• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 하계학술대회 논문집 D
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• pp.2190-2192
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• 2003

In this paper, a state observer based direct adaptive fuzzy controller for unknown nonlinear dynamical system is presented. The adaptive parameters of the direct adaptive fuzzy controller can be tuned by using a projection algorithm on-line based on the Lyapunov synthesis approach. A maximum control is used to guarantee the robustness of system. A stability analysis of the overall adaptive scheme is discussed based on the sense of Lyapunov. The inverted pendulum simulation example shows that proposed control algorithm can be used for the tracking problem of nonlinear system.

• 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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 V
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• pp.2863-2866
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• 2003

In nonlinear control fields, for irregular nonlinear systems, control form which consists of approximate tracking control law and exact tracking control law and which switches between two laws has been proposed recently. In this thesis, we design new switching control law which connect approximate linearization control law and exact linearization control law by fuzzy rules for irregular nonlinear system, ball and beam system. Fuzzy switching controller designed by fuzzy concept is proved that designed scheme overcomes singularities of irregular system, improves unstability problem of switching procedure, and has more efficient control value through simulation. Stability of fuzzy control system proved by Lyapunov's stability theorems.

• 전자공학회논문지SC
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• 제41권5호
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• pp.19-27
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• 2004

시간지연을 갖는 퍼지 시스템에 대한 지연 종속 퍼지 H₂/H/sub ∞/ 제어기 설계 방법을 제안한다. 지연 종속 Lyapunov 함수를 이용하여 폐루프 시스템의 점근적 안정화뿐만 아니라 H₂ 성능과 H/sub ∞/ 성능을 동시에 만족하는 혼합 H₂/H/sub ∞/ 성능 문제를 고려한다. 제어기의 존재성에 대한 충분조건을 유도하고 선형행렬부등식(LMI: linear matrix inequality)으로 나타낸다. 제어기 설계는 병렬 분산 보상의 개념을 이용하고, 퍼지 제어기는 LMI 해를 구함으로써 바로 구할 수 있다. 지연 종속 퍼지 제어기는 존재 조건을 나타내는 선형 행렬 부등식에 시간지연항의 크기를 포함하고 있으므로 시간지연항의 크기를 고려할 수 있다. 따라서 시간지연의 크기에 상관없이 시스템을 안정화 시키는 지연 독립적인 제어기 보다 더 효과적인 설계방법이다. 제안한 방법의 설계과정 및 타당성을 시뮬레이션 예제를 통하여 나타내고 기존의 시간 지연 독립적인 퍼지 H₂/H/sub ∞/ 제어기 설계 방법 보다 효과적인 방법임을 확인한다.

• 한국지능시스템학회논문지
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• 제25권4호
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• pp.349-354
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• 2015

본 논문은 비선형 시스템을 위한 T-S 퍼지 샘플치 필터의 안정도 조건을 제시한다. 퍼지 시스템과 퍼지 필터 사이의 에러 시스템을 제시하며, 리아푸노프 안정도 해석 기법을 이용해 에러 시스템의 안정도 조건을 선형행렬부등식의 형태로 표현한다. 제안된 안정도 조건은 기존과는 다른 접근법을 이용하며, 더 나은 성능을 보인다. 모의실험을 통해 제안한 기법의 효용성을 검증한다.

• International Journal of Aeronautical and Space Sciences
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• 제14권2호
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• pp.172-182
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• 2013

This paper focuses on the modeling and intelligent control of the new Eight-Rotor MAV, which is used to solve the problem of the low coefficient proportion between lift and gravity for the Quadrotor MAV. The Eight-Rotor MAV is a nonlinear plant, so that it is difficult to obtain stable control, due to uncertainties. The purpose of this paper is to propose a robust, stable attitude control strategy for the Eight-Rotor MAV, to accommodate system uncertainties, variations, and external disturbances. First, an interval type-II fuzzy neural network is employed to approximate the nonlinearity function and uncertainty functions in the dynamic model of the Eight-Rotor MAV. Then, the parameters of the interval type-II fuzzy neural network and gain of sliding mode control can be tuned on-line by adaptive laws based on the Lyapunov synthesis approach, and the Lyapunov stability theorem has been used to testify the asymptotic stability of the closed-loop system. The validity of the proposed control method has been verified in the Eight-Rotor MAV through real-time experiments. The experimental results show that the performance of the interval type-II fuzzy neural network based adaptive sliding mode controller could guarantee the Eight-Rotor MAV control system good performances under uncertainties, variations, and external disturbances. This controller is significantly improved, compared with the conventional adaptive sliding mode controller, and the type-I fuzzy neural network based sliding mode controller.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.211-216
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• 2004

