• Smart Structures and Systems
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• 제6권1호
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• pp.29-38
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• 2010

An ElectroMagnetic Actuator (EMA) is designed and assessed numerically and experimentally. The EMA has the advantage to be without contact with the structure so it could be applied to light and small mechanism. Nevertheless, the open-loop instability and the nonlinear dynamic behavior with respect to the excitation frequency could limit its application field. The EMA is designed and dimensioned as a function of the experimental structure to be controlled. An inverse model of the EMA is proposed in order to implement a linear action block for the used frequency range. The control strategy is a fuzzy controller with displacements and velocities as inputs. A fuzzy controller of Takagi-Sugeno type is used. The air gap is estimated by using a modal approximation of the displacements issued from all measurements. Several configurations of control are assessed by using numerical simulations. The block diagram used for numerical simulations is implemented under Dspace$^{(R)}$ environment. The implemented controller was tested experimentally in the context of impact perturbations. The results obtained show the effectiveness of the developed procedures and the robustness of the implemented control.

• 한국지능시스템학회논문지
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• 제15권7호
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• pp.881-886
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• 2005

본 논문은 복합 상태 공간에서의 피지 기반 제어기를 이용한 지능형 디지털 재설계의 전 역적 접근 방안에 대해 제안하고자 한다. 이산화를 통한 제어기 설계에 있어서 불확실성이 포함된 실시간 비선형 시스템에 대해 보다 효율적이고 안정적인 접근을 위해 TS 퍼지 모델이 사용되었다. 그리고 전 역적 접근을 위한 방안으로서 문제를 볼록 최적화 관점으로 변환 후, 에러가 가질 수 있는 놈의 영역을 최소화하여 상태 접합을 이루고자 하였다. 또한 power series를 사용함으로써 불확실성이 조합된 비선형 시스템을 보다 더 정확하게 분석하였다. 샘플링 기간이 충분히 작다면, 불확실 비선형 시스템의 실시간 시스템으로의 전환이 충분한 이유를 가지게 된다. 전 역적 접근을 통한 디지털로 제어된 시스템은 선형 행렬 부등식 형태로 바꾸어 시스템의 안정성을 보장하고자 하였다. 마지막으로 TS 퍼지 모델로 분석된 혼돈 Lorenz System에 적용함으로써 제안된 방법의 안정성과 효율성을 보장받게 된다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.1741_1742
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• 2009

본 논문은 측정 실패가 존재하는 비선형 시스템에 대한 동적 출력 궤환 퍼지 제어기의 설계에 대해 연구한다. 비선형 시스템을 Takagi-Sugeno (T-S) 퍼지 모델 기법을 이용하여 퍼지 시스템으로 모델링하고, 이를 바탕으로 동적 출력 궤환 퍼지 제어기를 설계한다. 폐루프 시스템의 안정도 조건을 선형 행렬 부등식 (LMI)로 나타낸다. 그리고 모의실험을 통해 제안된 제어기의 성능을 파악한다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.1745_1746
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• 2009

본 논문은 뉴트럴 퍼지 시스템의 안정도 분석 및 제어기 설계에 대해서 논의한다. 네트워크 상에서 발생하는 뉴트럴 타입 시간 지연을 모델링하며, 전체 뉴트럴 퍼지 시스템은 뉴트럴 타입 시간 지연을 가지는 비선형 시스템이 된다. 뉴트럴 퍼지 시스템을 타카기-수게노 (Takagi-Sugeno) 퍼지 시스템으로 모델링한다. 제안하는 퍼지 제어기를 모델링하는 뉴트럴 퍼지 시스템과 같은 멤버쉽 함수를 가지게 설계한다. 전체 폐루프 시스템의 안정도를 시간 지연 간격에 종속적이게 분석하고, 뉴트럴 퍼지 시스템을 안정화 시키는 퍼지 제어기 설계를 위한 충분 조건을 유도한다. 제안된 필요 충분 조건을 선형 행렬 부등식의 형태로 나타내고, 해를 통하여 퍼지 제어기의 이득값을 설계한다. 예제를 통하여 제안된 이론의 타당성을 확인한다.

• 전자공학회논문지S
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• 제36S권5호
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• pp.30-41
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• 1999

본 논문에서는 연속시간과 이산시간에서 파라미터 불확실성과 시간지연을 가지는 비선형시스템에 대한 퍼지 견실 H∞ 제어기 설계방법을 제시한다. 비선형시스템은 변형한 T-S(Takagi- Sugeno) 퍼지모델을 사용하여 나타내고, 퍼지제어는 PDC(parallel distributed compensation) 개념을 이용한다. 또한 Lyapunov 접근방법을 이용하여 불확실성, 외란과 시간지연을 가지는 변형한 T-S 퍼지모델의 H∞ 노옴 한계를 가지는 자승적 안정성을 언급하고, LMI(linear matrix inequality) 기법을 이용하여 퍼지 견실 H∞ 제어기의 존재 조건과 제어기 설계방법을 제시한다. 그러므로 제시한 기법은 구하여진 충분조건을 만족하는 해를 찾음과 동시에 제어기를 한번에 설계할 수 있다. 마지막으로 예제를 통하여 제시한 방법의 타당성을 확인한다.

