• 전기학회논문지
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• 제56권2호
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• pp.407-414
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• 2007

A sensor fault detection scheme(SFDS) for a class of nonlinear systems that can be represented by Takagi-Sugeno fuzzy model is proposed. Basically, the SFDS may be considered as a multiple observer scheme(MOS) in which the bank of state observers and the detection & isolation logic are included. However, the proposed scheme has two great differences from the conventional MOSs. First, the proposed scheme includes fuzzy fault detection observers(FFDO) that are constructed based on the T-S fuzzy model that provides very good approximation to nonlinear dynamic systems. Secondly, unlike the conventional MOS, the FFDOS are driven not parallelly but sequentially according to the predetermined sequence to avoid the massive computational burden, which is known to be the biggest obstacle to the practical application of the multiple observer based FDI schemes. During the operating time, each FFDO generates the residuals carrying the information of a specified fault, and the corresponding fault detection logic unit performs the logical operations to detect and isolate the fault of interest. The proposed scheme is applied to an inverted pendulum control system for sensor fault detection/isolation. Simulation study shows the practical feasibility of the proposed scheme.

• 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.

• 한국지능시스템학회논문지
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• 제12권6호
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• pp.559-564
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• 2002

This Paper Proposes a design method of a fuzzy output feedback controller for the nonlinear systems with the unknown time- delay. Recently, Cao et ai. proposed a stabilization method for the nonlinear time-delay systems using a fuzzy controller when the time-delay is known. However, the time-delay is likely to be unknown in practical. We represent the nonlinear systems with the unknown time-delay by Takagi-Sugeno (T-5) fuzzy model and design the fuzzy observer and the parallel distributed compensation (PDC) law based on this observer. By applying Lyapunov-Krasovskii theorem to the closed-loop system, the sufficient condition for the asymptotic stability of the equilibrium Point is derived and converted into the linear matrix inequality (LMI) Problem.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제9권2호
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• pp.76-82
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• 2009

A Heating, Ventilating and Air Conditioning (HVAC) system is a nonlinear multi-input multi-output (MIMO) system. This system is very difficult to control the temperature and the humidity ratio of a thermal space because of complex nonlinear characteristics. This paper proposes an adaptive fuzzy output feedback control based on observer for the nonlinear HVAC system. The nonlinear HVAC system is linearized through dynamic extension. State observers are designed for estimating state variables of the HVAC system. Fuzzy systems are employed to approximate uncertain nonlinear functions of the HVAC system with unavailable state variables. The obtained controller compares with an adaptive feedback controller. Simulation is given to demonstrate the effectiveness of our proposed adaptive fuzzy method.

• 제어로봇시스템학회논문지
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• 제17권11호
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• pp.1154-1158
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• 2011

In this paper, we discuss an observer-based fault tolerant controller design for the T-S (Takagi-Sugeno) fuzzy system with exogenous disturbance. To derive robust controller design conditions, we use $H_{\infty}$ design technique. The design conditions are derived in terms of linear matrix inequalities. An illustrative example is provided to show the effectiveness of the proposed methodology.

• Journal of information and communication convergence engineering
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• 제6권4호
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• pp.421-424
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• 2008

In torque transmission system, we must suppressed vibration for Accuracy characteristic response of motor, Therefore, vibration suppression factor is very important motor control. To suppress vibration, a various control method has been proposed. Specially, one method of vibration suppression used disturbance observer filter. This method is torsion torque passing disturbance observer filter. By the estimated torsion torque feedback, vibration can be suppressed. The CDM(coefficient diagram method) is used to design the filter and Proportional controller. But using coefficient diagram method, not adapted controller parameter in disturbance. For this solution, we used fuzzy controller for auto tuning controller parameter. We proved this approach is confirmed by simulation.

• 전기학회논문지P
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• 제59권2호
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• pp.163-172
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• 2010

A robust positioning control system has been studied using a friction parameter observer and a recurrent fuzzy neural network based on the sliding model. To estimate a nonlinear friction parameters of the LuGre friction model, a dual friction model-based observer is introduced. In addition, an approximating method for a system uncertainty has been developed using a recurrent fuzzy neural network technique to improve positioning performance. Experimental results have been presented to validate the performance of a proposed intelligent compensation scheme.

• 터널과지하공간
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• 제11권4호
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• pp.289-300
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• 2001

터널의 설계에는 지반조사 자료의 부정확성과 평가의 애매성 그리고 자료수집 과정의 오류(observer error)등이 내재되어 있다. 그러므로 터널의 안정성과 경제적인 시공을 위해서는 시공 중 막장면의 조사가 매우 중요한 역할을 한다. 본 연구는 막장면 조사 시 지반의 고유 특성을 보다 정확하게 평가하고, 조사자의 주관성을 최소화시키기 위하여 수행되었다. 이러한 목적을 위하여 막장관찰 자료로부터 RMR값을 추론하고자 인공지능기법 중 퍼지집합이론과 뉴로-퍼지기법을 적용하였고, 46개의 학습자료에 대해 원래의 RMR값과 퍼지이론 및 뉴로저지기법의 추론에 의한 RM $R_{_FU}$ 및 RM $R_{_NF}$값의 상관성을 분석하였다. 본 연구의 결과는 원래의 RMR값과 퍼지추론에 의한 RM $R_{_FU}$값 및 뉴로-퍼지기법에 의한 RM $R_{_NF}$값의 상관계수가 각각 ｜R｜= 0.96과 ｜R｜=0.95로 상관성이 우수한 것으로 조사되었다. 이 결과로부터 암반평가를 위한 퍼지집합이론 및 뉴로-피지기법의 적용성이 충분함을 검증할 수 있었다.할 수 있었다.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 1995년도 추계학술발표회논문집
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• pp.96-100
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• 1995

In this paper an induction motor control using fuzzy controller and neural network adptive observer is studied. The proposed observer which comprises neural network flux observer which comprises neural network flux observer and neural network torque observer is trained to learn the flux dynamics and torque dynamics and subjected to further on-line training by means of a backpropagation algorithem. Therefore it has been shown that the robust control of induction motor neglects the rotor time constant variations

• 한국지능시스템학회논문지
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• 제19권2호
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• pp.185-190
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• 2009

본 논문은 무선 센서 네트워크를 위한 패킷 손실을 포함하는 비선형 네트워크 제어 시스템의 관측기 기반 지능 제어기를 제시한다. 비선형 시스템의 지능 제어를 위해 Takagi-Sugeno (T-S) 퍼지 모델링 기법을 이용하고, 이를 통하여 비선형 네트워크 제어 시스템을 퍼지 모델로 표현한다. 퍼지 모델로 표현된 네트워크 제어 시스템에 대하여 퍼지 관측기를 설계하고, 관측기의 측정치와 실제 시스템의 상태변수 간의 오차를 안정화 시킬 수 있는 출력 궤환 제어기를 설계한다. 제안된 제어기를 포함한 폐루프 시스템의 안정도 조건을 선형 행렬 부등식으로 나타내고, 부등식을 이용하여 제어기의 이득값을 구한다. 모의실험을 통하여 제어기의 효용성을 평가한다.