• 전기학회논문지
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• 제58권9호
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• pp.1821-1826
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• 2009

An adaptive neural controller for perturbed strict-feedback nonlinear system is proposed. All the previous adaptive neural (or fuzzy) controllers are based on the backstepping scheme where the universal approximators are employed in every design steps. These schemes involve virtual controls and their time derivatives that make the stability analysis and implementation of the controller very complex. This fact is called 'explosion of complexty ' since the complexity grows exponentially as the system dynamic order increases. The proposed adaptive neural control scheme adopt the backstepping design procedure only for determining ideal control law and employ only one neural network to approximate the finally selected ideal controller, which makes the controller design procedure and stability analysis considerably simple compared to the previously proposed controllers. It is shown that all the time-varing signals containing tracking error are stable in the Lyapunov viewpoint.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.192-196
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• 한국지능시스템학회논문지
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• 제14권7호
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• pp.927-933
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• 조명전기설비학회논문지
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• 제23권11호
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• pp.9-21
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• 2009

This paper proposes the alternative observer and controller design scheme based on T-S fuzzy model. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given unknown nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. The proposed controller is based on a simple output feedback method. Therefore, it solves the singularity problem, without any additional algorithm, which occurs in the inverse dynamics based on the feedback linearization method. The adaptive fuzzy scheme estimates the parameters and the feedback gain comprising the fuzzy model representing the observation system. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observer and controller, they are applied to an inverted pendulum on a cart.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.348-353
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems arc represented by fuzzy models since fuzzy logic systems arc universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• 전기전자학회논문지
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• 제23권2호
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• pp.716-721
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• 2019

불확실한 순궤환 비선형 계통에 대한 스위칭 미분기 기반의 새로운 백스테핑 제어기를 제안한다. 제안된 제어기에서는 점근적 추종 특성을 갖는 스위칭 미분기를 사용하여 백스테핑 제어기의 매 설계 단계마다 가상 제어항이 직접 근사된다. 그 결과 제어식이 매우 단순화되고 계통에 내재된 파라미터 및 구조적 불확실성과 외란이 존재함에도 불구하고 계통의 출력이 원하는 출력을 점근적으로 추종함을 증명한다. 또한 신경망이나 퍼지시스템 같은 계통의 구조적인 불확실성에 적응적으로 실시간 보상하기 위한 범용 근사기가 불필요하다. 모의실험을 통해서 제안된 제어기의 성능과 간결함을 보인다.

• 한국콘텐츠학회논문지
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• 제10권6호
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• pp.166-174
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• 2010

다층퍼셉트론이 충분한 중간층 노드 수를 지니면 임의의 함수를 근사시킬 수 있다는 이론적 연구결과에 기초하여, 다층퍼셉트론을 실제 문제에 응용하는 경우에 일반적으로 입력층, 중간층, 출력층으로 이루어진 3층 구조의 다층퍼셉트론을 사용한다. 그렇지만, 이러한 구조의 다층퍼셉트론은 입력벡터가 여러 가지 성질로 이루어진 복잡한 문제의 경우 좋은 일반화 성능을 보이지 않는다. 이 논문에서는 입력 벡터가 여러 가지 정보를 지닌 데이터들로 구성되어 있는 문제인 경우에 계층적 구조를 지닌 다층퍼셉트론의 구성으로 성능을 향상시키는 방법을 제안한다. 즉, 입력데이터를 섭-벡터로 구분한 후 섭-벡터별로 다층퍼셉트론을 적용시키며, 이 섭-벡터별로 적용된 하위층 다층퍼셉트론으로부터 인식 결과를 받아서 최종 결정을 하는 상위 다층퍼셉트론을 구현한다. 제안한 방법의 효용성은 단백질의 구조를 예측하는 문제를 통하여 확인한다.

• 한국지능시스템학회논문지
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• 제7권2호
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• pp.70-78
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• 1997

여러 가지 고급 제어 이론들에 관한 연구가 심도있게 진행되고 있음에도 불구하고 아직까지 산업현장에는 여러가지 변형된 형태의 PID 제어기가 널리 사용되고있다. 이는 PID 제어기 자체가 가진 제어 구조의 단순성, 효율성, 강건성, 그리고 제어 기술자들에 대한 친밀감 등에 기인한다. 또한 요즘 제어 분야에서는 퍼지 이론을 도입하는 연구가 활발히 진행되고 있다. 특히, 퍼지 이론을 사용해서 거의 모든 함수들을 근사화시킬 수 있다는 연구 결과들이 발표되면서 수학적으로 안정성 및 강건성을 명확히 증명하기에 다소 미흡하였던 퍼지 논리 제어에 관한 연구가 활기를 띠고 있다. 본 논문에서는 먼저 간단한 퍼지 제어기로부터 선형 PID 제어기를 유도한다. 그리고 나서 다소 일반적인 경우의 퍼지 제어기를 사용하여 산업 현장에서 가장 널리 사용되고있는 선형PID 제어기를 유도하여 결굴 PID 제어기는 퍼지 제어기의 일종에 불과함을 입증할 것이다.

• Advances in aircraft and spacecraft science
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• 제6권6호
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• pp.529-550
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• 2019

The effect of multiple process parameters on a set of continuous response variables is, especially in experimental designs, difficult and intricate to determine. Due to the complexity in aeroacoustic and vibroacoustic studies, the often-performed simple one-factor-at-a-time method turns out to be the least effective approach. In contrast, the statistical Design of Experiments is a technique used with the objective to maximize the obtained information while keeping the experimental effort at a minimum. The presented work aims at giving insights on Design of Experiments applied to aeroacoustic and vibroacoustic problems while comparing different experimental designs and approximation models. For this purpose, an experimental rig of a ducted low-pressure fan is developed that allows gathering data of both, aerodynamic and aeroacoustic nature while analysing three independent process parameters. The experimental designs used to sample the design space are a Central Composite design and a Box-Behnken design, both used to model a response surface regression, and Latin Hypercube sampling to model an Artificial Neural network. The results indicate that Latin Hypercube sampling extracts information that is more diverse and, in combination with an Artificial Neural network, outperforms the quadratic response surface regressions. It is shown that the Latin Hypercube sampling, initially developed for computer-aided experiments, can also be used as an experimental design. To further increase the benefit of the presented approach, spectral information of every experimental test point is extracted and Artificial Neural networks are chosen for modelling the spectral information since they show to be the most universal approximators.