• 전기학회논문지
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• 제60권11호
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• pp.2119-2130
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• 2011

This paper proposes new delay-dependent robust stability criteria for neural networks with time-varying delays. By construction of a suitable Lyapunov-Krasovskii's (L-K) functional and use of Finsler's lemma, new stability criteria for the networks are established in terms of linear matrix inequalities (LMIs) which can be easily solved by various effective optimization algorithms. Two numerical examples are given to illustrate the effectiveness of the proposed methods.

• 제어로봇시스템학회논문지
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• 제17권9호
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• pp.897-901
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• 2011

This paper presents a TS (Takagi-Sugeno) type FLC (Fuzzy Logic Controller) with only 3 rules. The choice of parameters of FLC is very difficult job on design FLC controller. Therefore, the choice of appropriate linguistic variable is an important part of the design of fuzzy controller. However, since fuzzy controller is nonlinear, it is difficult to analyze mathematically the affection of the linguistic variable. So this choice is depend on the expert's experience and trial and error method. In the design of the system, we use a variety of response characteristics like stability, rising time, overshoot, settling time, steady-state error. In particular, it is important for a stable system design to predict the steady-state error because the system's steady-state response of the system is related to the overall quality. In this paper, we propose the method to choose the consequence linear equation's parameter of T-S type FLC in the view of steady-state error. The parameters of consequence linear equations of FLC are tuned according to the system error that is the input of FLC. The full equation of T-S type FLC is presented and using this equation, the relation between output and parameters can represented. As well as the FLC parameters of consequence linear equations affect the stability of the system, it also affects the steady-state error. In this study, The system according to the parameter of consequence linear equations of FLC predict the steady-state error and the method to remove the system's steady-state error is proposed using the prediction error value. The simulation is carried out to determine the usefulness of the proposed method.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.211-217
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• 1998

Many practical control problems for the complex, uncertain or large-scale plants, need to simultaneously achieve a number of objectives, which may conflict or compete with each other. If the conventional optimization methods are applied to solve these control problems, the solution process may be time-consuming and the resulting solution would ofter lose its original meaning of optimality. Nevertheless, the human operators usually performs satisfactory results based on their qualitative and heuristic knowledge. In this paper, we investigate the control strategies of the human operators, and propose a fuzzy model-based multi-objective satisfactory controller. We also apply it to the automatic train operation(ATO) system for the magnetically levitated vehicles(MAGLEV). One of the human operator's strategies is to predict the control result in order to find the meaningful solution. In this paper, Takagi-Sugeno fuzzy model is used to simulated the prediction procedure. Another str tegy is to evaluate the multiple objectives with respect to their own standards. To realize this strategy, we propose the concept of a satisfactory solution and a satisfactory control scheme. The MAGLEV train is a typical example of the uncertain, complex and large-scale plants. Moreover, the ATO system has to satisfy multiple objectives, such as seed pattern tracking, stop gap accuracy, safety and riding comfort. In this paper, the speed pattern tracking controller and the automatic stop controller of the ATO system is designed based on the proposed control scheme. The effectiveness of the ATO system based on the proposed scheme is shown by the experiments with a rotary test bed and a real MAGLEV train.

• Structural Engineering and Mechanics
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• 제83권3호
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• pp.327-340
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• 2022

The Collapse Margin Ratio (CMR) is a notable index used for seismic assessment of the structures. As proposed by FEMA P695, a set of analyses including the Nonlinear Static Analysis (NSA), Incremental Dynamic Analysis (IDA), together with Fragility Analysis, which are typically time-taking and computationally unaffordable, need to be conducted, so that the CMR could be obtained. To address this issue and to achieve a quick and efficient method to estimate the CMR, the Artificial Neural Network (ANN), Response Surface Method (RSM), and Adaptive Neuro-Fuzzy Inference System (ANFIS) will be introduced in the current research. Accordingly, using the NSA results, an attempt was made to find a fast and efficient approach to derive the CMR. To this end, 5016 IDA analyses based on FEMA P695 methodology on 114 various Reinforced Concrete (RC) frames with 1 to 12 stories have been carried out. In this respect, five parameters have been used as the independent and desired inputs of the systems. On the other hand, the CMR is regarded as the output of the systems. Accordingly, a double hidden layer neural network with Levenberg-Marquardt training and learning algorithm was taken into account. Moreover, in the RSM approach, the quadratic system incorporating 20 parameters was implemented. Correspondingly, the Analysis of Variance (ANOVA) has been employed to discuss the results taken from the developed model. Additionally, the essential parameters and interactions are extracted, and input parameters are sorted according to their importance. Moreover, the ANFIS using Takagi-Sugeno fuzzy system was employed. Finally, all methods were compared, and the effective parameters and associated relationships were extracted. In contrast to the other approaches, the ANFIS provided the best efficiency and high accuracy with the minimum desired errors. Comparatively, it was obtained that the ANN method is more effective than the RSM and has a higher regression coefficient and lower statistical errors.