• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 추계 학술대회 학술발표 논문집
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• pp.80-83
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• 2003

In this note, a separation principle of the Takagi-Sugeno (T-S) fuzzy-model-based controller/observer is investigated. The separation principle of T-S fuzzy-model-based controller/observer sharing the premise parts in the fuzzy rule with directly measurable premise variables is well established. In that case, the fact that the augmented observer-based control system has the eigenvalues of the sub-closed-loop control system by the state-feedback controller and the sub-closed-loop observer error system is used to prove the separation principle. This paper studies the separation principle of T-S fuzzy-model-based controller/observer in which the premise variables cannot be directly measurable.

• 제어로봇시스템학회논문지
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• 제20권11호
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• pp.1142-1146
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• 2014

This paper addresses on a $H_{\infty}$ sampled-data stabilization of a Takagi-Sugeno (T-S) fuzzy system. The sampled-data stabilization problem is formulated as a discrete-time stabilization one via a direct discrete-time design approach. It is shown that the sampled-data fuzzy control system is asymptotically stable whenever its exactly discretized model is asymptotically stable. Based on an exact discrete-time model, sufficient design conditions are derived in the format of linear matrix inequalities (LMIs). An example is provided to illustrate the effectiveness of the proposed methodology.

• 전자공학회논문지C
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• 제34C권5호
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• pp.43-54
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• 1997

The objective of this paper is to present a controller-design method that can guarantee the global stability for nonlinear systems described by takagi-sugeno fuzzy models, and to apply the method to a typical nonlinear control problem. The presented method gives us a compensated fuzzy controller through the following major steps: First, if each local linear model of a given takagi-sugeno fuzzy system does not have the same input matrix, the method expands the system into the one with a method finds a takagi-sugeno fuzzy controller guaranteeing the global stability of the closed loop via solving relevant linear matrix inequalities. Compared to the conventional PDC (paralled distributed compensation) technique, the presented method has an advantage that trial-and-errors to check the global stability are not necessary. An illustrative simulation on the control of inverted pendulum is performed to demonstrate the applicability of the presented method, and its results show that a controller satisfying the global stability and robustness can be obtained by the method.

• International Journal of Control, Automation, and Systems
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• 제2권1호
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• pp.68-75
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• 2004

In this paper, an estimator with an appropriate adaptive law for updating parameters is designed and analyzed based on the Lyapunov theory. The adaptive law is designed so that the estimation model follows the parameterized plant model. Using 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 indirect adaptive fuzzy control.

• 한국지능시스템학회논문지
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• 제8권5호
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• pp.51-60
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• 1998

퍼지 시스템의 안정도와 퍼지 제어기의 설계 방법론에 관한 연구는 최근 들어 많은 주목을 받아왔다. 본 논문은 TS(Takagi-Sugeno) 퍼지 모델로 표현된 비선형 시스템에 대한 제어기 설계분제가 선형행렬부등식(LMI, linear matrix inequality)을 포함하는 convex 문제로 간략화됨을 보인다. 입력행렬의 구조에 따라서 TS 퍼지 시스템을 세 가지로 분류하고, 각각에 대해 선형행렬부등식을 이용한 제어기 설계 방법을 제시한다. 또한 안정도 이외의 성능용건을 고려한 제어기를 설계한다. 제안된 설계 방법론을 설명하기 위해 예제를 다룬다.

• 한국수자원학회논문집
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• 제44권7호
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• pp.537-551
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• 2011

본 연구에서는 앞선 연구를 통해 선정된 최적 입력 자료 조합을 이용하여 한강수계의 왕숙천과 금강유역의 갑천에 대한 Takagi-Sugeno 퍼지기법과 신경망을 연계한 뉴로-퍼지 홍수예측 모형을 구축하였다. 구축된 뉴로-퍼지 홍수예측 모형을 한강수계의 왕숙천과 금강유역의 갑천에 적용하여 30분, 60분, 90분, 120분, 150분, 180분의 선행시간에 대해 각각 홍수예측을 수행하였다. 선행시간별 예측수위를 관측수위와 비교한 결과 안정되고 정확도 높은 홍수예측을 하는 것을 확인할 수 있었다. 추가적으로 정량적 평가를 위해 평균제곱근 오차(Root Mean Square Error)와 같은 통계지표를 산정하여 모형의 적용성을 검증하였다. 검증 결과 모든 통계지표에서 큰 오차 없이 성공적으로 홍수예측이 모의됨을 확인할 수 있었다. 본 연구결과는 향후 중소하천에서 충분한 선행시간을 확보한 정확도 높은 홍수정보시스템의 구축에 활용할 수 있을 것으로 판단된다.

• ETRI Journal
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• 제44권4호
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• pp.560-572
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• 2022

H²RDC (heuristic handover based on RCC-DTSK-C), a heuristic algorithm based on a highly interpretable deep Takagi-Sugeno-Kang fuzzy classifier, is proposed for suppressing the mobile heterogeneous networks problem of frequent handover and handover ping-pong in the multibase-station scenario. This classifier uses a stack structure between subsystems to form a deep classifier before generating a base station (BS) priority sequence during the handover process, and adaptive handover hysteresis is calculated. Simulation results show that H²RDC allows user equipment to switch to the best antenna at the optimal time. In high-BS density load and mobility scenarios, the proposed algorithm's handover success rate is similar to those of classic algorithms such as best connection (BC), self tuning handover algorithm (STHA), and heuristic for handover based on AHP-TOPSIS-FUZZY (H²ATF). Moreover, the handover rate is 83% lower under H²RDC than under BC, whereas the handover ping-pong rate is 76% lower.

• 한국지능시스템학회논문지
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• 제17권1호
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• pp.130-135
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• 2007

In this paper, a direct model reference adaptive fuzzy control (MRAFC) scheme is developed for the plant model whose structure is represented by the MIMO Takagi-Sugeno fuzzy model. The MRAFC scheme is proposed to provide asymptotic tracking of a reference signal lot the systems with uncertain or slowly time-varying parameters. The developed control law and adaptive law guarantee that all signals in the closed-loop system are bounded. In addition, the plant state tracks the state of the reference model asymptotically with time tot any bounded reference input signal.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.179-184
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• 1998

In this paper, a new hierarchical fuzzy inference system (HFIS) using structured Takagi-Sugeno type fuzzy inference units(FIUs) is proposed. The proposed HFIS not only solves the rule explosion problem in conventional HFIS, but also overcomes the readability problem caused by the structure where outputs of previous level FIUs are used as input variables directly. Gradient descent algorithm is used for adaptation of fuzzy rules. The ball and beam control is performed in computer simulation to illustrate the performance of the proposed controller.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.93.1-93
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• 2001

An evolutionary approach for the design of Fuzzy Logic Systems(FLSs) is proposed. Membership functions(MFs) in Takagi-Sugeno type fuzzy logic system is optimized through evolutionary process. Output singleton values are obtained through pseudo-inverse method. The proposed technique is unique for that, to prevent overfilling phenomenon, limited-level RBF membership functions are used and the new fitness function is invented. To show the effectiveness of the proposed method, some simulations results on model identification are given.