• Title/Summary/Keyword: Fuzzy matrix

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Fuzzy Controller for Intelligent Networked Control System with Neutral Type of Time-delay (뉴트럴 타입 시간 지연을 갖는 지능형 네트워크 제어 시스템의 퍼지 제어기 설계)

  • Joo, Young-Hoon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.19 no.2
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    • pp.174-179
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    • 2009
  • We consider the stabilization problem for a class of networked control systems with neutral type of time delays. The neutral type of time-delays occur in controller-to-actuator and sensor-to-controller. The Takagi-Sugeno (T-S) fuzzy model is employed to represent a nonlinear system with neutral type of time-delays. The stabilization via state-feedback is first addressed, and delay-range-dependent stabilization conditions are proposed in terms of linear matrix inequalities (LMIs). Finally, an application example will be given to show the merits and design a procedure of the proposed approach.

A Study on the Relaxed Stability of Fuzzy Control Systems (퍼지 제어 시스템의 완화된 안정조건에 관한 연구)

  • Kim, Eun-Tae;Lee, Chang-Hun;Park, Min-Yong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.5
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    • pp.11-18
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    • 2000
  • In this paper, we propose a new condition to test the quadratic stability of fuzzy control systems. The Proposed one enlarges the class of fuzzy control systems whose stability is ensured by representing the interactions among the fuzzy subsystems in a single power matrix and solving it by LMI (linear matrix inequality). Compared with the previous methods, the proposed one relaxes the stability condition to release the conservatism. Finally, the relationship between the suggested condition and the conventional well-known stability conditions reported in the previous literatures is discussed and it is shown in a rigorous manner that the proposed one includes the conventional conditions.

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A Study on Short-Term Load Forecasting System Using Data Mining (데이터 마이닝을 이용한 단기부하예측 시스템 연구)

  • Kim, Do-Wan;Park, Jin-Bae;Kim, Juhg-Chan;Joo, Young-Hoon
    • Proceedings of the KIEE Conference
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    • 2003.11c
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    • pp.588-591
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    • 2003
  • This paper presents a new short-term load forecasting system using data mining. Since the electric load has very different pattern according to the day, it definitely gives rise to the forecasting error if only one forecasting model is used. Thus, to resolve this problem, the fuzzy model-based classifier and predictor are proposed for the forecasting of the hourly electric load. The proposed classifier is the multi-input and multi-output fuzzy system of which the consequent part is composed of the Bayesian classifier. The proposed classifier attempts to categorize the input electric load into Monday, Tuesday$\sim$Friday, Saturday, and Sunday electric load, Then, we construct the Takagi-Sugeno (T-S) fuzzy model-based predictor for each class. The parameter identification problem is converted into the generalized eigenvalue problem (GEVP) by formulating the linear matrix inequalities (LMIs). Finally, to show the feasibility of the proposed method, this paper provides the short-term load forecasting example.

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RC structural system control subjected to earthquakes and TMD

  • Jenchung Shao;M. Nasir Noor;P. Ken;Chuho Chang;R. Wang
    • Structural Engineering and Mechanics
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    • v.89 no.2
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    • pp.213-223
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    • 2024
  • This paper proposes a composite design of fuzzy adaptive control scheme based on TMD RC structural system and the gain of two-dimensional fuzzy control is controlled by parameters. Monitoring and learning in LMI then produces performance indicators with a weighting matrix as a function of cost. It allows to control the trade-off between the two efficiencies by adjusting the appropriate weighting matrix. The two-dimensional Boost control model is equivalent to the LMI-constrained multi-objective optimization problem under dual performance criteria. By using the proposed intelligent control model, the fuzzy nonlinear criterion is satisfied. Therefore, the data connection can be further extended. Evaluation of controller performance the proposed controller is compared with other control techniques. This ensures good performance of the control routines used for position and trajectory control in the presence of model uncertainties and external influences. Quantitative verification of the effectiveness of monitoring and control. The purpose of this article is to ensure access to adequate, safe and affordable housing and basic services. Therefore, it is assumed that this goal will be achieved in the near future through the continuous development of artificial intelligence and control theory.

