariant plants. Simultaneous stabilization by static ouput feedback is represented in terms of LMIs with a rank condition. An iterative penalty method is proposed to solve the rank-constrained LMI problem. Numerical experiments show the effectiveness of the proposed algorithm.

• 제어로봇시스템학회논문지
• /
• 제13권11호
• /
• pp.1048-1052
• /
• 2007

This paper presents a rank-constrained linear matrix inequality(LMI) approach to simultaneous linear-quadratic(LQ) optimal control by static output feedback. Simultaneous LQ optimal control is formulated as an LMI optimization problem with a nonconvex rank condition. An iterative penalty method recently developed is applied to solve this rank-constrained LMI optimization problem. Numerical experiments are performed to illustrate the proposed method, and the results are compared with those of previous work.

• 제어로봇시스템학회논문지
• /
• 제15권1호
• /
• pp.15-22
• /
• 2009

The guidance controller of the conventional aircraft consists of inner-loop (autopilot) and outer-loop (guidance). If the guidance controller can be designed as an integrated guidance and control (IGC), the various advantages exist. The integrated guidance and control formulation can compensate for the effect of autopilot lag. An integrated approach also helps avoid the iterative procedure involved in tuning the guidance and autopilot subsystems, if designed separately. Integrated design is also less susceptible to saturation and stability problems. This paper presents an approach to IGC design for the unpowered air vehicle with the only flaperon using a combination of adaptive output feedback inversion and backstepping techniques. Adaptive neural networks are trained online with available measurements to compensate for unmodeled nonlinearities in the design process.

• 정보화연구
• /
• 제9권4호
• /
• pp.357-363
• /
• 2012

Ontologies are being used in order to define common vocabularies to describe the elements of schemas involved in a particular application. The problem of finding correspondences between ontologies concepts, called ontology matching, consists in the discovery of correspondences between terms of vocabularies (represented by ontologies) used by various applications. The majority of solutions proposed in the literature, despite being fully automatic, has heuristic nature and may produce nonsatisfactory results. The problem intensifies when dealing with large data sources. The goal of this paper is to propose a method for generation and incremental refinement of correspondences between ontologies. The proposed approach uses filtering techniques, as well as user feedback to support the generation and refinement of such matches. For validation purposes, a tool was developed and some experiments were conducted.

• 대한전기학회논문지:전력기술부문A
• /
• 제48권8호
• /
• pp.972-979
• /
• 1999

QFT(Quantitative Feedback Theory) is a very practical design technique that emphasizes the use of feedback for achieving the desired system performance tolerances in despite of plant uncertainty and disturbance. The fundamental concept of QFT is a loop shaping procedure that a suitable controller can be found by shaping a nominal loop transfer function. The loop shaping synthesis involves the identification of a structure and the specialization of parameter optimization of a desired system. This paper presents an improved loop shaping approach of QFT with model validation using GA(Genetic Algorithm). The method presented in this paper removes the problems of iterative operation, transformation error, and model validation in the conventional methods without consideration of frequency domain.

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