In this thesis, we present the Takagi-Sugeno-Kang (TSK) fuzzy model based adaptive controller and adaptive identification for a general class of uncertain nonlinear dynamic systems. We use an estimated model for the unknown plant model and use this model for designing the controller. The hybrid adaptive control combined direct and indirect adaptive control based on TSK fuzzy model is constructed. The direct adaptive law can be showed by ignoring the identification errors and fails to achieve parameter convergence. Thus, we propose an TSK fuzzy model based hybrid adaptive (HA) law combined of the tracking error and the model ins error to adjust the parameters. Using a Lyapunov synthesis approach, the proposed hybrid adaptive control is proved. The hybrid adaptive law (HA) is better than the direct adaptive (DA) method without identifying the model ins error in terms of faster and improved tracking and parameter convergence. In order to show the applicability of the proposed method, it is applied to the inverted pendulum system and the performance is verified by some simulation results.

• 제어로봇시스템학회논문지
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• 제16권4호
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• pp.319-328
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• 2010

This paper proposes a robust adaptive fuzzy tracking control scheme for a nonholonomic mobile robot with external disturbances as well as parameter uncertainties in the robot kinematics, the robot dynamics, and the actuator dynamics. In modeling a mobile robot, the actuator dynamics is integrated with the robot kinematics and dynamics so that the actuator input voltages are the control inputs. The presented controller is designed based on a FBFN (Fuzzy Basis Function Network) to approximate an unknown nonlinear dynamic function with the uncertainties, and a robust adaptive input to overcome the uncertainties. When the controller is designed, the different parameters for two actuator models in the actuator dynamics are taken into account. The proposed control scheme does not require the kinematic and dynamic parameters of the robot and actuators accurately. It can also alleviate the input chattering and overcome the unknown friction force. The stability of the closed-loop control system including the kinematic control system is guaranteed by using the Lyapunov stability theory and the presented adaptive laws. The validity and robustness of the proposed control scheme are shown through a computer simulation.

• Smart Structures and Systems
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• 제29권4호
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• pp.617-624
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• 2022

A new intelligent adaptive control scheme was proposed that combines the control based on interference observer and fuzzy adaptive s-curve for flight path tracking control of unmanned aerial vehicle (UAV). The most important contribution is that the control configurations don't need to know the uncertainty limit of the vehicle and the influence of interference is removed. The proposed control law is an integration of fuzzy control estimator and adaptive proportional integral (PI) compensator with input. The rated feedback drive specifies the desired dynamic properties of the closed control loop based on the known properties of the preferred acceleration vector. At the same time, the adaptive PI control compensate for the unknown of perturbation. Additional terms such as s-surface control can ensure rapid convergence due to the non-linear representation on the surface and also improve the stability. In addition, the observer improves the robustness of the adaptive fuzzy system. It has been proven that the stability of the regulatory system can be ensured according to linear matrix equality based Lyapunov's theory. In summary, the numerical simulation results show the efficiency and the feasibility by the use of the robust control methodology.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.188-190
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• 2000

This paper proposed design of robust fuzzy controller for nonlinear systems in the presence of parametric uncertainties. In the design procedure, we represent the nonlinear system using Takagi-Sugeno fuzzy model. A sufficient condition of the robust stability is presented in the sense of Lyapunov for the TSK fuzzy model with uncertainties. Finally, the effectiveness of proposed controller has been through a result of numerical simulation.