Static Output Feedback Control for Continuous T-S Fuzzy Systems (연속시간 T-S 퍼지 시스템에 대한 정적 출력궤환 제어)

  • Jeung, Eun Tae
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.6
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    • pp.560-564
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    • 2015
  • This paper presents a design method of a static output feedback controller for continuous T-S fuzzy systems via parallel distributed compensation (PDC). The existence condition of a set of static output feedback gains is represented in terms of linear matrix inequalities (LMIs). The sufficient condition presented here does not need any transformation matrices and equality constraints and is less conservative than the previous results seen in [20].

Fuzzy Model-Based Output-Tracking Control for 2 Degree-of-Freedom Helicopter

  • Chang, Wook;Moon, Ji Hyun;Lee, Ho Jae
    • Journal of Electrical Engineering and Technology
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    • v.12 no.4
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    • pp.1649-1656
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    • 2017
  • This paper addresses the control problem of a laboratory-level 2 degree-of-freedom helicopter. The exact fuzzy model in a Takagi - Sugeno form is constructed by the sector nonlinearity technique, and is then represented as a set of uncertain linear systems. Output-tracking controller is designed in terms of linear matrix inequalities and the closed-loop stability is rigorously analyzed. Experimental evaluation shows that the proposed method is of benefit to many real industrial plants.

A Stability Analysis of Mamdani Type Fuzzy Systems (맘다니형 퍼지 시스템의 안정 해석)

  • Lee, Chang-Hoon;Sugeno, Mickle
    • Proceedings of the KIEE Conference
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    • 2001.11c
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    • pp.76-79
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    • 2001
  • This paper is concerned with a stability analysis of Madam Type fuzzy systems. It Introduces the canonical form of an unforced fuzzy system and its stability theorem suggested in the previous study. Then it gives new simplified stability conditions based on the Lyapunov function method. A common positive definite matrix in the stability conditions is searched by the LMI method.

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SAOR METHOD FOR FUZZY LINEAR SYSTEM

  • Miao, Shu-Xin;Zheng, Bing
    • Journal of applied mathematics & informatics
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    • v.26 no.5_6
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    • pp.839-850
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    • 2008
  • In this paper, the symmetric accelerated overrelaxation (SAOR) method for solving $n{\times}n$ fuzzy linear system is discussed, then the convergence theorems in the special cases where matrix S in augmented system SX = Y is H-matrices or consistently ordered matrices and or symmetric positive definite matrices are also given out. Numerical examples are presented to illustrate the theory.

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Non-PDC Static Output Feedback Control for T-S Fuzzy Systems (T-S 퍼지 시스템에 대한 비병렬분산보상 정적 출력궤환 제어)

  • Jeung, Eun Tae
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.7
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    • pp.496-501
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    • 2016
  • This paper presents a design method of non-parallel distributed compensation (non-PDC) static output feedback controller for continuous- and discrete-time T-S fuzzy systems. The existence condition of static output feedback control law is represented in terms of linear matrix inequalities (LMIs). The proposed sufficient stabilizing condition does not need any transformation matrices and equality constraints and is less conservative than the previous result of [21].

A New Approach to Stability Analysis of Singleton-type Fuzzy Control Systems (싱글톤 퍼지 제어 시스템의 새로운 안정도 해석법)

  • 김은태;이희진;이상형;박민용
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.788-791
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    • 1999
  • In recent years, many studies have been conducted on fuzzy control since it can surpass the conventional control in several respects. In this paper, numerical stability analysis methodology for the singleton-type linguistic fuzzy control systems is proposed. The Proposed stability analysis is not the analytical method but the numerical method using the convex optimization technique of Quadratic Programming (QP) and Linear Matrix Inequalities (LMI).

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